The Correlation Between Middle Frontal Gyrus Cortical Thickness and Working Memory in First-episode Treatment-naïve Major Depressive Disorder

The Correlation Between Middle Frontal Gyrus Cortical Thickness and Working Memory in First-episode Treatment-naïve 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 Research Article The Correlation Between Middle Frontal Gyrus Cortical Thickness and Working Memory in First-episode Treatment-naïve Major Depressive Disorder Chenyu Liu, Hehua Li, Shixuan Feng, Ziyun Zhang, Miaolan Huang, and 5 more This is a preprint; it has not been peer reviewed by a journal.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-5978946/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 Background: Cognitive impairment is regarded as a pivotal symptom of Major Depressive Disorder (MDD). Previous studies have indicated the presence of abnormalities in cortical thickness (CT) in patients with MDD. However, the relationship between cognitive performance and CT abnormalities in patients with MDD remains unclear. Our study purposed to survey the changes in CT in patients with MDD and their relationship with cognitive impairment. Methods: A total of 105 patients with first-episode treatment-naïve MDD and 53 healthy controls (HCs) received T1-weighted magnetic resonance imaging (MRI) and a series of neuropsychological tests. Initially the differences in CT and cognitive performance between patients with MDD and HCs were contrasted. Subsequently, the correlation between CT and cognitive performance were analyzed for significant changes. Results: All five cognitive dimensions were significantly different between patients with MDD and HCs. Meanwhile, the CT of the bilateral precentral gyri and right middle frontal gyrus were reduced in the MDD group. Besides, the CT of the right middle frontal gyrus shows a positive relationship with working memory dimension scores of the MDD group. Conclusion: CT abnormalities in patients with MDD are correlated with cognitive performance. Cortical thickness Middle frontal gyrus Major depressive disorder Cognitive performance Figures Figure 1 Figure 2 Figure 3 Introduction Cognitive impairment is a characteristic manifestation of Major Depressive Disorder (MDD) that affects attention, memory, executive function, and information processing speed. This is one of the reasons for the poor prognosis of patients, seriously affecting their social function and ability to live independently, which pose a great burden and risk to the family and society. Cognitive impairment of varying degrees is a widespread clinical performance in patients with MDD; more than 20% of patients with first-episode MDD and more than 50% of patients with recurrent MDD have cognitive impairment [ 1 , 2 ]. Nevertheless, the current understanding of cognitive impairment in MDD is limited. Cortical thickness (CT) is a structural magnetic resonance imaging index that affects the pathophysiology and clinical course of MDD [ 3 ]. An earlier study demonstrated that individuals with MDD exhibit thinner cortices in the frontal, temporal, parietal, and insula regions [ 4 ]. Another study reported that patients with MDD show significantly CT reductions in several regions [ 5 ]. There have also been reports of a correlation between CT and disease duration in patients with MDD [ 5 , 6 ]. Moreover, CT correlates to the degree of depressive symptom severity in patients with MDD [ 7 ]. A meta-analysis reveals enhanced CT in the ventromedial prefrontal cortex for patients with MDD. In contrast, there was a reduction in CT of the middle temporal gyrus [ 8 ]. CT has also been identified as an important predictor of clinical symptom relief and cognitive improvement [ 9 ]. In summary, CT abnormalities significantly contribute to the pathological mechanism of MDD. However, there are still fewer studies on the correlation of CT abnormalities with cognitive impairment in MDD. Recently, more and more studies have demonstrated a close relationship between cognitive function and CT. The majority of current research has focused on schizophrenia. Fan et al. demonstrated that CT in the pars opercularis of the inferior frontal cortex, superior frontal cortex, and right caudal middle frontal gyrus was significantly associated with cognitive deficits in patients with schizophrenia [ 10 ]. Thielen et al. showed that CT in the anterior cingulate gyrus is correlated with performance in episodic and working memory [ 11 ]. In addition, a correlation between CT and cognitive function has been identified in patients with bipolar disorder [ 12 ]. However, only one recurrent MDD study has been reported there was a significant correlation between reduced bilateral insula and frontal cortex volume and cognitive deficits in working memory and processing speed in patients with MDD (Saleh et al., 2017). It’s unclear whether CT values have a correlation with cognitive function in patients with first-episode MDD. Consequently, the precise relationship between CT and cognitive impairment in patients with MDD still requires additional study. The purpose of this study was to elucidate the relationship between CT and cognitive impairment in patients with MDD. We hypothesized that CT abnormalities in patients with MDD are correlated with cognitive performance. Methods Participants Approval for this research was granted by the Ethics Committee of the Affiliated Brain Hospital of Guangzhou Medical University. All participants signed a written informed consent before participation. In this study, 105 patients with first-episode treatment-naïve MDD were included through the psychiatry departments of the Affiliated Brain Hospital of Guangzhou Medical University, and 53 healthy controls (HCs) of similar sex and age were recruited openly from WeChat through community advertisements and other forms. All participants of the inclusion criteria as follows: (I) Han Chinese and right-handed. (II) aged 18–45 years old and had at least 6 years of education. The criteria for including participants with MDD were: (I) they satisfied the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR) standards for diagnosing MDD. (II) MDD was defined as the first episode without medication or irregularly taking medication for less than 2 weeks and had a duration of less than 2 years. (III) The minimum score on the Hamilton Depression Rating Scale-17 (HAMD-17) was ≥ 17. All participants of the exclusionary criteria as follows: (I) presence of other mental disorders. (II) severe or unstable physical illness. (III) history of head trauma or impaired consciousness. (IV) contraindications to magnetic resonance scanning. (V) illnesses that may cause emotional problems such as thyroid dysfunction and anemia. The research was conducted in accordance with the most recent revision of the Declaration of Helsinki (2013). Assessment of clinical symptoms and cognitive functions HAMD-17 was employed to evaluate depressive symptoms [ 13 ]. Cognitive performance was evaluated with the Chinese version of the MATRICS Consensus Cognitive Battery (MCCB) [ 14 ], which comprises five dimensions of the MCCB [ 15 ]: Working Memory, Speed of Processing, Verbal Learning, Attention/Vigilance, and Visual Learning. The outcomes of these scales were presented as T-scores. Each scale was scored by psychiatric professionals who had undergone scale consistency training and met qualification criteria. Acquisition and analysis of magnetic resonance imaging(MRI) MRI was collected by the scanner of Siemens 3T at the hospital where we conducted research. At least one consultant radiologist and one psychiatrist performed the MRI scans, which were reviewed by at least one specialized radiologist and one psychiatrist. All participants were asked to lie on their backs and breathe calmly, stay awake and relaxed, minimize head and body movements, not engage in any thinking activities, and use special non-magnetic headphones and fixed headgear to minimize distractions and head movements during the scanning process. All participants had structural magnetic resonance imaging data generated by the sequence of magnetization-prepared rapid gradient-echo (MPRAGE) and the sets were as follow: repetition time = 2000 ms, echo time = 2.32 ms, flip angle = 8°, spatial resolution = 0.9 mm * 0.9 mm * 0.9 mm, and 256 * 256 * 208 matrix. The preprocessing of structural MRI data was carried out using the Statistical Parametric Mapping (SPM12, http://www.fil.ion.ucl.ac.uk/spm/software/spm12 ) and Computational Anatomy Toolbox (CAT12, http://www.neuro.uni-jena.de/cat ) software packages, operating within the Matlab2022b environment [ 16 ]. The specific processing flow was as follows: 1) Using default parameters, data were segmented to separate individual structural images into cortical data, cerebrospinal fluid, white matter, and gray matter. 