Brainy2Blessly and QEEG: A Neurofunctional Window into Schizophrenia Rehabilitation

Brainy2Blessly and QEEG: A Neurofunctional Window into Schizophrenia Rehabilitation | 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 Brainy2Blessly and QEEG: A Neurofunctional Window into Schizophrenia Rehabilitation Supalak Khemthong, Maliwan Rueankam, Winai Chatthong This is a preprint; it has not been peer reviewed by a journal.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-7780966/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 Introduction: The integration of digital tools and neurophysiological monitoring in mental health care presents new opportunities for cognitive and motor rehabilitation. This study investigated the Brainy2Blessly (B2B) app as a tool for assessing visuospatial prioritization and emotional habituation related to physical activity in individuals with schizophrenia. Simultaneous brain mapping was conducted to explore neurocognitive engagement and motor relearning. Methods: Thirty participants with schizophrenia (mean age = 38.9 ± 7.15 years) completed structured tasks using the B2B app under two conditions: with and without quantitative EEG (QEEG) monitoring. Percentages of top-ranking physical activities linked to “happy hormones” were calculated based on energy expenditure data from the Thai Physical Activity Guideline. QEEG measured theta relative power, beta relative power, and the theta/beta ratio at six scalp locations during task performance. Results: QEEG data revealed region-specific neural activation during the B2B and LCAR tasks. Theta relative power was highest at Fz, followed by Cz and F4, indicating robust engagement of executive and motor-planning regions. Theta/beta ratios peaked at Fp1 and Fz during calm states, reflecting prefrontal regulation and internal attention. Frontal beta power at F4, F7, and Fz showed moderate positive correlations with dopamine-, serotonin-, and endorphin-linked physical activity phases, suggesting sensitivity to reward, affective, and executive functions. Notably, the Fp1 theta/beta ratio was positively associated with serotonin-related calmness, while T3 beta power exhibited low correlations with oxytocin and serotonin, indicating diminished social-affective engagement. ANOVA results confirmed significant differences in EEG indices across sites (F = 28.57–38.29, p < .001), supporting the site-specific neurofunctional relevance of QEEG-informed occupational performance. Conclusion: QEEG-guided occupational tasks reveal distinct neural engagement patterns linked to emotional and executive functions in schizophrenia. These findings support the use of Brain Mapping Performance (BMP) and the B2B app as valuable tools for individualized rehabilitation planning in occupational therapy. Cognitive Neuroscience Psychiatry Occupational Medicine Schizophrenia motor relearning cognitive engagement B2B app occupational therapy QEEG 1. Introduction Rehabilitation in schizophrenia increasingly recognizes the need to integrate cognitive and motor training within meaningful activities. Deficits in executive functioning, emotional regulation, and behavioral initiation impair clients’ ability to engage in purposeful occupations [ 1 , 2 ]. Occupational therapy interventions must therefore address not only observable performance skills but also the underlying neurocognitive processes that support occupational engagement [ 3 , 4 ]. The Brainy2Blessly (B2B) app was developed as a dual-purpose tool for assessing and training cognitive-motor functions. It engages users in structured digital tasks simulating daily occupations while collecting performance metrics such as time-on-task, memory recall, and emotional self-report [ 5 ]. When paired with Brain Mapping Performance (BMP)—a task-based application of quantitative EEG (QEEG)—the system enables real-time monitoring of theta activity in frontal and central brain regions, which are known markers of attention and motor planning [ 6 , 7 ]. This hybrid approach integrates neuroscience-based monitoring with performance-based assessment, bridging the gap between cortical function and occupational behavior in schizophrenia rehabilitation. Recent models advocate for such integration of brain-behavior data to optimize individualized care and deepen understanding of cognitive-emotional dysfunctions [ 8 – 10 ]. In this study, BMP was used as a neurofunctional assessment tool to observe changes in theta, beta, and theta/beta ratio across six QEEG sites (frontal and temporal) while participants engaged in memory- and emotion-related activities. We aimed to determine whether the B2B app—under monitored versus unmonitored conditions—would reveal differences in task completion time, EEG dynamics, and perceived calmness, suggesting varying levels of executive function engagement. Contemporary occupational therapy in schizophrenia increasingly combines digital technology with occupation-based principles [ 11 ]. Thai executive function (EF) rehabilitation frameworks, such as the Neuro-Functional Approach (NFA), describe recovery as a graded process of relearning everyday routines through cognitive prompting, emotional regulation, and meaningful participation [ 12 , 13 ]. The B2B app aligns with these principles by providing stepwise simulations designed to activate key EF domains. Moreover, integrating B2B with real-time QEEG via BMP supports therapy approaches that prioritize humanized cueing, environmental familiarity, and emotional readiness [ 2 , 14 ]. This combination may enhance ecological validity and promote client-centered care—critical for functional gains in schizophrenia. 2. Methods 2.1. Participants. Thirty individuals diagnosed with schizophrenia (mean age = 38.9 ± 7.15 years; 10 male, 20 female; all right-handed) were recruited. Inclusion criteria included DSM-5 diagnosis and stable outpatient status. 