Quantitative EEG of Frontal and Central Cortices During Calm Memory Retrieval in Schizophrenia

Quantitative EEG of Frontal and Central Cortices During Calm Memory Retrieval in Schizophrenia | 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 Quantitative EEG of Frontal and Central Cortices During Calm Memory Retrieval in Schizophrenia Supalak Khemthong, Maliwan Rueankam, Winai Chatthong This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7781055/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 and emotional dysregulation in schizophrenia is frequently associated with altered neural oscillatory patterns. Frontal theta activity, in particular, has been linked to working memory and internalized calmness. This study investigated theta dynamics using quantitative EEG (QEEG) during a memory-related calmness task to identify brain regions involved in cognitive-emotional processing. Methods: Thirty individuals with schizophrenia (mean age = 38.9 ± 7.15 years) completed a structured memory recall task embedded in the Brain Mapping Performance (BMP) protocol. QEEG signals were recorded from 12 scalp locations, with analyses focused on theta relative power at key frontal and central sites (Fp1, Fz, F4, F7, Cz, T3). Behavioral performance (memory accuracy, task duration) and self-reported calmness were also measured. Repeated measures ANOVA assessed effects of condition (calm, rest, task), time, and their interaction. Results: Theta relative power significantly increased during memory recall at frontal-midline and central electrodes. Statistically significant effects were observed for Condition [F(1.185, 26.077) = 105.844, p < .001], Time [F(1.412, 31.073) = 119.687, p < .001], and the Condition × Time interaction [F(1.308, 1.357) = 125.381, p < .001]. Memory accuracy declined under EEG monitoring (41.43 ± 21.47%) compared to baseline (47.71 ± 27.20%), while task completion time increased (874.22 ± 331.82 s vs. 738.35 ± 191.11 s, p = .017), indicating elevated cognitive demands. Conclusion: Frontal and central theta activity reflects cognitive engagement during calm memory tasks in schizophrenia. BMP may offer a valuable behavioral-neurophysiological interface for individualized assessment and cognitive rehabilitation in psychiatric care. Cognitive Neuroscience Psychiatry Occupational Medicine Biomedical Engineering Theta relative power QEEG schizophrenia working memory calmness brain mapping executive function 1. Introduction Schizophrenia is a chronic psychiatric disorder marked by profound disturbances in cognition, emotion, and behavior. Among its cognitive sequelae, deficits in working memory, attentional regulation, and emotional processing are especially disabling and predictive of long-term functional outcomes (Su et al., 2011 ; Hasey & Kiang, 2013 ). Neurophysiological approaches, such as quantitative electroencephalography (QEEG), offer non-invasive and dynamic insights into these impairments by capturing oscillatory brain activity associated with cognitive and affective states (Newson & Thiagarajan, 2019 ; Sharma et al., 2020 ). Theta-band oscillations (4–7 Hz) have emerged as biomarkers of episodic memory, cognitive control, and internally directed attention. Frontal-midline theta, in particular, reflects top-down executive regulation and is frequently linked to calm, focused mental states (Tang et al., 2019 ; Choi et al., 2020 ). In schizophrenia, altered theta dynamics often characterized by hypoactivation or compensatory overactivation have been observed during memory encoding and cognitive control tasks, reflecting disrupted executive processing under varying demands (Xiang et al., 2019 ; Bose et al., 2014 ). Despite increasing interest in oscillatory biomarkers, few studies have explored the role of theta activity during tasks that simultaneously elicit memory retrieval and emotional calmness neurocognitive states essential for adaptive daily functioning. Furthermore, translating QEEG findings into meaningful, occupation-based interventions remains limited in psychiatric rehabilitation. The ability to identify neurophysiological signatures that reflect both cognitive readiness and affective regulation may advance precision-based occupational therapy approaches (Chatthong, Khemthong, & Wongsawat, 2020a , 2020b ). To address this gap, we employed the Brain Mapping Performance (BMP) protocol an occupation-integrated QEEG assessment to examine theta activity during a calm memory task in individuals with schizophrenia. Our objectives were twofold: (1) to identify brain regions where theta power is modulated during calm memory retrieval, and (2) to explore the relationship between these patterns and both behavioral performance and perceived calmness. We hypothesized that task-induced theta enhancement would be most prominent in frontal and central brain regions and would correspond to more efficient task engagement. From a neuro-occupational perspective, executive functions (EF) including working memory, attentional initiation, and inhibitory control are foundational to goal-directed behavior and everyday functioning (Grieve, 2000 ; Kluwe-Schiavon et al., 2013 ). In schizophrenia, disruption in these domains undermines one’s ability to initiate, sustain, and complete daily tasks. Thai-based occupational therapy models conceptualize EF recovery not only as cognitive restoration, but as a dynamic reintegration of self-regulation, environmental cueing, and emotional engagement through structured sensory tasks (Khemthong & Wee, 2016 ). This study contributes to emerging evidence that calm cognitive states supported by personalized cueing and humanized prompting can re-engage frontal brain systems, particularly the superior frontal gyrus and orbitofrontal cortex. These areas are central to memory consolidation and affective motivation, both of which are targeted through structured, culturally grounded sensory activities. Understanding calmness as an embodied neurofunctional state rather than merely a behavioral one may inform how BMP is used to scaffold therapeutic engagement and cognitive performance in schizophrenia. 2. Methods 2.1 Participants Thirty individuals (mean age = 38.9 ± 7.15 years; 10 male, 20 female; all right-handed) diagnosed with schizophrenia participated in this study. All participants were receiving outpatient psychiatric care and met DSM-5 and ICD-10 diagnostic criteria for schizophrenia (F20.0). All participants were assessed using the Thai version of the Positive and Negative Syndrome Scale (PANSS) prior to EEG recording to ensure clinical stability. Individuals who exhibited acute psychotic symptoms or high positive symptom scores were excluded from the session. The PANSS Thai version has demonstrated acceptable criterion validity and interrater reliability in local populations (Nilchaikovit et al., 2000). Exclusion criteria included comorbid neurological conditions and current substance use disorders. All participants provided written informed consent prior to participation. 2.2 Ethical Approval All procedures performed in this study involving human participants were approved by the Central Institutional Review Board of Mahidol University (MU-CIRB Project ID: 2020/114.1505; COA No. 2020/103.0708, approval date: August 7, 2020), and by the Ethics Committee on Mental Health Research in Human Subjects, Department of Mental Health, Ministry of Public Health, Thailand (DMH.IRB Project ID: 031/2563, Version 2; COA No. 041/2563, approval date: October 28, 2020). 2.3 Procedure and Task Design Participants completed a spatial memory recall task involving nine occupations, randomly arranged in a 3×3 matrix, based on the Thai Physical Activity Guideline. The task was delivered via a mobile application developed by the authors. Three cognitive conditions were assessed: (1) a 3-minute calming task with eyes closed, (2) a 3-minute resting task with eyes open, and (3) the memory task, consisting of four 30-second trials. During the memory task, participants were instructed to recall the nine occupations and their spatial locations within the matrix by touching the corresponding positions on the screen, while maintaining a relaxed posture. Quantitative EEG (QEEG) was continuously recorded using a 12-channel system known as Brain Mapping Performance (BMP). 