Although structural abnormalities has been reported in schizophrenia, generalizability across MRI scanners and protocols remains a major limitation for clinical application.
Our previous study demonstrated that general linear model (GLM)-based harmonization can effectively distinguish patients with schizophrenia from healthy controls (HC) across MRI scanners. In this method, regions of interest (ROIs) showing volume reduction in schizophrenia were pre-defined, and age, sex, and total intracranial volume were included as dependent variables in the scanner and protocol specific GLM (spsGLM). The residuals (ε) of the spsGLM, the difference between estimated and measured ROI volume, were used as an indicator of schizophrenia.
In the present study, we assessed required number of HC to apply this method, and adapted it to a larger dataset. We analyzed data from 1179 schizophrenia patients and 2381 HC across 15 MRI scanners. The minimum number of HC required was estimated to be 20. To avoid sampling bias, 20 HC were randomly selected 1000 times, and spsGLM model fitting was implemented for each set. The coefficients of spsGLM were calculated by averaging the results of 1000 trials, and ε was computed. Receiver operating characteristic (ROC) analyses were performed to evaluate ε.
Results indicated that the area under the curve (AUC) from ROC analysis ranged from 0.66 to 0.83. ROC analysis using full sample showed an AUC of 0.74. These results were comparable to those obtained using ComBat harmonization or a Random Forrest classifier.
In conclusion, scanning 20 HC enables our GLM-based harmonization method to generalize across scanners.
{"title":"Optimizing multi-site schizophrenia differentiation: MRI harmonization with 20 controls per scanner in a study of 3560 subjects across 15 MRI scanners","authors":"Naoki Hashimoto , Kiyotaka Nemoto , Masaki Fukunaga , Junya Matsumoto , Naohiro Okada , Kentaro Morita , Hidenaga Yamamori , Michiko Fujimoto , Yuka Yasuda , Michihiko Koeda , Takahiko Kawashima , Morio Aki , Daiki Sasabayashi , Daisuke Fujikane , Kenichiro Harada , Maeri Yamamoto , Shuhei Ishikawa , Naomi Hasegawa , Satsuki Ito , Kazutaka Ohi , Ryota Hashimoto","doi":"10.1016/j.pnpbp.2026.111607","DOIUrl":"10.1016/j.pnpbp.2026.111607","url":null,"abstract":"<div><div>Although structural abnormalities has been reported in schizophrenia, generalizability across MRI scanners and protocols remains a major limitation for clinical application.</div><div>Our previous study demonstrated that general linear model (GLM)-based harmonization can effectively distinguish patients with schizophrenia from healthy controls (HC) across MRI scanners. In this method, regions of interest (ROIs) showing volume reduction in schizophrenia were pre-defined, and age, sex, and total intracranial volume were included as dependent variables in the scanner and protocol specific GLM (spsGLM). The residuals (ε) of the spsGLM, the difference between estimated and measured ROI volume, were used as an indicator of schizophrenia.</div><div>In the present study, we assessed required number of HC to apply this method, and adapted it to a larger dataset. We analyzed data from 1179 schizophrenia patients and 2381 HC across 15 MRI scanners. The minimum number of HC required was estimated to be 20. To avoid sampling bias, 20 HC were randomly selected 1000 times, and spsGLM model fitting was implemented for each set. The coefficients of spsGLM were calculated by averaging the results of 1000 trials, and ε was computed. Receiver operating characteristic (ROC) analyses were performed to evaluate ε.</div><div>Results indicated that the area under the curve (AUC) from ROC analysis ranged from 0.66 to 0.83. ROC analysis using full sample showed an AUC of 0.74. These results were comparable to those obtained using ComBat harmonization or a Random Forrest classifier.</div><div>In conclusion, scanning 20 HC enables our GLM-based harmonization method to generalize across scanners.</div></div>","PeriodicalId":54549,"journal":{"name":"Progress in Neuro-Psychopharmacology & Biological Psychiatry","volume":"144 ","pages":"Article 111607"},"PeriodicalIF":3.9,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145907259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-02DOI: 10.1016/j.pnpbp.2025.111603
Fanghui Dong , Kaili Che , Yinghong Shi , Heng Ma , Feng Zhao , Haizhu Xie , Ning Mao , Tongpeng Chu , Xin Zhao
Background
Previous studies on brain functional networks in Major Depressive Disorder (MDD) have mainly focused on node changes, but the dynamics of edge-to-edge connectivity remain unclear. This study combines edge-centric functional connectivity (eFC) and whole-brain transcriptomics to reveal higher-order network interactions in MDD.