2) Calculation of the total intracranial volume (TIV) to correct for differences in brain size and volume. 3) All participant images have been aligned to the Montreal Neurological Institute (MNI) standard space. 4) The quality and homogeneity of the segmented images were assessed. 5) For the purpose of improving the signal-to-noise ratio (S/N) and fidelity of the data, the segmented cortical data were smoothed using a 15 mm*15 mm*15 mm full width at half-maximum (FWHM) Gaussian kernel to facilitate further statistical analysis. CT was the distance between the surface of the cerebral cortex and medulla. This can be calculated using a surface-based morphometry [ 17 , 18 ]. The basic principle of this calculation is to reconstruct the surface of the brain using three-dimensional structural images. This was followed by the calculation of the CT of each brain region using a series of algorithms. Statistical analysis The composition of sex within the groups underwent Chi-square test to ascertain the presence of any significant variations. The Kolmogorov-Smirnov test was employed to ensure whether other continuous variables coincident to a normal distribution across each group. Variables exhibiting a normal distribution within individual groups underwent two-sample t-test comparisons to detect differences. In cases where variables deviated from a normal distribution, the Wilcoxon rank-sum test was employed. The significance level was set at 0.05. CT differences between the two groups were assessed using two-sample t-tests with TIV, education, sex, and age as covariates using SPM12. Cluster-level inference was performed using Bonferroni correction with a significance level of 0.001. To inspect the relationship between CT and cognitive performance in the two groups of subjects, we identified regions where CT differences between groups as ROIs. We then conducted partial correlation analyses of these ROIs with five dimensions of MCCB scores for both groups of participants, including education, sex, and age as covariates. The level of significance for both demographic and clinical characteristic statistics was 0.05. Results Clinical data and cognitive functions Clinical and cognitive data are presented in Table 1 and Fig. 1. Patients with MDD had higher level of education and less scores of the five dimensions of MCCB than HCs (All p 0.05). Table 1 Clinical data and cognitive functions of MDD and HCs MDD(n = 105) HCs(n = 53) \(\:{\chi\:}^{2}/t\) p Sex (Male/Female) 39/66 26/27 1.704 0.090 Age (Year) 23.7 (3.1) 23.4 (2.5) 2.065 0.151 Education (Year) 16 (2.2) 17 (2.1) -4.518 <0.001 * Age at onset (Year) 22.8 (3.5) - - - Course of illness (month) 11.6 (9.5) - - - HAMD 23.2 (4.6) - - - MCCB Working Memory 40.1 (11.5) 48.3 (11.1) 10.582 0.001 * Speed of Processing 32.9 (9.9) 46.0 (11.0) 33.592 <0.001 * Verbal Learning 34.4 (9.5) 41.4 (8.7) 9.671 0.002 * Attention/Vigilance 34.7 (9.8) 42.0 (8.2) 13.153 <0.001 * Visual Learning 40.5 (8.0) 45.7 (7.7) 6.435 0.012 * Abbreviations : MDD, major depressive disorder; HCs, healthy controls; HAMD, Hamilton Rating Scale for Depression. Intergroup differences in CT Comparing the morphological indices of the MDD and HCs groups, we found significant differences in CT in the bilateral precentral gyri and right middle frontal gyrus (Table 2 , Fig. 2). Table 2 Comparison of CT between patients with MDD and HCs. Hemisphere Region Cluster-size Peak MNI (x,y,z) T value The overlap rate of DK atlas L precentral 216 (-37,-9,60) 5.06 99% R precentral 348 (33,-8,50) 4.36 59% R caudalmiddlefrontal 41% Abbreviations : CT, cortical thickness; MDD, major depressive disorder; HCs, healthy controls; DK atlas, Desikan-Killiany atlas. Correlation between CT and cognitive performance in MDD Correlation analysis revealed a positive correlation between CT in the right middle frontal gyrus and working memory in the MDD group. Furthermore, we didn’t find correlation results in HCs (Table 3 , Fig. 3). Table 3 Correlations between five dimensions score of MCCB and CT in MDD. Hemisphere Region WM SOP VRB AV VIS L precentral r -0.099 -0.016 -0.140 0.047 -0.101 p 0.323 0.876 0.160 0.637 0.311 R precentral r -0.113 -0.046 -0.171 -0.071 -0.159 p 0.257 0.646 0.086 0.478 0.111 R caudalmiddlefrontal r 0.220 -0.072 0.128 -0.094 0.188 p 0.026* 0.475 0.201 0.349 0.059 Abbreviations : CT, cortical thickness; MDD, major depressive disorder; WM, working memory; SOP, speed of processing domain; VRB, verbal learning; AV, attention/vigilance; VIS, visual learning. Discussion This study represents an inaugural investigation into the correlation between CT and cognitive performance, with the following pivotal findings: (1) Cognitive profiles indicated significantly diminished dimensional scores for in individuals diagnosed with MDD as compared to HCs. (2) There were abnormalities in the CT of the brain in patients with MDD compared with HCs, as evidenced by a decrease in the CT of the bilateral precentral gyri and right middle frontal gyrus in the MDD patients. (3) The working memory scores of cognitive performances in MDD were found to be positively associated with CT of right middle frontal gyrus. Our study found that patients with MDD had diminished cognitive performance scores than patients with HC in all five dimensions, which were consistent with previous research in patients with first-episode MDD experience a pervasive disturbance in cognitive functioning [ 19 – 21 ]. Wang et al. revealed pervasive and marked impairments in all cognitive domains in young and middle-aged Chinese patients diagnosed with MDD by MCCB [ 21 ]. Snyder et al. showed that patients with middle-aged MDD performed significantly worse than HCs in the domains of verbal fluency, coded symbols, and other information processing speed [ 22 ]. Nevertheless, only a small proportion of studies have yielded findings contrary to the aforementioned results. A study that included 36 cases of first-episode MDD, 71 cases of MDD receiving medication, and 59 HCs reported no evidence of cognitive impairment in young patients (aged 18–50 years) across multiple dimensions, including processing speed, attention, executive function, and spatial working memory [ 23 ]. Another study employed the Montreal Cognitive Assessment observed no cognitive deficits in patients aged 18–24 years with MDD compared to HCs [ 24 ]. Differences in these results may be attributed to differences in the general information and clinical characteristics of these studies and the use of different cognitive testing tools [ 25 ]. But in any case, cognitive impairment in MDD is definitive. Our results also showed that CT of the bilateral precentral gyri were markedly reduced in MDD patients compared to HCs. The reduction of CT in the precentral gyrus was paralleled by outcomes in previous studies [ 26 , 27 ]. The precentral gyrus is involved in working memory, including attention, cognitive control, and executive functions, and aids in maintaining attention, focus, and regulation of cognitive resources [ 28 , 29 ]. Abnormalities in the CT in this region may directly contribute to motor dysfunction, resulting in negative emotions and cognitive imbalances that can lead to depression. In addition, our study also exhibited that the CT of the right medial frontal gyrus was distinctly reduced compared with HCs in MDD patients. This is according with some previous studies [ 30 , 31 ]. But other studies have found the opposite result. For instance, a study involving 16 adolescents with MDD and 30 HCs reported an increased bilateral CT in the middle frontal gyrus in MDD [ 32 ]. The frontal lobe, situated anterior to the central sulcus, encompasses the frontal part of the brain and is intimately correlated with higher cognitive functions, behavioral control, and social interaction [ 33 ]. The middle frontal gyrus is a key brain region that supports numerous cognitive and motor functions and plays a significant role in the cognitive, emotional, and social functions that are essential for complex human thought and behavior [ 28 ]. Patients with major