Task-related Controllability of Functional Connectome During a Working Memory Task in Schizophrenia, Bipolar Disorder, and Major Depressive Disorder

Task-related Controllability of Functional Connectome During a Working Memory Task in Schizophrenia, Bipolar Disorder, and Major Depressive Disorder | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Task-related Controllability of Functional Connectome During a Working Memory Task in Schizophrenia, Bipolar Disorder, and Major Depressive Disorder Jie Yang, Jun Yang, Zhening Liu, Feiwen Wang, Wenjian Tan, Danqing Huang, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5412595/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Working memory (WM) deficit is a prominent and common cognitive impairment in major psychiatric disorders (MPDs). Altered control of brain states transitions may underlie the neural basis of WM deficit. Brain controllability derived from Network Control Theory provides a mathematical framework to study how external signals may affect neural network dynamics and influence the transition to desired states. We investigate if shared and illness-specific alterations in controllability underlie WM deficits in MPDs. We examined fMRI data during a n-back WM task from 105 patients with schizophrenia (SZ), 67 with bipolar disorder (BD), 51 with major depressive disorder (MDD), and 80 healthy controls (HCs). A region’s capacity to steer transitions to connectomic states with less input (average controllability) and difficult-to-reach states with high input (modal controllability) were compared across groups. The effect of altered controllability on clinical and cognitive characteristics, and their likely genetic and neurotransmitter basis were investigated. Compared to HCs, all MPDs had lower modal controllability of frontoparietal network. SZ and MDD shared modal controllability in default mode network and salience network nodes compared to BD and HCs. Only SZ had lower modal controllability of sensorimotor, auditory, and visual network nodes than HCs, indicating the need for higher sensory inputs to facilitate a state transition in SZ. Expression of genes that determine synaptic biology and chemoarchitecture involving glutamate/GABA and monoamine (dopamine and 5HT) receptor systems were more likely in the affected brain regions. A graded, transdiagnostic reduction in the influence of the triple network system and sensory networks in implementing state transitions underlies working memory deficits in MPDs. This deficit, especially pronounced in SZ, has its likely basis in synaptic biology and in glutamate/GABA and monoamine (dopamine and 5HT) systems. Biological sciences/Neuroscience Health sciences/Diseases/Psychiatric disorders/Schizophrenia major psychiatric disorder control theory frontoparietal network sensor cortex gene neurotransmitter Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Working memory (WM) refers to the ability to store, manipulate, and update temporary information for goal-directed behavior, which is the basis of advanced cognitive functions [ 1 ]. The WM deficit has long been recognized as a prominent and common cognitive impairment in major psychiatric disorders (MPDs; e.g., schizophrenia [SZ], bipolar disorders [BD], and major depressive disorders [MDD]), persisting even after remission[ 2 – 4 ], and significantly impacting patients’ quality of life and functional outcomes [ 5 , 6 ]. The transdiagnostic neurobiological basis of WM deficits are yet to be uncovered in MPDs which share overlapping clinical, genetic, and neuropathophysiological characteristics [ 7 – 9 ]. Task-based functional MRI (fMRI) approaches capture behaviorally-relevant, instantaneous neural processes evoked by cognitive tasks [ 10 ]. During WM tasks, both SZ and BD exhibited greater activations in the triple network system comprised of frontoparietal network (FPN), dorsal attentional network (DAN), and executive control/salience network than healthy controls (HCs) [SZ > BD] [ 11 ]. Meta-analytic evidence implicated higher than expected activation in the default mode network (DMN) in both SZ and MDD during WM tasks [ 12 ]. Such hyperactivations occurred in the background of reduced activity in the striatum, anterior insula, and frontal lobe [ 13 ] and abnormal functional connectivity of the prefrontal cortex [ 14 – 16 ] in SZ, BD and MDD. These functional deficits were generally more pronounced in SZ (e.g., in bilateral frontoparietal areas [ 17 ]). Taken together, this pattern of triple network hypo/hyperactivity and dysconnectivity indicates a generalized difficulty in making shifts from one brain state to another – a necessary physiological aspect of dynamic large-scale network-level operations [ 18 ]. Effective brain state transitions, achieved through the modulation and organization of task-related neural networks, are vital for the regulation of cognitive, emotional, and behavioral processes [ 19 ]. Network Control Theory emerged from engineering that energetic input regulates transitions from the current active state to another targeted state [ 20 , 21 ]. This theory quantitatively examines how to manipulate brain network components to reach a desired state for functional utility, based on the functional connectivity that links components and their dynamics [ 20 ]. Of the various metrics of Network Control, average controllability refers to the average input energy needed to steer the system into different states with little effort [ 20 ]. Average controllability quantifies the ability of brain areas that can push the brain to easy-to-reach states [ 20 ]. Modal controllability refers to the ability of a node to control each evolutionary mode of a dynamical network [ 22 ]. Modal controllability identifies brain areas that can move the brain into difficult-to-reach states [ 20 ]. Brain areas with high average controllability become ‘hubs’ with high node strength; conversely, modal controllability is associated with low node strength [ 20 ]. Brain controllability during resting state has been previously reported in MPDs. These studies have highlighted the presence of disrupted average and modal controllability across the triple network system and sensorimotor network in relation to symptom burden in first-episode never-treated SZ [ 23 ] as well as in BD [ 24 ]. Disrupted resting-state controllability in MDD appears to carry information that can potentially inform treatment choices (antidepressants/physical therapies) [ 25 , 26 ]. We do not yet know how complex task processing demands, which place greater energy cost and involve difficult-to-reach functional states [ 27 ], constrain state transitions in MPDs. This study examined brain network controllability based on the n-back WM fMRI data from a transdiagnostic sample including patients with SZ, BD, MDD, and HCs. We aimed to characterize brain controllability patterns across different WM loads and their overlapping features across three patient groups. We related disrupted controllability to symptom burden and WM performance. We also indirectly explored the molecular mechanisms underpinning the identified network controllability by analyzing spatial correlations with known patterns of gene expression and the chemoarchitecture of the brain. A schematic overview of the study design and analysis pipeline is shown in Fig. 1 . Methods and materials Participants This study recruited 110 SZ, 70 BD, and 55 MDD from the Second Xiangya Hospital, Central South University, and 82 healthy controls (HCs) from the community. All participants were right-handed native Chinese speakers and were provided written informed consent. The study received approval from the medical ethics committee of the Second Xiangya Hospital, Central South University. All the patients were diagnosed by board-certified psychiatrists using the DSM-5- criteria for SZ, BD, and MDD. Patients aged 18~50 years old with at least 9 years of education were included. Exclusion criteria included neurological disorders, major physical illness, history of substance dependence, history of receiving electroconvulsive therapy, or any contraindications to MRI. The other criteria for states of BD are described in Supplementary Material S 1 . HCs were recruited from the local community through advertisement. The inclusion and exclusion criteria for HCs were the same as those for patients except that the HCs and their first-degree relatives did not have personal histories of any psychiatric disorders. Clinical assessments We adopted the Brief Psychiatric Rating Scale (BPRS), Scale for the Assessment of Positive Symptoms (SAPS), and Scale for the Assessment of Negative Symptoms (SANS) to assess the severity of psychotic symptoms. The Young Mania Rating Scale (YMRS), Hamilton Rating Scale for Depression (HAMD), and Hamilton Rating Scale for Anxiety (HAMA) were used to evaluate the severity of manic, depressive, and anxiety symptoms. MRI data acquisition and preprocessing Imaging scans were performed on a Philips 3.0T scanner with an 8-channel head coil using a gradient-recalled echo-planar imaging (EPI) pulse sequence. Data preprocessing was performed using the DPABI toolbox (DPABI, http://www.rfmri.org/). Preprocessing included: discarded 2 first images, slice timing correction, head motion realignment, spatial normalization to Montreal Neurologic Institute space, and smoothing. The imaging parameters and preprocessing details are presented in Supplementary Material S2 . Working memory task paradigm We applied the n-back task as the WM paradigm, which included “0-back” and “2-back” loads in this study. In the “0-back”, participants pressed a button once when they saw the letter “x”; in the “2-back”, participants pressed a button once when the letter presented was the same as two letters prior. A detailed description of this paradigm is given in Supplementary Material S3 and Figure S1 . Calculation of controllability metrics We first constructed a functional connection matrix before calculating controllability metrics. Each block contains 20 volumes, and thus the “0-back” and “2-back” loads consist of 80 volumes respectively. For each participant, we separately concatenated the 80 volumes obtained under the 4 blocks of the “0-back” load and the 4 blocks of the “2-back” load. We extracted the mean time series from each of the 264 nodes using 6mm spheres defined by the Power atlas [28], and generated a 264 × 264 symmetric matrix for each participant by computing the Pearson correlation coefficients between the time series for each pair of nodes. The resultant matrix was converted to normally distributed scores by using Fisher’s z transformation. Then, two commonly used metrics of network controllability, average controllability, and modal controllability [29], are calculated in the matrices constructed under “0-back” and “2-back” loads, respectively. Details of the calculation of these metrics are provided in Supplementary Material S4 . Statistical analysis The SPSS statistical software (version 22) was adopted to compare the demographic and clinical data and controllability metrics across groups. Differences in age, years of education, clinical data, and “0-back” and “2-back” task performances were analyzed using one-way ANOVA analysis, and sex differences were assessed using χ 2 test ( p <0.05). Controllability metrics of 264 nodes were compared using the ANCOVA test with sex, age, years of education, and head motion as covariates. The 264 nodes were partitioned into various large-scale networks defined by the Power atlas [28]. We also performed correlation analysis to relate the detected regions with altered controllability with clinical and cognitive characteristics after age, gender, education, and head motion controlled. The threshold of statistical significance was set at false discovery rate corrected p ( p FDR )<0.05. Spatial Correlation Analysis We further conducted the imaging transcriptome analysis and neurotransmitter correlation analyses on the average and modal controllability maps of detected regions with omnibus differences across four groups. Imaging transcriptome analysis. We used the Brain Annotation Toolbox (BAT) [30] to perform genetic annotation analysis on the observed regions with abnormal average and modal controllability [30]. The gene expression profiles could be extracted from the Allen Human Brain Atlas (AHBA) [31] via BAT based on the brain regions. The permutation analysis was conducted to identify differentially expressed genes within the specified regions compared to samples in the background [30], with permutation times of 5000. The other parameters for genetic annotations were as follows: ROI size=6mm, minimal sample size=5. The statistical significance level was set as p FDR <0.05. The derived differentially expressed genes were uploaded to the Database for Annotation, Visualization, and Integrated Discovery (DAVID) (https://david.ncifcrf.gov/). The Gene Ontology (GO) database, specifically focusing on 3 domains including the biological process, cellular component, and molecular function, and the Kyoto Encyclopedia of Genes and Genomes (KEGG) database for Homo sapiens sets were adopted to achieve gene function and pathway enrichment analysis. The statistical significance level was set as p FDR <0.05. Neurotransmitter correlation analysis. We adopted JuSpace to explore the neurochemical basis underlying controllability abnormalities. JuSpace is a practical tool for spatial correlation analyses of MRI with nuclear imaging-derived neurotransmitter maps (https://github.com/juryxy/JuSpace)[32], which has been previously used to explore neurochemical basis of neural correlates [33]. We calculated Pearson correlation coefficients between detected regions with abnormal average and modal controllability and various neurotransmitter maps including dopamine, serotonin, glutamate, GABA, acetylcholine, opioid, cannabinoid, noradrenaline, and fluorodopa ( Supplementary Table S1 ), while