Methods
We enrolled 163 MDD patients and 135 healthy controls (HCs). First, time series were extracted to construct the functional connectivity (FC) matrix. Then, edges were extracted from this matrix, and their Pearson correlation coefficients were calculated to construct the eFC matrix. Between-group differences in eFC were compared. Subsequently, support vector machines (SVM), random forest (RF) and extreme gradient boosting (XGBoost) models were built to evaluate the classification performance of eFC in diagnosing MDD. Finally, by integrating transcriptomic data, we identified genes whose spatial expression profiles were associated with eFC alterations and performed functional enrichment analysis.
Results
We observed that compared to HCs, there are extensive changes in eFC. Specifically, individuals with MDD exhibited increased eFC in the left Superior frontal gyrus, right Middle frontal gyrus and bilateral Inferior temporal gyrus, while displaying decreased eFC in the bilateral Caudate nucleus. The classification results demonstrated that models based on eFC features outperformed those based on traditional FC in key metrics, and this advantage remained stable across different algorithms. Partial least squares (PLS) analysis revealed that alterations in eFC in MDD patients are associated with specific gene expression profiles. These genes were significantly enriched in pathways related to ion channels and synaptic transmission. These findings were replicated in validation cohort and HarvardOxford brain atlas.
Conclusion
Our study revealed alterations in the eFC network in MDD patients and their associations with gene expression profiles, providing a novel perspective to advance the understanding of MDD.
{"title":"Alterations in edge-centric functional connectivity in patients with major depressive disorder and their genetic mechanisms: A transcriptome-neuroimaging correlation study","authors":"Fanghui Dong , Kaili Che , Yinghong Shi , Heng Ma , Feng Zhao , Haizhu Xie , Ning Mao , Tongpeng Chu , Xin Zhao","doi":"10.1016/j.pnpbp.2025.111603","DOIUrl":"10.1016/j.pnpbp.2025.111603","url":null,"abstract":"<div><h3>Background</h3><div>Previous studies on brain functional networks in Major Depressive Disorder (MDD) have mainly focused on node changes, but the dynamics of edge-to-edge connectivity remain unclear. This study combines edge-centric functional connectivity (eFC) and whole-brain transcriptomics to reveal higher-order network interactions in MDD.</div></div><div><h3>Methods</h3><div>We enrolled 163 MDD patients and 135 healthy controls (HCs). First, time series were extracted to construct the functional connectivity (FC) matrix. Then, edges were extracted from this matrix, and their Pearson correlation coefficients were calculated to construct the eFC matrix. Between-group differences in eFC were compared. Subsequently, support vector machines (SVM), random forest (RF) and extreme gradient boosting (XGBoost) models were built to evaluate the classification performance of eFC in diagnosing MDD. Finally, by integrating transcriptomic data, we identified genes whose spatial expression profiles were associated with eFC alterations and performed functional enrichment analysis.</div></div><div><h3>Results</h3><div>We observed that compared to HCs, there are extensive changes in eFC. Specifically, individuals with MDD exhibited increased eFC in the left Superior frontal gyrus, right Middle frontal gyrus and bilateral Inferior temporal gyrus, while displaying decreased eFC in the bilateral Caudate nucleus. The classification results demonstrated that models based on eFC features outperformed those based on traditional FC in key metrics, and this advantage remained stable across different algorithms. Partial least squares (PLS) analysis revealed that alterations in eFC in MDD patients are associated with specific gene expression profiles. These genes were significantly enriched in pathways related to ion channels and synaptic transmission. These findings were replicated in validation cohort and HarvardOxford brain atlas.</div></div><div><h3>Conclusion</h3><div>Our study revealed alterations in the eFC network in MDD patients and their associations with gene expression profiles, providing a novel perspective to advance the understanding of MDD.</div></div>","PeriodicalId":54549,"journal":{"name":"Progress in Neuro-Psychopharmacology & Biological Psychiatry","volume":"144 ","pages":"Article 111603"},"PeriodicalIF":3.9,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145879421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-02DOI: 10.1016/j.pnpbp.2025.111601
Wiktoria Ratajczak
Purpose of the review
Generalized Anxiety Disorder (GAD) is a chronic and prevalent psychiatric condition affecting approximately 4.05 % of the global population, with a higher incidence in women and early onset in childhood. GAD is associated with significant mental, emotional, and physical impairments, including insomnia, metabolic syndrome, and other psychiatric comorbidities such as depression. Current treatment options include pharmacotherapy and cognitive behavioural therapy (CBT), face challenges such as side effects, long treatment durations, and accessibility issues. This review explores the role of the vestibular system in anxiety pathophysiology and examines the potential of electrical vestibular stimulation (VeNS) as a novel, safe, and effective treatment option.