depression show varying degrees of impairment in cognitive function, which may lead to inconsistent CT changes in different parts of the frontal lobe in different studies. Besides, abnormalities in the middle frontal gyrus can disrupt its connectivity with regions such as the anterior cingulate and amygdala gyrus, leading to disturbances in emotion regulation and memory function [ 34 – 36 ]. Certain patients may experience cortical thickening due to the overuse of emotion-regulating mechanisms, whereas others may exhibit cortical thinning due to diminished emotion-regulating abilities. This may also be one of the reasons for the inconsistent CT changes in the middle frontal gyrus in different studies. Furthermore, the sample size and method of calculating CT may also contribute to this discrepancy. But in any case, these studies suggest that frontal lobe structure is abnormal in patients with MDD and that frontal lobe damage may contribute to the pathophysiology of cognitive impairment in major depression by affecting mood, memory, and social function. Finally, and most importantly, our study is the first to show a positive correlation between the working memory score of the MCCB and the CT of the right middle frontal gyrus in the MDD patients after adjusting for demographic variables and clinical symptoms. So far, only one study on the relationship between frontal CT and cognitive deficits in individuals with treatment-resistant MDD, and the results suggest a positive correlation between frontal lobe structure and working memory tasks [ 37 ], which is similar to our findings. Similar findings have been observed for other psychiatric disorders. Prior research on bipolar disorder has demonstrated a correlation between CT in the frontal and parietal lobes and working memory [ 38 – 40 ]. Working memory, a component of short-term memory, involves the temporary storage and processing of information to perform cognitive tasks such as reasoning, comprehension, and learning [ 14 ]. The middle frontal gyrus is a component of the brain's executive control network that supports numerous cognitive and motor functions and plays a significant role in the cognitive, emotional, and social functions essential for complex human thought and behavior [ 28 ] [ 41 ]. This function is achieved through the coordinated activity of multiple frontal and parietal regions, which collectively facilitate the management and regulation of complex tasks such as working memory. Furthermore, an increase in CT is typically associated with an increase in neuronal density [ 3 , 42 ]. An increase in the number of neurons and the prominence of their connections enhances the processing and integration of information, which is essential for the completion of complex cognitive tasks [ 42 ]. This indicates that cognitive alterations observed in patients with MDD may be attributed to the decrease of middle frontal gyrus. However, more research is needed to further affirm the relationship between CT of the right middle frontal gyrus and working memory. Future studies may investigate interventions directed at the middle frontal gyrus to enhance cognitive function in patients with MDD, potentially offering novel therapeutic targets and approaches for addressing cognitive deficits correlated with the disorder. Conclusion In conclusion, this study found that patients with first-episode MDD exhibited substantial impairments in cognitive functioning, with significant reductions in multiple domains, including working memory, speed of processing, verbal learning, attention/vigilance and visual learning, when compared with HCs. Moreover, individuals with MDD demonstrated reduced CT in the bilateral precentral gyri and right middle frontal gyrus than HCs. Furthermore, decreased CT in the right middle frontal gyrus correlated with impaired working memory in individuals with MDD. Our research results indicate that frontal CT is a pivotal factor in the etiology of MDD and cognitive impairment in those affected. This study has several limitations. First, as an exploratory investigation of the connection between the brain structure and cognitive performance, we were unable to establish a causal relationship between these two variables. Rather, it can only speculate on potential correlations. Second, despite controlling for educational level to mitigate its effects, the generalizability of the current findings to individuals of different educational backgrounds may be constrained. Abbreviations MDD Major Depressive Disorder CT cortical thickness MRI magnetic resonance imaging HCs healthy controls DSM-V Diagnostic and Statistical Manual of Mental Disorders HAMD-17 17-item Hamilton Depression Rating Scale MCCB MATRICS Consensus Cognitive Battery WM Working Memory SOP Speed of Processing Domain VRB Verbal Learning AV Attention/Vigilance VIS Visual Learning MPRAGE magnetization-prepared rapid gradient-echo sequence CAT12 Computational Anatomy Toolbox TIV total intracranial volume MNI Montreal Neurological Institute FWHM full width at half-maximum Declarations Funding This study was funded by Key-Area Research and Development Program of Guangdong Province (2023B0303020001), National Natural Science Foundation of China (82301688), the Science and Technology Program of Guangzhou (202206060005, 202201010093, 2023A03J0856, 2023A03J0839), Guangdong Basic and Applied Basic Research Foundation Outstanding Youth Project (2021B1515020064), Medical Science and Technology Research Foundation of Guangdong (A2023224), the Natural Science Foundation Program of Guangdong (2023A1515011383), the Health Science and Technology Program of Guangzhou (20231A010036), Guangzhou TCM Clinical Core Technology Construction Project：Acupuncture method of "TongyangXingshen" to Treat Mental Disorders Caused by Stagnation of yang qi., "1+N" Construction Project of Guangzhou Acupuncture and Moxibustion Hospital, Major Innovation Technology Construction Project of Synergistic Chinese Medicine and Western Medicine of Guangzhou (No.2023-2318), Primary and Secondary School Teachers' educational Capacity Improvement Program of Guangdong (2023YQJK438), National Traditional Chinese and Western Medicine Collaborative Project for Major and Complex Diseases (Comprehensive Department of the National Administration of Traditional Chinese Medicine [2024] No. 3), Guangzhou Municipal Key Discipline in Medicine (2025-2027), the Research capacity improvement project of Guangzhou Medical University (2024SRP200), and Guangzhou Research-oriented Hospital. Data Availability The datasets used and analysed during the current study are available from the corresponding author on reasonable request. Author information Authors and Affiliations Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China Chenyu Liu, Hehua Li, Shixuan Feng, Ziyun Zhang, Miaolan Huang, Junhao Li, Yuanyuan Huang & Fengchun Wu The town of Dalang Experimental Primary School, Dongguan, China Dongchang Huang School of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou, China Kai Wu Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China Fengchun Wu Guangdong Engineering Technology Research Center for Diagnosis and Rehabilitation of Dementia, Guangzhou, China Fengchun Wu Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, China Fengchun Wu Contributions Chenyu Liu, Hehua Li: Conceptualization, Investigation, Writing-Original draft preparation; Chenyu Liu, Shixuan Feng: Methodology, Software; Chenyu Liu, Ziyun Zhang, Miaolan Huang, Junhao Li, Dongchang Huang: Subject Recruitment, Data collection; Fengchun Wu, Yuanyuan Huang, Kai Wu, Dongchang Huang: Supervision; Hehua Li, Yuanyuan Huang: Language polishing; Fengchun Wu, Yuanyuan Huang, Kai Wu: Revision. Corresponding authors Correspondence to Kai Wu or Fengchun Wu. Declaration of competing interest The authors declare no conflicts of interest in conducting this study or preparing the manuscript. Acknowledgments None. Ethics approval and consent to participate All procedures in this study were conducted in accordance with the Declaration of Helsinki, and the current study was approved by the ethics committee of Affiliated Brain Hospital of Guangzhou Medical University. All participants signed informed consents during recruiting. Clinical trial number Not Applicable. Consent for publication Not Applicable. References Brewster GS, Peterson L, Roker R, Ellis ML, Edwards JD. Depressive Symptoms, Cognition, and Everyday Function Among Community-Residing Older Adults. J Aging Health. 