adjusting for spatial autocorrelation and partial volume with the gray matter probability map [32]. The spatial permutation-based null maps with 5000 permutations were used to compute exact p -values. The statistical significance level was set as p FDR <0.05. Results Demographic and clinical characteristics A total of 303 participants (105 patients with SZ, 67 patients with BD, 51 patients with MDD, and 80 HCs) were enrolled in this study. The demographic and clinical characteristics are shown in Table 1 . There were significant differences in age and education years across four groups and illness duration and medication across patient groups. SZ showed higher a BRPS score than BD and MDD. BD had higher YMRS scores and lower HAMD and HAMA scores than MDD. Patient groups all exhibited poorer WM task performances including lower “0-back” and “2-back” reaction time and target accuracy than HCs. SZ had the lowest “0-back” and “2-back” target accuracy among four groups. Among BD, there were 29 patients in a depressive state, 13 in a manic/hypomanic state, 2 in a mixed state, and 23 in a euthymic state. Group differences in controllability Metrics For the average controllability ( Table 2 and Figure 2A-2D ), we observed significant differences across four groups in the memory retrieval network (MRN; 1 node) under the “0-back” load. Post-hoc analysis revealed that lower average controllability in SZ compared to MDD and HCs. Under the “2-back” load, significant differences across four groups in the visual network (VN; 3 nodes), and the frontoparietal task control network (FPN; 1 node) were identified. SZ and MDD had lower average controllability in VN nodes than BD and HCs. SZ had lower average controllability in the FPN node than other three groups. For the modal controllability, no significant difference among groups was found under the “0-back” load. Under the “2-back” load ( Table 2 and Figure 2E-2G ), we observed significant differences in the sensorimotor network (SMN; 2 nodes), cingulo-opercular network (CON; 1 node), auditory network (AN; 1 node), DMN (2 nodes), VN (1 node), FPN (12 nodes), salience network (SN; 3 nodes), cerebellum (1 node), and dorsal attention network (DAN; 1 node). Post-hoc analysis revealed that SZ showed lower modal controllability in all detected regions than HCs. SZ and MDD showed lower modal controllability in DMN and SN than BD and HCs. SZ, BD, and MDD exhibited shared abnormality of lower modal controllability in FPN compared to HCs. Clinical and cognitive correlation of abnormal average and modal controllability Under the “2-back” load, average controllability of 1 node (ROI No.169) in VN was positively correlated with YMRS scores ( r =0.39, p FDR =0.010) and 0-back target accuracy ( r =0.20, p FDR =0.036). The node (ROI No.179) in FPN was also positively correlated with the 0-back target accuracy ( r =0.21, p FDR =0.036), as shown in Figure 3A and Supplementary Table S2 . We observed positive correlations between the modal controllability of 1 node (ROI No.54) in CON and YMRS scores ( r =0.32, p FDR =0.036). The 0-back target accuracy was positively associated with the modal controllability of two nodes (ROI No.20: r =0.20, p FDR =0.036; ROI No.33: r =0.20, p FDR =0.036) in SMN, 1 node (ROI No.54: r =0.23, p FDR =0.027) in CON, 1 node (ROI No.69: r =0.23, p FDR =0.022) in AN, 2 nodes (ROI No.187: r =0.19, p FDR =0.047; ROI No.202: r =0.20, p FDR =0.036) in FPN, and 1 node (ROI No.213: r =0.20, p FDR =0.036) in SN, as shown in Figure 3B and Supplementary Table S3 . Spatial Correlation Analysis The genetic annotation analyses identified 3245 and 6202 statistically overexpressed genes associated with detected regions of abnormal average and modal controllability respectively ( p FDR <0.05). Enrichment results of GO terms for abnormal average and modal controllability were similar. These genes were mainly enriched in GO terms of synapse-related cellular components, such as “glutamatergic synapse”, “synapse”, and “GABAergic synapse” (all p FDR <0.05; Figure 4A , 4C ). In the enrichment results of the KEGG pathway, we noted that differentially expressed genes for abnormal average and modal controllability were both enriched in organismal systems, such as “glutamatergic synapse”, “dopaminergic synapse”, and “GABAergic synapse”; in addition, the differentially expressed genes for abnormal modal controllability were also enriched in the “metabolic pathways” (all p FDR <0.05; Figure 4B , 4D ). We further investigated the spatial relationship between neurotransmitter systems and abnormal average and modal controllability respectively. The average controllability was negatively associated with opioid receptors (MOR_1: r =-0.31, p FDR =0.013; MOR_2: r =-0.33, p FDR =0.012, Figure 4E and Supplementary Table S3 ). The abnormal modal controllability overlapped with regions that had higher concentration of 5-hydroxytryptamine (5-HT; 5HT1b_1: r =0.28, p FDR =0.015; 5HT1a_2: r =0.27, p FDR =0.015), cannabinoid (CB1: r =0.33, p FDR =0.005), glutamate (mGluR5_1: r =0.24, p FDR =0.035; mGluR5_2: r =0.27, p FDR =0.015; mGluR5_3: r =0.28, p FDR =0.015), and opioid receptors (KOR: r =0.35, p FDR =0.005) ( Figure 4F and Supplementary Table S4 . Discussion The present study unveiled brain controllability patterns during WM tasks among MPDs, with a potential link to gene and neurotransmitter profiles. SZ showed reduced average and modal controllability in all detected regions than HCs, suggesting that the generalized reduction in the capacity to control transition dynamics during WM task is most pronounced in SZ among MPDs. We highlight three more specific findings. First, under the “2-back” load, SZ exhibited the lower average controllability of FPN nodes compared with BD and MDD who already had lower controllability than HCs. SZ and MDD had lower modal controllability of DMN and SN nodes relative to BD and HCs. Second, SZ and MDD showed lower average controllability of VN nodes compared with BD and HCs. SZ had lower modal controllability of SMN, AN, and VN nodes than HCs. Correlation analyses revealed that lower average and modal controllability of FPN, SN, VN, SMN, and AN nodes were associated with poor WM task performances. Third, gene annotation and enrichment analyses suggest that differentially overexpressed genes associated with abnormal controllability may be involved in distributed synaptic functions within the glutamatergic and GABAergic systems. There were significant associations between abnormal controllability and specific neurotransmitter systems including glutamate, opioid, 5-HT, and cannabinoid receptors. We noted that under the “0-back” load there were few significant differences in average and modal controllability in patient groups compared with HCs; when the WM load increased, patient groups, especially SZ, had altered controllability in distributed brain areas. Increased complexity/load of n-back task likely demands more manipulation of cognitive resources, as evidenced by extensive functional recruitment [ 34 ]. Most areas recognized for their role in WM exhibited load-dependent activity and connectivity when performing WM tasks in SZ [ 35 ]; our results are in concordance with this literature. We observed that SZ had lower average controllability of FPN than BD, MDD, and HCs; SZ, BD, and MDD shared lower modal controllability of FPN than HCs. FPN plays an important role in the top-down modulation of cortical dynamic activity during preparatory attention and orientation within WM [ 36 ]. Impaired functional activation and connectivity in FPN during WM tasks have been demonstrated in SZ [ 37 , 38 ]. Our previous work [ 39 ] reported that compared to HCs, SZ had increased temporal variability of degree centrality in the inferior parietal lobe under the “2-back” load, which was the critical node of FPN in our results. Our results extend and complement the abnormal WM-related functional controllability of FPN in SZ based on Network Control Theory. We hypothesize that the excessive neural dynamics observed in SZ may lead to instability, confusion, and an inability to effectively organize and modulate brain activity to achieve desired brain states. Among MPDs, SZ had the illness-specific low average controllability of FPN, and the low modal controllability of FPN appears to be a transdiagnostic trait. Average controllability focuses on the ability of driving brain states to expected easy-to-reach states and modal controllability reflects the ability to transition toward difficult-to-reach states. We speculated that in BD and MDD, FPN only showed abnormal functional dynamics when performing complex cognitive processes. In a previous transdiagnostic study, patients with MPDs showed reduced functional connectivity of FPN than HCs, and patients with psychosis had reduced connectivity of FPN than patients without psychosis in a resting state [ 40 ]. This finding implicates a shared functional dysconnectivity of FPN across MPDs, with a more pronounced dysconnectivity in psychosis. Our results indicate that brain controllability may serve as a more sensitive metric for detecting both transdiagnostic and SZ-specific functional features of FPN during WM tasks among MPDs. We noted that SZ and MDD had lower modal controllability of DMN and SN than BD and HCs under the “2-back” load. Lower controllability of FPN and SN nodes were associated with poor WM task performances. The classical triple network model of cognitive control system emphasizes the key role of coordination of the DMN, SN, and FPN in the execution of WM [ 41 ]. It is proposed that SN facilitates switching brain networks, resulting in the engagement of FPN to manage oriented attention, and disengagement of the DMN to be involved in oriented self-referential mental processes during WM tasks [ 42 ]. The insula in the SN is an integral hub in driving dynamic interactions among large-scale networks [ 42 ]. Our results indicated that this cognitive triple network model less readily shifts to expected difficult-to-reach states, which is consistent with previous work on functional dysconnectivity of triple network shared in MDD and SZ [ 43 ]. The disrupted dynamics of the triple network may contribute to negative symptoms in SZ, as well as psychomotor retardation in MDD. Differences of controllability in sensory cortex (SMN, AN, and VN) had also been observed among groups under the “2-back” load. SZ and MDD showed lower average controllability of VN compared with BD and HCs. SZ had lower modal controllability of SMN, AN, and VN than HCs, and other patient groups did not differ from HCs, indicating that activity of the sensory cortex may less readily drive brain states transition to desired states necessary for WM tasks. This might be related to the abnormal activation and connectivity of sensory systems under WM in SZ [ 35 , 44 ]. This functional deficiency in the sensory cortex may impair the ability to effectively process diverse external sensory stimulation, especially visual stimulation, and integrate this information with higher-level systems [ 45 ]. Our results highlight that SZ exhibited a notable transition disturbance of the sensory cortex, which is crucial for cognitive tasks. We explored and elucidated the gene expression, transcription, and neurotransmitter to provide an integrated interpretation of the molecular mechanisms underpinning the identified network controllability. Neurotransmitters in the brain are partially driven by gene expression profiles, and disruptions in neurotransmitter balance can lead to abnormal signal transmission and neural activity, thereby impairing cognitive function [ 46 , 47 ]. Our results demonstrated that the relevant gene expression primarily pertains to neurotransmitter systems, including GO categories involving glutamatergic synapse and GABAergic synapse, and KEGG pathway involving glutamatergic synapse, dopaminergic synapse, and GABAergic synapse. The neurotransmitter correlation analysis also revealed that glutamate and 5-HT were associated with abnormal controllability. The classical and common neurotransmitter hypotheses concerning the pathogenic mechanisms of MPDs have emphasized altered neurotransmission in the dopamine and 5-HT pathways, along with the inhibitory-excitatory imbalance mediated by GABA and glutamate [ 48 – 50 ]. Previous studies have identified that these neurotransmitters play critical roles in cognitive function and may hold potential as the targets for treating cognitive deficits [ 51 – 53 ]. These converging findings from gene expression and neurotransmitter analyses suggested disruptions in these classical neurotransmitter pathways may underlie neural dysregulation when performing WM tasks in MPDs. Beyond MPDs, our findings also have implications for uncovering domain-general computational principles of WM highlighted as a priority in a recent review [ 54 ]. Several limitations need to be considered. First, three patient groups showed significant differences in the age and education years. Despite incorporating these variables as covariates in the controllability analyses, they may still introduce confounding effects. Second, the BD group comprised patients in various states - depressive, manic/hypomanic, mixed, and euthymic states. While this inclusion provides a more comprehensive view of BD, it introduces a degree of heterogeneity that may obscure state-specific brain controllability patterns associated with each clinical presentation. Third, as our study was cross-sectional, we cannot infer any causal relationship between abnormal brain controllability and MPDs. It remains unknown whether these controllability patterns vary with the different stages of illness duration. Future longitudinal studies comparing the controllability across pre- and post-treatment states, as well as during illness onset and remission will be needed. Third, this study only calculated the controllability based on fMRI data. There are likely abnormal