Recent findings
While the exact pathophysiology of anxiety remains unclear, recent studies suggest that GAD involves complex neurobiological mechanisms, including dysregulated inhibitory neurotransmission, hyperactivity of the amygdala, and impaired connectivity in anxiety-related neural circuits. The vestibular system has been identified as a critical modulator of emotional and stress responses, with vestibular dysfunction being linked to heightened anxiety levels. VeNS, a non-invasive neuromodulation technique, has demonstrated effectiveness in reducing anxiety symptoms by influencing key brain structures, including the amygdala, prefrontal cortex, hippocampus, and locus coeruleus. Clinical trials have shown significant reductions in GAD-7 scores and improvements in sleep and overall quality of life following VeNS treatment.
Summary: electrical
Vestibular stimulation (VeNS) has emerged as a promising, non-invasive therapeutic approach for managing GAD. By targeting the vestibular system's extensive neural connections, VeNS modulates anxiety-related brain regions, regulates stress responses, and enhances emotional well-being. Clinical evidence supports its efficacy in significantly reducing anxiety symptoms and improving sleep quality. Given its favorable safety profile and ease of use, VeNS presents a viable alternative or complementary option to conventional pharmacological and psychotherapeutic treatments for anxiety disorders.
{"title":"Unveiling the vestibular system's role in anxiety and the promise of electrical vestibular stimulation (VeNS) therapy","authors":"Wiktoria Ratajczak","doi":"10.1016/j.pnpbp.2025.111601","DOIUrl":"10.1016/j.pnpbp.2025.111601","url":null,"abstract":"<div><h3>Purpose of the review</h3><div>Generalized Anxiety Disorder (GAD) is a chronic and prevalent psychiatric condition affecting approximately 4.05 % of the global population, with a higher incidence in women and early onset in childhood. GAD is associated with significant mental, emotional, and physical impairments, including insomnia, metabolic syndrome, and other psychiatric comorbidities such as depression. Current treatment options include pharmacotherapy and cognitive behavioural therapy (CBT), face challenges such as side effects, long treatment durations, and accessibility issues. This review explores the role of the vestibular system in anxiety pathophysiology and examines the potential of electrical vestibular stimulation (VeNS) as a novel, safe, and effective treatment option.</div></div><div><h3>Recent findings</h3><div>While the exact pathophysiology of anxiety remains unclear, recent studies suggest that GAD involves complex neurobiological mechanisms, including dysregulated inhibitory neurotransmission, hyperactivity of the amygdala, and impaired connectivity in anxiety-related neural circuits. The vestibular system has been identified as a critical modulator of emotional and stress responses, with vestibular dysfunction being linked to heightened anxiety levels. VeNS, a non-invasive neuromodulation technique, has demonstrated effectiveness in reducing anxiety symptoms by influencing key brain structures, including the amygdala, prefrontal cortex, hippocampus, and locus coeruleus. Clinical trials have shown significant reductions in GAD-7 scores and improvements in sleep and overall quality of life following VeNS treatment.</div></div><div><h3>Summary: electrical</h3><div>Vestibular stimulation (VeNS) has emerged as a promising, non-invasive therapeutic approach for managing GAD. By targeting the vestibular system's extensive neural connections, VeNS modulates anxiety-related brain regions, regulates stress responses, and enhances emotional well-being. Clinical evidence supports its efficacy in significantly reducing anxiety symptoms and improving sleep quality. Given its favorable safety profile and ease of use, VeNS presents a viable alternative or complementary option to conventional pharmacological and psychotherapeutic treatments for anxiety disorders.</div></div>","PeriodicalId":54549,"journal":{"name":"Progress in Neuro-Psychopharmacology & Biological Psychiatry","volume":"144 ","pages":"Article 111601"},"PeriodicalIF":3.9,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145879490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-02DOI: 10.1016/j.pnpbp.2025.111604
Le Gao , Yue Hou , Xiaojiao Dong , Chenchen Wang , Dong Cui , Xiaonan Guo
Autism spectrum disorder (ASD) is a neurodevelopmental condition exhibiting marked sex heterogeneity in functional connectivity. Given that high-amplitude co-fluctuation patterns dominate whole-brain functional connectivity, this study investigated sex heterogeneity in these patterns in ASD from the perspective of temporal variability. Resting-state functional magnetic resonance imaging data were obtained from the Autism Brain Imaging Data Exchange database, comprising 284 males/65 females with ASD and 340 male/119 female typical controls. High-amplitude co-fluctuation patterns were obtained using an edge time series analysis, and temporal variability of intra-network and inter-network functional architecture was calculated to characterize functional brain network dynamics. A two-way analysis of variance was further conducted to explore sex heterogeneity of functional brain network dynamics in ASD. At the intra-network level, significant diagnosis-by-sex interactions were observed in the default-mode network (DMN), salience network (SAN), cingulo-opercular network (CO), motor and somatosensory network (SMN), subcortical network (SUB), and visual network (VN). In ASD, sex differences in temporal variability were reduced in the DMN, SMN, and VN, increased in the CO and SUB, and an additional sex difference emerged in the SAN relative to controls. In contrast, at the inter-network level, all brain networks showed varying degrees of diagnosis-by-sex interaction effects. Moreover, network-level functional connectivity dynamics predicted the severity of social interaction impairments in females with ASD and social communication impairments in males with ASD, respectively. These findings reveal the sex heterogeneity of functional brain network dynamics in ASD, and highlight the potential role of altered high-amplitude co-fluctuations in the sex-specific neural mechanism underlying ASD.