2017;29(3):367–88. LeMoult J, Carver CS, Johnson SL, Joormann J. Predicting change in symptoms of depression during the transition to university: the roles of BDNF and working memory capacity. 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A biologically informed polygenic score of neuronal plasticity moderates the association between cognitive aptitudes and cortical thickness in adolescents. Dev Cogn Neurosci. 2023;60:101232. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-5978946","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":416512512,"identity":"061035c9-dceb-4bda-a548-753286bd7797","order_by":0,"name":"Chenyu Liu","email":"","orcid":"","institution":"Department of Psychiatry, The Affiliated Brain Hospital, Guangzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Chenyu","middleName":"","lastName":"Liu","suffix":""},{"id":416512513,"identity":"43a93916-08fa-437b-89b2-0210472a3bef","order_by":1,"name":"Hehua Li","email":"","orcid":"","institution":"Department of Psychiatry, The Affiliated Brain Hospital, Guangzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Hehua","middleName":"","lastName":"Li","suffix":""},{"id":416512514,"identity":"1df3e21c-62fe-4af6-beb7-2cf2a54ce779","order_by":2,"name":"Shixuan Feng","email":"","orcid":"","institution":"Department of Psychiatry, The Affiliated Brain Hospital, Guangzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Shixuan","middleName":"","lastName":"Feng","suffix":""},{"id":416512515,"identity":"67dae5ca-f160-42e2-8faf-6c0e95d131aa","order_by":3,"name":"Ziyun Zhang","email":"","orcid":"","institution":"Department of Psychiatry, The Affiliated Brain Hospital, Guangzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Ziyun","middleName":"","lastName":"Zhang","suffix":""},{"id":416512516,"identity":"a5bee6a5-cb88-4293-ba8f-d74007e3c882","order_by":4,"name":"Miaolan Huang","email":"","orcid":"","institution":"Department of Psychiatry, The Affiliated Brain Hospital, Guangzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Miaolan","middleName":"","lastName":"Huang","suffix":""},{"id":416512517,"identity":"ffc35b0b-5012-43aa-85f9-85991211915f","order_by":5,"name":"Junhao Li","email":"","orcid":"","institution":"Department of Psychiatry, The Affiliated Brain Hospital, Guangzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Junhao","middleName":"","lastName":"Li","suffix":""},{"id":416512518,"identity":"6093b64c-d544-4029-b16b-83ee2f1ff776","order_by":6,"name":"Dongchang Huang","email":"","orcid":"","institution":"The town of Dalang Experimental Primary School","correspondingAuthor":false,"prefix":"","firstName":"Dongchang","middleName":"","lastName":"Huang","suffix":""},{"id":416512519,"identity":"9ecda55c-612b-4284-a1cf-417a8982785e","order_by":7,"name":"Yuanyuan Huang","email":"","orcid":"","institution":"Department of Psychiatry, The Affiliated Brain Hospital, Guangzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yuanyuan","middleName":"","lastName":"Huang","suffix":""},{"id":416512520,"identity":"f0f532cc-c77e-418f-8eac-7893da39a64f","order_by":8,"name":"Kai Wu","email":"","orcid":"","institution":"School of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus","correspondingAuthor":false,"prefix":"","firstName":"Kai","middleName":"","lastName":"Wu","suffix":""},{"id":416512521,"identity":"934506f7-4e25-4beb-ab68-1bb05c014dcb","order_by":9,"name":"Fengchun Wu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABD0lEQVRIie3RsUoDMRjA8S8E7paoa26QvkJKoXQQ+yoXhJtuE8ShQ0IkLoprX8Pl6OgRuC5xPziHykFBcKg4FTqY3uaQ40bB/IcMIT9CvgCEQn+wM4xke7ill/O1egEkuk3WS5J7pRixF1dgq3QYYXat6cldhkSds2EEaq5YIgxGIv/+2K8KLmJVUFi8eQVacrkZr8wphtdiltiGC1LdUKi2XoKpu4VbgyP0WLCxdoTmU4qE8ZKIck1LbdADJlvGj2T02U8IKXUidYaWEcGbsruF9BMaSzUBN2RGoimSuplokl3P0spP5iZ+b8F9JRu17ddeN+dPsXmudws/+f2ubj0u6SDgprcbeDAUCoX+WT+vcV6bJWYWLgAAAABJRU5ErkJggg==","orcid":"","institution":"Department of Psychiatry, The Affiliated Brain Hospital, Guangzhou Medical University","correspondingAuthor":true,"prefix":"","firstName":"Fengchun","middleName":"","lastName":"Wu","suffix":""}],"badges":[],"createdAt":"2025-02-07 07:53:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5978946/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5978946/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":76572380,"identity":"2afb9f27-ee87-4c80-a131-338e3c9f357b","added_by":"auto","created_at":"2025-02-18 13:50:41","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":118569,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of MCCB between patients with MDD and HCs.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5978946/v1/bd8dd66d689e814d7e3123c9.png"},{"id":76572382,"identity":"7d0d09e5-c943-4346-941c-1c8502729d3e","added_by":"auto","created_at":"2025-02-18 13:50:41","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":515862,"visible":true,"origin":"","legend":"\u003cp\u003eDifferences in CT between patients with MDD and HCs.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5978946/v1/d4897c227e860815f860baef.png"},{"id":76572381,"identity":"36bfe5da-2a8e-4d96-ad8a-89094fe17b59","added_by":"auto","created_at":"2025-02-18 13:50:41","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":48567,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelations between CT in the right middle frontal gyrus and working memory score in the MDD.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5978946/v1/9d943f1ce4dbafa514ecea40.png"},{"id":107861672,"identity":"e733d342-2368-4033-96e3-73600a750297","added_by":"auto","created_at":"2026-04-27 05:41:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1088254,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5978946/v1/41183ae3-9443-4c48-8d93-5aecd9740643.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Correlation Between Middle Frontal Gyrus Cortical Thickness and Working Memory in First-episode Treatment-naïve Major Depressive Disorder","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCognitive impairment is a characteristic manifestation of Major Depressive Disorder (MDD) that affects attention, memory, executive function, and information processing speed. This is one of the reasons for the poor prognosis of patients, seriously affecting their social function and ability to live independently, which pose a great burden and risk to the family and society. Cognitive impairment of varying degrees is a widespread clinical performance in patients with MDD; more than 20% of patients with first-episode MDD and more than 50% of patients with recurrent MDD have cognitive impairment [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Nevertheless, the current understanding of cognitive impairment in MDD is limited.\u003c/p\u003e \u003cp\u003eCortical thickness (CT) is a structural magnetic resonance imaging index that affects the pathophysiology and clinical course of MDD [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. An earlier study demonstrated that individuals with MDD exhibit thinner cortices in the frontal, temporal, parietal, and insula regions [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Another study reported that patients with MDD show significantly CT reductions in several regions [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. There have also been reports of a correlation between CT and disease duration in patients with MDD [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Moreover, CT correlates to the degree of depressive symptom severity in patients with MDD [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. A meta-analysis reveals enhanced CT in the ventromedial prefrontal cortex for patients with MDD. In contrast, there was a reduction in CT of the middle temporal gyrus [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. CT has also been identified as an important predictor of clinical symptom relief and cognitive improvement [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In summary, CT abnormalities significantly contribute to the pathological mechanism of MDD. However, there are still fewer studies on the correlation of CT abnormalities with cognitive impairment in MDD.