structural controllability patterns of MPDs based on other imaging modalities, which have been explored in neurological disorders [ 55 , 56 ]. A previous study revealed structural controllability was positively correlated with functional participation coefficient, and played a mediating role in brain anatomical structure to support functional dynamics [ 57 ]. Therefore, investigations on structural controllability may elucidate the structural foundations that facilitate the transition of brain states in response to diverse cognitive tasks. Moreover, future transdiagnostic studies could adopt WM tasks with a greater diversity of difficulty levels to identify shared and illness-specific load-dependent controllability patterns. Conclusion Aberrant brain network controllability during WM in MPDs affects the triple network (FPN, DMN, SN) and sensory systems (SMN, AN, and VN) in SZ and other MPDs, and has a synaptic and neurotransmitter basis pertaining to glutamate, dopamine, GABA, and 5-HT, all of which play key roles in the clinical expression of MPDs. These results provide novel insight into a shared dysfunction in the ability to switch network states required for WM in MPDs. Declarations Contributors Jie Yang, Zhening Liu, and Lena Palaniyappan designed the research. Jun Yang, Feiwen Wang, Wenjian Tan, Danqing Huang, Xuan Ouyang, Haojuan Tao, Guowei Wu, and Yunzhi Pan collected the data. Jun Yang and Jie Yang analyzed the data and wrote the manuscript along with Lena Palaniyappan. Zhening Liu and Lena Palaniyappan revised various versions of the manuscript. All authors reviewed the manuscript and approved the submitted version. Acknowledgments We would like to thank all participants in this study. This work was supported by grants from the National Natural Science Foundation of China (82071506 to Zhening Liu, 82201663 to Jie Yang), the Training Program for Excellent Young Innovators of Changsha (kq2306008 to Jie Yang), the Scientific Research Program of Hunan Provincial Health Commission, China (B202303095947 to Jie Yang), and the Scientific Research Launch Project for new employees of the Second Xiangya Hospital of Central South University to Jie Yang. Lena Palaniyappan’s research is supported by the Canada First Research Excellence Fund, awarded to the Healthy Brains, Healthy Lives initiative at McGill University (through a New Investigator Supplement to LP) and Monique H, Bourgeois Chair in Developmental Disorders. He receives a salary award from the Fonds de recherche du Québec-Santé (FROS). Conflict of Interest Lena Palaniyappan reports personal fees for serving as chief editor from the Canadian Medical Association Journals, speaker/consultant fee from Janssen Canada and Otsuka Canada, SPMM Course Limited, UK, Canadian Psychiatric Association; book royalties from Oxford University Press; investigator-initiated educational grants from Janssen Canada, Sunovion and Otsuka Canada outside the submitted work. All other authors report no potential conflicts. Supplementary information is available at MP’s website. References Hartley T, Hitch GJ. Working Memory. Oxford University Press2022. Park S, Püschel J, Sauter BH, Rentsch M, Hell D. Spatial working memory deficits and clinical symptoms in schizophrenia: a 4-month follow-up study. Biological psychiatry 1999; 46 (3) : 392-400. Soraggi-Frez C, Santos FH, Albuquerque PB, Malloy-Diniz LF. Disentangling Working Memory Functioning in Mood States of Bipolar Disorder: A Systematic Review. Frontiers in psychology 2017; 8: 574. 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Tables Table 1 Demographic and clinical characteristics of each group Variables SZ (n=105) BD (n=67) MDD (n=51) HCs (n=80) c 2 / F / t p Post hoc analysis Comparisons LSD-t p Gender (M/F) 63/42 30/37 28/23 39/41 4.53 a 0.209 - - - Age (years) 25.32±5.59 26.19±5.65 29.45±8.12 23.23±4.30 12.21 b <0.001 SZ<MDD -4.15 HCs 2.05 0.042 BDHCs 2.73 0.007 MDD>HCs 5.60 <0.001 Education (years) 11.87±2.74 13.31±2.79 12.14±3.07 13.95±2.56 10.36 b <0.001 SZ<BD -3.33 0.001 SZ<HCs -5.05 MDD 2.28 0.023 MDD<HCs -3.67 <0.001 Illness duration (m) 28.25±32.01 52.32±51.45 47.56±58.76 - 6.67 b 0.002 SZ<BD -3.39 0.001 SZ<MDD -2.47 0.014 CPZ 410.10±211.32 227.98±247.02 54.72±150.31 - 51.00 b BD 5.50 MDD 9.87 MDD 4.41 <0.001 FLU 0.80±4.06 9.97±14.45 23.63±18.25 - 61.77 b <0.001 SZ<BD -4.83 <0.001 SZ<MDD -11.07 <0.001 BD<MDD -6.06 <0.001 SANS 36.57±28.54 - - - - - - - - SAPS 20.86±15.41 - - - - - - - - BPRS 37.97±11.30 26.78±7.69 28.69±5.78 - 28.76 b BD 7.16 MDD 5.63 <0.001 YMRS - 6.57±8.78 2.35±2.74 - 3.65 c <0.001 - - - HAMD - 12.78±9.61 19.41±6.38 - -4.45 c <0.001 - - - HAMA - 9.97±9.33 15.55±8.51 - -3.32 0.001 - - - 0-back target ACC 0.73±0.28 0.88±0.15 0.90±0.15 0.92±0.14 14.09 b <0.001 SZ<BD -4.15 <0.001 SZ<MDD -4.30 <0.001 SZ<HCs -5.59 HCs 4.03 HCs 2.25 0.025 MDD>HCs 2.45 0.015 2-back target ACC 0.49±0.25 0.60±0.27 0.62±0.23 0.74±0.18 16.19 b <0.001 SZ<BD -2.79 0.006 SZ<MDD -3.06 0.002 SZ<HCs -6.68 <0.001 BD<HCs -3.28 0.001 MDDHCs 2.14 0.033 BD>HCs 3.06 0.004 MDD>HCs 2.18 0.030 Note: Quantitative data were presented as mean ± standard deviation. Abbreviations: SZ, Schizophrenia; BD, bipolar disorder; MDD, major depressive disorder patients; HCs, healthy controls; M/F, male/female; m, month; CPZ, chlorpromazine equivalent dose [58]; FLU, fluoxetine equivalents dose [59]; SANS, Scale for the Assessment of Negative Symptoms; SAPS, Scale for the Assessment of Positive Symptoms; BPRS, Brief Psychiatric Rating Scale; YMRS, Young Mania Rating Scale; HAMD, Hamilton Depression Rating Scale; ACC, accuracy; RT, response time. a χ 2 test; b One-way ANOVA; c Two-sample t-test. Table 2 Significant differences in average and modal controllability under“0-back” and“2-back” loads among all groups ROI Network Brain Regions MNI F p FDR Post-hoc analysis X Y Z Comparisons t p Bon Average controllability under “0-back” load 136 MRN R Posterior Cingulate Cortex 4 -48 51 7.86 0.013 SZ<MDD -3.99 <0.001 SZ<HCs -3.88 0.001 Average controllability under “2-back” load 159 VN R Cuneus 15 -77 31 6.14 0.030 SZ<BD -3.39 0.005 SZ<HCs -3.85 0.001 160 VN L Lingual Gyrus -16 -52 -1 6.51 0.025 SZMDD 3.60 0.002 MDD<HCs -3.80 0.001 169 VN R Middle Occipital Gyrus 37 -84 13 7.73 0.015 SZ<BD -3.77 0.001 SZMDD 3.12 0.012 MDD<HCs -2.99 0.019 179 FPN R Inferior Temporal Gyrus 58 -53 -14 7.11 0.017 SZ<BD -2.88 0.026 SZ<MDD -3.76 0.001 SZ<HCs -3.65 0.002 Modal controllability under “2-back” load 20 SMN L Postcentral Gyrus -54 -23 43 5.41 0.020 SZ<HCs -4.63 0.001 BD<HCs -2.15 0.027 33 SMN L Postcentral Gyrus -45 -32 47 5.51 0.020 SZ<HCs -4.71 0.001 54 CON R Medial Frontal Gyrus 7 8 51 7.23 0.008 SZ<BD -2.06 0.034 SZ<HCs -4.22 <0.001 69 AN L Postcentral Gyrus -53 -22 23 5.07 0.029 SZ<HCs -2.67 0.001 96 DMN R Angular Gyrus 52 -59 36 6.08 0.013 SZ<HCs -4.28 <0.001 137 DMN L Inferior Frontal Gyrus -46 31 -13 5.67 0.019 SZ<BD -2.10 0.040 SZ<HCs -4.29 0.001 172 VN L Inferior Occipital Gyrus -33 -79 -13 4.63 0.040 SZ<HCs -4.01 0.005 176 FPN L Inferior Frontal Gyrus -47 11 23 4.65 0.040 SZ<HCs -4.32 0.002 187 FPN L Inferior Frontal Gyrus -41 6 33 6.42 0.012 SZ<HCs -4.53 <0.001 MDD<HCs -3.64 0.017 190 FPN R Inferior Parietal Lobule 49 -42 45 4.43 0.048 SZ<HCs -4.39 0.003 191 FPN L Superior Parietal Lobule -28 -58 48 4.61 0.040 SZ<HCs -3.95 0.001 192 FPN R Inferior Parietal Lobule 44 -53 47 4.97 0.031 SZ<HCs -4.29 0.001 194 FPN R Inferior Parietal Lobule 37 -65 40 5.60 0.019 SZ<HCs -4.57 0.001 MDD<HCs -3.68 0.006 195 FPN L Inferior Parietal Lobule -42 -55 45 5.82 0.017 SZ<HCs -4.28 <0.001 197 FPN L Middle Frontal Gyrus -34 55 4 7.14 0.008 SZ<HCs -4.90 <0.001 BD<HCs -2.28 0.005 MDD<HCs -1.97 0.030 198 FPN L Middle Frontal Gyrus -42 45 -2 9.29 0.002 SZ<HCs -5.32 <0.001 BD<HCs -2.47 0.036 199 FPN R Inferior Parietal Lobule 33 -53 44 6.40 0.012 SZ<HCs -4.05 <0.001 MDD<HCs -3.26 0.009 201 FPN L Middle Frontal Gyrus -42 25 30 7.40 0.008 SZ<HCs -4.53 <0.001 BD<HCs -2.11 0.029 MDD<HCs -3.65 0.001 202 FPN L Superior Frontal Gyrus -3 26 44 6.13 0.013 SZ<HCs -4.65 <0.001 208 SN L Insula -35 20 0 5.48 0.020 SZ<HCs -4.79 0.001 MDD<HCs -3.85 0.010 209 SN R Insula 36 22 3 4.86 0.034 SZ<HCs -4.73 0.001 213 SN L Median cingulate and paracingulate gyri -1 15 44 4.32 0.049 SZ<HCs -4.28 0.002 246 Cerebellar R Cerebellum Posterior Lobe 1 -62 -18 4.80 0.035 SZ<HCs -2.72 0.004 261 DAN L Middle Frontal Gyrus -32 -1 54 6.50 0.012 SZ<HCs -4.52 <0.001 182 Uncertain L Middle Frontal Gyrus -21 41 -20 5.11 0.029 SZ<HCs -4.71 0.002 BD<HCs -3.79 0.014 183 Uncertain L Cerebellum Posterior Lobe -18 -76 -24 6.10 0.013 SZ<HCs -4.34 <0.001 Note: ROI refers to the index number of the node in the Power Atlas. Abbreviations: FDR, False Discovery Rate correction; Bon, Bonferroni correction; MRN, Memory Retrieval Network; VN, Visual Network; FPN, Frontoparietal Task Control Network; SMN, Sensory/somatomotor Network; CON, Cingulo-opercular Task Control Network; AN, Auditory Network; DMN, Default Mode Network; SN, Salience Network; DAN, Dorsal Attention Network; L, left; R, right; SZ, Schizophrenia; BD, bipolar disorder; MDD, major depressive disorder patients; HCs, healthy controls. Additional Declarations Yes This work was supported by grants from the National Natural Science Foundation of China (82071506 to Zhening Liu, 82201663 to Jie Yang), the Training Program for Excellent Young Innovators of Changsha (kq2306008 to Jie Yang), the Scientific Research Program of Hunan Provincial Health Commission, China (B202303095947 to Jie Yang), and the Scientific Research Launch Project for new employees of the Second Xiangya Hospital of Central South University to Jie Yang. Lena Palaniyappan’s research is supported by the Canada First Research Excellence Fund, awarded to the Healthy Brains, Healthy Lives initiative at McGill University (through a New Investigator Supplement to LP) and Monique H, Bourgeois Chair in Developmental Disorders. He receives a salary award from the Fonds de recherche du Québec-Santé (FROS). Lena Palaniyappan reports personal fees for serving as chief editor from the Canadian Medical Association Journals, speaker/consultant fee from Janssen Canada and Otsuka Canada, SPMM Course Limited, UK, Canadian Psychiatric Association; book royalties from Oxford University Press; investigator-initiated educational grants from Janssen Canada, Sunovion and Otsuka Canada outside the submitted work. All other authors report no potential conflicts. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5412595","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":387231907,"identity":"40f880bb-d87f-4066-b28a-26768c769111","order_by":0,"name":"Jie 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University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yunzhi","middleName":"","lastName":"Pan","suffix":""},{"id":387231917,"identity":"1e8ca484-1113-43c6-b5e0-2550632dbc55","order_by":10,"name":"Lena Palaniyappan","email":"","orcid":"https://orcid.org/0000-0003-1640-7182","institution":"Douglas Mental Health University Institute","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lena","middleName":"","lastName":"Palaniyappan","suffix":""}],"badges":[],"createdAt":"2024-11-08 00:05:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5412595/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5412595/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":72300895,"identity":"8044b98d-5617-4fa5-95af-dcdc21ca38a6","added_by":"auto","created_at":"2024-12-25 01:25:06","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1576993,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA schematic overview of the study design and analysis pipeline.\u003c/strong\u003e This study collected N-back task-based fMRI data from a transdiagnostic sample of patients with SZ, BD, MDD, and HCs. The time series under “0-back” and “2-back” were extracted and functional connectomes based on Power atlas [28] were constructed. Controllability metrics were calculated in the functional matrices. Average controllability quantifies the ability to transition into easy-to-reach states with little effort; modal controllability quantifies the ability to transition into difficult-to-reach states with large effort. We further identified the difference in controllability among groups and explored associations between abnormal controllability and clinical symptoms, cognitive performances, gene expression and neurotransmitter profiles.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-5412595/v1/781502f8930254cabda159e1.png"},{"id":72300899,"identity":"e5386195-15cd-4574-82df-23c403bed661","added_by":"auto","created_at":"2024-12-25 01:25:06","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":3595097,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eBrain regions with significant differences in average and modal controllability. \u003c/strong\u003eA) and C) Brain maps show the regions with omnibus differences in average controllability under “0-back” and “2-back” loads respectively. B) and D) Violin plots show average controllability values in detected regions for each group. In D), the mean values of average controllability of three nodes in VN are adopted to describe the average controllability in VN. E) Brain map shows the regions with omnibus differences in modal controllability under the “2-back” load. F) Radar map exhibits the modal controllability values in detected regions for each group. Similarly, the mean values of modal controllability of all detected nodes in the corresponding network are used if the network has several nodes. G) Pie chart shows the proportion of detected nodes in each large-scale network. MRN, Memory Retrieval Network; VN, Visual Network; FPN, Frontoparietal Task Control Network; SMN, Sensory/somatomotor Network; CON, Cingulo-opercular Task Control Network; AN, Auditory Network; DMN, Default Mode Network; SN, Salience Network; DAN, Dorsal Attention Network; SZ, Schizophrenia; BD, bipolar disorder; MDD, major depressive disorder patients; HCs, healthy controls.