{"title":"Sex heterogeneity of functional brain network dynamics in autism spectrum disorder based on the high-amplitude co-fluctuation analysis","authors":"Le Gao , Yue Hou , Xiaojiao Dong , Chenchen Wang , Dong Cui , Xiaonan Guo","doi":"10.1016/j.pnpbp.2025.111604","DOIUrl":"10.1016/j.pnpbp.2025.111604","url":null,"abstract":"<div><div>Autism spectrum disorder (ASD) is a neurodevelopmental condition exhibiting marked sex heterogeneity in functional connectivity. Given that high-amplitude co-fluctuation patterns dominate whole-brain functional connectivity, this study investigated sex heterogeneity in these patterns in ASD from the perspective of temporal variability. Resting-state functional magnetic resonance imaging data were obtained from the Autism Brain Imaging Data Exchange database, comprising 284 males/65 females with ASD and 340 male/119 female typical controls. High-amplitude co-fluctuation patterns were obtained using an edge time series analysis, and temporal variability of intra-network and inter-network functional architecture was calculated to characterize functional brain network dynamics. A two-way analysis of variance was further conducted to explore sex heterogeneity of functional brain network dynamics in ASD. At the intra-network level, significant diagnosis-by-sex interactions were observed in the default-mode network (DMN), salience network (SAN), cingulo-opercular network (CO), motor and somatosensory network (SMN), subcortical network (SUB), and visual network (VN). In ASD, sex differences in temporal variability were reduced in the DMN, SMN, and VN, increased in the CO and SUB, and an additional sex difference emerged in the SAN relative to controls. In contrast, at the inter-network level, all brain networks showed varying degrees of diagnosis-by-sex interaction effects. Moreover, network-level functional connectivity dynamics predicted the severity of social interaction impairments in females with ASD and social communication impairments in males with ASD, respectively. These findings reveal the sex heterogeneity of functional brain network dynamics in ASD, and highlight the potential role of altered high-amplitude co-fluctuations in the sex-specific neural mechanism underlying ASD.</div></div>","PeriodicalId":54549,"journal":{"name":"Progress in Neuro-Psychopharmacology & Biological Psychiatry","volume":"144 ","pages":"Article 111604"},"PeriodicalIF":3.9,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145879466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-25DOI: 10.1016/j.pnpbp.2025.111593
Gema Mijancos-Martínez , Inés Fernández-Linsenbarth , Alejandro Bachiller , Rosa Beño-Ruiz de la Sierra , Emma Osorio-Iriarte , Alejandro Roig , Claudia Rodríguez-Valbuena , Juan Carlos Fiorini-Talavera , Saúl J. Ruiz-Gómez , Ricardo D. Mancha , Vicente Molina , Miguel Angel Mañanas
Background
EEG recordings associated with transcranial magnetic stimulation (TMS) with paired pulse paradigms allow the in vivo assessment of cortical inhibitory function. The long-interval cortical inhibition (LICI) paradigm can be used to estimate this function related to GABAb receptors.
Methods
We compared LICI values between 25 patients with schizophrenia, 16 patients with bipolar disorder (BD), and 23 healthy controls (HC). We also assessed the relationship between LICI values and cognitive performance, as well as the treatment with antipsychotics, benzodiazepines, and anticonvulsants.
Results
LICI was significantly lower in patients with schizophrenia than in controls, but not in BD patients. In the former group, LICI was negatively associated with cognitive performance and positive symptoms. However, benzodiazepines increased LICI values, which does not explain its decrease in schizophrenia patients.
Conclusions
Our data support the existence of a functional inhibitory deficit mediated by GABAb receptors in schizophrenia, that is associated with cognitive performance and symptoms. In the context of existing literature, this deficit may characterize a subgroup of patients with this diagnosis.