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 [15]. Exclusion criteria involved comorbid neurological disorders or recent substance use. All participants provided written informed consent by signing a consent form before participating in the study. 2.2. Human Research Ethics. Ethical Approval Ethical clearance was granted by Mahidol University Central IRB (MU-CIRB 2020/114.1505; COA No. 2020/103.0708) and the Department of Mental Health IRB (DMH.IRB 031/2563; COA No. 041/2563). 2.3. Study Process . B2B Task Conditions EEG signals were recorded using a QEEG system during Brain Mapping Performance (BMP) tasks, allowing functional interpretation of brain activity in context-specific B2B tasks. Each participant completed two B2B task sessions: one with BMP and one without. To examine how physical activity (PA) engagement relates to emotional-cognitive processing in individuals with schizophrenia, the B2B application integrated a classification of 16 daily activities, each theoretically linked to one of the four "happy hormones": dopamine, oxytocin, serotonin, and endorphin [14]. Participants were asked to prioritize these 16 activities based on their frequency of participation in daily life. For each neurotransmitter, a subset of four activities was presented, grounded in occupational therapy literature and neuropsychological associations: Dopamine-related (reward, goal achievement): e.g., cooking, playing games, solving puzzles, planning a trip Oxytocin-related (social bonding, trust): e.g., group singing, giving compliments, storytelling, sharing meals Serotonin-related (emotion regulation, mindfulness): e.g., mindful walking, gardening, meditation, journaling Endorphin-related (pleasure, pain relief): e.g., jogging, dancing, laughing, stretching The top four participant-selected activities were matched with their respective energy expenditure values (METs) based on the Thai Physical Activity Guideline (2020)[16]. A normalized score was then computed for each neurotransmitter phase by summing the MET values of the top four activities within each domain and dividing by the maximum reference value (5.9 METs). These individualized habit success scores were used as behavioral proxies for engagement in dopamine-, oxytocin-, serotonin-, and endorphin-related physical activity patterns. 2.4. Outcome Measures and Statistical Analysis . QEEG Recording and Analysis QEEG signals were recorded using a 12-electrode setup based on the International 10–20 system. Data were sampled and analyzed offline to extract theta relative power (4–7 Hz), calculated as the proportion of total spectral power, was used to compare brain activation patterns from six primary electrode sites: Fp1, Fz, F4, F7, Cz, and T3. Artifact rejection and bandpass filtering were applied. The theta/beta ratio was used interpretating: high theta/beta for inattention and low theta/beta for focused attention. A repeated-measures ANOVA was conducted to examine the effects of condition and time on participants’ cognitive-emotional performance. 3. Results 3.1. Theta and Beta Dynamics Across QEEG Sites During Cognitive Engagement. One-way repeated measures ANOVA was conducted separately for each QEEG site to compare theta relative power, theta/beta ratio, and beta relative power during the memory task (see Table 1 ). The results revealed significant differences across the three measures at all sites: Fp1 [F(2, 58) = 52.22, p < .001], F7 [F(2, 58) = 74.04, p < .001], F4 [F(2, 58) = 59.88, p < .001], Fz [F(2, 58) = 61.18, p < .001], Cz [F(2, 58) = 52.26, p < .001], and T3 [F(2, 58) = 33.33, p < .001]. Table 1 Repeated Measures ANOVA of QEEG Indices in 6 Sites. QEEG Sites Theta Relative Power (Mean ± SD) Theta/Beta Ratio (Mean ± SD) Beta Relative Power (Mean ± SD) F-value Fp1 18.21 ± 5.70 1.32 ± 0.58 13.80 ± 7.44 52.22* F7 17.83 ± 4.05 1.18 ± 0.47 15.11 ± 6.93 74.04* F4 20.12 ± 4.99 1.14 ± 0.51 17.65 ± 9.03 59.88* Fz 22.77 ± 6.04 1.39 ± 0.67 16.38 ± 9.01 61.18* Cz 20.85 ± 5.51 1.14 ± 0.55 18.29 ± 10.06 52.26* T3 14.40 ± 4.72 0.68 ± 0.36 21.18 ± 13.19 33.33* * p < 0.001. Theta relative power during B2B was highest at Fz, followed by Cz, and F4, consistent with cognitive-motor integration. These findings suggest elevated attentional and motor planning load. Further analysis at individual sites indicated that T3 had disproportionately high beta relative power, while Fz maintained the highest theta dominance, reflecting region-specific cognitive engagement patterns. QEEG results also showed theta/beta ratios peaking in calm states (Fz). 3.2. Impact of BMP Guidance on Neurotransmitter-Related Habit Formation. As shown in Table 2 , habit success scores across the four neurotransmitter-related activity phases were compared under conditions with and without BMP guidance. Participants showed slightly higher success in dopamine (t 29 = -3.179, p = 0.013), serotonin (t 29 = -1.317, p = 0.011), oxytocin (t 29 = -2.418, p = 0.022), and endorphin (t 29 = -3.291, p = 0.012). Beside the data comparison, strongest correlations (p < 0.05) with neurotransmitter indices were selected for each QEEG site (see Table 3 ). Key moderately associated finding were at F7 (serotonin) and Fz (endorphin), indicating neurophysiological sensitivity to emotional-affective modulation. Table 2 Habit Success (%) by Neurotransmitter Related Activity Phases. Neurotransmitter-Related Activity Phases Habit success (%) with BMP Habit success (%) with No BMP Dopamine 75.61 ± 8.57 79.95 ± 9.86* Serotonin 56.34 ± 15.31 57.36 ± 13.88* Oxytocin 55.13 ± 13.54 58.09 ± 13.59* Endorphin 58.56 ± 13.85 55.74 ± 14.27* *p < 0.05. Additional correlations revealed distinct roles of each frontal QEEG site in B2B performance. Fp1 theta/beta ratios showed positive associations with serotonin-linked calmness, while F7 and F4 frontal beta power