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-5412595/v1/a9ec81c94ff860c18e55f6c9.png"},{"id":72300896,"identity":"1ae9ea85-739e-41dd-aa7a-c525ff9c7d0a","added_by":"auto","created_at":"2024-12-25 01:25:06","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":482512,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eClinical and cognitive correlation of abnormal average controllability and modal controllability. \u003c/strong\u003eA) Heat map depicts the correlation between regions with omnibus differences in average controllability and clinical and cognitive characteristics under “0-back” and “2-back” loads. B) Heat map depicts the correlation between regions with omnibus differences in modal controllability and clinical and cognitive characteristics under the “2-back” load. ROI refers to the index number of the node in the Power Atlas. SAPS, Scale for the Assessment of Positive Symptoms; SANS, Scale for the Assessment of Negative Symptoms; BPRS, Brief Psychiatric Rating Scale; YMRS, Young Mania Rating Scale; HAMD, Hamilton Depression Rating Scale; ACC, accuracy; RT, response time; MRN, Memory Retrieval Network; VN, Visual Network; FPN, Frontoparietal Task Control Network; SMN, Sensory/somatomotor Network; CON, Cingulo-opercular Task Control Network; AN, Auditory Network; DMN, Default Mode Network; SN, Salience Network; DAN, Dorsal Attention Network. \u003csup\u003ea\u003c/sup\u003e Under the “0-back” load; \u003csup\u003eb \u003c/sup\u003eUnder the “2-back” load; * \u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR\u003c/sub\u003e \u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-5412595/v1/4cddf95ec50103f005af19a8.png"},{"id":72300898,"identity":"ccd48193-5642-4a4d-a78d-9a2981a3c700","added_by":"auto","created_at":"2024-12-25 01:25:06","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2492118,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSpatial correlation between transcriptome and neurotransmitter and abnormal average controllability and modal controllability. \u003c/strong\u003eA) and C) The top 20 significantly enriched GO terms associated with abnormal average and modal controllability. B) and D) The top 20 significantly enriched KEGG terms associated with abnormal modal controllability abnormal average and modal controllability. E) and F) Neurotransmitters associated with abnormal average (E) and modal controllability (F). FDR, False Discovery Rate correction; BP, biological process; CC, cellular component; MF, molecular function; 5-HT, 5-hydroxytryptamine; SERT, serotonin transporter; CB1, cannabinoid type 1; D, dopamine; DAT, dopamine transporter: FDOPA. fluorodopa; GABAa, gamma-aminobutyric acid a; KOR, kappa opioid receptor; MOR, mu opioid receptor; NAT, noradrenaline transporter; NMDA, N-methyl-D-aspartic acid; SERT, serotonin transporter; VAChT, vesicular acetylcholine transporter; mGluR5, metabotropic glutamate type 5. * \u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR\u003c/sub\u003e \u0026lt; 0.05, ** \u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR\u003c/sub\u003e \u0026lt; 0.01.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-5412595/v1/f93dbac0a0363be55ddf9d20.png"},{"id":75172899,"identity":"7727c608-5555-40ad-a476-6afb913062b7","added_by":"auto","created_at":"2025-01-31 14:39:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":9552920,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5412595/v1/4d200579-597c-4d75-ac18-0cc617abe048.pdf"},{"id":72300897,"identity":"61599af6-70f1-4327-a705-7f18033a66cb","added_by":"auto","created_at":"2024-12-25 01:25:06","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":271370,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"SupplementaryControllabilityunderWMinMPDsMPnew.docx","url":"https://assets-eu.researchsquare.com/files/rs-5412595/v1/9fa52fa67c80572720c72c92.docx"}],"financialInterests":"\u003cb\u003eYes\u003c/b\u003e\nThis work was supported by grants from the National Natural Science Foundation of China (82071506 to Zhening Liu, 82201663 to Jie Yang), the Training Program for Excellent Young Innovators of Changsha (kq2306008 to Jie Yang), the Scientific Research Program of Hunan Provincial Health Commission, China (B202303095947 to Jie Yang), and the Scientific Research Launch Project for new employees of the Second Xiangya Hospital of Central South University to Jie Yang. Lena Palaniyappan’s research is supported by the Canada First Research Excellence Fund, awarded to the Healthy Brains, Healthy Lives initiative at McGill University (through a New Investigator Supplement to LP) and Monique H, Bourgeois Chair in Developmental Disorders. He receives a salary award from the Fonds de recherche du Québec-Santé (FROS).\r\nLena Palaniyappan reports personal fees for serving as chief editor from the Canadian Medical Association Journals, speaker/consultant fee from Janssen Canada and Otsuka Canada, SPMM Course Limited, UK, Canadian Psychiatric Association; book royalties from Oxford University Press; investigator-initiated educational grants from Janssen Canada, Sunovion and Otsuka Canada outside the submitted work. All other authors report no potential conflicts.","formattedTitle":"Task-related Controllability of Functional Connectome During a Working Memory Task in Schizophrenia, Bipolar Disorder, and Major Depressive Disorder","fulltext":[{"header":"Introduction","content":"\u003cp\u003eWorking memory (WM) refers to the ability to store, manipulate, and update temporary information for goal-directed behavior, which is the basis of advanced cognitive functions [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The WM deficit has long been recognized as a prominent and common cognitive impairment in major psychiatric disorders (MPDs; e.g., schizophrenia [SZ], bipolar disorders [BD], and major depressive disorders [MDD]), persisting even after remission[\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], and significantly impacting patients\u0026rsquo; quality of life and functional outcomes [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The transdiagnostic neurobiological basis of WM deficits are yet to be uncovered in MPDs which share overlapping clinical, genetic, and neuropathophysiological characteristics [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTask-based functional MRI (fMRI) approaches capture behaviorally-relevant, instantaneous neural processes evoked by cognitive tasks [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. During WM tasks, both SZ and BD exhibited greater activations in the triple network system comprised of frontoparietal network (FPN), dorsal attentional network (DAN), and executive control/salience network than healthy controls (HCs) [SZ\u0026thinsp;\u0026gt;\u0026thinsp;BD] [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Meta-analytic evidence implicated higher than expected activation in the default mode network (DMN) in both SZ and MDD during WM tasks [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Such hyperactivations occurred in the background of reduced activity in the striatum, anterior insula, and frontal lobe [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] and abnormal functional connectivity of the prefrontal cortex [\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] in SZ, BD and MDD. These functional deficits were generally more pronounced in SZ (e.g., in bilateral frontoparietal areas [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]). Taken together, this pattern of triple network hypo/hyperactivity and dysconnectivity indicates a generalized difficulty in making shifts from one brain state to another \u0026ndash; a necessary physiological aspect of dynamic large-scale network-level operations [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eEffective brain state transitions, achieved through the modulation and organization of task-related neural networks, are vital for the regulation of cognitive, emotional, and behavioral processes [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Network Control Theory emerged from engineering that energetic input regulates transitions from the current active state to another targeted state [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. This theory quantitatively examines how to manipulate brain network components to reach a desired state for functional utility, based on the functional connectivity that links components and their dynamics [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Of the various metrics of Network Control, \u003cem\u003eaverage controllability\u003c/em\u003e refers to the average input energy needed to steer the system into different states with little effort [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Average controllability quantifies the ability of brain areas that can push the brain to easy-to-reach states [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. \u003cem\u003eModal controllability\u003c/em\u003e refers to the ability of a node to control each evolutionary mode of a dynamical network [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Modal controllability identifies brain areas that can move the brain into difficult-to-reach states [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Brain areas with high average controllability become \u0026lsquo;hubs\u0026rsquo; with high node strength; conversely, modal controllability is associated with low node strength [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBrain controllability during resting state has been previously reported in MPDs. These studies have highlighted the presence of disrupted average and modal controllability across the triple network system and sensorimotor network in relation to symptom burden in first-episode never-treated SZ [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] as well as in BD [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Disrupted resting-state controllability in MDD appears to carry information that can potentially inform treatment choices (antidepressants/physical therapies) [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. We do not yet know how complex task processing demands, which place greater energy cost and involve difficult-to-reach functional states [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], constrain state transitions in MPDs.\u003c/p\u003e \u003cp\u003eThis study examined brain network controllability based on the n-back WM fMRI data from a transdiagnostic sample including patients with SZ, BD, MDD, and HCs. We aimed to characterize brain controllability patterns across different WM loads and their overlapping features across three patient groups. We related disrupted controllability to symptom burden and WM performance. We also indirectly explored the molecular mechanisms underpinning the identified network controllability by analyzing spatial correlations with known patterns of gene expression and the chemoarchitecture of the brain. A schematic overview of the study design and analysis pipeline is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Methods and materials","content":"\u003ch3\u003eParticipants\u003c/h3\u003e\n\u003cp\u003eThis study recruited 110 SZ, 70 BD, and 55 MDD from the Second Xiangya Hospital, Central South University, and 82 healthy controls (HCs) from the community. All participants were right-handed native Chinese speakers and\u0026nbsp;were provided written informed consent. The study received approval from the medical ethics committee of the Second Xiangya Hospital, Central South University.\u003c/p\u003e\n\u003cp\u003eAll the patients were diagnosed by board-certified psychiatrists using the DSM-5- criteria for SZ, BD, and MDD. Patients aged 18~50 years old with at least 9 years of education were included.\u0026nbsp;Exclusion criteria included neurological disorders, major physical illness, history of substance dependence, history of receiving electroconvulsive therapy, or any contraindications to MRI. The other criteria for states of BD are described in \u003cem\u003eSupplementary Material S\u003c/em\u003e\u003cem\u003e1\u003c/em\u003e. HCs were recruited from the local community through advertisement. The inclusion and exclusion criteria for HCs were the same as those for patients except that the HCs and their first-degree relatives did not have personal histories of any psychiatric disorders.\u003c/p\u003e\n\u003ch3\u003eClinical assessments\u003c/h3\u003e\n\u003cp\u003eWe adopted the Brief Psychiatric Rating Scale (BPRS), Scale for the Assessment of Positive Symptoms (SAPS), and Scale for the Assessment of Negative Symptoms (SANS) to assess the severity of psychotic symptoms. The Young Mania Rating Scale (YMRS), Hamilton Rating Scale for Depression (HAMD), and Hamilton Rating Scale for Anxiety (HAMA) were used to evaluate the severity of manic, depressive, and anxiety symptoms.\u003c/p\u003e\n\u003ch3\u003eMRI data acquisition and preprocessing\u003c/h3\u003e\n\u003cp\u003eImaging scans were performed on a Philips 3.0T scanner with an 8-channel head coil using a gradient-recalled echo-planar imaging (EPI) pulse sequence.\u0026nbsp;Data preprocessing was performed using the DPABI toolbox (DPABI, http://www.rfmri.org/). Preprocessing included: discarded 2 first images, slice timing correction, head motion realignment, spatial normalization to Montreal Neurologic Institute space, and smoothing. The imaging parameters and preprocessing details are presented in \u003cem\u003eSupplementary Material S2\u003c/em\u003e.\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003eWorking memory task paradigm\u003c/h3\u003e\n\u003cp\u003eWe applied the n-back task as the WM paradigm, which included \u0026ldquo;0-back\u0026rdquo; and \u0026ldquo;2-back\u0026rdquo; loads in this study. In the \u0026ldquo;0-back\u0026rdquo;, participants pressed a button once when they saw the letter \u0026ldquo;x\u0026rdquo;; in the \u0026ldquo;2-back\u0026rdquo;, participants pressed a button once when the letter presented was the same as two letters prior. A detailed description of this paradigm is given in \u003cem\u003eSupplementary Material S3\u0026nbsp;\u003c/em\u003eand\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cem\u003eFigure S1\u003c/em\u003e.