2.4 QEEG Recording and Analysis QEEG signals were recorded using a 12-electrode montage based on the International 10–20 system. Data were sampled and processed offline to extract theta relative power (4–7 Hz), calculated as the proportion of total spectral power. Analyses focused on six primary electrode sites: Fp1, Fz, F4, F7, Cz, and T3, selected for their relevance to frontal and temporal cognitive functions. Standard artifact rejection and bandpass filtering procedures were applied to ensure signal integrity. In addition, the theta/beta ratio was computed to aid in interpretation: higher theta/beta ratios were indicative of internalized or inattentive states, while lower ratios reflected focused attention. A repeated-measures ANOVA was conducted to examine the effects of condition and time on cognitive-emotional performance. 3. Results 3.1 QEEG Theta Relative Power Significant increases in theta relative power were observed during the BMP-monitored memory task compared to the non-memory task, particularly in the frontal-midline (Fz) and central (Cz) regions. Statistical analysis showed a significant main effect of condition, F(1.185, 26.077) = 105.844, p < .001, indicating that different tasks led to statistically different performance outcomes. There was also a significant main effect of time, F(1.412, 31.073) = 119.687, p < .001, suggesting that performance changed significantly across time points. Importantly, a significant interaction effect was found between condition and time, F(1.308, 1.357) = 125.381, p < .001, indicating that the effectiveness of each condition varied depending on the time of assessment. When a descriptive data of theta relative power showed at six QEEG site, under eye-closed conditions were the highest percent at Fz (23.87 ± 10.88), followed by Cz (22.52 ± 11.76), suggesting a strong activation of midline structures during relaxed memory states. Compared to eye-opened resting, all frontal sites demonstrated higher percent, indicating a neurophysiological signature of calmness during internalized condition. The resting condition produced intermediate values, suggesting a transition between internal and external processing states (see Table 1.) Table 1. Mean + SD Theta Relative Power (%) at Each QEEG Site (Calm vs. Rest vs. Memory) QEEG Site Calm (Eyes Closed) Rest (Eyes Opened) Memory Task Fp1 20.50 + 9.15 16.51 + 4.97 18.21 + 5.70 F7 19.61 + 8.42 18.45 + 5.04 17.83 + 4.05 F4 21.97 + 10.23 20.75 + 5.47 20.12 + 4.99 Fz 23.87 + 10.88 22.99 + 6.42 22.77 + 6.04 Cz 22.52 + 11.76 21.95 + 6.20 20.85 + 5.51 T3 17.37 + 9.50 16.29 + 6.83 14.40 + 4.72 3.2 QEEG Theta/Beta Ratio Six frontal and central QEEG sites were measured under three cognitive states: calm (eyes closed), rest (eyes opened), and active memory task as shown in Table 2. Theta/beta ratios varied systematically across cognitive conditions and QEEG sites. The highest ratios were observed during the calm condition (eyes closed), with peak values at Fz (1.56 ± 0.22) and Fp1 (1.54 ± 0.15), indicating elevated internalized attention and relaxation. In contrast, lower ratios were seen during the memory task, particularly at T3 (0.68 ± 0.15) and Cz (1.14 ± 0.10), reflecting increased executive effort and sensory-motor integration. Table 2. Mean + SD Theta/Beta Ratio at Each QEEG Site (Calm vs. Rest vs. Memory) QEEG Site Calm (Eyes Closed) Rest (Eyes Opened) Memory Task Fp1 1.54 + 0.15 1.18 + 0.15 1.32 + 0.10 F7 1.34 + 0.15 1.03 + 0.10 1.18 + 0.13 F4 1.33 + 0.13 1.08 + 0.15 1.14 + 0.21 Fz 1.56 + 0.22 1.31 + 0.12 1.39 + 0.15 Cz 1.40 + 0.11 1.19 + 0.14 1.14 + 0.10 T3 1.04 + 0.10 0.76 + 0.20 0.68 + 0.15 At Fp1, both theta relative power and theta/beta ratio followed a similar trend, with the highest values during the calm condition and the lowest during the resting state. An increase was observed again during the memory task, suggesting that the theta/beta ratio at Fp1 was largely influenced by variations in frontal theta activity. At F7, a modest decrease in theta relative power was accompanied by a more pronounced decline in the theta/beta ratio from calm to rest. This discrepancy suggests that increased beta relative power may have contributed more significantly to the reduced ratio, particularly during the memory task. F4 exhibited relatively stable theta relative power across conditions, yet the theta/beta ratio showed a mild U-shaped pattern, with the lowest value during rest. This may reflect fluctuating beta activity levels, indicating dynamic shifts in cognitive engagement at this site. Both theta relative power and theta/beta ratio peaked at Fz during the calm condition and declined slightly during rest and memory tasks. The parallel trends suggest that Fz’s ratio is a sensitive marker of theta modulation during transitions from rest to task-oriented attention. At Cz, theta relative power and theta/beta ratio decreased progressively across conditions, with the lowest values during the memory task. This consistent pattern reflects reduced central theta dominance under increased cognitive demands and working memory engagement. T3 demonstrated the steepest decline in both theta relative power and theta/beta ratio from calm to memory conditions. This finding may indicate enhanced beta activation in the temporal lobe during memory processing, contributing to the sharply reduced theta dominance at this site. 4. Discussion This study explored task-related changes in QEEG theta relative power and theta/beta ratio across six cortical sites in individuals with schizophrenia, comparing calm (eyes-closed), rest (eyes-opened), and memory-task conditions. The results contribute to our understanding of frontal-midline and temporal dynamics during internalized attention, resting alertness, and active cognitive engagement, offering implications for cognitive assessment and intervention design in psychiatric rehabilitation (Newson & Thiagarajan, 2019; Sharma et al., 2020). 4.1 Frontal-Midline Dominance of Theta Activity The most robust finding was the consistently elevated theta relative power at Fz and Cz across all conditions, with the calm (eyes-closed) state producing the highest amplitudes (Fz = 23.87 ± 10.88; Cz = 22.52 ± 11.76). These results align with previous research associating frontal-midline theta with internalized attention, relaxation, and top-down control of cognitive processes (Tang et al., 2019; Choi et al., 2020). The decline in theta power from calm to rest, and further into the memory task—especially at Cz (from 22.52 to 20.85)—reflects increasing executive demands and sensorimotor integration as task complexity increases (Xiang et al., 2019; Bose et al., 2014). The significant interaction between condition and time (F(1.308, 1.357) = 125.381, p < .001) supports this dynamic modulation across both brain sites and task phases, suggesting time-sensitive cognitive adaptation under load. 4.2 Theta/Beta Ratio as a Biomarker of Task Engagement Theta/beta ratios demonstrated strong state sensitivity, with the highest ratios during calm conditions, especially at Fz (1.56 ± 0.22) and Fp1 (1.54 ± 0.15), and the lowest ratios at T3 during memory tasks (0.68 ± 0.15). This progression supports the role of theta/beta ratio as a neurophysiological marker of attentional regulation and cognitive readiness (Newson & Thiagarajan, 2019). The drop in this ratio from rest to task reflects enhanced beta synchronization during focused task performance, particularly at temporal and lateral frontal sites (Hasey & Kiang, 2013). The parallel decrease in both theta power and theta/beta ratios at Fz and Cz during memory conditions underscores their utility as dual indicators of central executive effort. In contrast, the disproportionate reduction in ratio at F7 and T3, without commensurate theta decline, highlights site-specific beta recruitment—likely reflecting increased affective inhibition at F7 and auditory-emotional processing at T3 (Sklar et al., 2020; Liu et al., 2019). 