Schizophrenia is a severe psychiatric disorder characterized by widespread white matter (WM) alterations, manifesting as neurodevelopmental deficits and dysconnectivity abnormalities. Over the past two decades, studies have focused on the clinical high-risk (CHR) stage of psychosis and have yielded fruitful information on WM abnormalities that exist prior to the full onset of psychosis, shedding light on biological mechanisms underlying psychosis development. This review presents a summary of current findings on cross-sectional and longitudinal WM alterations in individuals with CHR and their links to clinical symptoms and neurocognitive dysfunction. Next, we review the utilization of WM characterization in predicting clinical outcomes. Taken together, the literature suggests the clinical significance of WM characteristics and their great potential in predicting the conversion to psychosis, despite some methodological and conceptual challenges that remain to be addressed in future studies. Future CHR research would greatly benefit from utilizing WM to guide pharmacological and non-pharmacological targeted treatments, optimize clinical prediction models, and enable more accurate clinical care.
Background: We previously reported lower baseline arteriolar cerebral blood volumes (CBVa) in almost all gray matter regions in a cohort of individuals with schizophrenia of varying ages and disease duration. The extent to which decreased CBVa is also present in recent-onset schizophrenia, and how this impacts neurovascular coupling, remains to be determined. In this study, we sought to determine the extent of CBVa deficits in recent-onset schizophrenia and the relationship of CBVa to region-specific resting-state neural activity.
Methods: Using 7 T MRI, CBVa was measured in 90 regions using 3D inflow-based vascular-space-occupancy (iVASO) imaging in 16 individuals with recent-onset schizophrenia (disease duration: x̄ = 1.18 ± 1.4 years) and 12 age-matched controls. Resting-state functional MRI (rs-fMRI) was used to determine fractional amplitudes of low-frequency fluctuations (fALFF) and intrinsic connectivity (ICC) in spontaneous blood oxygen level-dependent (BOLD) signal. The region-specific relationship between CBVa and fALFF was determined as an index of neurovascular coupling.
Results: Compared with healthy participants, CBVa was lower in individuals with schizophrenia in almost all brain regions, with a global effect size of 0.23 and regional effect sizes up to 0.41. Individuals with schizophrenia also exhibited lower fALFF diffusely across cortical and subcortical gray matter regions. Ratios of mean regional CBVa to fALFF and ICC were significantly lower in patients in numerous brain regions
Conclusion: These findings indicate that early-stage schizophrenia is characterized by widespread microvascular abnormalities and associated resting-state deficits in neural activity, suggesting that abnormalities in neurovascular coupling may contribute to the pathophysiology of schizophrenia.
From 20 to 22 July 2024, the International Society for Magnetic Resonance in Medicine (ISMRM)-endorsed workshop on Magnetic Resonance (MR) for Psychiatry was held in Chengdu City, China. This prestigious event attracted numerous academic elites worldwide.
Vincent Dousset is a professor of medicine and radiology at the University of Bordeaux, France, and the chairman of Medical Imaging at the University Hospital of Bordeaux. The hospital is running a completely new project dedicated to applying MRI technology in the field of psychiatry, and Professor Dousset will manage the project. However, this is an entirely new domain for the radiologists and technicians in the hospital. Therefore, Professor Dousset attended the ISMRM-endorsed Workshop on MR for Psychiatry in Chengdu to gain insight into the latest advancements in psychoradiology and hoped to apply valuable experience to their project.
Following the conference, the Psychoradiology journal interviewed Professor Dousset. In the interview, Professor Dousset was enthusiastic about merging radiology and psychiatry teams and regarded the term “psychoradiology” as a bridge to unite these fields. Despite the challenges of distinguishing normal from abnormal brains in psychiatric disorders, he was optimistic about the future of psychoradiology and its clinical applications. He recognized the significance and prospects of the term “psychoradiology”, and offered valuable suggestions for the development of the Psychoradiology journal.
Introduction: Lithium treatment is considered the first-line option in the pharmacological treatment of bipolar disorder. At the same time, individual responses vary greatly, which complicates achieving rapid stabilization in many subjects with bipolar disorder. The neurobiological mechanism of action of lithium remains largely unknown, hindering the development of clinically applicable predictors of individual treatment responses. The recent introduction of ultra-high-field lithium magnetic resonance imaging (MRI) has opened up a promising avenue for better linking brain measures with clinical response to lithium treatment.
Methods and analysis: This is an observational study involving 80 adults with bipolar disorder who begin lithium as part of their regular treatment. Within 4 weeks of reaching stable therapeutic serum lithium concentrations, brain lithium concentrations will be measured by employing a 3D lithium-7 chemical shift imaging (7Li CSI) sequence on a 7T MR system. The primary outcome is the clinical response to lithium treatment at 1 year follow-up, assessed using a validated questionnaire. Linear regression analysis will be used to establish correlations between brain lithium concentrations—measured through mean brain, voxel-wise, parcellation, and region-of-interest approaches—and clinical lithium response.