\u003c/p\u003e\n\u003ch3\u003eCalculation of controllability metrics\u003c/h3\u003e\n\u003cp\u003eWe first constructed a functional connection matrix before calculating controllability metrics. Each block contains 20 volumes, and thus the \u0026ldquo;0-back\u0026rdquo; and \u0026ldquo;2-back\u0026rdquo; loads consist of 80 volumes respectively. For each participant, we separately concatenated the 80 volumes obtained under the 4 blocks of the \u0026ldquo;0-back\u0026rdquo; load and the 4 blocks of the \u0026ldquo;2-back\u0026rdquo; load. We extracted the mean time series from each of the 264 nodes using 6mm spheres defined by the Power atlas [28], and generated a\u0026nbsp;264 \u0026times; 264 symmetric matrix for each participant by computing the Pearson correlation coefficients between the time series for each pair of nodes. The resultant matrix was converted to normally distributed scores by using Fisher\u0026rsquo;s z transformation.\u003c/p\u003e\n\u003cp\u003eThen, two commonly used metrics of network controllability, average controllability, and modal controllability [29], are calculated in the matrices constructed under \u0026ldquo;0-back\u0026rdquo; and \u0026ldquo;2-back\u0026rdquo; loads, respectively. Details of the calculation of these metrics are provided in \u003cem\u003eSupplementary Material S4\u003c/em\u003e.\u003c/p\u003e\n\u003ch3\u003eStatistical analysis\u003c/h3\u003e\n\u003cp\u003eThe SPSS statistical software (version 22) was adopted to compare the demographic and clinical data and controllability metrics across groups. Differences in age, years of education, clinical data, and \u0026ldquo;0-back\u0026rdquo; and \u0026ldquo;2-back\u0026rdquo; task performances were analyzed using one-way ANOVA analysis, and sex differences were assessed using \u0026chi;\u003csup\u003e2\u003c/sup\u003e test (\u003cem\u003ep\u003c/em\u003e \u0026lt;0.05).\u0026nbsp;Controllability metrics of 264 nodes were compared using the ANCOVA test with sex, age, years of education, and head motion as covariates. The 264 nodes were partitioned into various large-scale networks defined by the Power atlas [28]. We also performed correlation analysis to relate the detected regions with altered controllability with clinical and cognitive characteristics after age, gender, education, and head motion controlled. The threshold of statistical significance was set at false discovery rate corrected\u003cem\u003e\u0026nbsp;p\u003c/em\u003e (\u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR\u003c/sub\u003e)\u0026lt;0.05.\u003c/p\u003e\n\u003ch3\u003eSpatial Correlation Analysis\u003c/h3\u003e\n\u003cp\u003eWe further conducted the imaging transcriptome analysis and neurotransmitter correlation analyses on the average and modal controllability maps of detected regions with omnibus differences across four groups.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImaging transcriptome analysis.\u0026nbsp;\u003c/strong\u003eWe used the Brain Annotation\u0026nbsp;Toolbox (BAT) [30]\u0026nbsp;to perform genetic annotation analysis on the observed regions with abnormal average and modal controllability\u0026nbsp;[30]. The gene expression profiles could be extracted from the Allen Human Brain Atlas (AHBA)\u0026nbsp;[31]\u0026nbsp;via BAT\u0026nbsp;based on the brain regions. The permutation analysis was conducted to identify differentially expressed genes within the specified regions compared to samples in the background\u0026nbsp;[30], with permutation times of 5000.\u0026nbsp;The other parameters for genetic annotations were as follows: ROI size=6mm, minimal sample size=5.\u0026nbsp;The statistical significance level was set as\u0026nbsp;\u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR\u003c/sub\u003e\u0026lt;0.05.\u003c/p\u003e\n\u003cp\u003eThe derived differentially expressed genes were uploaded to the Database for Annotation, Visualization, and Integrated Discovery (DAVID) (https://david.ncifcrf.gov/). The Gene Ontology (GO) database, specifically focusing on 3 domains including the biological process, cellular component, and molecular function, and the Kyoto Encyclopedia of Genes and Genomes (KEGG) database for Homo sapiens sets were adopted to achieve gene function and pathway enrichment analysis. The statistical significance level was set as\u0026nbsp;\u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR\u003c/sub\u003e\u0026lt;0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNeurotransmitter correlation analysis.\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eWe adopted JuSpace to explore the neurochemical basis underlying controllability abnormalities. JuSpace is a practical tool for spatial correlation analyses of MRI with nuclear imaging-derived neurotransmitter maps (https://github.com/juryxy/JuSpace)[32], which has been previously used to explore neurochemical basis of neural correlates [33]. We calculated Pearson correlation coefficients between detected regions with abnormal average and modal controllability and various neurotransmitter maps including dopamine, serotonin, glutamate, GABA, acetylcholine, opioid, cannabinoid, noradrenaline, and fluorodopa (\u003cem\u003eSupplementary Table S1\u003c/em\u003e), while adjusting for spatial autocorrelation and partial volume with the gray matter probability map [32]. The spatial permutation-based null maps with 5000 permutations were used to compute exact \u003cem\u003ep\u003c/em\u003e-values.\u0026nbsp;The statistical significance level was set as\u0026nbsp;\u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR\u003c/sub\u003e\u0026lt;0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003ch3\u003eDemographic and clinical characteristics\u003c/h3\u003e\n\u003cp\u003eA total of 303 participants (105 patients with SZ, 67 patients with BD, 51 patients with MDD, and 80 HCs) were enrolled in this study. The demographic and clinical characteristics are shown in \u003cem\u003eTable 1\u003c/em\u003e. There were significant differences in age and education years across four groups and illness duration and medication across patient groups. SZ showed higher a BRPS score than BD and MDD. BD had higher YMRS scores and lower HAMD and HAMA scores than MDD. Patient groups all exhibited poorer WM task performances including lower \u0026ldquo;0-back\u0026rdquo; and \u0026ldquo;2-back\u0026rdquo; reaction time and target accuracy than HCs. SZ had the lowest \u0026ldquo;0-back\u0026rdquo; and \u0026ldquo;2-back\u0026rdquo; target accuracy among four groups. Among BD, there were 29 patients in a depressive state, 13 in a manic/hypomanic state, 2 in a mixed state, and 23 in a euthymic state.\u003c/p\u003e\n\u003ch3\u003eGroup differences in controllability Metrics\u003c/h3\u003e\n\u003cp\u003eFor the average controllability (\u003cem\u003eTable 2\u0026nbsp;\u003c/em\u003eand \u003cem\u003eFigure 2A-2D\u003c/em\u003e), we observed significant differences across four groups in the memory retrieval network (MRN; 1 node) under the \u0026ldquo;0-back\u0026rdquo; load. Post-hoc analysis revealed that lower average controllability in SZ compared to MDD and HCs. Under the \u0026ldquo;2-back\u0026rdquo; load, significant differences across four groups in the visual network (VN; 3 nodes), and the frontoparietal task control network (FPN; 1 node) were identified. SZ and MDD had lower average controllability in VN nodes than BD and HCs. SZ had lower average controllability in the FPN node than other three groups.\u003c/p\u003e\n\u003cp\u003eFor the modal controllability, no significant difference among groups was found under the \u0026ldquo;0-back\u0026rdquo; load. Under the \u0026ldquo;2-back\u0026rdquo; load (\u003cem\u003eTable 2\u0026nbsp;\u003c/em\u003eand \u003cem\u003eFigure 2E-2G\u003c/em\u003e),\u0026nbsp;we observed\u0026nbsp;significant differences\u0026nbsp;in the\u0026nbsp;sensorimotor network (SMN; 2 nodes), cingulo-opercular network (CON; 1 node), auditory network (AN; 1 node), DMN (2 nodes), VN (1 node), FPN (12 nodes), salience network (SN; 3 nodes), cerebellum (1 node), and dorsal attention network (DAN; 1 node). Post-hoc analysis revealed that SZ showed lower modal controllability in all detected regions than HCs. SZ and MDD showed lower modal controllability in DMN and SN than BD and HCs. SZ, BD, and MDD exhibited shared abnormality of lower modal controllability in FPN compared to HCs.\u003c/p\u003e\n\u003ch3\u003eClinical and cognitive correlation of abnormal average and modal controllability\u003c/h3\u003e\n\u003cp\u003eUnder the \u0026ldquo;2-back\u0026rdquo; load, average controllability of 1 node (ROI No.169) in VN was positively correlated with YMRS scores (\u003cem\u003er\u003c/em\u003e=0.39, \u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR\u003c/sub\u003e=0.010) and 0-back target accuracy (\u003cem\u003er\u003c/em\u003e=0.20, \u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR\u003c/sub\u003e=0.036). The node (ROI No.179) in FPN was also positively correlated with the 0-back target accuracy (\u003cem\u003er\u003c/em\u003e=0.21, \u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR\u003c/sub\u003e=0.036), as shown in \u003cem\u003eFigure 3A\u003c/em\u003e and\u003cem\u003e\u0026nbsp;Supplementary Table S2\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003eWe observed positive correlations between the modal controllability of 1 node (ROI No.54) in CON and YMRS scores\u003cem\u003e\u0026nbsp;\u003c/em\u003e(\u003cem\u003er\u003c/em\u003e=0.32, \u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR\u003c/sub\u003e=0.036). The 0-back target accuracy was positively associated with the modal controllability of two nodes (ROI No.20: \u003cem\u003er\u003c/em\u003e=0.20, \u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR\u003c/sub\u003e=0.036; ROI No.33: \u003cem\u003er\u003c/em\u003e=0.20, \u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR\u003c/sub\u003e=0.036) in SMN, 1 node (ROI No.54: \u003cem\u003er\u003c/em\u003e=0.23, \u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR\u003c/sub\u003e=0.027) in CON, 1 node (ROI No.69: \u003cem\u003er\u003c/em\u003e=0.23, \u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR\u003c/sub\u003e=0.022) in AN, 2 nodes (ROI No.187: \u003cem\u003er\u003c/em\u003e=0.19, \u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR\u003c/sub\u003e=0.047; ROI No.202: \u003cem\u003er\u003c/em\u003e=0.20, \u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR\u003c/sub\u003e=0.036) in FPN, and 1 node (ROI No.213: \u003cem\u003er\u003c/em\u003e=0.20, \u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR\u003c/sub\u003e=0.036) in SN, as shown in \u003cem\u003eFigure 3B\u0026nbsp;\u003c/em\u003eand\u003cem\u003e\u0026nbsp;Supplementary Table S3\u003c/em\u003e.\u003c/p\u003e\n\u003ch3\u003eSpatial Correlation Analysis\u003c/h3\u003e\n\u003cp\u003eThe genetic annotation analyses identified 3245 and 6202 statistically overexpressed genes associated with detected regions of\u0026nbsp;abnormal average and modal controllability respectively (\u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR\u003c/sub\u003e\u0026lt;0.05).\u0026nbsp;Enrichment results of GO terms for\u0026nbsp;abnormal average and modal controllability were similar. These genes were mainly enriched in GO terms of synapse-related cellular components, such as \u0026ldquo;glutamatergic synapse\u0026rdquo;, \u0026ldquo;synapse\u0026rdquo;, and \u0026ldquo;GABAergic synapse\u0026rdquo; (all \u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR\u003c/sub\u003e\u0026lt;0.05;\u0026nbsp;\u003cem\u003eFigure\u0026nbsp;\u003c/em\u003e\u003cem\u003e4A\u003c/em\u003e, \u003cem\u003e4C\u003c/em\u003e). In the enrichment results of the KEGG pathway, we noted that differentially expressed genes for\u0026nbsp;abnormal average and modal controllability\u0026nbsp;were both enriched in organismal systems, such as \u0026ldquo;glutamatergic synapse\u0026rdquo;, \u0026ldquo;dopaminergic synapse\u0026rdquo;, and \u0026ldquo;GABAergic synapse\u0026rdquo;; in addition, the differentially expressed genes for abnormal modal controllability were also enriched in the \u0026ldquo;metabolic pathways\u0026rdquo; (all \u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR\u003c/sub\u003e\u0026lt;0.05;\u003cem\u003e\u0026nbsp;Figure 4B\u003c/em\u003e, \u003cem\u003e4D\u003c/em\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe further investigated the spatial relationship between neurotransmitter systems and abnormal average and modal controllability respectively. The average controllability was negatively associated with opioid receptors (MOR_1: \u003cem\u003er\u003c/em\u003e=-0.31, \u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR\u003c/sub\u003e=0.013; MOR_2: \u003cem\u003er\u003c/em\u003e=-0.33, \u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR\u003c/sub\u003e=0.012, \u003cem\u003eFigure 4E\u003c/em\u003e and \u003cem\u003eSupplementary\u0026nbsp;\u003c/em\u003e\u003cem\u003eTable S3\u003c/em\u003e). The abnormal modal controllability overlapped with regions that had higher concentration of 5-hydroxytryptamine (5-HT; 5HT1b_1: \u003cem\u003er\u003c/em\u003e=0.28,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR\u003c/sub\u003e=0.015; 5HT1a_2: \u003cem\u003er\u003c/em\u003e=0.27,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR\u003c/sub\u003e=0.015), cannabinoid (CB1: \u003cem\u003er\u003c/em\u003e=0.33,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR\u003c/sub\u003e=0.005), glutamate (mGluR5_1: \u003cem\u003er\u003c/em\u003e=0.24,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR\u003c/sub\u003e=0.035;\u0026nbsp;mGluR5_2: \u003cem\u003er\u003c/em\u003e=0.27,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR\u003c/sub\u003e=0.015; mGluR5_3: \u003cem\u003er\u003c/em\u003e=0.28,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR\u003c/sub\u003e=0.015), and opioid receptors (KOR: \u003cem\u003er\u003c/em\u003e=0.35,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR\u003c/sub\u003e=0.005) (\u003cem\u003eFigure 4F\u003c/em\u003e and\u0026nbsp;\u003cem\u003eSupplementary\u0026nbsp;\u003c/em\u003e\u003cem\u003eTable S4\u003c/em\u003e.