positively correlated with three neurotransmitter-linked phases (serotonin, endorphin, and dopamine), suggesting emotional and executive inhibition. Fz and Cz also demonstrated midline involvement in dopaminergic reward and endorphin processing. Oxytocin and serotonin showed low correlations with beta activity at T3. Table 3 QEEG Site-Highest Correlations and Functional Roles. QEEG Feature Functional Role Key Correlation Fp1 Theta/beta Anterior prefrontal – calm attentional control & self-monitoring Serotonin (r = .419) Fp1 Beta Anterior prefrontal – task engagement & dopaminergic alertness Dopamine (r = .440) F7 Theta/beta Left dorsolateral prefrontal – emotional inhibition & top-down regulation Serotonin (r = .511) F7 Beta Left frontal – affective effort, inhibition, and mood regulation Endorphin (r = .419) F4 Beta Right dorsolateral prefrontal – working memory, executive planning Dopamine (r = .418) Fz Beta Midline frontal – cognitive control, conflict monitoring, set shifting Dopamine (r = .454) Endorphin (r = .500) Cz Beta Sensorimotor cortex – motor planning, procedural learning, habit formation Endorphin (r = .450) T3 Beta Left temporal – auditory-linguistic integration, procedural memory, social-affective processing Serotonin (r = .434) Oxytocin (r = .432) 4. Discussion The B2B protocol, enhanced through BMP monitoring, engaged multiple facets of executive function via digital, culturally relevant tasks. The longer task durations observed under monitored conditions, particularly during the emotion- and memory-linked phases, suggest that real-time neurofeedback elicited greater self-regulation and cognitive effort [ 6 , 7 ]. In line with occupational therapy theories emphasizing internal cognitive readiness for participation, these findings highlight the utility of BMP as a neurofunctional interface within task-based rehabilitation [ 1 , 13 ]. Theta activity in frontal regions—especially Fz and Cz—was consistently elevated during monitored conditions. These sites are associated with working memory, attentional control, and emotional self-monitoring, and their activation aligns with previous EEG findings in schizophrenia showing disrupted but compensatory theta engagement during executive tasks [ 2 , 17 ]. The theta/beta ratio provided further insight, with elevated beta activity during memory-linked phases reflecting increased executive inhibition and motor planning [ 18 ]. The observed delay in performance during monitored tasks supports the hypothesis that BMP feedback modulates cognitive engagement, likely activating mechanisms for shifting, inhibition, and emotional control. This mirrors previous research using remediation-based tasks (e.g., brushing, eating, washing) that progressively train attention, flexibility, and sequencing [ 9 , 11 ]. Importantly, the B2B and BMP integration reflects Thai models of rehabilitation, such as the Neuro-Functional Approach (NFA), which promote recovery through graded challenge, culturally relevant occupation, and affective attunement [ 12 ]. By simulating everyday tasks in an emotionally resonant, structured format, the B2B tool aligns with principles of motivational readiness and ecological validity—central tenets of effective occupational engagement [ 10 , 14 ]. From a clinical perspective, B2B paired with BMP offers dual utility: (1) it captures performance-based metrics such as time and task success, and (2) it provides neurophysiological insight into executive strain and affective readiness. This hybrid tool could be particularly effective in psychiatric occupational therapy, where abstract assessments often fail to reflect real-world functioning [ 2 , 3 ]. The correlation of task-phase with EEG activation underscores its potential as a digital biomarker for schizophrenia. Further studies are warranted to explore the predictive validity of the B2B tool, including its use for therapy monitoring, motivation enhancement, and longitudinal executive rehabilitation. By combining culturally embedded tasks with neuroscience-based assessment, B2B and BMP represent a promising advancement in occupational therapy for individuals with schizophrenia. 5. Conclusion The findings demonstrate that QEEG-based monitoring during occupational tasks can reveal distinct patterns of executive, motor, and emotional engagement in individuals with schizophrenia. Frontal theta and beta activity patterns were differentially associated with neurotransmitter-linked behavioral phases, underscoring the potential of brain mapping performance (BMP) as a neurofunctional assessment tool. This supports the integration of real-time neurophysiological feedback into occupational therapy to tailor interventions that enhance emotional regulation, cognitive flexibility, and motivational readiness. Declarations Conflicts of Interest The authors declare no competing interests. Funding This work was supported by Electricity Generating Authority of Thailand (EGAT) in the year of 2020. Author Contributions S.K. developed the B2B app and conducted the study. M.R. supported data analysis and interpretation. W.C. provided project supervision and manuscript oversight as corresponding author. Acknowledgments The authors thank the participants and clinical partners who made this study possible. No third-party services or individuals not listed as authors contributed to the research or preparation of this manuscript. Data Availability Statement The data are not publicly available due to privacy and ethical restrictions related to participant confidentiality. References P. D. Harvey, "Assessment of everyday functioning in schizophrenia," (in eng), Innov Clin Neurosci, vol. 8, no. 5, pp. 21-4, May 2011. [Online]. Available: https://pmc.ncbi.nlm.nih.gov/articles/PMC3115762/. C.-Y. Su, P.-C. Tsai, W.-L. Su, T.-C. Tang, and A. 