Ethics and dissemination: The BLISS study protocol (NL80214.058.22) has been approved by the Medical Ethics Committee of Leiden, The Hague, and Delft in The Netherlands. Results will be submitted for publication in peer-reviewed journals and shared with the key population.
Registration Online at clinicaltrials.gov (NCT06134349), 20 November 2023.
Background: Emotional symptomatology is a hallmark of depression. Antidepressant often fail to effectively target emotional blunting, while acupuncture, by contrast, has emerged as a promising alternative. However, the exact electrophysiologic mechanisms remain unclear. This study aimed to investigate how acupuncture influences emotional reactivity in youth with self-reported depressive symptoms.
Methods: A modified oddball paradigm incorporating a negative emotional valence deviant, combined with event-related potential analysis, was used to measure emotional reactivity before and after intervention. Seventy individuals exhibiting depressive symptoms in the previous 2 weeks, were randomly assigned to either a verum or sham acupuncture group. Electroencephalogram data from 59 participants were analyzed following preprocessing and quality assessment. Occipital P1, N170, frontal N1, N2, and parietal P3 components were extracted. The Positive and Negative Affect Schedule (PANAS) was completed after each oddball session. The Massachusetts General Hospital Acupuncture Sensation Scale (MASS) was completed after each intervention session.
Results: The MASS Index was significantly higher in the verum group. However, significant increases in occipital P1, N170, frontal N1, N2, and parietal P3 amplitudes for high-negative, mild-negative, and neutral pictures were observed after the intervention in both the verum and sham groups, with no significant difference between the groups. Additionally, both groups induced PANAS changes, and positive effect changes were significantly correlated with N170 and P1 (in response to high-negative pictures) changes in the sham group.
Conclusion: Acupuncture altered emotional reactivity in youth with depressive symptoms, highlighting its potential role, albeit possibly non-specific, in depression prevention and treatment.
Functional magnetic resonance imaging (fMRI) provides a powerful tool for studying brain function by capturing neural activity in a non-invasive manner. Mapping brain function from fMRI data enables researchers to investigate the spatial and temporal dynamics of neural processes, providing insights into how the brain responds to various tasks and stimuli. In this review, we explore the evolution of deep learning-based methods for brain function mapping using fMRI. We begin by discussing various network architectures such as convolutional neural networks, recurrent neural networks, and transformers. We further examine supervised, unsupervised, and self-supervised learning paradigms for fMRI-based brain function mapping, highlighting the strengths and limitations of each approach. Additionally, we discuss emerging trends such as fMRI embedding, brain foundation models, and brain-inspired artificial intelligence, emphasizing their potential to revolutionize brain function mapping. Finally, we delve into the real-world applications and prospective impact of these advancements, particularly in the diagnosis of neural disorders, neuroscientific research, and brain-computer interfaces for decoding brain activity. This review aims to provide a comprehensive overview of current techniques and future directions in the field of deep learning and fMRI-based brain function mapping.
Background: Major depressive disorder (MDD) is a prevalent psychiatric disorder with disruptions in brain white matter (WM). While much research has focused on WM structure, the dysfunctional organization of WM in MDD remains poorly understood.
Methods: Using resting-state functional magnetic resonance imaging data from 48 MDD patients and 68 healthy controls (HC), we characterized the WM functional connectome gradients across participants and identified both global and regional alterations in MDD. Furthermore, we examined the relationship between gradient properties and depressive symptom severity. External validation and sensitivity analyses were finally conducted to ensure the reliability of results.
Results: The principal WM connectome gradient extended from the forceps major and superior longitudinal fasciculus to the uncinate fasciculus (UF) and anterior thalamic radiation (ATR), exhibiting a superficial-to-deep pattern in both groups. Compared to HC, MDD patients displayed a narrower gradient range and lower spatial variation, indicating a contracted WM hierarchy. At the tract-specific level, MDD patients exhibited lower gradient scores in the forceps minor, left ATR and UF, and bilateral cingulate gyrus and cingulum hippocampus, but higher gradient scores in the forceps major, bilateral inferior longitudinal fasciculus and superior longitudinal fasciculus. WM tract gradient patterns explained 37.2% of the variance in clinical severity, with the strongest contributions from the inferior fronto-occipital fasciculus, cingulum hippocampus, ATR, UF, and corticospinal tract.
Conclusions: These findings highlight altered WM functional connectome gradient in MDD and their association with clinical severity, offering novel insights into the neurobiological mechanisms of the disorder and potential biomarkers for symptom evaluation.