\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study unveiled brain controllability patterns during WM tasks among MPDs, with a potential link to gene and neurotransmitter profiles. SZ showed reduced average and modal controllability in all detected regions than HCs, suggesting that the generalized reduction in the capacity to control transition dynamics during WM task is most pronounced in SZ among MPDs. We highlight three more specific findings. First, under the \u0026ldquo;2-back\u0026rdquo; load, SZ exhibited the lower average controllability of FPN nodes compared with BD and MDD who already had lower controllability than HCs. SZ and MDD had lower modal controllability of DMN and SN nodes relative to BD and HCs. Second, SZ and MDD showed lower average controllability of VN nodes compared with BD and HCs. SZ had lower modal controllability of SMN, AN, and VN nodes than HCs. Correlation analyses revealed that lower average and modal controllability of FPN, SN, VN, SMN, and AN nodes were associated with poor WM task performances. Third, gene annotation and enrichment analyses suggest that differentially overexpressed genes associated with abnormal controllability may be involved in distributed synaptic functions within the glutamatergic and GABAergic systems. There were significant associations between abnormal controllability and specific neurotransmitter systems including glutamate, opioid, 5-HT, and cannabinoid receptors.\u003c/p\u003e \u003cp\u003eWe noted that under the \u0026ldquo;0-back\u0026rdquo; load there were few significant differences in average and modal controllability in patient groups compared with HCs; when the WM load increased, patient groups, especially SZ, had altered controllability in distributed brain areas. Increased complexity/load of n-back task likely demands more manipulation of cognitive resources, as evidenced by extensive functional recruitment [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Most areas recognized for their role in WM exhibited load-dependent activity and connectivity when performing WM tasks in SZ [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]; our results are in concordance with this literature.\u003c/p\u003e \u003cp\u003eWe observed that SZ had lower average controllability of FPN than BD, MDD, and HCs; SZ, BD, and MDD shared lower modal controllability of FPN than HCs. FPN plays an important role in the top-down modulation of cortical dynamic activity during preparatory attention and orientation within WM [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Impaired functional activation and connectivity in FPN during WM tasks have been demonstrated in SZ [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Our previous work [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e] reported that compared to HCs, SZ had increased temporal variability of degree centrality in the inferior parietal lobe under the \u0026ldquo;2-back\u0026rdquo; load, which was the critical node of FPN in our results. Our results extend and complement the abnormal WM-related functional controllability of FPN in SZ based on Network Control Theory. We hypothesize that the excessive neural dynamics observed in SZ may lead to instability, confusion, and an inability to effectively organize and modulate brain activity to achieve desired brain states.\u003c/p\u003e \u003cp\u003eAmong MPDs, SZ had the illness-specific low average controllability of FPN, and the low modal controllability of FPN appears to be a transdiagnostic trait. Average controllability focuses on the ability of driving brain states to expected easy-to-reach states and modal controllability reflects the ability to transition toward difficult-to-reach states. We speculated that in BD and MDD, FPN only showed abnormal functional dynamics when performing complex cognitive processes. In a previous transdiagnostic study, patients with MPDs showed reduced functional connectivity of FPN than HCs, and patients with psychosis had reduced connectivity of FPN than patients without psychosis in a resting state [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. This finding implicates a shared functional dysconnectivity of FPN across MPDs, with a more pronounced dysconnectivity in psychosis. Our results indicate that brain controllability may serve as a more sensitive metric for detecting both transdiagnostic and SZ-specific functional features of FPN during WM tasks among MPDs.\u003c/p\u003e \u003cp\u003eWe noted that SZ and MDD had lower modal controllability of DMN and SN than BD and HCs under the \u0026ldquo;2-back\u0026rdquo; load. Lower controllability of FPN and SN nodes were associated with poor WM task performances. The classical triple network model of cognitive control system emphasizes the key role of coordination of the DMN, SN, and FPN in the execution of WM [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. It is proposed that SN facilitates switching brain networks, resulting in the engagement of FPN to manage oriented attention, and disengagement of the DMN to be involved in oriented self-referential mental processes during WM tasks [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. The insula in the SN is an integral hub in driving dynamic interactions among large-scale networks [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Our results indicated that this cognitive triple network model less readily shifts to expected difficult-to-reach states, which is consistent with previous work on functional dysconnectivity of triple network shared in MDD and SZ [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. The disrupted dynamics of the triple network may contribute to negative symptoms in SZ, as well as psychomotor retardation in MDD.\u003c/p\u003e \u003cp\u003eDifferences of controllability in sensory cortex (SMN, AN, and VN) had also been observed among groups under the \u0026ldquo;2-back\u0026rdquo; load. SZ and MDD showed lower average controllability of VN compared with BD and HCs. SZ had lower modal controllability of SMN, AN, and VN than HCs, and other patient groups did not differ from HCs, indicating that activity of the sensory cortex may less readily drive brain states transition to desired states necessary for WM tasks. This might be related to the abnormal activation and connectivity of sensory systems under WM in SZ [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. This functional deficiency in the sensory cortex may impair the ability to effectively process diverse external sensory stimulation, especially visual stimulation, and integrate this information with higher-level systems [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Our results highlight that SZ exhibited a notable transition disturbance of the sensory cortex, which is crucial for cognitive tasks.\u003c/p\u003e \u003cp\u003eWe explored and elucidated the gene expression, transcription, and neurotransmitter to provide an integrated interpretation of the molecular mechanisms underpinning the identified network controllability. Neurotransmitters in the brain are partially driven by gene expression profiles, and disruptions in neurotransmitter balance can lead to abnormal signal transmission and neural activity, thereby impairing cognitive function [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Our results demonstrated that the relevant gene expression primarily pertains to neurotransmitter systems, including GO categories involving glutamatergic synapse and GABAergic synapse, and KEGG pathway involving glutamatergic synapse, dopaminergic synapse, and GABAergic synapse. The neurotransmitter correlation analysis also revealed that glutamate and 5-HT were associated with abnormal controllability. The classical and common neurotransmitter hypotheses concerning the pathogenic mechanisms of MPDs have emphasized altered neurotransmission in the dopamine and 5-HT pathways, along with the inhibitory-excitatory imbalance mediated by GABA and glutamate [\u003cspan additionalcitationids=\"CR49\" citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Previous studies have identified that these neurotransmitters play critical roles in cognitive function and may hold potential as the targets for treating cognitive deficits [\u003cspan additionalcitationids=\"CR52\" citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. These converging findings from gene expression and neurotransmitter analyses suggested disruptions in these classical neurotransmitter pathways may underlie neural dysregulation when performing WM tasks in MPDs. Beyond MPDs, our findings also have implications for uncovering domain-general computational principles of WM highlighted as a priority in a recent review [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSeveral limitations need to be considered. First, three patient groups showed significant differences in the age and education years. Despite incorporating these variables as covariates in the controllability analyses, they may still introduce confounding effects. Second, the BD group comprised patients in various states - depressive, manic/hypomanic, mixed, and euthymic states. While this inclusion provides a more comprehensive view of BD, it introduces a degree of heterogeneity that may obscure state-specific brain controllability patterns associated with each clinical presentation. Third, as our study was cross-sectional, we cannot infer any causal relationship between abnormal brain controllability and MPDs. It remains unknown whether these controllability patterns vary with the different stages of illness duration. Future longitudinal studies comparing the controllability across pre- and post-treatment states, as well as during illness onset and remission will be needed. Third, this study only calculated the controllability based on fMRI data. There are likely abnormal structural controllability patterns of MPDs based on other imaging modalities, which have been explored in neurological disorders [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. A previous study revealed structural controllability was positively correlated with functional participation coefficient, and played a mediating role in brain anatomical structure to support functional dynamics [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. Therefore, investigations on structural controllability may elucidate the structural foundations that facilitate the transition of brain states in response to diverse cognitive tasks. Moreover, future transdiagnostic studies could adopt WM tasks with a greater diversity of difficulty levels to identify shared and illness-specific load-dependent controllability patterns.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eAberrant brain network controllability during WM in MPDs affects the triple network (FPN, DMN, SN) and sensory systems (SMN, AN, and VN) in SZ and other MPDs, and has a synaptic and neurotransmitter basis pertaining to glutamate, dopamine, GABA, and 5-HT, all of which play key roles in the clinical expression of MPDs. These results provide novel insight into a shared dysfunction in the ability to switch network states required for WM in MPDs.\u003c/p\u003e "},{"header":"Declarations","content":"\u003ch2\u003eContributors\u003c/h2\u003e\n\u003cp\u003eJie Yang, Zhening Liu, and Lena Palaniyappan designed the research. Jun Yang, Feiwen Wang, Wenjian Tan, Danqing Huang, Xuan Ouyang, Haojuan Tao, Guowei Wu, and Yunzhi Pan collected the data. Jun Yang and Jie Yang analyzed the data and wrote the manuscript along with Lena Palaniyappan. Zhening Liu and Lena Palaniyappan revised various versions of the manuscript. All authors reviewed the manuscript and approved the submitted version.\u003c/p\u003e\n\u003ch2\u003eAcknowledgments\u003c/h2\u003e\n\u003cp\u003eWe would like to thank all participants in this study. This work was supported by grants from the National Natural Science Foundation of China (82071506 to Zhening Liu, 82201663 to Jie Yang), the Training Program for Excellent Young Innovators of Changsha (kq2306008\u0026nbsp;to Jie Yang), the Scientific Research Program of Hunan Provincial Health Commission, China (B202303095947 to Jie Yang), and the Scientific Research Launch Project for new employees of the Second Xiangya Hospital of Central South University\u0026nbsp;to Jie Yang. Lena Palaniyappan\u0026rsquo;s research is supported by the Canada First Research Excellence Fund, awarded to the Healthy Brains, Healthy Lives initiative at McGill University (through a New Investigator Supplement to LP) and Monique H, Bourgeois Chair in Developmental Disorders. He receives a salary award from the Fonds de recherche du Qu\u0026eacute;bec-Sant\u0026eacute; (FROS).\u003c/p\u003e\n\u003ch2\u003eConflict of Interest\u003c/h2\u003e\n\u003cp\u003eLena Palaniyappan reports personal fees for serving as chief editor from the Canadian Medical Association Journals, speaker/consultant fee from Janssen Canada and Otsuka Canada, SPMM Course Limited, UK, Canadian Psychiatric Association; book royalties from Oxford University Press; investigator-initiated educational grants from Janssen Canada, Sunovion and Otsuka Canada outside the submitted work. All other authors report no potential conflicts.\u003c/p\u003e\n\u003cp\u003eSupplementary information is available at MP\u0026rsquo;s website.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHartley T, Hitch GJ. Working Memory. Oxford University Press2022.