{"title":"Distinct cortical inhibitory profiles in schizophrenia and bipolar disorder: A TMS-EEG study of GABAb function","authors":"Gema Mijancos-Martínez , Inés Fernández-Linsenbarth , Alejandro Bachiller , Rosa Beño-Ruiz de la Sierra , Emma Osorio-Iriarte , Alejandro Roig , Claudia Rodríguez-Valbuena , Juan Carlos Fiorini-Talavera , Saúl J. Ruiz-Gómez , Ricardo D. Mancha , Vicente Molina , Miguel Angel Mañanas","doi":"10.1016/j.pnpbp.2025.111593","DOIUrl":"10.1016/j.pnpbp.2025.111593","url":null,"abstract":"<div><h3>Background</h3><div>EEG recordings associated with transcranial magnetic stimulation (TMS) with paired pulse paradigms allow the in vivo assessment of cortical inhibitory function. The long-interval cortical inhibition (LICI) paradigm can be used to estimate this function related to GABAb receptors.</div></div><div><h3>Methods</h3><div>We compared LICI values between 25 patients with schizophrenia, 16 patients with bipolar disorder (BD), and 23 healthy controls (HC). We also assessed the relationship between LICI values and cognitive performance, as well as the treatment with antipsychotics, benzodiazepines, and anticonvulsants.</div></div><div><h3>Results</h3><div>LICI was significantly lower in patients with schizophrenia than in controls, but not in BD patients. In the former group, LICI was negatively associated with cognitive performance and positive symptoms. However, benzodiazepines increased LICI values, which does not explain its decrease in schizophrenia patients.</div></div><div><h3>Conclusions</h3><div>Our data support the existence of a functional inhibitory deficit mediated by GABAb receptors in schizophrenia, that is associated with cognitive performance and symptoms. In the context of existing literature, this deficit may characterize a subgroup of patients with this diagnosis.</div></div>","PeriodicalId":54549,"journal":{"name":"Progress in Neuro-Psychopharmacology & Biological Psychiatry","volume":"144 ","pages":"Article 111593"},"PeriodicalIF":3.9,"publicationDate":"2025-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145841435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Schizophrenia unfolds through a dynamic course in which perceptual instability, aberrant salience, negative symptoms, and cognitive impairment emerge and interact over time. Existing models have not fully explained how acute disturbances in perceptual inference develop into persistent dysfunction across large-scale neural systems. Here, we advance the Hyperlearning Hypothesis, a mechanistic account proposing that schizophrenia arises from a two-stage disruption in neural learning. First, NMDA/GABA abnormalities impair the precision of prediction-error signaling, leading to unstable perceptual inferences. Second, excessive hippocampal ripple activity drives maladaptive overlearning, which reinforces and stabilizes inaccurate internal models. This cascade links acute perceptual instability to long-term network disorganization and the emergence of chronic negative and cognitive symptoms. Importantly, this framework highlights how aberrant learning signals—rather than static structural deficits—shape the evolution of psychopathology over time.
Electrophysiological evidence supports this framework, as individuals with schizophrenia exhibit elevated ripple frequency and power, delayed ripple-initiated network transitions, and reduced clustering and local efficiency within beta-band cortical networks. Together, these abnormalities suggest a progressive disintegration of large-scale templates that normally support stable cognitive function.
By integrating computational psychiatry, electrophysiology, and network neuroscience, the Hyperlearning Hypothesis offers a coherent mechanistic account of schizophrenia's evolution and outlines potential avenues for clarifying how learning-related and network-level processes contribute to illness progression.
{"title":"Hyperlearning Hypothesis: Network disruption and maladaptive learning in schizophrenia","authors":"Yuichi Takei , Masakazu Sunaga , Kazuyuki Fujihara , Takefumi Ohki , Yutaka Kato , Seiichiro Jinde","doi":"10.1016/j.pnpbp.2025.111599","DOIUrl":"10.1016/j.pnpbp.2025.111599","url":null,"abstract":"<div><div>Schizophrenia unfolds through a dynamic course in which perceptual instability, aberrant salience, negative symptoms, and cognitive impairment emerge and interact over time. Existing models have not fully explained how acute disturbances in perceptual inference develop into persistent dysfunction across large-scale neural systems. Here, we advance the Hyperlearning Hypothesis, a mechanistic account proposing that schizophrenia arises from a two-stage disruption in neural learning. First, NMDA/GABA abnormalities impair the precision of prediction-error signaling, leading to unstable perceptual inferences. Second, excessive hippocampal ripple activity drives maladaptive overlearning, which reinforces and stabilizes inaccurate internal models. This cascade links acute perceptual instability to long-term network disorganization and the emergence of chronic negative and cognitive symptoms. Importantly, this framework highlights how aberrant learning signals—rather than static structural deficits—shape the evolution of psychopathology over time.