4.3 Functional Interpretation by Region Frontal-midline sites (Fz, Cz) demonstrated sustained theta activity and the highest theta/beta ratios during calm states, aligning with their known roles in executive regulation and working memory (Tang et al., 2019; Grieve, 2000). These regions appear to support cognitive shifting and attentional maintenance, especially under memory load (Nahum et al., 2020). Fp1 activity may reflect internal attentional monitoring, relevant for calm-focused or mindfulness-based interventions (Bauer et al., 2020). Lateral sites revealed unique dynamics: F7 showed emotional inhibitory modulation, consistent with increased beta power during memory engagement (Khemthong & Wee, 2016), while F4 patterns suggest a role in working memory and flexible goal setting (Kluwe-Schiavon et al., 2013). Temporal site T3 showed sharp theta suppression and increased beta activity, highlighting its involvement in auditory-linguistic processing and affective responsiveness (Su et al., 2011; Sharma et al., 2020). These patterns may reflect region-specific demands placed on procedural memory and social-emotional integration during complex tasks. 4.4 Clinical and Theoretical Implications These patterns have important implications for executive function rehabilitation in schizophrenia. The ability to differentiate cognitive conditions through region-specific theta and beta activity supports the development of neuroadaptive assessment tools (Harvey, 2011; Arigo et al., 2019). The combination of theta dominance during calm states and beta activation during memory tasks may be leveraged to inform task design, therapy progression, and real-time neurofeedback (Markov-Vetter et al., 2020). Moreover, these results support the feasibility of using frontal-midline theta and theta/beta ratio as performance-sensitive biomarkers in both clinical and community-based interventions (Chatthong et al., 2020a, 2020b). The distinct electrophysiological signatures at midline (Fz, Cz) versus lateral (F7, T3) sites underscore the need for site-specific analysis in EEG-based rehabilitation, avoiding overgeneralization across frontal lobes (Xiang et al., 2019; Sharma et al., 2020). Lateral beta activation during task load may serve as an index for emotional regulation and auditory-attentional control—components often impaired in schizophrenia (Nahum et al., 2020; Liu et al., 2019). 5. Conclusion Theta relative power in frontal and central brain regions reflects cognitive and emotional states during calm memory tasks in schizophrenia. Brain Mapping Performance or BMP provide promising avenues for integrating neurophysiological data into individualized rehabilitation planning and monitoring. These findings support the use of QEEG-based metrics as a foundation for goal-oriented rehabilitation strategies in mental health care. Declarations Conflict of Interest Statement The authors declare no conflict of interest. Funding This work was supported by Electricity Generating Authority of Thailand (EGAT) in the year of 2020. Author Contributions S.K. designed the study and led data collection and manuscript drafting. M.R. contributed to data analysis and interpretation. W.C. supervised the project and finalized the manuscript as corresponding author. Acknowledgments The authors thank all participants and clinical staff involved in this study. References Bauer, M., Glenn, T., Geddes, J., Gitlin, M., Grof, P., Kessing, L. V., ... & Whybrow, P. C. (2020). Smartphones in mental health: A critical review of background issues, current status and future concerns. International Journal of Bipolar Disorders, 8(1), 2. https://doi.org/10.1186/s40345-019-0164-x Bose, A., Agarwal, S. M., Kalmady, S. V., & Venkatasubramanian, G. (2014). Cognitive mapping deficits in schizophrenia: A critical overview. Indian Journal of Psychological Medicine, 36(1), 9–26. https://doi.org/10.4103/0253-7176.127242 Breuning, L. G. (2016). Habits of a happy brain. Avon, MA: Adams Media. Cavanagh, J. F., & Frank, M. J. (2014). Frontal theta as a mechanism for cognitive control. Trends in Cognitive Sciences, 18(8), 414–421. https://doi.org/10.1016/j.tics.2014.04.012 Chatthong, W., Khemthong, S., & Wongsawat, Y. (2020a). A design thinking model based on quantitative electroencephalography in social emotional learning for attention deficit hyperactivity disorder. Mind, Brain, and Education. https://doi.org/10.1111/mbe.12235 Chatthong, W., Khemthong, S., & Wongsawat, Y. (2020b). Brain mapping performance as an occupational therapy assessment aid in ADHD. American Journal of Occupational Therapy, 74. https://doi.org/10.5014/ajot.2020.035477 Choi, J., Lim, E., Park, M. G., & Cha, W. (2020). Assessing the retest reliability of prefrontal EEG markers of brain rhythm slowing in the eyes-closed resting state. Clinical EEG and Neuroscience, 51(5), 348–356. https://doi.org/10.1177/1550059420914832 Grieve, J. I. (2000). Neuropsychology for occupational therapists: Assessment of perception and cognition. Oxford, UK: Blackwell Science. Haugen, I., Stubberud, J., Haug, E., McGurk, S. R., Hovik, K. T., Ueland, T., & Øie, M. G. (2022). A randomized controlled trial of Goal Management Training for executive functioning in schizophrenia spectrum disorders or psychosis risk syndromes. BMC Psychiatry, 22, 575. https://doi.org/10.1186/s12888-022-04197-3 Hasey, G. M., & Kiang, M. (2013). A review of recent literature employing electroencephalographic techniques to study the pathophysiology, phenomenology, and treatment response of schizophrenia. Current Psychiatry Reports, 15, 388. https://doi.org/10.1007/s11920-013-0388-x Kluwe-Schiavon, B., Sanvicente-Vieira, B., Kristensen, C. H., & Grassi-Oliveira, R. (2013). Executive functions rehabilitation for schizophrenia: A critical systematic review. Journal of Psychiatric Research, 47, 91–104. Khemthong, S., & Wee, B. (2016). Integration of occupational therapy and neuro-linguistic programming for Thais with mental health experiences. Bulletin of the Chiang Mai Association of Medical Sciences , 49 (1), 10–16. https://doi.org/10.14456/jams.2016.14 Liu, T., Zhang, J., Dong, X., Wu, J., Wang, C., & Yan, T. (2019). Occipital alpha connectivity during resting-state electroencephalography in patients with ultra-high risk for psychosis and schizophrenia. Frontiers in Psychiatry, 10, 553. https://doi.org/10.3389/fpsyt.2019.00553 Michopoulos, I., Tzavellas, E., Papakosta, V. M., & Koutsouleris, N. (2021). Cognitive rehabilitation in schizophrenia-associated cognitive impairment: A review. Mental Illness, 15(1), 2. https://doi.org/10.3390/mi15010002 Minzenberg, M. J., Laird, A. R., Thelen, S., Carter, C. S., & Glahn, D. C. (2009). Meta-analysis of 41 functional neuroimaging studies of executive function in schizophrenia. Archives of General Psychiatry, 66(8), 811–822. https://doi.org/10.1001/archgenpsychiatry.2009.91 Nahum, M., Lee, H., Fisher, M., Green, M. F., Hooker, C. I., Ventura, J., ... & Vinogradov, S. (2020). Online social cognition training in schizophrenia: A double-blind, randomized, controlled multi-site clinical trial. Schizophrenia Bulletin, 46(6), 1427–1436. https://doi.org/10.1093/schbul/sbaa085 Newson, J. J., & Thiagarajan, T. C. (2019). EEG frequency bands in psychiatric disorders: A review of resting state studies. Frontiers in Human Neuroscience, 12, 521. https://doi.org/10.3389/fnhum.2018.00521 Nilchaikovit, T., Uneanong, S., Kessawai, D., & Thomyangkoon, P. (2000). The Thai version of the Positive and Negative Syndrome Scale (PANSS) for schizophrenia: Criterion validity and interrater reliability. Journal of the Medical Association of Thailand, 83, 646–651. Sharma, A., Rai, J. K., & Tewari, R. P. (2020). Schizophrenia detection using biomarkers from electroencephalogram signals. IETE Journal of Research. https://doi.org/10.1080/03772063.2020.1753587 Sklar, A. L., Coffman, B. A., Haas, G. L., et al. (2020). Inefficient visual search strategies in the first-episode schizophrenia spectrum. Schizophrenia Research. https://doi.org/10.1016/j.schres.2020.09.015 Su, C. Y., Tsai, P. C., Su, W. L., Tang, T. C., & Tsai, A. Y. J. (2011). Cognitive profile difference between Allen cognitive levels 4 and 5 in schizophrenia. American Journal of Occupational Therapy, 65, 453–461. https://doi.org/10.5014/ajot.2011.000711 Tang, Y.