\u003c/li\u003e\n\u003cli\u003ePark S, P\u0026uuml;schel J, Sauter BH, Rentsch M, Hell D. Spatial working memory deficits and clinical symptoms in schizophrenia: a 4-month follow-up study. \u003cem\u003eBiological psychiatry\u003c/em\u003e 1999; \u003cstrong\u003e46\u003c/strong\u003e(3)\u003cstrong\u003e: \u003c/strong\u003e392-400.\u003c/li\u003e\n\u003cli\u003eSoraggi-Frez C, Santos FH, Albuquerque PB, Malloy-Diniz LF. 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\u003cstrong\u003e180: \u003c/strong\u003e179-184.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 Demographic and clinical characteristics of each group\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"760\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSZ\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=105)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBD\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=67)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMDD\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=51)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHCs\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=80)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 53px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ec\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e/\u003cem\u003eF\u003c/em\u003e/\u003cem\u003et\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 53px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 181px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePost hoc analysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComparisons\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eLSD-t\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eGender (M/F)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e63/42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e30/37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e28/23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e39/41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e4.53\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e0.209\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e25.32\u0026plusmn;5.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e26.19\u0026plusmn;5.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e29.45\u0026plusmn;8.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e23.23\u0026plusmn;4.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e12.21\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003eSZ\u0026lt;MDD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e-4.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003eSZ\u0026gt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e2.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003eBD\u0026lt;MDD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e-3.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003eBD\u0026gt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e2.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003eMDD\u0026gt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e5.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eEducation (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e11.87\u0026plusmn;2.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e13.31\u0026plusmn;2.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e12.14\u0026plusmn;3.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e13.95\u0026plusmn;2.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e10.36\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003eSZ\u0026lt;BD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e-3.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003eSZ\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e-5.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003eBD\u0026gt;MDD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e2.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003eMDD\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e-3.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eIllness duration (m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e28.25\u0026plusmn;32.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e52.32\u0026plusmn;51.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e47.56\u0026plusmn;58.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e6.67\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n 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style=\"width: 91px;\"\u003e\n \u003cp\u003e0.49\u0026plusmn;0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e0.60\u0026plusmn;0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e0.62\u0026plusmn;0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e0.74\u0026plusmn;0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e16.19\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003eSZ\u0026lt;BD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e-2.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003eSZ\u0026lt;MDD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e-3.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003eSZ\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e-6.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003eBD\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e-3.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003eMDD\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e-2.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e2-back target RT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e701.51\u0026plusmn;173.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e738.57\u0026plusmn;173.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e716.44\u0026plusmn;225.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e642.04\u0026plusmn;139.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e3.49\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003eSZ\u0026gt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e2.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003eBD\u0026gt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e3.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003eMDD\u0026gt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e2.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: Quantitative data were presented as mean\u0026nbsp;\u0026plusmn;\u0026nbsp;standard deviation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAbbreviations: SZ, Schizophrenia; BD, bipolar disorder; MDD, major depressive disorder patients; HCs, healthy controls; M/F, male/female; m, month; CPZ, chlorpromazine equivalent dose\u0026nbsp;[58]; FLU, fluoxetine equivalents dose [59]; SANS, Scale for the Assessment of Negative Symptoms; SAPS, Scale for the Assessment of Positive Symptoms; BPRS, Brief Psychiatric Rating Scale; YMRS, Young Mania Rating Scale; HAMD, Hamilton Depression Rating Scale; ACC, accuracy; RT, response time.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003e \u0026chi;\u003csup\u003e2\u003c/sup\u003e test; \u003csup\u003eb\u0026nbsp;\u003c/sup\u003eOne-way ANOVA; \u003csup\u003ec\u0026nbsp;\u003c/sup\u003eTwo-sample t-test.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e Significant differences in average and modal controllability under\u0026ldquo;0-back\u0026rdquo; and\u0026ldquo;2-back\u0026rdquo; loads among all groups\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"684\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eROI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNetwork\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" style=\"width: 159px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBrain Regions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"6\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMNI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eF\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csub\u003eFDR\u003c/sub\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"6\" style=\"width: 197px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePost-hoc analysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eX\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eY\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eZ\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComparisons\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003et\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 51px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep\u003csub\u003eBon\u003c/sub\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" style=\"width: 295px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAverage controllability under \u0026ldquo;0-back\u0026rdquo; load\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 61px;\"\u003e\n \u003cp\u003e136\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eMRN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\n \u003cp\u003eR Posterior Cingulate Cortex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e-48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e7.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;MDD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e-3.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 61px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e-3.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" style=\"width: 295px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAverage controllability under \u0026ldquo;2-back\u0026rdquo; load\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 61px;\"\u003e\n \u003cp\u003e159\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eVN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\n \u003cp\u003eR Cuneus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e-77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e6.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;BD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e-3.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 61px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e-3.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 61px;\"\u003e\n \u003cp\u003e160\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eVN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\n \u003cp\u003eL Lingual Gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e-16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e-52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e6.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e-2.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 61px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eBD\u0026gt;MDD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e3.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 61px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eMDD\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e-3.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 61px;\"\u003e\n \u003cp\u003e169\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eVN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\n \u003cp\u003eR Middle Occipital Gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e-84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e7.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;BD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e-3.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 61px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e-3.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 61px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eBD\u0026gt;MDD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e3.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 61px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eMDD\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e-2.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 61px;\"\u003e\n \u003cp\u003e179\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eFPN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\n \u003cp\u003eR Inferior Temporal Gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e-53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e-14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e7.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;BD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e-2.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 61px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;MDD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e-3.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 61px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e-3.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" style=\"width: 295px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModal controllability under \u0026ldquo;2-back\u0026rdquo; load\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eSMN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\n \u003cp\u003eL Postcentral Gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e-54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e-23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e5.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-4.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eBD\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-2.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eSMN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\n \u003cp\u003eL Postcentral Gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e-45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e-32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e5.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-4.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eCON\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\n \u003cp\u003eR Medial Frontal Gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e7.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;BD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-2.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-4.