\u003c/p\u003e \u003cp\u003eRecently, more and more studies have demonstrated a close relationship between cognitive function and CT. The majority of current research has focused on schizophrenia. Fan et al. demonstrated that CT in the pars opercularis of the inferior frontal cortex, superior frontal cortex, and right caudal middle frontal gyrus was significantly associated with cognitive deficits in patients with schizophrenia [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Thielen et al. showed that CT in the anterior cingulate gyrus is correlated with performance in episodic and working memory [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. In addition, a correlation between CT and cognitive function has been identified in patients with bipolar disorder [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. However, only one recurrent MDD study has been reported there was a significant correlation between reduced bilateral insula and frontal cortex volume and cognitive deficits in working memory and processing speed in patients with MDD (Saleh et al., 2017). It\u0026rsquo;s unclear whether CT values have a correlation with cognitive function in patients with first-episode MDD. Consequently, the precise relationship between CT and cognitive impairment in patients with MDD still requires additional study.\u003c/p\u003e \u003cp\u003eThe purpose of this study was to elucidate the relationship between CT and cognitive impairment in patients with MDD. We hypothesized that CT abnormalities in patients with MDD are correlated with cognitive performance.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003e Approval for this research was granted by the Ethics Committee of the Affiliated Brain Hospital of Guangzhou Medical University. All participants signed a written informed consent before participation. In this study, 105 patients with first-episode treatment-na\u0026iuml;ve MDD were included through the psychiatry departments of the Affiliated Brain Hospital of Guangzhou Medical University, and 53 healthy controls (HCs) of similar sex and age were recruited openly from WeChat through community advertisements and other forms.\u003c/p\u003e \u003cp\u003eAll participants of the inclusion criteria as follows: (I) Han Chinese and right-handed. (II) aged 18\u0026ndash;45 years old and had at least 6 years of education. The criteria for including participants with MDD were: (I) they satisfied the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR) standards for diagnosing MDD. (II) MDD was defined as the first episode without medication or irregularly taking medication for less than 2 weeks and had a duration of less than 2 years. (III) The minimum score on the Hamilton Depression Rating Scale-17 (HAMD-17) was \u0026ge;\u0026thinsp;17. All participants of the exclusionary criteria as follows: (I) presence of other mental disorders. (II) severe or unstable physical illness. (III) history of head trauma or impaired consciousness. (IV) contraindications to magnetic resonance scanning. (V) illnesses that may cause emotional problems such as thyroid dysfunction and anemia. The research was conducted in accordance with the most recent revision of the Declaration of Helsinki (2013).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAssessment of clinical symptoms and cognitive functions\u003c/h3\u003e\n\u003cp\u003eHAMD-17 was employed to evaluate depressive symptoms [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Cognitive performance was evaluated with the Chinese version of the MATRICS Consensus Cognitive Battery (MCCB) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], which comprises five dimensions of the MCCB [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]: Working Memory, Speed of Processing, Verbal Learning, Attention/Vigilance, and Visual Learning. The outcomes of these scales were presented as T-scores. Each scale was scored by psychiatric professionals who had undergone scale consistency training and met qualification criteria.\u003c/p\u003e\n\u003ch3\u003eAcquisition and analysis of magnetic resonance imaging(MRI)\u003c/h3\u003e\n\u003cp\u003eMRI was collected by the scanner of Siemens 3T at the hospital where we conducted research. At least one consultant radiologist and one psychiatrist performed the MRI scans, which were reviewed by at least one specialized radiologist and one psychiatrist. All participants were asked to lie on their backs and breathe calmly, stay awake and relaxed, minimize head and body movements, not engage in any thinking activities, and use special non-magnetic headphones and fixed headgear to minimize distractions and head movements during the scanning process. All participants had structural magnetic resonance imaging data generated by the sequence of magnetization-prepared rapid gradient-echo (MPRAGE) and the sets were as follow: repetition time\u0026thinsp;=\u0026thinsp;2000 ms, echo time\u0026thinsp;=\u0026thinsp;2.32 ms, flip angle\u0026thinsp;=\u0026thinsp;8\u0026deg;, spatial resolution\u0026thinsp;=\u0026thinsp;0.9 mm * 0.9 mm * 0.9 mm, and 256 * 256 * 208 matrix.\u003c/p\u003e \u003cp\u003eThe preprocessing of structural MRI data was carried out using the Statistical Parametric Mapping (SPM12, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.fil.ion.ucl.ac.uk/spm/software/spm12\u003c/span\u003e\u003cspan address=\"http://www.fil.ion.ucl.ac.uk/spm/software/spm12\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and Computational Anatomy Toolbox (CAT12, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.neuro.uni-jena.de/cat\u003c/span\u003e\u003cspan address=\"http://www.neuro.uni-jena.de/cat\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) software packages, operating within the Matlab2022b environment [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The specific processing flow was as follows: 1) Using default parameters, data were segmented to separate individual structural images into cortical data, cerebrospinal fluid, white matter, and gray matter. 2) Calculation of the total intracranial volume (TIV) to correct for differences in brain size and volume. 3) All participant images have been aligned to the Montreal Neurological Institute (MNI) standard space. 4) The quality and homogeneity of the segmented images were assessed. 5) For the purpose of improving the signal-to-noise ratio (S/N) and fidelity of the data, the segmented cortical data were smoothed using a 15 mm*15 mm*15 mm full width at half-maximum (FWHM) Gaussian kernel to facilitate further statistical analysis.\u003c/p\u003e \u003cp\u003eCT was the distance between the surface of the cerebral cortex and medulla. This can be calculated using a surface-based morphometry [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The basic principle of this calculation is to reconstruct the surface of the brain using three-dimensional structural images. This was followed by the calculation of the CT of each brain region using a series of algorithms.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe composition of sex within the groups underwent Chi-square test to ascertain the presence of any significant variations. The Kolmogorov-Smirnov test was employed to ensure whether other continuous variables coincident to a normal distribution across each group. Variables exhibiting a normal distribution within individual groups underwent two-sample t-test comparisons to detect differences. In cases where variables deviated from a normal distribution, the Wilcoxon rank-sum test was employed. The significance level was set at 0.05. CT differences between the two groups were assessed using two-sample t-tests with TIV, education, sex, and age as covariates using SPM12. Cluster-level inference was performed using Bonferroni correction with a significance level of 0.001. To inspect the relationship between CT and cognitive performance in the two groups of subjects, we identified regions where CT differences between groups as ROIs. We then conducted partial correlation analyses of these ROIs with five dimensions of MCCB scores for both groups of participants, including education, sex, and age as covariates. The level of significance for both demographic and clinical characteristic statistics was 0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eClinical data and cognitive functions\u003c/h2\u003e\n \u003cp\u003eClinical and cognitive data are presented in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig. 1. Patients with MDD had higher level of education and less scores of the five dimensions of MCCB than HCs (All \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05), but there were no differences in sex and age (All \u003cem\u003ep\u003c/em\u003e\u0026gt;0.05).