Background: Emotion control represents a promising intervention target for mental disorders. In a recent study Bramson, et al. (2023) demonstrate a functional-anatomical shift from the lateral frontal pole (FPl) to the dorsolateral prefrontal cortex (DLPFC) in anxious individuals during emotional action control. However, findings of neuroimaging experiments are often limited regarding generalizability and reproducibility. The present study examined the robustness of the reported functional shift across samples, cultures and paradigms.
Methods: We capitalized on large-scale task fMRI data (n = 250 participants) using an affective linguistic Go/NoGo paradigm to examine the anxiety-related shift between FPl and DLPFC during emotional action control. Additionally, context-dependent functional connectivity analyses were employed to examine anxiety-related differences and associations on the network level.
Results: Non-anxious individuals engaged the left FPl while highly anxious individuals specifically recruited the DLPFC, but non-significant between-group differences were found (see also Bramson, et al.). The secondary analyses revealed moderate evidence for the absence of left FPl activation in the high-anxious as well as for left DLPFC activation in the non-anxious group. Additionally, trait anxiety scores were positively correlated with left DLPFC activity but negatively correlated with left FPl activity across groups. Furthermore, we found a context-specific connectivity shift between the subgenual anterior cingulate cortex (sgACC) with the FPl and DLPFC specifically in highly anxious individuals.
Conclusion: The results partially confirmed the anxiety-related shift as reported by Bramson and colleagues across paradigms and samples. The findings provide further support for the functional shift in anxiety and can inform target-based interventions of persistent emotional control deficits in anxiety disorders.
Background: Spinocerebellar ataxia type 3 (SCA3) is a hereditary disease characterized by cerebellar atrophy and motor dysfunction. Patients also exhibit non-ataxic symptoms such as cognitive impairment. While prior neuroimaging studies have identified multiple cognition-associated brain regions in SCA3 patients, research on Papez circuit structural damage (e.g., mammillary bodies (MBs)) remains sparse. Advancements in 7T magnetic resonance imaging (MRI) technology have enabled scanning and quantitative analysis of structures such as the MBs within the Papez circuit. In this study, we investigated the relationship between cognitive impairment in patients with SCA3 and structural changes in the three Papez circuit structures: the MBs, the mammillothalamic tract (MTT), and the post-commissural fornix (PF).
Methods: This cross-sectional study included 46 SCA3 patients and 48 healthy controls undergoing 7T MRI and neuropsychological assessments. Using manual delineation and a deep learning model, we extracted the MB, MTT, and PF volumes from participants. Subsequently, we statistically analyzed the quantitative data.
Results: SCA3 patients exhibited reduced MB, PF, and MTT volumes compared with those of the healthy controls. The MB, left MTT, and left PF volumes were significantly lower in cognitive impairment than in cognitive preserved. Cognitive function in SCA3 patients was positively correlated with the MB, left MTT, and left PF, whereas motor function was negatively correlated with the MB and left PF.
Conclusion: Decreased cognitive and memory function in SCA3 patients is associated with MB, MTT, and PF alterations and is more pronounced on the left side. Motor dysfunction may be correlated with cognitive impairment development.
Ex vivo magnetic resonance imaging (MRI) has revolutionized psychoradiological research by enabling detailed structural and pathological assessments of the brain in conditions ranging from psychiatric disorders to neurodegenerative diseases. By providing high-resolution images of postmortem brain tissue, ex vivo MRI overcomes several limitations inherent in in vivo imaging, offering unparalleled insights into the underlying pathophysiology of mental disorders. This review critically summarizes the state-of-the-art ex vivo MRI methodologies for neuroanatomical mapping and pathological characterization in psychoradiology, while also establishing standardized specimen processing protocols. Furthermore, we explore the prospects of application in ex vivo MRI in schizophrenia, major depressive disorder and bipolar disorder, highlighting its role in understanding neuroanatomical alterations, disease progression, and the validation of in vivo neuroimaging biomarkers.
Mobile psychophysiological technologies, such as portable eye tracking, electroencephalography, and functional near-infrared spectroscopy, are advancing ecologically valid findings in cognitive and educational neuroscience research. Staying informed on the field's current status and main themes requires continuous updates. Here, we conducted a bibliometric and text-based content analysis on 135 articles from Web of Science, specifically parsing publication trends, identifying prolific journals, authors, institutions, and countries, along with influential articles, and visualizing the characteristics of cooperation among authors, institutions, and countries. Using a keyword co-occurrence analysis, five clusters of research trends were identified: (i) cognitive and emotional processes, intelligent education, and motor learning; (ii) professional vision and collaborative learning; (iii) face-to-face social learning and real classroom learning; (iv) cognitive load and spatial learning; and (v) virtual reality-based learning, child learning, and technology-assisted special education. These trends illustrate a consistent growth in the use of portable technologies in education over the past 20 years and an emerging shift towards “naturalistic” approaches, with keywords such as “face-to-face” and “real-world” gaining prominence. These observations underscore the need to further generalize the current research to real-world classroom settings and call for interdisciplinary collaboration between researchers and educators. Also, combining multimodal technologies and conducting longitudinal studies will be essential for a comprehensive understanding of teaching and learning processes.