-Y., Tang, R., Rothbart, M. K., & Posner, M. I. (2019). Frontal theta activity and white matter plasticity following mindfulness meditation. Current Opinion in Psychology, 28, 294–297. https://doi.org/10.1016/j.copsyc.2019.04.004 Thai Physical Activity Guideline. (n.d.). Retrieved from http://www.pt.mahidol.ac.th/tpag/index.php Tyburski, E., Mak, M., Sokołowski, A., Starkowska, A., Karabanowicz, E., Kerestey, M., & Samochowiec, J. (2021). Executive dysfunctions in schizophrenia: A critical review of traditional, ecological, and virtual reality assessments. Journal of Clinical Medicine, 10(13), 2782. https://doi.org/10.3390/jcm10132782 Xiang, J., Tian, C., Niu, Y., Yan, T., Li, D., Cao, R., et al. (2019). Abnormal entropy modulation of the EEG signal in patients with schizophrenia during the auditory paired-stimulus paradigm. Frontiers in Neuroinformatics, 13, 4. https://doi.org/10.3389/fninf.2019.00004 Zhao, L., Jiang, Y., & Zhang, H. (2016). Effects of modified electroconvulsive therapy on the electroencephalogram of schizophrenia patients. SpringerPlus, 5(1), 1063. https://doi.org/10.1186/s40064-016-2747-7 Additional Declarations The authors declare no competing interests. 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-7781055","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":524713743,"identity":"1087b7d2-2ee0-4f98-a808-5aa7ef9b71d2","order_by":0,"name":"Supalak Khemthong","email":"","orcid":"https://orcid.org/0000-0002-1974-3862","institution":"Mahidol University","correspondingAuthor":false,"prefix":"","firstName":"Supalak","middleName":"","lastName":"Khemthong","suffix":""},{"id":524713744,"identity":"01be9ebf-d78e-4cd1-8242-dd99b1e154fb","order_by":1,"name":"Maliwan Rueankam","email":"","orcid":"https://orcid.org/0000-0003-4720-9795","institution":"Mahidol University","correspondingAuthor":false,"prefix":"","firstName":"Maliwan","middleName":"","lastName":"Rueankam","suffix":""},{"id":524713745,"identity":"186a941f-1fb8-464a-a80f-731aca876d5b","order_by":2,"name":"Winai Chatthong","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7ElEQVRIiWNgGAWjYDACZiBOACH2BiDbgJmBDyJ+gAgtPAcgWtjAwgl4tEBBAoNEAkg7EVoMjvMe/PCAwS6Pf+brxM8FBdZybAzMDz8w/riDW8thvmSg+cnFErdzN0vPMEg3ZmNgM5ZgSHiGU4vZYR4DoJYDiQ23czdI8xgcTmwDCgIddhifFuMfIC3zb57d/Buihf0bIS1mYFs23ODdBrWFB78t9kAtFgkGyYkbz+Rus+YB+YWZp1giIQ23Fsn+M8Y3f1TYJc47fnbzbZ4/1nL87O0bP3ywwa0FAgyQOdDIHQWjYBSMglFAAQAAeKxPFroWXDUAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-5845-940X","institution":"Mahidol University","correspondingAuthor":true,"prefix":"","firstName":"Winai","middleName":"","lastName":"Chatthong","suffix":""}],"badges":[],"createdAt":"2025-10-04 16:33:52","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":true,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-7781055/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7781055/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":92922056,"identity":"b665742d-5cdc-4e0f-a33a-aa5fde480d86","added_by":"auto","created_at":"2025-10-07 07:19:09","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":46244,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript1RS.docx","url":"https://assets-eu.researchsquare.com/files/rs-7781055/v1/aee157c058800240fc601e89.docx"},{"id":92922057,"identity":"e51f4fc6-d922-495a-a2ed-cc72113e7ec2","added_by":"auto","created_at":"2025-10-07 07:19:09","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":342,"visible":true,"origin":"","legend":"","description":"","filename":"rs7781055.json","url":"https://assets-eu.researchsquare.com/files/rs-7781055/v1/c8a676d7227dee8766c54a98.json"},{"id":92923447,"identity":"cfbaddf2-d0b5-4237-a51d-58edebaf85b7","added_by":"auto","created_at":"2025-10-07 07:27:09","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":70764,"visible":true,"origin":"","legend":"","description":"","filename":"rs77810550enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7781055/v1/edbd15f9eb57d831c21a50b6.xml"},{"id":92922061,"identity":"7bd6ea7f-7a61-4638-a860-0f8e4d7dea8f","added_by":"auto","created_at":"2025-10-07 07:19:09","extension":"xml","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":68269,"visible":true,"origin":"","legend":"","description":"","filename":"rs77810550structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7781055/v1/87111f1bd8a70fabd2f51a2f.xml"},{"id":92922060,"identity":"be15d035-0d9c-4e6d-8a33-fcf7302449bd","added_by":"auto","created_at":"2025-10-07 07:19:09","extension":"html","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":75341,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7781055/v1/a2011713ed181ffd32af8777.html"},{"id":92924039,"identity":"4fca68d7-df79-4faf-a623-1853864f5183","added_by":"auto","created_at":"2025-10-07 07:35:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":553291,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7781055/v1/af50cc50-be37-4c53-9dfa-88491321a3ce.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eQuantitative EEG of Frontal and Central Cortices During Calm Memory Retrieval in Schizophrenia\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eSchizophrenia is a chronic psychiatric disorder marked by profound disturbances in cognition, emotion, and behavior. Among its cognitive sequelae, deficits in working memory, attentional regulation, and emotional processing are especially disabling and predictive of long-term functional outcomes (Su et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Hasey \u0026amp; Kiang, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Neurophysiological approaches, such as quantitative electroencephalography (QEEG), offer non-invasive and dynamic insights into these impairments by capturing oscillatory brain activity associated with cognitive and affective states (Newson \u0026amp; Thiagarajan, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Sharma et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTheta-band oscillations (4\u0026ndash;7 Hz) have emerged as biomarkers of episodic memory, cognitive control, and internally directed attention. Frontal-midline theta, in particular, reflects top-down executive regulation and is frequently linked to calm, focused mental states (Tang et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Choi et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In schizophrenia, altered theta dynamics often characterized by hypoactivation or compensatory overactivation have been observed during memory encoding and cognitive control tasks, reflecting disrupted executive processing under varying demands (Xiang et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Bose et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDespite increasing interest in oscillatory biomarkers, few studies have explored the role of theta activity during tasks that simultaneously elicit memory retrieval and emotional calmness neurocognitive states essential for adaptive daily functioning. Furthermore, translating QEEG findings into meaningful, occupation-based interventions remains limited in psychiatric rehabilitation. The ability to identify neurophysiological signatures that reflect both cognitive readiness and affective regulation may advance precision-based occupational therapy approaches (Chatthong, Khemthong, \u0026amp; Wongsawat, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020b\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTo address this gap, we employed the Brain Mapping Performance (BMP) protocol an occupation-integrated QEEG assessment to examine theta activity during a calm memory task in individuals with schizophrenia. Our objectives were twofold: (1) to identify brain regions where theta power is modulated during calm memory retrieval, and (2) to explore the relationship between these patterns and both behavioral performance and perceived calmness. We hypothesized that task-induced theta enhancement would be most prominent in frontal and central brain regions and would correspond to more efficient task engagement.