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Capra, "Food skills assessment tools for people with a mental illness," Australian Occupational Therapy Journal, vol. 45, no. 2, pp. 65-71, 1998, doi: https://doi.org/10.1111/j.1440-1630.1998.tb00784.x. C. E. Synovec, "Implementing Recovery Model Principles as Part of Occupational Therapy in Inpatient Psychiatric Settings," Occupational Therapy in Mental Health, vol. 31, no. 1, pp. 50-61, 2015/01/02 2015, doi: 10.1080/0164212X.2014.1001014. M. o. P. H. Department of Mental Health, "Annual Report Department of Mental Health Fiscal Year 2019," Department of Mental Health, Nonthaburi, 2019-12-01 2019. [Online]. Available: https://dmh-elibrary.org/items/show/189 T. Shimada, A. Nishi, T. Yoshida, S. Tanaka, and M. Kobayashi, "Development of an Individualized Occupational Therapy Programme and its Effects on the Neurocognition, Symptoms and Social Functioning of Patients with Schizophrenia," (in eng), Occup Ther Int, vol. 23, no. 4, pp. 425-435, Dec 2016, doi: 10.1002/oti.1445. L. G. Breuning, Habits of a Happy Brain: Retrain Your Brain to Boost Your Serotonin, Dopamine, Oxytocin, & Endorphin Levels . Adams Media, 2015. T. Nilchaikovit, S. Uneanong, D. Kessawai, and P. Thomyangkoon, "The Thai version of the Positive and Negative Syndrome Scale (PANSS) for schizophrenia: criterion validity and interrater reliability," (in eng), J Med Assoc Thai, vol. 83, no. 6, pp. 646-51, Jun 2000. M. U. Faculty of Physical Therapy. "Thai Physio Aging Group (TPAG)." Mahidol University. https://pt.mahidol.ac.th/tpag/ (accessed April 1, 2020). X. L. Liu et al. , "Task-specific Disruptions in Theta Oscillations during Working Memory for Temporal Order in People with Schizophrenia," Journal of Cognitive Neuroscience, vol. 32, no. 11, pp. 2117-2130, 2020, doi: 10.1162/jocn_a_01598. B. Kluwe-Schiavon, B. Sanvicente-Vieira, C. H. Kristensen, and R. Grassi-Oliveira, "Executive functions rehabilitation for schizophrenia: a critical systematic review," (in eng), J Psychiatr Res, vol. 47, no. 1, pp. 91-104, Jan 2013, doi: 10.1016/j.jpsychires.2012.10.001. 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. 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Introduction","content":"\u003cp\u003eRehabilitation in schizophrenia increasingly recognizes the need to integrate cognitive and motor training within meaningful activities. Deficits in executive functioning, emotional regulation, and behavioral initiation impair clients\u0026rsquo; ability to engage in purposeful occupations [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Occupational therapy interventions must therefore address not only observable performance skills but also the underlying neurocognitive processes that support occupational engagement [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe Brainy2Blessly (B2B) app was developed as a dual-purpose tool for assessing and training cognitive-motor functions. It engages users in structured digital tasks simulating daily occupations while collecting performance metrics such as time-on-task, memory recall, and emotional self-report [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. When paired with Brain Mapping Performance (BMP)\u0026mdash;a task-based application of quantitative EEG (QEEG)\u0026mdash;the system enables real-time monitoring of theta activity in frontal and central brain regions, which are known markers of attention and motor planning [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis hybrid approach integrates neuroscience-based monitoring with performance-based assessment, bridging the gap between cortical function and occupational behavior in schizophrenia rehabilitation. Recent models advocate for such integration of brain-behavior data to optimize individualized care and deepen understanding of cognitive-emotional dysfunctions [\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn this study, BMP was used as a neurofunctional assessment tool to observe changes in theta, beta, and theta/beta ratio across six QEEG sites (frontal and temporal) while participants engaged in memory- and emotion-related activities. We aimed to determine whether the B2B app\u0026mdash;under monitored versus unmonitored conditions\u0026mdash;would reveal differences in task completion time, EEG dynamics, and perceived calmness, suggesting varying levels of executive function engagement.\u003c/p\u003e\u003cp\u003eContemporary occupational therapy in schizophrenia increasingly combines digital technology with occupation-based principles [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Thai executive function (EF) rehabilitation frameworks, such as the Neuro-Functional Approach (NFA), describe recovery as a graded process of relearning everyday routines through cognitive prompting, emotional regulation, and meaningful participation [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The B2B app aligns with these principles by providing stepwise simulations designed to activate key EF domains.\u003c/p\u003e\u003cp\u003eMoreover, integrating B2B with real-time QEEG via BMP supports therapy approaches that prioritize humanized cueing, environmental familiarity, and emotional readiness [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. This combination may enhance ecological validity and promote client-centered care\u0026mdash;critical for functional gains in schizophrenia.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cp\u003e\u003cem\u003e2.1. Participants.\u0026nbsp;\u003c/em\u003eThirty individuals diagnosed with schizophrenia (mean age = 38.9 \u0026plusmn; 7.15 years; 10 male, 20 female; all right-handed) were recruited. Inclusion criteria included DSM-5 diagnosis and stable outpatient status. 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 [15]. Exclusion criteria involved comorbid neurological disorders or recent substance use. All participants provided written informed consent by signing a consent form before participating in the study.