\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eClinical data and cognitive functions of MDD and HCs\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMDD(n\u0026thinsp;=\u0026thinsp;105)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHCs(n\u0026thinsp;=\u0026thinsp;53)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\chi\\:}^{2}/t\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e (Male/Female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39/66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26/27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.704\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.090\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e (Year)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.7 (3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.4 (2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.065\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.151\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation\u003c/strong\u003e (Year)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17 (2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-4.518\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge at onset\u003c/strong\u003e (Year)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22.8 (3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCourse of illness\u003c/strong\u003e (month)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.6 (9.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHAMD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.2 (4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMCCB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eWorking Memory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40.1 (11.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48.3 (11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.582\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpeed of Processing\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32.9 (9.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46.0 (11.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.592\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eVerbal Learning\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34.4 (9.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41.4 (8.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.671\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.002\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAttention/Vigilance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34.7 (9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42.0 (8.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.153\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eVisual Learning\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40.5 (8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45.7 (7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.435\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.012\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eAbbreviations\u003c/strong\u003e: MDD, major depressive disorder; HCs, healthy controls; HAMD, Hamilton Rating Scale for Depression.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eIntergroup differences in CT\u003c/h3\u003e\n\u003cp\u003eComparing the morphological indices of the MDD and HCs groups, we found significant differences in CT in the bilateral precentral gyri and right middle frontal gyrus (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, Fig.\u0026nbsp;2).\u003c/p\u003e\n\u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eComparison of CT between patients with MDD and HCs.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHemisphere\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRegion\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCluster-size\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePeak MNI\u003c/p\u003e\n \u003cp\u003e(x,y,z)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eT value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eThe overlap rate of DK atlas\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eprecentral\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-37,-9,60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eprecentral\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e348\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(33,-8,50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecaudalmiddlefrontal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003e\u003cstrong\u003eAbbreviations\u003c/strong\u003e: CT, cortical thickness; MDD, major depressive disorder; HCs, healthy controls; DK atlas, Desikan-Killiany atlas.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ch3\u003eCorrelation between CT and cognitive performance in MDD\u003c/h3\u003e\n\u003cp\u003eCorrelation analysis revealed a positive correlation between CT in the right middle frontal gyrus and working memory in the MDD group. Furthermore, we didn\u0026rsquo;t find correlation results in HCs (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, Fig.\u0026nbsp;3).\u003c/p\u003e\n\u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCorrelations between five dimensions score of MCCB and CT in MDD.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHemisphere\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRegion\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eWM\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSOP\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVRB\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAV\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVIS\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eprecentral\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003er\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.099\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.140\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.101\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.323\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.876\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.160\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.637\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.311\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eprecentral\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003er\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.046\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.159\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.257\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.646\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.086\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.478\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.111\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003ecaudalmiddlefrontal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003er\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.094\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.188\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.026*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.475\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.201\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.349\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"8\"\u003e\n \u003cp\u003e\u003cstrong\u003eAbbreviations\u003c/strong\u003e: CT, cortical thickness; MDD, major depressive disorder; WM, working memory; SOP, speed of processing domain; VRB, verbal learning; AV, attention/vigilance; VIS, visual learning.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study represents an inaugural investigation into the correlation between CT and cognitive performance, with the following pivotal findings: (1) Cognitive profiles indicated significantly diminished dimensional scores for in individuals diagnosed with MDD as compared to HCs. (2) There were abnormalities in the CT of the brain in patients with MDD compared with HCs, as evidenced by a decrease in the CT of the bilateral precentral gyri and right middle frontal gyrus in the MDD patients. (3) The working memory scores of cognitive performances in MDD were found to be positively associated with CT of right middle frontal gyrus.