\u003c/p\u003e\u003cp\u003eFrom a neuro-occupational perspective, executive functions (EF) including working memory, attentional initiation, and inhibitory control are foundational to goal-directed behavior and everyday functioning (Grieve, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Kluwe-Schiavon et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). In schizophrenia, disruption in these domains undermines one\u0026rsquo;s ability to initiate, sustain, and complete daily tasks. Thai-based occupational therapy models conceptualize EF recovery not only as cognitive restoration, but as a dynamic reintegration of self-regulation, environmental cueing, and emotional engagement through structured sensory tasks (Khemthong \u0026amp; Wee, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThis study contributes to emerging evidence that calm cognitive states supported by personalized cueing and humanized prompting can re-engage frontal brain systems, particularly the superior frontal gyrus and orbitofrontal cortex. These areas are central to memory consolidation and affective motivation, both of which are targeted through structured, culturally grounded sensory activities. Understanding calmness as an embodied neurofunctional state rather than merely a behavioral one may inform how BMP is used to scaffold therapeutic engagement and cognitive performance in schizophrenia.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cp\u003e\u003cstrong\u003e2.1 Participants\u003c/strong\u003e Thirty individuals (mean age = 38.9 \u0026plusmn; 7.15 years; 10 male, 20 female; all right-handed) diagnosed with schizophrenia participated in this study. All participants were receiving outpatient psychiatric care and met DSM-5 and ICD-10 diagnostic criteria for schizophrenia (F20.0). All participants were assessed using the Thai version of the Positive and Negative Syndrome Scale (PANSS) prior to EEG recording to ensure clinical stability. Individuals who exhibited acute psychotic symptoms or high positive symptom scores were excluded from the session. The PANSS Thai version has demonstrated acceptable criterion validity and interrater reliability in local populations (Nilchaikovit et al., 2000). Exclusion criteria included comorbid neurological conditions and current substance use disorders. All participants provided written informed consent prior to participation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 Ethical Approval\u003c/strong\u003e All procedures performed in this study involving human participants were approved by the Central Institutional Review Board of Mahidol University (MU-CIRB Project ID: 2020/114.1505; COA No. 2020/103.0708, approval date: August 7, 2020), and by the Ethics Committee on Mental Health Research in Human Subjects, Department of Mental Health, Ministry of Public Health, Thailand (DMH.IRB Project ID: 031/2563, Version 2; COA No. 041/2563, approval date: October 28, 2020).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Procedure and Task Design\u003c/strong\u003e Participants completed a spatial memory recall task involving nine occupations, randomly arranged in a 3\u0026times;3 matrix, based on the Thai Physical Activity Guideline. The task was delivered via a mobile application developed by the authors. Three cognitive conditions were assessed: (1) a 3-minute calming task with eyes closed, (2) a 3-minute resting task with eyes open, and (3) the memory task, consisting of four 30-second trials. During the memory task, participants were instructed to recall the nine occupations and their spatial locations within the matrix by touching the corresponding positions on the screen, while maintaining a relaxed posture. Quantitative EEG (QEEG) was continuously recorded using a 12-channel system known as Brain Mapping Performance (BMP).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4 QEEG Recording and Analysis\u003c/strong\u003e QEEG signals were recorded using a 12-electrode montage based on the International 10\u0026ndash;20 system. Data were sampled and processed offline to extract theta relative power (4\u0026ndash;7 Hz), calculated as the proportion of total spectral power. Analyses focused on six primary electrode sites: Fp1, Fz, F4, F7, Cz, and T3, selected for their relevance to frontal and temporal cognitive functions. Standard artifact rejection and bandpass filtering procedures were applied to ensure signal integrity. In addition, the theta/beta ratio was computed to aid in interpretation: higher theta/beta ratios were indicative of internalized or inattentive states, while lower ratios reflected focused attention. A repeated-measures ANOVA was conducted to examine the effects of condition and time on cognitive-emotional performance.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003e\u003cstrong\u003e3.1 QEEG Theta Relative Power\u0026nbsp;\u003c/strong\u003eSignificant increases in theta relative power were observed during the BMP-monitored memory task compared to the non-memory task, particularly in the frontal-midline (Fz) and central (Cz) regions. Statistical analysis showed a significant main effect of condition, F(1.185, 26.077) = 105.844, p \u0026lt; .001, indicating that different tasks led to statistically different performance outcomes. There was also a significant main effect of time, F(1.412, 31.073) = 119.687, p \u0026lt; .001, suggesting that performance changed significantly across time points. Importantly, a significant interaction effect was found between condition and time, F(1.308, 1.357)\u0026nbsp;\u003cbr\u003e\u0026nbsp;= 125.381, p \u0026lt; .001, indicating that the effectiveness of each condition varied depending on the time of assessment.\u003c/p\u003e\n\u003cp\u003eWhen\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003ea descriptive data of theta relative power showed at six QEEG site, under eye-closed conditions were the highest percent at Fz (23.87 \u0026plusmn; 10.88), followed by Cz\u0026nbsp;\u003cbr\u003e(22.52 \u0026plusmn; 11.76), suggesting a strong activation of midline structures during relaxed memory states. Compared to eye-opened resting, all frontal sites demonstrated higher percent, indicating a neurophysiological signature of calmness during internalized condition. The resting condition produced intermediate values, suggesting a transition between internal and external processing states (see Table 1.) \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Mean \u003cu\u003e+\u003c/u\u003e SD Theta Relative Power (%) at Each QEEG Site (Calm vs. Rest vs. Memory)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25.0423%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eQEEG Site\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.7191%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCalm (Eyes Closed)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.0575%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRest (Eyes Opened)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.181%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMemory Task\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25.0423%;\"\u003e\n \u003cp\u003eFp1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.7191%;\"\u003e\n \u003cp\u003e20.50 \u003cu\u003e+\u003c/u\u003e 9.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.0575%;\"\u003e\n \u003cp\u003e16.51 \u003cu\u003e+\u003c/u\u003e 4.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.181%;\"\u003e\n \u003cp\u003e18.21 + 5.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25.0423%;\"\u003e\n \u003cp\u003eF7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.7191%;\"\u003e\n \u003cp\u003e19.61 \u003cu\u003e+\u003c/u\u003e 8.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.0575%;\"\u003e\n \u003cp\u003e18.45 \u003cu\u003e+\u003c/u\u003e 5.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.181%;\"\u003e\n \u003cp\u003e17.83 + 4.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25.0423%;\"\u003e\n \u003cp\u003eF4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.7191%;\"\u003e\n \u003cp\u003e21.97 \u003cu\u003e+\u003c/u\u003e 10.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.0575%;\"\u003e\n \u003cp\u003e20.75 \u003cu\u003e+\u003c/u\u003e 5.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.181%;\"\u003e\n \u003cp\u003e20.12 + 4.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25.0423%;\"\u003e\n \u003cp\u003eFz\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.7191%;\"\u003e\n \u003cp\u003e23.87 \u003cu\u003e+\u003c/u\u003e 10.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.0575%;\"\u003e\n \u003cp\u003e22.99 \u003cu\u003e+\u003c/u\u003e 6.