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.2. Human Research Ethics.\u003c/em\u003e Ethical Approval Ethical clearance was granted by Mahidol University Central IRB (MU-CIRB 2020/114.1505; COA No. 2020/103.0708) and the Department of Mental Health IRB (DMH.IRB 031/2563; COA No. 041/2563).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.3. Study Process\u003c/em\u003e. B2B Task Conditions EEG signals were recorded using a QEEG system during Brain Mapping Performance (BMP) tasks, allowing functional interpretation of brain activity in context-specific B2B tasks. Each participant completed two B2B task sessions: one with BMP and one without. To examine how physical activity (PA) engagement relates to emotional-cognitive processing in individuals with schizophrenia, the B2B application integrated a classification of 16 daily activities, each theoretically linked to one of the four \u0026quot;happy hormones\u0026quot;: dopamine, oxytocin, serotonin, and endorphin [14].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eParticipants were asked to prioritize these 16 activities based on their frequency of participation in daily life. For each neurotransmitter, a subset of four activities was presented, grounded in occupational therapy literature and neuropsychological associations: Dopamine-related (reward, goal achievement): e.g., cooking, playing games, solving puzzles, planning a trip Oxytocin-related (social bonding, trust): e.g., group singing, giving compliments, storytelling, sharing meals Serotonin-related (emotion regulation, mindfulness): e.g., mindful walking, gardening, meditation, journaling Endorphin-related (pleasure, pain relief): e.g., jogging, dancing, laughing, stretching\u003c/p\u003e\n\u003cp\u003eThe top four participant-selected activities were matched with their respective energy expenditure values (METs) based on the Thai Physical Activity Guideline (2020)[16]. A normalized score was then computed for each neurotransmitter phase by summing the MET values of the top four activities within each domain and dividing by the maximum reference value (5.9 METs). These individualized habit success scores were used as behavioral proxies for engagement in dopamine-, oxytocin-, serotonin-, and endorphin-related physical activity patterns.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.4. Outcome Measures and Statistical Analysis\u003c/em\u003e. QEEG Recording and Analysis QEEG signals were recorded using a 12-electrode setup based on the International 10\u0026ndash;20 system. Data were sampled and analyzed offline to extract theta relative power (4\u0026ndash;7 Hz), calculated as the proportion of total spectral power, was used to compare brain activation patterns from six primary electrode sites: Fp1, Fz, F4, F7, Cz, and T3. Artifact rejection and bandpass filtering were applied. The theta/beta ratio was used interpretating: high theta/beta for inattention and low theta/beta for focused attention. A repeated-measures ANOVA was conducted to examine the effects of condition and time on participants\u0026rsquo; cognitive-emotional performance.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003e\u003cem\u003e3.1. Theta and Beta Dynamics Across QEEG Sites During Cognitive Engagement.\u003c/em\u003e One-way repeated measures ANOVA was conducted separately for each QEEG site to compare theta relative power, theta/beta ratio, and beta relative power during the memory task (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The results revealed significant differences across the three measures at all sites: Fp1 [F(2, 58)\u0026thinsp;=\u0026thinsp;52.22, p\u0026thinsp;\u0026lt;\u0026thinsp;.001], F7 [F(2, 58)\u0026thinsp;=\u0026thinsp;74.04, p\u0026thinsp;\u0026lt;\u0026thinsp;.001], F4 [F(2, 58)\u0026thinsp;=\u0026thinsp;59.88, p\u0026thinsp;\u0026lt;\u0026thinsp;.001], Fz [F(2, 58)\u0026thinsp;=\u0026thinsp;61.18, p\u0026thinsp;\u0026lt;\u0026thinsp;.001], Cz [F(2, 58)\u0026thinsp;=\u0026thinsp;52.26, p\u0026thinsp;\u0026lt;\u0026thinsp;.001], and T3 [F(2, 58)\u0026thinsp;=\u0026thinsp;33.33, p\u0026thinsp;\u0026lt;\u0026thinsp;.001].\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eRepeated Measures ANOVA of QEEG Indices in 6 Sites.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQEEG Sites\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTheta Relative Power\u003c/p\u003e\u003cp\u003e(Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTheta/Beta Ratio (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBeta Relative Power\u003c/p\u003e\u003cp\u003e(Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eF-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFp1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e18.21\u0026thinsp;\u0026plusmn;\u0026thinsp;5.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e1.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e13.80\u0026thinsp;\u0026plusmn;\u0026thinsp;7.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e52.22*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eF7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e17.83\u0026thinsp;\u0026plusmn;\u0026thinsp;4.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e1.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e15.11\u0026thinsp;\u0026plusmn;\u0026thinsp;6.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e74.04*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eF4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e20.12\u0026thinsp;\u0026plusmn;\u0026thinsp;4.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e1.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e17.65\u0026thinsp;\u0026plusmn;\u0026thinsp;9.