Background: Rumination is a pivotal psychopathological process in major depressive disorder (MDD). The neurotrophic hypothesis suggests that glial cell line-derived neurotrophic factor (GDNF) might play a role in brain dysfunction and clinical symptoms of MDD. However, the relationship remains unclear.
Methods: Thirty-three individuals with MDD and 33 healthy controls (HCs) underwent functional magnetic resonance imaging (fMRI) while performing a rumination state task designed to induce sustained, active rumination. The Ruminative Response Scale (RRS) was administered to assess individual rumination tendency. Brain activity within the default mode network (DMN) subsystems during rumination was characterized using both fractional amplitude of low-frequency fluctuations (fALFF) and functional connectivity (FC) analyses. Serum levels of GDNF and inflammatory markers [interleukin (IL)-6, IL-8, and C-reactive protein] were quantified in all participants. We then examined the relationships between regional brain activity (fALFF values), GDNF levels, and rumination severity (RRS scores) in the MDD group.
Results: Compared to HCs, MDD patients exhibited significantly reduced serum levels of both GDNF (t = −3.204, P = 0.002) and IL-8 (t = −3.239, P = 0.002). Significant interaction effects were observed in fALFF within both the dorsal medial prefrontal cortex (DMPFC; F = 25.075, P < 0.001) and medial temporal lobe (MTL; F = 28.753, P < 0.001) subsystems of the DMN. Mediation analysis revealed that the relationship between GDNF levels and brooding rumination in MDD patients was mediated by neural activity within the DMPFC subsystem.
Conclusions: In MDD patients, GDNF levels were associated with neural activity within the DMPFC subsystem of the DMN, which statistically mediated the link to rumination severity.
Background: We aimed to evaluate the relationship between cerebral white matter quantitative anomalies and postoperative clinical outcomes in patients with drug-resistant epilepsies.
Methods: Automatic fiber quantification methodology was used to determine the diffusional anomalies in cerebral white matter tracts, from eight patients with frontal lobe epilepsy (FLE) and 12 with temporal lobe epilepsy (TLE) candidates and/or undergoing epilepsy surgery. We studied the fractional anisotropy (FA), mean diffusivity (MD), volume (Vol), and number of fibers (Fib) of white matter tracts related to the physiopathologic mechanism of these epilepsies. The information was compared with that obtained from 19 healthy controls and between patients with seizure freedom and those with seizure recurrence 1 year after epilepsy surgery.
Results: Significant pre- and postsurgical global and segmental abnormalities were characterized by increased MD and decreased FA, Vol, and Fib in tracts from both hemispheres. TLE patients with postsurgical seizure freedom had preoperative increased global MD of the contralateral inferior longitudinal fasciculus and uncinate fasciculus. Furthermore, drug-resistant epilepsy patients with seizure freedom had a presurgical segmental increased MD in the contralateral thalamic radiation. Additionally, FLE patients with seizure freedom exhibited postsurgical increases in the Fib of the ipsilateral thalamic radiation and contralateral inferior longitudinal fasciculus. Furthermore, temporal lobe epilepsy patients with seizure freedom had a postsurgical lower global MD in the ipsilateral inferior fronto-occipital fasciculus.
Conclusions: Patients with drug-resistant epilepsies have global and segmental quantitative white matter tract anomalies, which suggests cerebral neural involvement in this disease. These abnormalities can vary regarding the postsurgical clinical outcome.
Professor Jeffrey Bishop from the University of Minnesota and Professor Konasale Prasad from the University of Pittsburgh were invited to attend the ISMRM-Endorsed Workshop on MR for Psychiatry in Chengdu, China, from 20 to 22 July 2024. Professor Bishop and Professor Prasad delivered lectures on the molecular and neuro-mechanism of schizophrenia respectively during the session titled “Exploring Schizophrenia with MRI” on the morning of 21 July. Their presentations were met with great enthusiasm and sparked lively discussions among the participants. Following the conference, the Psychoradiology journal interviewed Professors Prasad and Bishop. In the interview, they narrated their personal journeys into the research field and unanimously agreed that psychoradiological techniques have brought a revolutionary change in the characterization of phenotypes with potential future implications for facilitating diagnosis, prognosis, and treatment strategies of mental disorders. They also noted that the field is now facing technological challenges and resource constraints, and that defining mental illnesses biologically and achieving precision treatment will be significant opportunities and challenges in the future. They highlighted the importance of interdisciplinary collaboration, believing it fosters in-depth dialogue across various domains. Additionally, they encouraged young researchers to maintain perseverance and patience in the long run of scientific research, aligning their goals effectively with practice.