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.181%;\"\u003e\n \u003cp\u003e22.77 + 6.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25.0423%;\"\u003e\n \u003cp\u003eCz\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.7191%;\"\u003e\n \u003cp\u003e22.52 \u003cu\u003e+\u003c/u\u003e 11.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.0575%;\"\u003e\n \u003cp\u003e21.95 \u003cu\u003e+\u003c/u\u003e 6.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.181%;\"\u003e\n \u003cp\u003e20.85 + 5.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25.0423%;\"\u003e\n \u003cp\u003eT3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.7191%;\"\u003e\n \u003cp\u003e17.37 \u003cu\u003e+\u003c/u\u003e 9.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.0575%;\"\u003e\n \u003cp\u003e16.29 \u003cu\u003e+\u003c/u\u003e 6.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.181%;\"\u003e\n \u003cp\u003e14.40 + 4.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 QEEG Theta/Beta Ratio\u0026nbsp;\u003c/strong\u003eSix frontal and central QEEG sites were measured under three cognitive states: calm (eyes closed), rest (eyes opened), and active memory task as shown in Table 2. Theta/beta ratios varied systematically across cognitive conditions and QEEG sites. The highest ratios were observed during the calm condition (eyes closed), with peak values at Fz (1.56 \u0026plusmn; 0.22) and Fp1 (1.54 \u0026plusmn; 0.15), indicating elevated internalized attention and relaxation. In contrast, lower ratios were seen during the memory task, particularly at T3 (0.68 \u0026plusmn; 0.15) and Cz (1.14 \u0026plusmn; 0.10), reflecting increased executive effort and sensory-motor integration.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e Mean \u003cu\u003e+\u003c/u\u003e SD Theta/Beta Ratio at Each QEEG Site (Calm vs. Rest vs. Memory)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25.0423%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eQEEG Site\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.7191%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCalm (Eyes Closed)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.0575%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRest (Eyes Opened)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.181%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMemory Task\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25.0423%;\"\u003e\n \u003cp\u003eFp1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.7191%;\"\u003e\n \u003cp\u003e1.54\u0026nbsp;\u003cu\u003e+\u003c/u\u003e 0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.0575%;\"\u003e\n \u003cp\u003e1.18\u0026nbsp;\u003cu\u003e+\u003c/u\u003e 0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.181%;\"\u003e\n \u003cp\u003e1.32\u0026nbsp;\u003cu\u003e+\u003c/u\u003e 0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25.0423%;\"\u003e\n \u003cp\u003eF7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.7191%;\"\u003e\n \u003cp\u003e1.34\u0026nbsp;\u003cu\u003e+\u003c/u\u003e 0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.0575%;\"\u003e\n \u003cp\u003e1.03\u0026nbsp;\u003cu\u003e+\u003c/u\u003e 0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.181%;\"\u003e\n \u003cp\u003e1.18\u0026nbsp;\u003cu\u003e+\u003c/u\u003e 0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25.0423%;\"\u003e\n \u003cp\u003eF4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.7191%;\"\u003e\n \u003cp\u003e1.33\u0026nbsp;\u003cu\u003e+\u003c/u\u003e 0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.0575%;\"\u003e\n \u003cp\u003e1.08\u0026nbsp;\u003cu\u003e+\u003c/u\u003e 0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.181%;\"\u003e\n \u003cp\u003e1.14\u0026nbsp;\u003cu\u003e+\u003c/u\u003e 0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25.0423%;\"\u003e\n \u003cp\u003eFz\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.7191%;\"\u003e\n \u003cp\u003e1.56\u0026nbsp;\u003cu\u003e+\u003c/u\u003e 0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.0575%;\"\u003e\n \u003cp\u003e1.31\u0026nbsp;\u003cu\u003e+\u003c/u\u003e 0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.181%;\"\u003e\n \u003cp\u003e1.39\u0026nbsp;\u003cu\u003e+\u003c/u\u003e 0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25.0423%;\"\u003e\n \u003cp\u003eCz\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.7191%;\"\u003e\n \u003cp\u003e1.40\u0026nbsp;\u003cu\u003e+\u003c/u\u003e 0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.0575%;\"\u003e\n \u003cp\u003e1.19\u0026nbsp;\u003cu\u003e+\u003c/u\u003e 0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.181%;\"\u003e\n \u003cp\u003e1.14\u0026nbsp;\u003cu\u003e+\u003c/u\u003e 0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25.0423%;\"\u003e\n \u003cp\u003eT3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.7191%;\"\u003e\n \u003cp\u003e1.04\u0026nbsp;\u003cu\u003e+\u003c/u\u003e 0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.0575%;\"\u003e\n \u003cp\u003e0.76\u0026nbsp;\u003cu\u003e+\u003c/u\u003e 0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.181%;\"\u003e\n \u003cp\u003e0.68\u0026nbsp;\u003cu\u003e+\u003c/u\u003e 0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAt Fp1, both theta relative power and theta/beta ratio followed a similar trend, with the highest values during the calm condition and the lowest during the resting state. An increase was observed again during the memory task, suggesting that the theta/beta ratio at Fp1 was largely influenced by variations in frontal theta activity.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAt F7, a modest decrease in theta relative power was accompanied by a more pronounced decline in the theta/beta ratio from calm to rest. This discrepancy suggests that increased beta relative power may have contributed more significantly to the reduced ratio, particularly during the memory task.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eF4 exhibited relatively stable theta relative power across conditions, yet the theta/beta ratio showed a mild U-shaped pattern, with the lowest value during rest. This may reflect fluctuating beta activity levels, indicating dynamic shifts in cognitive engagement at this site.\u003c/p\u003e\n\u003cp\u003eBoth theta relative power and theta/beta ratio peaked at Fz during the calm condition and declined slightly during rest and memory tasks. The parallel trends suggest that Fz\u0026rsquo;s ratio is a sensitive marker of theta modulation during transitions from rest to task-oriented attention.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAt Cz, theta relative power and theta/beta ratio decreased progressively across conditions, with the lowest values during the memory task. This consistent pattern reflects reduced central theta dominance under increased cognitive demands and working memory engagement.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eT3 demonstrated the steepest decline in both theta relative power and theta/beta ratio from calm to memory conditions. This finding may indicate enhanced beta activation in the temporal lobe during memory processing, contributing to the sharply reduced theta dominance at this site.\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study explored task-related changes in QEEG theta relative power and theta/beta ratio across six cortical sites in individuals with schizophrenia, comparing calm\u0026nbsp;\u003cbr\u003e\u0026nbsp;(eyes-closed), rest (eyes-opened), and memory-task conditions. The results contribute to our understanding of frontal-midline and temporal dynamics during internalized attention, resting alertness, and active cognitive engagement, offering implications for cognitive assessment and intervention design in psychiatric rehabilitation (Newson \u0026amp; Thiagarajan, 2019; Sharma et al., 2020).