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e59.88*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFz\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e22.77\u0026thinsp;\u0026plusmn;\u0026thinsp;6.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e1.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e16.38\u0026thinsp;\u0026plusmn;\u0026thinsp;9.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e61.18*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCz\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e20.85\u0026thinsp;\u0026plusmn;\u0026thinsp;5.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e1.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e18.29\u0026thinsp;\u0026plusmn;\u0026thinsp;10.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e52.26*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eT3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e14.40\u0026thinsp;\u0026plusmn;\u0026thinsp;4.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e0.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e21.18\u0026thinsp;\u0026plusmn;\u0026thinsp;13.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e33.33*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e* p\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/p\u003e\u003cp\u003eTheta relative power during B2B was highest at Fz, followed by Cz, and F4, consistent with cognitive-motor integration. These findings suggest elevated attentional and motor planning load. Further analysis at individual sites indicated that T3 had disproportionately high beta relative power, while Fz maintained the highest theta dominance, reflecting region-specific cognitive engagement patterns. QEEG results also showed theta/beta ratios peaking in calm states (Fz).\u003c/p\u003e\u003cp\u003e\u003cem\u003e3.2. Impact of BMP Guidance on Neurotransmitter-Related Habit Formation.\u003c/em\u003e As shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, habit success scores across the four neurotransmitter-related activity phases were compared under conditions with and without BMP guidance. Participants showed slightly higher success in dopamine (t\u003csub\u003e29\u003c/sub\u003e = -3.179, p\u0026thinsp;=\u0026thinsp;0.013), serotonin (t\u003csub\u003e29\u003c/sub\u003e = -1.317, p\u0026thinsp;=\u0026thinsp;0.011), oxytocin (t\u003csub\u003e29\u003c/sub\u003e = -2.418, p\u0026thinsp;=\u0026thinsp;0.022), and endorphin (t\u003csub\u003e29\u003c/sub\u003e = -3.291, p\u0026thinsp;=\u0026thinsp;0.012). Beside the data comparison, strongest correlations (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) with neurotransmitter indices were selected for each QEEG site (see Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Key moderately associated finding were at F7 (serotonin) and Fz (endorphin), indicating neurophysiological sensitivity to emotional-affective modulation.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eHabit Success (%) by Neurotransmitter Related Activity Phases.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNeurotransmitter-Related Activity Phases\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHabit success (%) with BMP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHabit success (%) with No BMP\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDopamine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e75.61\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;8.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e79.95\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;9.86*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerotonin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e56.34\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;15.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e57.36\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;13.88*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOxytocin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e55.13\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;13.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e58.09\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;13.59*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEndorphin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e58.56\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;13.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e55.74\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;14.27*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e*p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003cp\u003eAdditional correlations revealed distinct roles of each frontal QEEG site in B2B performance. Fp1 theta/beta ratios showed positive associations with serotonin-linked calmness, while F7 and F4 frontal beta power positively correlated with three neurotransmitter-linked phases (serotonin, endorphin, and dopamine), suggesting emotional and executive inhibition. Fz and Cz also demonstrated midline involvement in dopaminergic reward and endorphin processing. Oxytocin and serotonin showed low correlations with beta activity at T3.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eQEEG Site-Highest Correlations and Functional Roles.