</div><div>Electrophysiological evidence supports this framework, as individuals with schizophrenia exhibit elevated ripple frequency and power, delayed ripple-initiated network transitions, and reduced clustering and local efficiency within beta-band cortical networks. Together, these abnormalities suggest a progressive disintegration of large-scale templates that normally support stable cognitive function.</div><div>By integrating computational psychiatry, electrophysiology, and network neuroscience, the Hyperlearning Hypothesis offers a coherent mechanistic account of schizophrenia's evolution and outlines potential avenues for clarifying how learning-related and network-level processes contribute to illness progression.</div></div>","PeriodicalId":54549,"journal":{"name":"Progress in Neuro-Psychopharmacology & Biological Psychiatry","volume":"144 ","pages":"Article 111599"},"PeriodicalIF":3.9,"publicationDate":"2025-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145841434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-24DOI: 10.1016/j.pnpbp.2025.111592
Prabhjeet Singh , Tak Pan Wong
Norepinephrine, a stress-related neuromodulator, is a key regulator of synaptic transmission and neuronal activity. While the impact of norepinephrine on excitatory transmission has been frequently discussed, how norepinephrine regulates inhibitory transmission remains poorly understood. Norepinephrine modulates inhibitory synaptic function and the firing property of inhibitory neurons. These norepinephrine effects on inhibitory transmission are complex and often region- and inhibitory neuron subtype-specific. Malfunctioning of the norepinephrine-induced modulation of inhibitory transmission could underlie various brain diseases, especially norepinephrine-related psychiatric and neurodegenerative disorders. In this review, we examine findings on the expression of norepinephrine receptors in inhibitory neurons and norepinephrine-induced modulation of inhibitory transmission across different regions of the central nervous system. Furthermore, we discuss the role of adrenergic receptors, norepinephrine concentrations, signaling and inhibitory neuron subtypes in norepinephrine-induced modulation of inhibitory transmission. Overall, this review highlights inhibitory transmission as a major target of norepinephrine for influencing circuit functions and shaping behavioral outcomes.
{"title":"Norepinephrine and inhibitory transmission: Regional diversity and mechanisms of modulation","authors":"Prabhjeet Singh , Tak Pan Wong","doi":"10.1016/j.pnpbp.2025.111592","DOIUrl":"10.1016/j.pnpbp.2025.111592","url":null,"abstract":"<div><div>Norepinephrine, a stress-related neuromodulator, is a key regulator of synaptic transmission and neuronal activity. While the impact of norepinephrine on excitatory transmission has been frequently discussed, how norepinephrine regulates inhibitory transmission remains poorly understood. Norepinephrine modulates inhibitory synaptic function and the firing property of inhibitory neurons. These norepinephrine effects on inhibitory transmission are complex and often region- and inhibitory neuron subtype-specific. Malfunctioning of the norepinephrine-induced modulation of inhibitory transmission could underlie various brain diseases, especially norepinephrine-related psychiatric and neurodegenerative disorders. In this review, we examine findings on the expression of norepinephrine receptors in inhibitory neurons and norepinephrine-induced modulation of inhibitory transmission across different regions of the central nervous system. Furthermore, we discuss the role of adrenergic receptors, norepinephrine concentrations, signaling and inhibitory neuron subtypes in norepinephrine-induced modulation of inhibitory transmission. Overall, this review highlights inhibitory transmission as a major target of norepinephrine for influencing circuit functions and shaping behavioral outcomes.</div></div>","PeriodicalId":54549,"journal":{"name":"Progress in Neuro-Psychopharmacology & Biological Psychiatry","volume":"144 ","pages":"Article 111592"},"PeriodicalIF":3.9,"publicationDate":"2025-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145841436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-23DOI: 10.1016/j.pnpbp.2025.111597
Xianliang Chen , Hui Chen , Sihong Li , Huajia Tang , Jiawei Zhou , Bohao Cheng , Zhengqian Jiang , Yanyue Ye , Jiali Liu , Peiqu Liu , Fengmei Lu , Jiansong Zhou
Background
Emerging evidence posits repetitive non-suicidal self-injury (NSSI) shares behavioral and neurobiological parallels with addiction. However, the neural mechanisms underlying NSSI, particularly within the framework of “sensation of pain” addiction, remain poorly understood. This study combines the effective connectivity (EC) and transcriptomic profiling to explore addiction-related neural circuit and their potential genetic substrates of NSSI.
Method
A total of 76 medication-free adolescents with depression were included in the study, comprising 36 with NSSI (NSSI group) and 40 without NSSI (non-NSSI group). The addictive subscale of the Ottawa Self-Injury Inventory (OSI) was used to assess the addictive features of NSSI in the NSSI group. Resting-state functional magnetic resonance imaging were analyzed using Spectral dynamic causal modeling to explore the directed neural interactions within predefined circuits of “sensation of pain” addiction. Correlation analyses were performed between the EC and clinical data. Spatial transcriptomic mapping integrated with Allen Human Brain Atlas further detect alterations in connectivity-associated gene expression signatures.