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.1 Frontal-Midline Dominance of Theta Activity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe most robust finding was the consistently elevated theta relative power at Fz and Cz across all conditions, with the calm (eyes-closed) state producing the highest amplitudes (Fz = 23.87 ± 10.88; Cz = 22.52 ± 11.76). These results align with previous research associating frontal-midline theta with internalized attention, relaxation, and top-down control of cognitive processes (Tang et al., 2019; Choi et al., 2020). The decline in theta power from calm to rest, and further into the memory task—especially at Cz (from 22.52 to 20.85)—reflects increasing executive demands and sensorimotor integration as task complexity increases (Xiang et al., 2019; Bose et al., 2014). The significant interaction between condition and time (F(1.308, 1.357) = 125.381, p \u0026lt; .001) supports this dynamic modulation across both brain sites and task phases, suggesting time-sensitive cognitive adaptation under load.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.2 Theta/Beta Ratio as a Biomarker of Task Engagement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTheta/beta ratios demonstrated strong state sensitivity, with the highest ratios during calm conditions, especially at Fz (1.56 ± 0.22) and Fp1 (1.54 ± 0.15), and the lowest ratios at T3 during memory tasks (0.68 ± 0.15). This progression supports the role of theta/beta ratio as a neurophysiological marker of attentional regulation and cognitive readiness (Newson \u0026amp; Thiagarajan, 2019). The drop in this ratio from rest to task reflects enhanced beta synchronization during focused task performance, particularly at temporal and lateral frontal sites (Hasey \u0026amp; Kiang, 2013). The parallel decrease in both theta power and theta/beta ratios at Fz and Cz during memory conditions underscores their utility as dual indicators of central executive effort. In contrast, the disproportionate reduction in ratio at F7 and T3, without commensurate theta decline, highlights site-specific beta recruitment—likely reflecting increased affective inhibition at F7 and auditory-emotional processing at T3 (Sklar et al., 2020; Liu et al., 2019).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.3 Functional Interpretation by Region\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFrontal-midline sites (Fz, Cz) demonstrated sustained theta activity and the highest theta/beta ratios during calm states, aligning with their known roles in executive regulation and working memory (Tang et al., 2019; Grieve, 2000). These regions appear to support cognitive shifting and attentional maintenance, especially under memory load (Nahum et al., 2020). Fp1 activity may reflect internal attentional monitoring, relevant for calm-focused or mindfulness-based interventions (Bauer et al., 2020). Lateral sites revealed unique dynamics: F7 showed emotional inhibitory modulation, consistent with increased beta power during memory engagement (Khemthong \u0026amp; Wee, 2016), while F4 patterns suggest a role in working memory and flexible goal setting (Kluwe-Schiavon et al., 2013). Temporal site T3 showed sharp theta suppression and increased beta activity, highlighting its involvement in auditory-linguistic processing and affective responsiveness (Su et al., 2011; Sharma et al., 2020). These patterns may reflect region-specific demands placed on procedural memory and social-emotional integration during complex tasks.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.4 Clinical and Theoretical Implications\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThese patterns have important implications for executive function rehabilitation in schizophrenia. The ability to differentiate cognitive conditions through region-specific theta and beta activity supports the development of neuroadaptive assessment tools (Harvey, 2011; Arigo et al., 2019). The combination of theta dominance during calm states and beta activation during memory tasks may be leveraged to inform task design, therapy progression, and real-time neurofeedback (Markov-Vetter et al., 2020). Moreover, these results support the feasibility of using frontal-midline theta and theta/beta ratio as performance-sensitive biomarkers in both clinical and community-based interventions (Chatthong et al., 2020a, 2020b).\u003c/p\u003e\n\u003cp\u003eThe distinct electrophysiological signatures at midline (Fz, Cz) versus lateral (F7, T3) sites underscore the need for site-specific analysis in EEG-based rehabilitation, avoiding overgeneralization across frontal lobes (Xiang et al., 2019; Sharma et al., 2020). Lateral beta activation during task load may serve as an index for emotional regulation and auditory-attentional control—components often impaired in schizophrenia (Nahum et al., 2020; Liu et al., 2019).\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eTheta relative power in frontal and central brain regions reflects cognitive and emotional states during calm memory tasks in schizophrenia. Brain Mapping Performance or BMP provide promising avenues for integrating neurophysiological data into individualized rehabilitation planning and monitoring. These findings support the use of QEEG-based metrics as a foundation for goal-oriented rehabilitation strategies in mental health care.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eConflict of Interest Statement\u003c/h2\u003e\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis work was supported by Electricity Generating Authority of Thailand (EGAT) in the year of 2020.\u003c/p\u003e\u003ch2\u003eAuthor Contributions\u003c/h2\u003e\u003cp\u003eS.K. designed the study and led data collection and manuscript drafting. M.R. contributed to data analysis and interpretation. W.C. supervised the project and finalized the manuscript as corresponding author.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e\u003cp\u003eThe authors thank all participants and clinical staff involved in this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBauer, M., Glenn, T., Geddes, J., Gitlin, M., Grof, P., Kessing, L. V., ... \u0026amp; Whybrow, P. C. (2020). Smartphones in mental health: A critical review of background issues, current status and future concerns. International Journal of Bipolar Disorders, 8(1), 2. https://doi.org/10.1186/s40345-019-0164-x\u003c/li\u003e\n\u003cli\u003eBose, A., Agarwal, S. M., Kalmady, S. V., \u0026amp; Venkatasubramanian, G. (2014). Cognitive mapping deficits in schizophrenia: A critical overview. Indian Journal of Psychological Medicine, 36(1), 9\u0026ndash;26. https://doi.org/10.4103/0253-7176.127242\u003c/li\u003e\n\u003cli\u003eBreuning, L. G. (2016). Habits of a happy brain. Avon, MA: Adams Media.\u003c/li\u003e\n\u003cli\u003eCavanagh, J. F., \u0026amp; Frank, M. J. (2014). Frontal theta as a mechanism for cognitive control. Trends in Cognitive Sciences, 18(8), 414\u0026ndash;421. https://doi.org/10.1016/j.tics.2014.04.012\u003c/li\u003e\n\u003cli\u003eChatthong, W., Khemthong, S., \u0026amp; Wongsawat, Y. (2020a). A design thinking model based on quantitative electroencephalography in social emotional learning for attention deficit hyperactivity disorder. Mind, Brain, and Education. https://doi.org/10.1111/mbe.12235\u003c/li\u003e\n\u003cli\u003eChatthong, W., Khemthong, S., \u0026amp; Wongsawat, Y. (2020b). Brain mapping performance as an occupational therapy assessment aid in ADHD. American Journal of Occupational Therapy, 74. https://doi.org/10.5014/ajot.2020.035477\u003c/li\u003e\n\u003cli\u003eChoi, J., Lim, E., Park, M. G., \u0026amp; Cha, W. (2020). Assessing the retest reliability of prefrontal EEG markers of brain rhythm slowing in the eyes-closed resting state. Clinical EEG and Neuroscience, 51(5), 348\u0026ndash;356. https://doi.org/10.1177/1550059420914832\u003c/li\u003e\n\u003cli\u003eGrieve, J. I. (2000). Neuropsychology for occupational therapists: Assessment of perception and cognition. Oxford, UK: Blackwell Science.\u003c/li\u003e\n\u003cli\u003eHaugen, I., Stubberud, J., Haug, E., McGurk, S. R., Hovik, K. T., Ueland, T., \u0026amp; \u0026Oslash;ie, M. G. (2022). A randomized controlled trial of Goal Management Training for executive functioning in schizophrenia spectrum disorders or psychosis risk syndromes. BMC Psychiatry, 22, 575. https://doi.org/10.1186/s12888-022-04197-3\u003c/li\u003e\n\u003cli\u003eHasey, G. M., \u0026amp; Kiang, M. (2013). A review of recent literature employing electroencephalographic techniques to study the pathophysiology, phenomenology, and treatment response of schizophrenia. Current Psychiatry Reports, 15, 388. https://doi.org/10.1007/s11920-013-0388-x\u003c/li\u003e\n\u003cli\u003eKluwe-Schiavon, B., Sanvicente-Vieira, B., Kristensen, C. H., \u0026amp; Grassi-Oliveira, R. (2013). Executive functions rehabilitation for schizophrenia: A critical systematic review. Journal of Psychiatric Research, 47, 91\u0026ndash;104.