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQEEG Feature\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFunctional Role\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eKey Correlation\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFp1 Theta/beta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAnterior prefrontal \u0026ndash; calm attentional control \u0026amp; self-monitoring\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSerotonin (r\u0026thinsp;=\u0026thinsp;.419)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFp1 Beta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAnterior prefrontal \u0026ndash; task engagement \u0026amp; dopaminergic alertness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDopamine (r\u0026thinsp;=\u0026thinsp;.440)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eF7 Theta/beta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLeft dorsolateral prefrontal \u0026ndash; emotional inhibition \u0026amp; top-down regulation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSerotonin (r\u0026thinsp;=\u0026thinsp;.511)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eF7 Beta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLeft frontal \u0026ndash; affective effort, inhibition, and mood regulation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEndorphin (r\u0026thinsp;=\u0026thinsp;.419)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eF4 Beta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRight dorsolateral prefrontal \u0026ndash; working memory, executive planning\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDopamine (r\u0026thinsp;=\u0026thinsp;.418)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFz Beta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMidline frontal \u0026ndash; cognitive control, conflict monitoring, set shifting\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDopamine (r\u0026thinsp;=\u0026thinsp;.454) Endorphin (r\u0026thinsp;=\u0026thinsp;.500)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCz Beta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSensorimotor cortex \u0026ndash; motor planning, procedural learning, habit formation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEndorphin (r\u0026thinsp;=\u0026thinsp;.450)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eT3 Beta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLeft temporal \u0026ndash; auditory-linguistic integration, procedural memory, social-affective processing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSerotonin (r\u0026thinsp;=\u0026thinsp;.434)\u003c/p\u003e\u003cp\u003eOxytocin (r\u0026thinsp;=\u0026thinsp;.432)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe B2B protocol, enhanced through BMP monitoring, engaged multiple facets of executive function via digital, culturally relevant tasks. The longer task durations observed under monitored conditions, particularly during the emotion- and memory-linked phases, suggest that real-time neurofeedback elicited greater self-regulation and cognitive effort [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. In line with occupational therapy theories emphasizing internal cognitive readiness for participation, these findings highlight the utility of BMP as a neurofunctional interface within task-based rehabilitation [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTheta activity in frontal regions\u0026mdash;especially Fz and Cz\u0026mdash;was consistently elevated during monitored conditions. These sites are associated with working memory, attentional control, and emotional self-monitoring, and their activation aligns with previous EEG findings in schizophrenia showing disrupted but compensatory theta engagement during executive tasks [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The theta/beta ratio provided further insight, with elevated beta activity during memory-linked phases reflecting increased executive inhibition and motor planning [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe observed delay in performance during monitored tasks supports the hypothesis that BMP feedback modulates cognitive engagement, likely activating mechanisms for shifting, inhibition, and emotional control. This mirrors previous research using remediation-based tasks (e.g., brushing, eating, washing) that progressively train attention, flexibility, and sequencing [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eImportantly, the B2B and BMP integration reflects Thai models of rehabilitation, such as the Neuro-Functional Approach (NFA), which promote recovery through graded challenge, culturally relevant occupation, and affective attunement [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. By simulating everyday tasks in an emotionally resonant, structured format, the B2B tool aligns with principles of motivational readiness and ecological validity\u0026mdash;central tenets of effective occupational engagement [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFrom a clinical perspective, B2B paired with BMP offers dual utility: (1) it captures performance-based metrics such as time and task success, and (2) it provides neurophysiological insight into executive strain and affective readiness. This hybrid tool could be particularly effective in psychiatric occupational therapy, where abstract assessments often fail to reflect real-world functioning [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The correlation of task-phase with EEG activation underscores its potential as a digital biomarker for schizophrenia.\u003c/p\u003e\u003cp\u003eFurther studies are warranted to explore the predictive validity of the B2B tool, including its use for therapy monitoring, motivation enhancement, and longitudinal executive rehabilitation. By combining culturally embedded tasks with neuroscience-based assessment, B2B and BMP represent a promising advancement in occupational therapy for individuals with schizophrenia.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThe findings demonstrate that QEEG-based monitoring during occupational tasks can reveal distinct patterns of executive, motor, and emotional engagement in individuals with schizophrenia. Frontal theta and beta activity patterns were differentially associated with neurotransmitter-linked behavioral phases, underscoring the potential of brain mapping performance (BMP) as a neurofunctional assessment tool. This supports the integration of real-time neurophysiological feedback into occupational therapy to tailor interventions that enhance emotional regulation, cognitive flexibility, and motivational readiness.