Results
Compared with the non-NSSI group, the NSSI group exhibited four distinct EC alterations from the ventral tegmental area (VTA) to left amygdala (AMYG), from the right medial prefrontal cortex (mPFC) to right AMYG, from the left ventral striatum (VS) to right insula (INS) and from the right VS to left AMYG. Crucially, EC values from the VTA to left AMYG and from the right VS to left AMYG are associated with the addictive characteristics and the NSSI frequency, respectively. Genes associated with altered connectivity patterns primarily focus on the brain development, axon, dendrite, oligodendrocytes, D1+ spiny neurons, D2+ spiny neurons, and cholinergic neurons of habenula.
Conclusion
Our findings yield empirical support for reconceptualizing the NSSI within behavioral addiction frameworks, revealing underlying neurobiological pathways and genetic basis driving repeated NSSI. Notably, EC from the VTA to the left AMYG was positively associated with the addictive features of NSSI, highlighting a potentially important neural pathway underlying its addictive nature. The identified EC dysfunction and associated genetic markers could offer novel potential targets for therapeutic interventions.
{"title":"The neural pathways and genetic substrates of non-suicidal self-injury as a “sensation of pain” addiction in drug-naïve depressed adolescents","authors":"Xianliang Chen , Hui Chen , Sihong Li , Huajia Tang , Jiawei Zhou , Bohao Cheng , Zhengqian Jiang , Yanyue Ye , Jiali Liu , Peiqu Liu , Fengmei Lu , Jiansong Zhou","doi":"10.1016/j.pnpbp.2025.111597","DOIUrl":"10.1016/j.pnpbp.2025.111597","url":null,"abstract":"<div><h3>Background</h3><div>Emerging evidence posits repetitive non-suicidal self-injury (NSSI) shares behavioral and neurobiological parallels with addiction. However, the neural mechanisms underlying NSSI, particularly within the framework of “sensation of pain” addiction, remain poorly understood. This study combines the effective connectivity (EC) and transcriptomic profiling to explore addiction-related neural circuit and their potential genetic substrates of NSSI.</div></div><div><h3>Method</h3><div>A total of 76 medication-free adolescents with depression were included in the study, comprising 36 with NSSI (NSSI group) and 40 without NSSI (non-NSSI group). The addictive subscale of the Ottawa Self-Injury Inventory (OSI) was used to assess the addictive features of NSSI in the NSSI group. Resting-state functional magnetic resonance imaging were analyzed using Spectral dynamic causal modeling to explore the directed neural interactions within predefined circuits of “sensation of pain” addiction. Correlation analyses were performed between the EC and clinical data. Spatial transcriptomic mapping integrated with Allen Human Brain Atlas further detect alterations in connectivity-associated gene expression signatures.</div></div><div><h3>Results</h3><div>Compared with the non-NSSI group, the NSSI group exhibited four distinct EC alterations from the ventral tegmental area (VTA) to left amygdala (AMYG), from the right medial prefrontal cortex (mPFC) to right AMYG, from the left ventral striatum (VS) to right insula (INS) and from the right VS to left AMYG. Crucially, EC values from the VTA to left AMYG and from the right VS to left AMYG are associated with the addictive characteristics and the NSSI frequency, respectively. Genes associated with altered connectivity patterns primarily focus on the brain development, axon, dendrite, oligodendrocytes, D1+ spiny neurons, D2+ spiny neurons, and cholinergic neurons of habenula.</div></div><div><h3>Conclusion</h3><div>Our findings yield empirical support for reconceptualizing the NSSI within behavioral addiction frameworks, revealing underlying neurobiological pathways and genetic basis driving repeated NSSI. Notably, EC from the VTA to the left AMYG was positively associated with the addictive features of NSSI, highlighting a potentially important neural pathway underlying its addictive nature. The identified EC dysfunction and associated genetic markers could offer novel potential targets for therapeutic interventions.</div></div>","PeriodicalId":54549,"journal":{"name":"Progress in Neuro-Psychopharmacology & Biological Psychiatry","volume":"144 ","pages":"Article 111597"},"PeriodicalIF":3.9,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145835231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-20DOI: 10.1016/j.pnpbp.2025.111591
Marianela E. Traetta , Martin G. Codagnone , Einav Litvak , María José Maleville Corpa , Nonthué A. Uccelli , Sandra C. Zárate , Analía G. Reinés