Background: Suicide has profound effects on individuals, families, and societies globally, underscoring the urgent need for effective early detection and prevention strategies. This systematic review aims to investigate the use of event-related potentials (ERPs) as a tool for identifying and monitoring suicide risk.
Methods: A comprehensive literature search was conducted, resulting in the inclusion of 23 articles that met the eligibility criteria. The review synthesized findings related to various ERP components associated with suicide risk.
Results: The analysis revealed that individuals with a history of suicide risk exhibited significantly reduced P3 amplitudes in response to novel stimuli during the go/no-go paradigm compared to healthy controls [standardized mean difference (SMD) = −0.53, 95% confidence interval (CI) = [−0.96; −0.10]]. Additionally, altered P3 responses to positive feedback on rewards indicated impairments in those at risk (SMD = −1.12, 95% CI = [−1.74; −0.49]). Variability in other ERP components was also highlighted, with several moderators, such as sample characteristics and methodological design, influencing ERP components.
Conclusion: The findings suggest that specific ERP components, particularly the P3, may serve as valuable indicators for assessing suicide risk. The review emphasizes the need for future research to utilize larger, more homogeneous samples and advanced analytical techniques to enhance detection accuracy. The application of ERPs is posited as a promising avenue for improving understanding of the neurocognitive mechanisms associated with suicide risk and enhancing prevention efforts.
Healthcare systems require the efficient development of expert performance. Several studies have explored the cognitive foundations of medical expert performance, especially in radiology. Studying at the brain level could provide further insight into specific mechanisms mediating medical expert performance. Researchers have recently begun to systematically employ neuroimaging in this field. Most studies focus on specific specializations rather than identifying shared neural substrates across disciplines. This systematic review and activation likelihood estimation (ALE) meta-analysis followed the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) guidelines. A total of 297 studies examining neural correlates were identified by comparing expert and novice medical performance. After screening, 22 studies were included in the final analysis. For studies reporting three-dimensional coordinates, ALE meta-analysis revealed consistent involvement of the medial frontal lobe, including the superior frontal gyrus, dorsomedial and ventromedial prefrontal cortex, and inferior frontal and fusiform gyri. Radiology-specific analyses highlighted activation in the ventromedial prefrontal cortex, the left pre-supplementary motor area (pre-SMA), along with the fusiform and opercular inferior frontal gyri. Internal medicine-based studies highlighted involvement of the SMA, inferior frontal gyrus, and dorsomedial prefrontal cortex. Our results revealed involvement, at different levels, of the medial frontal cortex, including the SMA and superior and inferior frontal gyri, which is part of the network relevant for inhibitory control and decision-making. The development of decision-making during the diagnostic process is relevant for the training of future professionals.
Chemotherapy-induced cognitive impairment (CICI), commonly known as “chemo brain,” affects a significant proportion of cancer survivors, manifesting as memory deficits, reduced attention, and impaired executive function. Conventional pharmacological treatments offer limited efficacy, prompting interest in complementary, non-invasive interventions. Yoga nidra (YN), a structured form of guided yogic relaxation, has demonstrated potential benefits for neurocognitive and emotional regulation. Grounded in ancient Indian traditions and increasingly supported by modern neuroscientific findings, YN appears to influence brainwave activity, autonomic function, and stress-related biomarker mechanisms implicated in the pathophysiology of CICI. This perspective review explores the emerging role of YN in managing chemo brain, integrating insights from neuroimaging, cognitive neuroscience, and psychophysiology. Drawing on peer-reviewed literature from PubMed- and Scopus-indexed sources, the article highlights the need for further research, including functional imaging and biomarker-based studies, to elucidate its therapeutic mechanisms. The findings underscore YN's potential as an adjunctive tool within integrative oncology and neurorehabilitation frameworks.
Background: Altered connectivity patterns in socio-emotional brain networks are characteristic of individuals with autism spectrum disorder. Despite recent research on intranasal oxytocin's modulation effects of network topology in autism, its specific effects on the functional connectivity network topology remain underexplored.
Methods: To address this gap, we conducted an exploratory data-driven study employing a dimensional approach using data from a large cohort of 250 neurotypical adult male subjects with either high or low autistic traits and who had administered 24 IU of intranasal oxytocin or placebo in a randomized, controlled, double-blind design. Resting-state functional connectivity data were analyzed using network-based statistical methods and graph theoretical approaches.