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eConflicts of Interest\u003c/h2\u003e\u003cp\u003eThe authors declare no competing interests.\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. developed the B2B app and conducted the study. M.R. supported data analysis and interpretation. W.C. provided project supervision and manuscript oversight as corresponding author.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e\u003cp\u003eThe authors thank the participants and clinical partners who made this study possible. No third-party services or individuals not listed as authors contributed to the research or preparation of this manuscript.\u003c/p\u003e\u003ch2\u003eData Availability Statement\u003c/h2\u003e\u003cp\u003eThe data are not publicly available due to privacy and ethical restrictions related to participant confidentiality.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eP. D. Harvey, \u0026quot;Assessment of everyday functioning in schizophrenia,\u0026quot; (in eng), \u003cem\u003eInnov Clin Neurosci, \u003c/em\u003evol. 8, no. 5, pp. 21-4, May 2011. [Online]. Available: https://pmc.ncbi.nlm.nih.gov/articles/PMC3115762/.\u003c/li\u003e\n\u003cli\u003eC.-Y. Su, P.-C. Tsai, W.-L. Su, T.-C. Tang, and A. 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Faculty of Physical Therapy. \u0026quot;Thai Physio Aging Group (TPAG).\u0026quot; Mahidol University. https://pt.mahidol.ac.th/tpag/ (accessed April 1, 2020).\u003c/li\u003e\n\u003cli\u003eX. L. Liu\u003cem\u003e et al.\u003c/em\u003e, \u0026quot;Task-specific Disruptions in Theta Oscillations during Working Memory for Temporal Order in People with Schizophrenia,\u0026quot; \u003cem\u003eJournal of Cognitive Neuroscience, \u003c/em\u003evol. 32, no. 11, pp. 2117-2130, 2020, doi: 10.1162/jocn_a_01598.\u003c/li\u003e\n\u003cli\u003eB. Kluwe-Schiavon, B. Sanvicente-Vieira, C. H. Kristensen, and R. Grassi-Oliveira, \u0026quot;Executive functions rehabilitation for schizophrenia: a critical systematic review,\u0026quot; (in eng), \u003cem\u003eJ Psychiatr Res, \u003c/em\u003evol. 47, no. 1, pp. 91-104, Jan 2013, doi: 10.1016/j.jpsychires.2012.10.001.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"Schizophrenia, motor relearning, cognitive engagement, B2B app, occupational therapy, QEEG","lastPublishedDoi":"10.21203/rs.3.rs-7780966/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7780966/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eIntroduction:\u003c/h2\u003e\u003cp\u003eThe integration of digital tools and neurophysiological monitoring in mental health care presents new opportunities for cognitive and motor rehabilitation. This study investigated the Brainy2Blessly (B2B) app as a tool for assessing visuospatial prioritization and emotional habituation related to physical activity in individuals with schizophrenia. Simultaneous brain mapping was conducted to explore neurocognitive engagement and motor relearning.\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e\u003cp\u003eThirty participants with schizophrenia (mean age\u0026thinsp;=\u0026thinsp;38.9\u0026thinsp;\u0026plusmn;\u0026thinsp;7.15 years) completed structured tasks using the B2B app under two conditions: with and without quantitative EEG (QEEG) monitoring. Percentages of top-ranking physical activities linked to \u0026ldquo;happy hormones\u0026rdquo; were calculated based on energy expenditure data from the Thai Physical Activity Guideline. QEEG measured theta relative power, beta relative power, and the theta/beta ratio at six scalp locations during task performance.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e\u003cp\u003eQEEG data revealed region-specific neural activation during the B2B and LCAR tasks. Theta relative power was highest at Fz, followed by Cz and F4, indicating robust engagement of executive and motor-planning regions. Theta/beta ratios peaked at Fp1 and Fz during calm states, reflecting prefrontal regulation and internal attention. Frontal beta power at F4, F7, and Fz showed moderate positive correlations with dopamine-, serotonin-, and endorphin-linked physical activity phases, suggesting sensitivity to reward, affective, and executive functions. Notably, the Fp1 theta/beta ratio was positively associated with serotonin-related calmness, while T3 beta power exhibited low correlations with oxytocin and serotonin, indicating diminished social-affective engagement. ANOVA results confirmed significant differences in EEG indices across sites (F\u0026thinsp;=\u0026thinsp;28.57\u0026ndash;38.29, p\u0026thinsp;\u0026lt;\u0026thinsp;.001), supporting the site-specific neurofunctional relevance of QEEG-informed occupational performance.\u003c/p\u003e\u003ch2\u003eConclusion:\u003c/h2\u003e\u003cp\u003eQEEG-guided occupational tasks reveal distinct neural engagement patterns linked to emotional and executive functions in schizophrenia. These findings support the use of Brain Mapping Performance (BMP) and the B2B app as valuable tools for individualized rehabilitation planning in occupational therapy.\u003c/p\u003e","manuscriptTitle":"Brainy2Blessly and QEEG: A Neurofunctional Window into Schizophrenia Rehabilitation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-07 07:14:18","doi":"10.21203/rs.3.rs-7780966/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":55772216,"name":"Cognitive Neuroscience"},{"id":55772217,"name":"Psychiatry"},{"id":55772218,"name":"Occupational Medicine"}],"tags":[],"updatedAt":"2025-10-07T07:14:19+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-07 07:14:18","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7780966","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7780966","identity":"rs-7780966","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}