\u003c/li\u003e\n\u003cli\u003eKhemthong, S., \u0026amp; Wee, B. (2016). Integration of occupational therapy and neuro-linguistic programming for Thais with mental health experiences. \u003cem\u003eBulletin of the Chiang Mai Association of Medical Sciences\u003c/em\u003e, \u003cem\u003e49\u003c/em\u003e(1), 10\u0026ndash;16. https://doi.org/10.14456/jams.2016.14\u003c/li\u003e\n\u003cli\u003eLiu, T., Zhang, J., Dong, X., Wu, J., Wang, C., \u0026amp; Yan, T. (2019). Occipital alpha connectivity during resting-state electroencephalography in patients with ultra-high risk for psychosis and schizophrenia. Frontiers in Psychiatry, 10, 553. https://doi.org/10.3389/fpsyt.2019.00553\u003c/li\u003e\n\u003cli\u003eMichopoulos, I., Tzavellas, E., Papakosta, V. M., \u0026amp; Koutsouleris, N. (2021). Cognitive rehabilitation in schizophrenia-associated cognitive impairment: A review. Mental Illness, 15(1), 2. https://doi.org/10.3390/mi15010002\u003c/li\u003e\n\u003cli\u003eMinzenberg, M. J., Laird, A. R., Thelen, S., Carter, C. S., \u0026amp; Glahn, D. C. (2009). Meta-analysis of 41 functional neuroimaging studies of executive function in schizophrenia. Archives of General Psychiatry, 66(8), 811\u0026ndash;822. https://doi.org/10.1001/archgenpsychiatry.2009.91\u003c/li\u003e\n\u003cli\u003eNahum, M., Lee, H., Fisher, M., Green, M. F., Hooker, C. I., Ventura, J., ... \u0026amp; Vinogradov, S. (2020). Online social cognition training in schizophrenia: A double-blind, randomized, controlled multi-site clinical trial. Schizophrenia Bulletin, 46(6), 1427\u0026ndash;1436. https://doi.org/10.1093/schbul/sbaa085\u003c/li\u003e\n\u003cli\u003eNewson, J. J., \u0026amp; Thiagarajan, T. C. (2019). EEG frequency bands in psychiatric disorders: A review of resting state studies. Frontiers in Human Neuroscience, 12, 521. https://doi.org/10.3389/fnhum.2018.00521\u003c/li\u003e\n\u003cli\u003eNilchaikovit, T., Uneanong, S., Kessawai, D., \u0026amp; Thomyangkoon, P. (2000). The Thai version of the Positive and Negative Syndrome Scale (PANSS) for schizophrenia: Criterion validity and interrater reliability. Journal of the Medical Association of Thailand, 83, 646\u0026ndash;651.\u003c/li\u003e\n\u003cli\u003eSharma, A., Rai, J. K., \u0026amp; Tewari, R. P. (2020). Schizophrenia detection using biomarkers from electroencephalogram signals. IETE Journal of Research. https://doi.org/10.1080/03772063.2020.1753587\u003c/li\u003e\n\u003cli\u003eSklar, A. L., Coffman, B. A., Haas, G. L., et al. (2020). Inefficient visual search strategies in the first-episode schizophrenia spectrum. Schizophrenia Research. https://doi.org/10.1016/j.schres.2020.09.015\u003c/li\u003e\n\u003cli\u003eSu, C. Y., Tsai, P. C., Su, W. L., Tang, T. C., \u0026amp; Tsai, A. Y. J. (2011). Cognitive profile difference between Allen cognitive levels 4 and 5 in schizophrenia. American Journal of Occupational Therapy, 65, 453\u0026ndash;461. https://doi.org/10.5014/ajot.2011.000711\u003c/li\u003e\n\u003cli\u003eTang, Y.-Y., Tang, R., Rothbart, M. K., \u0026amp; Posner, M. I. (2019). Frontal theta activity and white matter plasticity following mindfulness meditation. Current Opinion in Psychology, 28, 294\u0026ndash;297. https://doi.org/10.1016/j.copsyc.2019.04.004\u003c/li\u003e\n\u003cli\u003eThai Physical Activity Guideline. (n.d.). Retrieved from http://www.pt.mahidol.ac.th/tpag/index.php\u003c/li\u003e\n\u003cli\u003eTyburski, E., Mak, M., Sokołowski, A., Starkowska, A., Karabanowicz, E., Kerestey, \u003cbr\u003e M., \u0026amp; Samochowiec, J. (2021). Executive dysfunctions in schizophrenia: A critical review of traditional, ecological, and virtual reality assessments. Journal of Clinical Medicine, 10(13), 2782. https://doi.org/10.3390/jcm10132782\u003c/li\u003e\n\u003cli\u003eXiang, J., Tian, C., Niu, Y., Yan, T., Li, D., Cao, R., et al. (2019). Abnormal entropy modulation of the EEG signal in patients with schizophrenia during the auditory paired-stimulus paradigm. Frontiers in Neuroinformatics, 13, 4. https://doi.org/10.3389/fninf.2019.00004\u003c/li\u003e\n\u003cli\u003eZhao, L., Jiang, Y., \u0026amp; Zhang, H. (2016). Effects of modified electroconvulsive therapy on the electroencephalogram of schizophrenia patients. SpringerPlus, 5(1), 1063. https://doi.org/10.1186/s40064-016-2747-7\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[{"identity":"c406e4fc-97ba-4ca7-877e-6fa9db41430e","identifier":"10.13039/501100006290","name":"Electricity Generating Authority of Thailand","awardNumber":"62-B602000-11-IO.SS03B3008479","order_by":0}],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Mahidol University","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":"Theta relative power, QEEG, schizophrenia, working memory, calmness, brain mapping, executive function","lastPublishedDoi":"10.21203/rs.3.rs-7781055/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7781055/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Cognitive and emotional dysregulation in schizophrenia is frequently associated with altered neural oscillatory patterns. Frontal theta activity, in particular, has been linked to working memory and internalized calmness. This study investigated theta dynamics using quantitative EEG (QEEG) during a memory-related calmness task to identify brain regions involved in cognitive-emotional processing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e Thirty individuals with schizophrenia (mean age = 38.9 ± 7.15 years) completed a structured memory recall task embedded in the Brain Mapping Performance (BMP) protocol. QEEG signals were recorded from 12 scalp locations, with analyses focused on theta relative power at key frontal and central sites (Fp1, Fz, F4, F7, Cz, T3). Behavioral performance (memory accuracy, task duration) and self-reported calmness were also measured. Repeated measures ANOVA assessed effects of condition (calm, rest, task), time, and their interaction.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Theta relative power significantly increased during memory recall at frontal-midline and central electrodes. Statistically significant effects were observed for Condition [F(1.185, 26.077) = 105.844, p \u0026lt; .001], Time [F(1.412, 31.073) = 119.687, p \u0026lt; .001], and the Condition × Time interaction [F(1.308, 1.357) = 125.381, p \u0026lt; .001]. Memory accuracy declined under EEG monitoring (41.43 ± 21.47%) compared to baseline (47.71 ± 27.20%), while task completion time increased (874.22 ± 331.82 s vs. 738.35 ± 191.11 s, p = .017), indicating elevated cognitive demands.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e Frontal and central theta activity reflects cognitive engagement during calm memory tasks in schizophrenia. BMP may offer a valuable behavioral-neurophysiological interface for individualized assessment and cognitive rehabilitation in psychiatric care.\u003c/p\u003e","manuscriptTitle":"Quantitative EEG of Frontal and Central Cortices During Calm Memory Retrieval in Schizophrenia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-07 07:19:05","doi":"10.21203/rs.3.rs-7781055/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":"b4b59cb4-e92d-432f-9519-9a41fde9bd52","owner":[],"postedDate":"October 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":55772652,"name":"Cognitive Neuroscience"},{"id":55772653,"name":"Psychiatry"},{"id":55772654,"name":"Occupational Medicine"},{"id":55772655,"name":"Biomedical Engineering"}],"tags":[{"value":"featured","date":"2025-10-07 13:37:18"}],"updatedAt":"2026-03-03T18:24:20+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-07 07:19:05","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7781055","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7781055","identity":"rs-7781055","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}