Results: The findings from treatment × autistic trait group interactions revealed significantly different effects of oxytocin in local (cluster coefficient, efficiency, nodal path length, degree and betweenness centrality) but not global graph metrics in individuals with higher autistic traits compared to those with lower ones, across multiple brain regions. Changes across multiple measures were found in the motor, auditory/language, visual, default mode and socio-emotional processing networks, all of which are influenced in autism spectrum disorder.
Conclusion: Overall, findings from this dimensional approach demonstrate that oxytocin particularly targets widespread enhancement of local but not global neural network processing parameters in neurotypical individuals with higher autistic traits. This suggests that intranasal oxytocin may represent a therapeutic option for social, emotional and sensorimotor symptoms in individuals with autism spectrum disorder by modulating local integration within brain regions involved in their regulation.
Background: Despite advances in understanding the effective connectivity (EC) of brain networks in leucine-rich glioma-inactivated 1 (LGI1) antibody encephalitis, the specific cause and underlying mechanisms of LGI1 encephalitis remain unclear.
Materials and methods: The study included 27 patients with anti-LGI1 encephalitis and 28 age- and sex-matched normal controls. Amplitude of low-frequency fluctuation (ALFF) analysis identified altered brain regions. Spectral dynamic causal modeling (spDCM) then assessed EC between these regions. Relationships between EC strength and both clinical severity and cognitive function were analyzed.
Results: Distinct EC patterns were found in patients versus controls. Specifically, inhibitory EC was observed from the hippocampus to the superior temporal gyrus, while excitatory EC was noted in the reverse direction. Patients also showed reduced inhibitory self-connections in the posterior cingulate cortex. Crucially, inhibitory EC from the right hippocampus to the left superior temporal gyrus correlated inversely with symptom severity and positively with cognitive performance. Conversely, reduced inhibitory self-connections in the posterior cingulate cortex correlated positively with symptom severity and negatively with cognitive function.
Conclusions: These findings indicate that changes in causal connections between specific brain regions significantly contribute to neurological deficits in anti-LGI1 encephalitis. The inhibitory connectivity from the hippocampus to the superior temporal gyrus may serve as a potential biomarker for personalized diagnosis, offering new insights into the underlying pathological mechanisms of this disorder.
Background: Suicide attempts (SA) and non-suicidal self-injury (NSSI) are serious public health problems that frequently co-occur in adolescents females with major depressive disorder (MDD), yet their neurobiological distinctions remain unclear. Here, we sought to explore female adolescents’ neural mechanisms via the local gyrification index (LGI) and resting-state functional connectivity (RS-FC) analysis.
Methods: We compared scale scores, LGI, and seed-based RS-FC among three groups of female adolescents: MDD with both NSSI and SA (SA + NSSI, n = 43), MDD with NSSI only (NSSI, n = 28), and healthy controls (HC, n = 27). Exploratory correlation analysis was applied to examine associations between the neuroimaging alterations and clinical symptom severity in depressed adolescents with SA and NSSI.
Results: Compared with the HC group, both SA + NSSI and NSSI groups showed significantly decreased LGI in the prefrontal cortex, including right rostral/caudal middle frontal gyrus (MFG), precentral gyrus and postcentral gyrus (po-CG.R), as well as left rostral MFG, precentral gyrus and opercular part of the inferior frontal gyrus. The brain regions with altered RS-FC (seeds based on po-CG.R and the rostral MFG.L) are mainly distributed in the anterior cingulate cortex, insula, postcentral gyrus, and occipital lobe (P < 0.05, FDR correction). Moreover, exploratory correlation analysis suggested no statistically significant correlations after FDR correction (α = 0.05).
Conclusion: Reduced cortical folding in postcentral and middle frontal gyri was found in both patient groups, alongside distinct functional connectivity, offering deeper neurobiological insights into SA and NSSI.
Magnetic resonance imaging (MRI) biomarkers have shown considerable potential in elucidating the neurobiological underpinnings of major depressive disorder (MDD). However, clinical translation of these biomarkers remains limited due to reliance on group-level analyses, which fail to capture the individual variability inherent in MDD. Precision psychiatry, which advocates for individualized approaches, offers a framework that could enhance the clinical utility of MRI biomarkers across multiple domains, including diagnostic classification, treatment response prediction, and individualized interventions. Despite this potential, current research applying MRI biomarkers to MDD within the framework of precision psychiatry remains fragmented, lacking an integrated clinical system that seamlessly combines these components. This review introduces the concept of a closed-loop clinical system, emphasizing the integration of diagnostic classification, treatment response prediction, and individualized interventions into a unified approach at the individual patient level. We summarize recent advances in these three clinical domains, highlight existing fragmentation, and discuss the challenges of achieving a cohesive system. Finally, we propose that the integration of MRI biomarkers into a closed-loop clinical system, as envisioned by precision psychiatry, holds great promise for the individualized management of MDD, improving clinical outcomes from diagnosis through recovery.