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eAN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\n \u003cp\u003eL Postcentral Gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e-53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e-22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e5.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-2.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eDMN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\n \u003cp\u003eR Angular Gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e-59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e6.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-4.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e137\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eDMN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\n \u003cp\u003eL Inferior Frontal Gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e-46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e-13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e5.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;BD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-2.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-4.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eVN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\n \u003cp\u003eL Inferior Occipital Gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e-33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e-79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e-13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e4.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-4.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e176\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eFPN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\n \u003cp\u003eL Inferior Frontal Gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e-47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e4.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-4.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eFPN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\n \u003cp\u003eL Inferior Frontal Gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e-41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e6.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-4.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eMDD\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-3.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e190\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eFPN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\n \u003cp\u003eR Inferior Parietal Lobule\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e-42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e4.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-4.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e191\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eFPN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\n \u003cp\u003eL Superior Parietal Lobule\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e-28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e-58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e4.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-3.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e192\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eFPN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\n \u003cp\u003eR Inferior Parietal Lobule\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e-53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e4.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-4.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e194\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eFPN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\n \u003cp\u003eR Inferior Parietal Lobule\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e-65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e5.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-4.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eMDD\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-3.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e195\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eFPN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\n \u003cp\u003eL Inferior Parietal Lobule\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e-42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e-55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e5.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-4.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e197\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eFPN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\n \u003cp\u003eL Middle Frontal Gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e-34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e7.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-4.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eBD\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-2.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eMDD\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-1.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e198\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eFPN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\n \u003cp\u003eL Middle Frontal Gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e-42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e-2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e9.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-5.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eBD\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-2.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e199\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eFPN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\n \u003cp\u003eR Inferior Parietal Lobule\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e-53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e6.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-4.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eMDD\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-3.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e201\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eFPN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\n \u003cp\u003eL Middle Frontal Gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e-42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e7.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-4.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eBD\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-2.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eMDD\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-3.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e202\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eFPN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\n \u003cp\u003eL Superior Frontal Gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e-3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e6.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-4.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e208\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eSN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\n \u003cp\u003eL Insula\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e-35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e5.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-4.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eMDD\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-3.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e209\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eSN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\n \u003cp\u003eR Insula\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e4.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-4.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e213\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eSN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\n \u003cp\u003eL Median cingulate and paracingulate gyri\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e4.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.049\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-4.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e246\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eCerebellar\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\n \u003cp\u003eR Cerebellum Posterior Lobe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e-62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e-18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e4.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-2.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e261\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eDAN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\n \u003cp\u003eL Middle Frontal Gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e-32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e6.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-4.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eUncertain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\n \u003cp\u003eL Middle Frontal Gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e-21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e-20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e5.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-4.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eBD\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-3.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e183\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eUncertain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\n \u003cp\u003eL Cerebellum Posterior Lobe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e-18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e-76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 32px;\"\u003e\n \u003cp\u003e-24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e6.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSZ\u0026lt;HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e-4.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eNote: ROI refers to the index number of the node in the Power Atlas.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAbbreviations: FDR, False Discovery Rate correction; Bon, Bonferroni correction; MRN, Memory Retrieval Network; VN, Visual Network; FPN, Frontoparietal Task Control Network; SMN, Sensory/somatomotor Network; CON, Cingulo-opercular Task Control Network; AN, Auditory Network; DMN, Default Mode Network; SN, Salience Network; DAN, Dorsal Attention Network; L, left; R, right; SZ, Schizophrenia; BD, bipolar disorder; MDD, major depressive disorder patients; HCs, healthy controls.\u003cbr\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"major psychiatric disorder, control theory, frontoparietal network, sensor cortex, gene, neurotransmitter","lastPublishedDoi":"10.21203/rs.3.rs-5412595/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5412595/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWorking memory (WM) deficit is a prominent and common cognitive impairment in major psychiatric disorders (MPDs). Altered control of brain states transitions may underlie the neural basis of WM deficit. Brain controllability derived from Network Control Theory provides a mathematical framework to study how external signals may affect neural network dynamics and influence the transition to desired states. We investigate if shared and illness-specific alterations in controllability underlie WM deficits in MPDs. We examined fMRI data during a n-back WM task from 105 patients with schizophrenia (SZ), 67 with bipolar disorder (BD), 51 with major depressive disorder (MDD), and 80 healthy controls (HCs). A region\u0026rsquo;s capacity to steer transitions to connectomic states with less input (average controllability) and difficult-to-reach states with high input (modal controllability) were compared across groups. The effect of altered controllability on clinical and cognitive characteristics, and their likely genetic and neurotransmitter basis were investigated. Compared to HCs, all MPDs had lower modal controllability of frontoparietal network. SZ and MDD shared modal controllability in default mode network and salience network nodes compared to BD and HCs. Only SZ had lower modal controllability of sensorimotor, auditory, and visual network nodes than HCs, indicating the need for higher sensory inputs to facilitate a state transition in SZ. Expression of genes that determine synaptic biology and chemoarchitecture involving glutamate/GABA and monoamine (dopamine and 5HT) receptor systems were more likely in the affected brain regions. A graded, transdiagnostic reduction in the influence of the triple network system and sensory networks in implementing state transitions underlies working memory deficits in MPDs. This deficit, especially pronounced in SZ, has its likely basis in synaptic biology and in glutamate/GABA and monoamine (dopamine and 5HT) systems.\u003c/p\u003e","manuscriptTitle":"Task-related Controllability of Functional Connectome During a Working Memory Task in Schizophrenia, Bipolar Disorder, and Major Depressive Disorder","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-25 01:25:01","doi":"10.21203/rs.3.rs-5412595/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f274a6df-2eae-4859-b1d0-a5b9852a174b","owner":[],"postedDate":"December 25th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":41269565,"name":"Biological sciences/Neuroscience"},{"id":41269566,"name":"Health sciences/Diseases/Psychiatric disorders/Schizophrenia"}],"tags":[],"updatedAt":"2025-01-31T14:30:58+00:00","versionOfRecord":[],"versionCreatedAt":"2024-12-25 01:25:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5412595","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5412595","identity":"rs-5412595","version":["v1"]},"buildId":"cBFmMYwuxLRRLfASyISRj","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}