\u003c/p\u003e \u003cp\u003eOur study found that patients with MDD had diminished cognitive performance scores than patients with HC in all five dimensions, which were consistent with previous research in patients with first-episode MDD experience a pervasive disturbance in cognitive functioning [\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Wang et al. revealed pervasive and marked impairments in all cognitive domains in young and middle-aged Chinese patients diagnosed with MDD by MCCB [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Snyder et al. showed that patients with middle-aged MDD performed significantly worse than HCs in the domains of verbal fluency, coded symbols, and other information processing speed [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Nevertheless, only a small proportion of studies have yielded findings contrary to the aforementioned results. A study that included 36 cases of first-episode MDD, 71 cases of MDD receiving medication, and 59 HCs reported no evidence of cognitive impairment in young patients (aged 18\u0026ndash;50 years) across multiple dimensions, including processing speed, attention, executive function, and spatial working memory [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Another study employed the Montreal Cognitive Assessment observed no cognitive deficits in patients aged 18\u0026ndash;24 years with MDD compared to HCs [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Differences in these results may be attributed to differences in the general information and clinical characteristics of these studies and the use of different cognitive testing tools [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. But in any case, cognitive impairment in MDD is definitive.\u003c/p\u003e \u003cp\u003eOur results also showed that CT of the bilateral precentral gyri were markedly reduced in MDD patients compared to HCs. The reduction of CT in the precentral gyrus was paralleled by outcomes in previous studies [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The precentral gyrus is involved in working memory, including attention, cognitive control, and executive functions, and aids in maintaining attention, focus, and regulation of cognitive resources [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Abnormalities in the CT in this region may directly contribute to motor dysfunction, resulting in negative emotions and cognitive imbalances that can lead to depression. In addition, our study also exhibited that the CT of the right medial frontal gyrus was distinctly reduced compared with HCs in MDD patients. This is according with some previous studies [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. But other studies have found the opposite result. For instance, a study involving 16 adolescents with MDD and 30 HCs reported an increased bilateral CT in the middle frontal gyrus in MDD [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. The frontal lobe, situated anterior to the central sulcus, encompasses the frontal part of the brain and is intimately correlated with higher cognitive functions, behavioral control, and social interaction [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. The middle frontal gyrus is a key brain region that supports numerous cognitive and motor functions and plays a significant role in the cognitive, emotional, and social functions that are essential for complex human thought and behavior [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Patients with major depression show varying degrees of impairment in cognitive function, which may lead to inconsistent CT changes in different parts of the frontal lobe in different studies. Besides, abnormalities in the middle frontal gyrus can disrupt its connectivity with regions such as the anterior cingulate and amygdala gyrus, leading to disturbances in emotion regulation and memory function [\u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Certain patients may experience cortical thickening due to the overuse of emotion-regulating mechanisms, whereas others may exhibit cortical thinning due to diminished emotion-regulating abilities. This may also be one of the reasons for the inconsistent CT changes in the middle frontal gyrus in different studies. Furthermore, the sample size and method of calculating CT may also contribute to this discrepancy. But in any case, these studies suggest that frontal lobe structure is abnormal in patients with MDD and that frontal lobe damage may contribute to the pathophysiology of cognitive impairment in major depression by affecting mood, memory, and social function.\u003c/p\u003e \u003cp\u003eFinally, and most importantly, our study is the first to show a positive correlation between the working memory score of the MCCB and the CT of the right middle frontal gyrus in the MDD patients after adjusting for demographic variables and clinical symptoms. So far, only one study on the relationship between frontal CT and cognitive deficits in individuals with treatment-resistant MDD, and the results suggest a positive correlation between frontal lobe structure and working memory tasks [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], which is similar to our findings. Similar findings have been observed for other psychiatric disorders. Prior research on bipolar disorder has demonstrated a correlation between CT in the frontal and parietal lobes and working memory [\u003cspan additionalcitationids=\"CR39\" citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Working memory, a component of short-term memory, involves the temporary storage and processing of information to perform cognitive tasks such as reasoning, comprehension, and learning [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The middle frontal gyrus is a component of the brain's executive control network that supports numerous cognitive and motor functions and plays a significant role in the cognitive, emotional, and social functions essential for complex human thought and behavior [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. This function is achieved through the coordinated activity of multiple frontal and parietal regions, which collectively facilitate the management and regulation of complex tasks such as working memory. Furthermore, an increase in CT is typically associated with an increase in neuronal density [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. An increase in the number of neurons and the prominence of their connections enhances the processing and integration of information, which is essential for the completion of complex cognitive tasks [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. This indicates that cognitive alterations observed in patients with MDD may be attributed to the decrease of middle frontal gyrus. However, more research is needed to further affirm the relationship between CT of the right middle frontal gyrus and working memory. Future studies may investigate interventions directed at the middle frontal gyrus to enhance cognitive function in patients with MDD, potentially offering novel therapeutic targets and approaches for addressing cognitive deficits correlated with the disorder.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, this study found that patients with first-episode MDD exhibited substantial impairments in cognitive functioning, with significant reductions in multiple domains, including working memory, speed of processing, verbal learning, attention/vigilance and visual learning, when compared with HCs. Moreover, individuals with MDD demonstrated reduced CT in the bilateral precentral gyri and right middle frontal gyrus than HCs. Furthermore, decreased CT in the right middle frontal gyrus correlated with impaired working memory in individuals with MDD. Our research results indicate that frontal CT is a pivotal factor in the etiology of MDD and cognitive impairment in those affected.\u003c/p\u003e \u003cp\u003eThis study has several limitations. First, as an exploratory investigation of the connection between the brain structure and cognitive performance, we were unable to establish a causal relationship between these two variables. Rather, it can only speculate on potential correlations. Second, despite controlling for educational level to mitigate its effects, the generalizability of the current findings to individuals of different educational backgrounds may be constrained.