Autism spectrum disorder (ASD) is a common neurodevelopmental disorder marked by significant deficits in social interaction and restricted repetitive behaviors. Despite rigorous research efforts, the early and effective diagnosis and intervention of ASD remain challenging, due primarily to its considerable heterogeneity and complex neurobiological underpinnings. Traditional neuroimaging techniques have largely focused on individual brain responses to social stimuli, often overlooking the critical interactive dynamics that contribute to social impairments in individuals with ASD. This review explored hyperscanning, an innovative neuroimaging approach that features simultaneous recording of brain activity across multiple individuals, to enhance our understanding of the neural mechanisms underlying social difficulties in ASD. By searching published articles conducted between 2000 and 2024, we found eight empirical studies conducted between 2012 and 2024, which employed various brain imaging techniques. We analyzed and summarized participant demographics, experimental designs, and key outcomes, with a particular focus on inter-brain synchrony (IBS) as a measure of social engagement and the quality of interpersonal interactions. Our review identified specific patterns of neural synchrony that correlate with the severity of ASD symptoms. Furthermore, we critically evaluated the limitations of current studies and proposed future research directions, highlighting the need for more nuanced hyperscanning methodologies. Such advancements could significantly deepen our understanding of social impairments in ASD and inform targeted intervention strategies. This comprehensive review aimed to assess the potential of hyperscanning techniques to propel progress in ASD research and intervention, ultimately contributing to more effective clinical practices.
Background: Molecular imaging plays a key role in advancing understanding of neuropsychiatric disorders. However, the conceptual structure of this interdisciplinary field remains poorly mapped from a bibliometric perspective. The objective of this study was to explore the intellectual structure and thematic development of research on molecular imaging applied to neuropsychiatric disorders using co-citation network analysis.
Methods: A bibliometric co-citation analysis was conducted using data retrieved from Scopus. A targeted search strategy identified articles from 2014 to 2023 focused on MRS, fMRI, PET, and SPECT in the context of neuropsychiatric disorders. Bibliographic data were exported, and cited references were analyzed using VOSviewer. A manually curated thesaurus was applied to unify variant citations and reduce duplication. Co-citation networks were generated, and thematic clusters were identified and interpreted based on total link strength and citation density.
Results: The co-citation network included 51 documents and revealed six major thematic clusters encompassing automated anatomical labeling and brain segmentation, functional and structural connectivity, affective neuroscience, clinical biomarkers, and methodological standardization. Notable references included foundational works on resting-state functional connectivity, motion correction, and diagnostic criteria for neuropsychiatric disorders. The clustering structure highlighted the convergence of radiology, neuroscience, and psychiatry around shared methodological tools and conceptual frameworks.
Conclusion: Co-citation analysis revealed a well-defined and maturing intellectual landscape in molecular imaging applied to neuropsychiatry. The identified clusters represent distinct yet interconnected research lines, reflecting methodological innovation and translational potential. These findings offer a roadmap for future research, emphasizing methodological rigor, interdisciplinary collaboration, and clinical applicability.
Background: The thalamo-prefrontal white matter (WM) pathway, a core structural element of the frontal-limbic system disrupted in premenstrual syndrome (PMS), remains poorly understood.
Methods: Diffusion tensor imaging (DTI), functional MRI (fMRI), and serum cytokine levels were collected from 41 PMS participants and 51 healthy controls (HCs), all diagnosed using the Daily Record of Severity of Problems (DRSP) scale. Bilateral thalamic-frontal WM pathways—the anterior thalamic radiations (ATRs)—were reconstructed using probabilistic fiber tracking. Two-sample tests examined group differences in fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), and amplitude of low-frequency fluctuation (ALFF) within bilateral ATRs. Spearman correlations assessed associations among these MRI metrics, inflammatory cytokines, and DRSP scores. Machine learning models further evaluated the diagnostic and predictive utility of left ATR features combined with inflammatory cytokines.
Results: Compared to HCs, PMS patients exhibited increased MD, AD, RD, and ALFF values in the left ATR, as well as elevated tumor necrosis factor (TNF)-α levels. Correlation analysis revealed that these MRI alterations in the left ATR and TNF-α levels were linked to DRSP scores. Additionally, the machine learning models constructed using the optimal feature subset, involved in MD, AD and ALFF of left ATR as well as TNF-α, demonstrated robust performance in diagnosing PMS and predicting DRSP scores.