Neurodevelopmental disorders, such as autism spectrum disorders (ASD), exhibit a poorly understood male bias. While sex differences may provide key insights into ASD etiology and treatment, the female side of animal models, such as prenatal valproic acid (VPA) exposure, remains incompletely characterized. Here, we evaluated the behavioral, synaptic, and microglial profiles of female VPA rats. Female VPA animals exhibited social deficits, including a decreased sociability index in the three-chamber test and reduced play and social-recognition behaviors in a peer-interaction test, while exploratory and repetitive activities were preserved. At the synaptic level, the medial prefrontal cortex (mPFC) showed increased synaptophysin (SYN) immunostaining, whereas the hippocampal subfield CA3, displayed reduced SYN. Additionally, CA3 neurons exhibited increased neuronal cell adhesion molecule (NCAM) immunostaining, while the mPFC showed increased levels of its polysialylated form (PSA-NCAM), resulting in distinct NCAM/PSA-NCAM ratio shifts in each region. In vitro, hippocampal and cortical neurons from female VPA animals exhibited preserved synaptic puncta number and dendritic tree length and responded to glutamate-induced remodeling similarly to controls, suggesting no intrinsic neuronal alterations. Microglia from the mPFC and the hippocampus exhibited a less ramified morphology, with increased cell numbers in the mPFC. Isolated and cultured microglia retained this reactive phenotype, yet they responded to the exposure to synaptic terminals similarly to controls. Our findings indicate that female VPA rats display a distinctive social deficit linked to brain-area-specific synaptic remodeling impairment and microglial reactivity. Sex-differences in the VPA model could provide valuable insights into neuron-glia interactions underlying autism.
{"title":"Uncovering the female phenotype in the VPA autism model: Brain-region specific synaptic pattern, microglial priming and behavioral singularity","authors":"Marianela E. Traetta , Martin G. Codagnone , Einav Litvak , María José Maleville Corpa , Nonthué A. Uccelli , Sandra C. Zárate , Analía G. Reinés","doi":"10.1016/j.pnpbp.2025.111591","DOIUrl":"10.1016/j.pnpbp.2025.111591","url":null,"abstract":"<div><div>Neurodevelopmental disorders, such as autism spectrum disorders (ASD), exhibit a poorly understood male bias. While sex differences may provide key insights into ASD etiology and treatment, the female side of animal models, such as prenatal valproic acid (VPA) exposure, remains incompletely characterized. Here, we evaluated the behavioral, synaptic, and microglial profiles of female VPA rats. Female VPA animals exhibited social deficits, including a decreased sociability index in the three-chamber test and reduced play and social-recognition behaviors in a peer-interaction test, while exploratory and repetitive activities were preserved. At the synaptic level, the medial prefrontal cortex (mPFC) showed increased synaptophysin (SYN) immunostaining, whereas the hippocampal subfield CA3, displayed reduced SYN. Additionally, CA3 neurons exhibited increased neuronal cell adhesion molecule (NCAM) immunostaining, while the mPFC showed increased levels of its polysialylated form (PSA-NCAM), resulting in distinct NCAM/PSA-NCAM ratio shifts in each region. <em>In vitro</em>, hippocampal and cortical neurons from female VPA animals exhibited preserved synaptic puncta number and dendritic tree length and responded to glutamate-induced remodeling similarly to controls, suggesting no intrinsic neuronal alterations. Microglia from the mPFC and the hippocampus exhibited a less ramified morphology, with increased cell numbers in the mPFC. Isolated and cultured microglia retained this reactive phenotype, yet they responded to the exposure to synaptic terminals similarly to controls. Our findings indicate that female VPA rats display a distinctive social deficit linked to brain-area-specific synaptic remodeling impairment and microglial reactivity. Sex-differences in the VPA model could provide valuable insights into neuron-glia interactions underlying autism.</div></div>","PeriodicalId":54549,"journal":{"name":"Progress in Neuro-Psychopharmacology & Biological Psychiatry","volume":"144 ","pages":"Article 111591"},"PeriodicalIF":3.9,"publicationDate":"2025-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145812104","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-20Epub Date: 2025-10-28DOI: 10.1016/j.pnpbp.2025.111542
{"title":"Expression of concern: \"Adolescent nicotine abstinence increases anxiety and depressive-like behaviors, alcohol consumption, oxidative stress and inflammatory response accompanied by attenuated serotonergic/dopaminergic and cholinergic function in rats\" [Progress in Neuro-Psychopharmacology & Biological Psychiatry, volume 141 (2025), 111464].","authors":"","doi":"10.1016/j.pnpbp.2025.111542","DOIUrl":"https://doi.org/10.1016/j.pnpbp.2025.111542","url":null,"abstract":"","PeriodicalId":54549,"journal":{"name":"Progress in Neuro-Psychopharmacology & Biological Psychiatry","volume":"143 ","pages":"111542"},"PeriodicalIF":3.9,"publicationDate":"2025-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145764314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}