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eMDD\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Major Depressive Disorder\u003c/p\u003e\n\u003cp\u003eCT\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;cortical thickness\u003c/p\u003e\n\u003cp\u003eMRI\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;magnetic resonance imaging\u003c/p\u003e\n\u003cp\u003eHCs\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;healthy controls\u003c/p\u003e\n\u003cp\u003eDSM-V\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Diagnostic and Statistical Manual of Mental Disorders\u003c/p\u003e\n\u003cp\u003eHAMD-17\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;17-item Hamilton Depression Rating Scale\u003c/p\u003e\n\u003cp\u003eMCCB\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;MATRICS Consensus Cognitive Battery\u003c/p\u003e\n\u003cp\u003eWM\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Working Memory\u003c/p\u003e\n\u003cp\u003eSOP\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Speed of Processing Domain\u003c/p\u003e\n\u003cp\u003eVRB\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Verbal Learning\u003c/p\u003e\n\u003cp\u003eAV\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Attention/Vigilance\u003c/p\u003e\n\u003cp\u003eVIS\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Visual Learning\u003c/p\u003e\n\u003cp\u003eMPRAGE\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;magnetization-prepared rapid gradient-echo sequence\u003c/p\u003e\n\u003cp\u003eCAT12\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Computational Anatomy Toolbox\u003c/p\u003e\n\u003cp\u003eTIV\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;total intracranial volume\u003c/p\u003e\n\u003cp\u003eMNI\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Montreal Neurological Institute\u003c/p\u003e\n\u003cp\u003eFWHM \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;full width at half-maximum\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by Key-Area Research and Development Program of Guangdong Province (2023B0303020001), National Natural Science Foundation of China (82301688), the Science and Technology Program of Guangzhou (202206060005, 202201010093, 2023A03J0856, 2023A03J0839), Guangdong Basic and Applied Basic Research Foundation Outstanding Youth Project (2021B1515020064), Medical Science and Technology Research Foundation of Guangdong (A2023224), the Natural Science Foundation Program of Guangdong (2023A1515011383), the Health Science and Technology Program of Guangzhou (20231A010036), Guangzhou TCM Clinical Core Technology Construction Project：Acupuncture method of \u0026quot;TongyangXingshen\u0026quot; to Treat Mental Disorders Caused by Stagnation of yang qi., \u0026quot;1+N\u0026quot; Construction Project of Guangzhou Acupuncture and Moxibustion Hospital, Major Innovation Technology Construction Project of Synergistic Chinese Medicine and Western Medicine of Guangzhou (No.2023-2318), Primary and Secondary School Teachers\u0026apos; educational Capacity Improvement Program of Guangdong (2023YQJK438), National Traditional Chinese and Western Medicine Collaborative Project for Major and Complex Diseases (Comprehensive Department of the National Administration of Traditional Chinese Medicine [2024] No. 3), Guangzhou Municipal Key Discipline in Medicine (2025-2027), the Research capacity improvement project of Guangzhou Medical University (2024SRP200), and Guangzhou Research-oriented Hospital. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors and Affiliations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDepartment of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China\u003c/p\u003e\n\u003cp\u003eChenyu Liu, Hehua Li, Shixuan Feng, Ziyun Zhang, Miaolan Huang, Junhao Li, Yuanyuan Huang \u0026amp; Fengchun Wu\u003c/p\u003e\n\u003cp\u003eThe town of Dalang Experimental Primary School, Dongguan, China\u003c/p\u003e\n\u003cp\u003eDongchang Huang\u003c/p\u003e\n\u003cp\u003eSchool of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou, China\u003c/p\u003e\n\u003cp\u003eKai Wu\u003c/p\u003e\n\u003cp\u003eGuangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China\u003c/p\u003e\n\u003cp\u003eFengchun Wu\u003c/p\u003e\n\u003cp\u003eGuangdong Engineering Technology Research Center for Diagnosis and Rehabilitation of Dementia, Guangzhou, China\u003c/p\u003e\n\u003cp\u003eFengchun Wu\u003c/p\u003e\n\u003cp\u003eKey Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, China\u003c/p\u003e\n\u003cp\u003eFengchun Wu\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eChenyu Liu, Hehua Li: Conceptualization, Investigation, Writing-Original draft preparation; Chenyu Liu, Shixuan Feng: Methodology, Software; Chenyu Liu, Ziyun Zhang, Miaolan Huang, Junhao Li, Dongchang Huang: Subject Recruitment, Data collection; Fengchun Wu, Yuanyuan Huang, Kai Wu, Dongchang Huang: Supervision; Hehua Li, Yuanyuan Huang: Language polishing; Fengchun Wu, Yuanyuan Huang, Kai Wu: Revision.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding authors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence to Kai Wu or Fengchun Wu.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of competing interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflicts of interest in conducting this study or preparing the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll procedures in this study were conducted in accordance with the Declaration of Helsinki, and the current study was approved by the ethics committee of Affiliated Brain Hospital of Guangzhou Medical University. All participants signed informed consents during recruiting.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBrewster GS, Peterson L, Roker R, Ellis ML, Edwards JD. Depressive Symptoms, Cognition, and Everyday Function Among Community-Residing Older Adults. J Aging Health. 2017;29(3):367\u0026ndash;88.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLeMoult J, Carver CS, Johnson SL, Joormann J. Predicting change in symptoms of depression during the transition to university: the roles of BDNF and working memory capacity. 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Dev Cogn Neurosci. 2023;60:101232.\u003c/span\u003e\u003c/li\u003e\u003c/ol\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":"Cortical thickness, Middle frontal gyrus, Major depressive disorder, Cognitive performance","lastPublishedDoi":"10.21203/rs.3.rs-5978946/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5978946/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eCognitive impairment is regarded as a pivotal symptom of Major Depressive Disorder (MDD). Previous studies have indicated the presence of abnormalities in cortical thickness (CT) in patients with MDD. However, the relationship between cognitive performance and CT abnormalities in patients with MDD remains unclear. Our study purposed to survey the changes in CT in patients with MDD and their relationship with cognitive impairment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eA total of 105 patients with first-episode treatment-naïve MDD and 53 healthy controls (HCs) received T1-weighted magnetic resonance imaging (MRI) and a series of neuropsychological tests. Initially the differences in CT and cognitive performance between patients with MDD and HCs were contrasted. Subsequently, the correlation between CT and cognitive performance were analyzed for significant changes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eAll five cognitive dimensions were significantly different between patients with MDD and HCs. Meanwhile, the CT of the bilateral precentral gyri and right middle frontal gyrus were reduced in the MDD group. Besides, the CT of the right middle frontal gyrus shows a positive relationship with working memory dimension scores of the MDD group.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eCT abnormalities in patients with MDD are correlated with cognitive performance.\u003c/p\u003e","manuscriptTitle":"The Correlation Between Middle Frontal Gyrus Cortical Thickness and Working Memory in First-episode Treatment-naïve Major Depressive Disorder","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-02-18 13:50:37","doi":"10.21203/rs.3.rs-5978946/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":"8fa2c6ab-2578-4b13-8779-c51b9d881f84","owner":[],"postedDate":"February 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-27T05:40:46+00:00","versionOfRecord":[],"versionCreatedAt":"2025-02-18 13:50:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5978946","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5978946","identity":"rs-5978946","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}