Conclusion: These findings suggest altered thalamo-frontal WM connectivity and elevated TNF-α in PMS. The left ATR may serve as a biomarker of PMS neuro-mechanisms when combined with multi-MRI and inflammation metrics.
In contemporary neuroscience, mapping the human brain’s functional connectomes is essential to understanding its functional organization. Functional organizations in the brain gray matter have been the subject of previous research, but the functional information in white matter (WM), the other half of the brain, has been relatively underexplored. However, the dynamics of functional magnetic resonance imaging (fMRI) have been reliably identified in the brain WM. This review summarizes current knowledge about task-free (resting-state) fMRI neuroimaging analyses for the WM functional connectome. We present comparative findings of the WM functional connectome, including its mapping, physiological underpinnings, cognitive neuroscience relationships, and clinical applications. Furthermore, we explore the emerging consensus that WM functional networks have valid topological characteristics that can distinguish between individuals with brain diseases and healthy controls, predict general intelligence, and identify inter-subject variabilities. Lastly, we emphasize the need for further studies and the limitations, challenges, and future directions for the WM functional connectome. An overview of these developments could lead to new directions for cognitive neuroscience and clinical neuropsychiatry.
Background: Accumulating evidence indicates that COVID-19 may cause neurological complications detectable on brain imaging. Yet, the overall prevalence, modality-specific characteristics, and clinical implications of these neuroimaging abnormalities have not been systematically summarized through comprehensive quantitative synthesis.
Methods: We searched the PubMed, Web of Science, Scopus, Embase, Cochrane Library, and China National Knowledge Infrastructure (CNKI) databases, and Wanfang for original articles published up to August 5, 2025. The pooled proportions of brain-imaging findings on computed tomography (CT), magnetic resonance imaging (MRI), and electroencephalography (EEG), including hemorrhage, microbleeds, ischemia, stroke, encephalitis, background activity abnormality, periodic or rhythmic activity, and epileptiform discharge, were estimated using a random-effects model. This study was conducted according to PRISMA guidelines.
Results: Eighty-three eligible studies that included 9466 COVID-19 patients were included in the meta-analysis. Pooled results from 27 studies, including 3081 patients, showed that more than two-fifths (42.60%) of patients who underwent CT/MRI had objective brain abnormalities. The most frequently reported abnormalities on CT/MRI were changes in white matter and non-specific stroke. Twenty-five EEG studies, including 1273 patients, reported epileptiform discharges in one-fifth (20.54%) of cases. The systematic review of long-term brain imaging manifestations in COVID-19 survivors also found common changes in brain microstructure and function.
Conclusion: While these findings offer insights into the potential pathological mechanisms of neuroimaging abnormalities in COVID-19 patients, the high heterogeneity and variability across studies highlight the need for cautious interpretation. It will be necessary to conduct large-scale longitudinal studies with extended follow-up periods in order to validate these neuroimaging findings and clarify the long-term neuropsychiatric consequences of COVID-19.
Although the glymphatic system has been extensively investigated in neurodegenerative diseases, its potential role in psychiatric disorders is only beginning to be recognized. Conditions such as major depressive disorder, schizophrenia, and bipolar disorder frequently exhibit physiological disturbances, including disrupted sleep, neuroinflammation, vascular impairment, and altered astrocytic function, that may modulate glymphatic transport. Recent neuroimaging studies have started to explore these associations. Structural magnetic resonance imaging (MRI) has been used to quantify perivascular space enlargement in depression and schizophrenia. Diffusion-based approaches, including low-b-value diffusion and the diffusion tensor image analysis along the perivascular space (DTI-ALPS) index, have been used to estimate perivascular diffusivity, with some studies linking these measures to symptom severity. Functional MRI metrics such as blood oxygen level-dependent-cerebrospinal fluid (BOLD-CSF) coupling have provided indirect markers of CSF pulsatility, revealing associations with sleep quality and cognition. Positron emission tomography (PET) has been investigated for assessing CSF tracer dynamics and targeting neuroinflammation. While these imaging results are promising, they are often indirect, methodologically heterogeneous, and derived from small samples. This review examines current evidence on glymphatic alterations in psychiatric conditions, describes shared and disorder-specific mechanisms, and assesses how complementary MRI and PET approaches can provide a more integrated understanding of glymphatic function. It also addresses methodological challenges, identifies research gaps, and discusses opportunities to incorporate glymphatic imaging into psychiatric diagnostics, prognosis, and treatment monitoring. The article is intended for researchers and clinicians in psychiatry, neurology, and neuroimaging who are interested in the translational potential of glymphatic research.