Functional Brain Abnormalities Research Articles

Targeting the Manifestations of Subclinical and Overt Hypothyroidism Within the Hippocampus.

The past decade has witnessed a surge of articles describing the neurocognitive sequelae and associated structural and functional brain abnormalities of patients with overt hypothyroidism (OH) and subclinical hypothyroidism (SCH). Findings show effects primarily within the frontal lobes with usually worse outcomes for OH than SCH. Several recent studies have also indicated hypothyroid patients may have smaller hippocampi, a key structure for memory. The JCEM paper by Zhang and colleagues applies 2 novel approaches for analyzing hippocampal structure and function. One uses an automated processing tool that segments the hippocampus into distinct subregions, and the other performs connectivity analysis to assess the relationships between specific hippocampal subregions and cortical areas. Relatively large samples of OH and SCH patients and healthy controls received a test of global cognitive functioning and underwent structural and functional magnetic resonance imaging. Results showed hypothyroid groups scored significantly below controls on the memory scale and also had smaller hippocampal volumes in selective subregions. Effects were stronger for SCH than OH groups, who also showed different patterns of interconnectivity between hippocampal subregions and specific frontal lobe areas. To make sense of these findings, I explored the rodent and human literatures on thyroid hormone's role in hippocampal functioning and on hippocampal subfields and their purported functions and interconnections. Because current results suggest SCH may represent a distinct clinical entity with unique brain manifestations, I hypothesized 2 explanations for these findings, one involving transporter defects in the brain barriers and the other, differential neurodegeneration of the blood-brain barrier vascular unit.

The impact of illness duration on brain activity in goal-directed and habit-learning systems in obsessive-compulsive disorder progression: A resting-state functional imaging study

It is increasingly evident that structural and functional changes in brain regions associated with obsessive–compulsive disorder (OCD) are often related to the development of the disease. However, limited research has been conducted on how the progression of OCD may lead to an imbalance between goal-directed and habit-learning systems. This study employs resting-state functional imaging to examine the relationship between illness duration and abnormal brain function in goal-directed/habitual-learning systems. Demographic, clinical, and multimodal fMRI data were collected from participants. Our findings suggest that, compared to healthy controls, individuals with OCD exhibit abnormal brain functional indicators in both goal-directed and habit-learning brain regions, with a more pronounced reduction observed in the goal-directed regions. Additionally, abnormal brain activity is associated with illness duration, and the abnormalities observed in goal-directed regions are more effective in distinguishing different courses of OCD patients. Patients with different durations of OCD have functional abnormalities in the goal-directed and habitual-learning brain regions. There are differences in the degree of abnormality in different brain regions, and these abnormalities may disrupt the balance between goal-directed and habitual-learning systems, leading to increasing reliance on repetitive behaviors.

Altered Intrinsic Brain Activity in Ischemic Stroke Patients Assessed Using the Percent Amplitude of a Fluctuation Method.

Ischemic stroke is a vascular disease that may cause cognitive and behavioral abnormalities. This study aims to assess abnormal brain function in ischemic stroke patients using the percent amplitude of fluctuation (PerAF) method and further explore the feasibility of PerAF as an imaging biomarker for investigating ischemic stroke pathophysiology mechanisms. Sixteen ischemic stroke patients and 22 healthy controls (HCs) underwent resting state functional magnetic resonance imaging (rs-fMRI) scanning, and the resulting data were analyzed using PerAF. Then a correlation analysis was conducted between PerAF values and Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores. Finally, the abnormal PerAF values were extracted and defined as features for support vector machine (SVM) analysis. Compared with HCs, ischemic stroke patients showed decreased PerAF in the bilateral cuneus, left middle frontal gyrus, precuneus and right inferior temporal gyrus, and increased PerAF in the bilateral orbital part of middle frontal gyrus and right orbital part of superior frontal gyrus. Correlation analyses revealed that PerAF values in the left orbital part of middle frontal gyrus was negatively correlated with the MoCA scores. The SVM classification of the PerAF values achieved an area under the curve (AUC) of 0.98 and an accuracy of 94.74%. Abnormal brain function has been found among ischemic stroke patients, which may be correlated with visual impairment, attention deficits, and dysregulation of negative emotions following a stroke. Our findings may support the potential of PerAF as a sensitive biomarker for investigating the underlying mechanisms of ischemic stroke.

AutYOLO-ATT: an attention-based YOLOv8 algorithm for early autism diagnosis through facial expression recognition

Autism Spectrum Disorder (ASD) is a developmental condition resulting from abnormalities in brain structure and function, which can manifest as communication and social interaction difficulties. Conventional methods for diagnosing ASD may not be effective in the early stages of the disorder. Hence, early diagnosis is crucial to improving the patient's overall health and well-being. One alternative and effective method for early autism diagnosis is facial expression recognition since autistic children typically exhibit distinct facial expressions that can aid in distinguishing them from other children. This paper provides a deep convolutional neural network (DCNN)-based real-time emotion recognition system for autistic kids. The proposed system is designed to identify six facial emotions, including surprise, delight, sadness, fear, joy, and natural, and to assist medical professionals and families in recognizing facial expressions in autistic children for early diagnosis and intervention. In this study, an attention-based YOLOv8 (AutYOLO-ATT) algorithm for facial expression recognition is proposed, which enhances the YOLOv8 model's performance by integrating an attention mechanism. The proposed method (AutYOLO-ATT) outperforms all other classifiers in all metrics, achieving a precision of 93.97%, recall of 97.5%, F1-score of 92.99%, and accuracy of 97.2%. These results highlight the potential of the proposed method for real-world applications, particularly in fields where high accuracy is essential.

Brain Function and Marijuana: Are there Changes after Abstinence of Consumption? Preliminary Results.

The legalization of cannabis use and false claims about the plant Cannabis sativa to be considered a pharmaceutical product have been found to increase consumption, lower risk perception, and lead to more health problems, without reducing criminal activity. Brain function, typically assessed by neuropsychological tests, shows abnormalities with acute marijuana use, but inconsistent results have been published after abstinence, with a maximum follow-up of 28 days. Our previous research, using neuropsychological tests and brain perfusion single photon emission computed tomography (neuroSPECT), demonstrated consistent abnormalities in brain function among schoolchildren who consume marijuana compared to their non-consuming peers. The aim of this study is to investigate whether brain function changes in 20 adult marijuana users after 6 months of abstinence. Comparison of neuropsychological tests (Rey Complex Figure; Porteus Maze; Four subtests of WAIS-IV Intellectual Tests; STROOP; D2) and perfusion neuroSPECT (functional images), obtained in relation to recent consumption and after 6 months of serial drug-screening test confirmed abstinence. In a one-year period (2020-2021) only five compliant participants were recruited. The COVID-19 pandemic was a limiting factor. Preliminary results of neuropsychological tests, functional brain perfusion images and limited statistical analysis are presented. The results of the neuropsychological tests of the three subjects who completed the abstinence period so far show some improvement in working memory and attention after abstinence. NeuroSPECT shows disorganized hypoperfusion of variable severity in relation to recent consumption, involving areas associated with cognitive function such as the posterior cingulate and temporal lobes, in our five initially enrolled patients, when compared to a normal database. Of these, only two participants have already been re-evaluated with neuroSPECT after 6 months of abstinence, one of whom showed some improvement on the post-abstinence images. We analyze the methodological challenges of this research, including the pandemic, to incorporate the appropriate corrections in the next phase of our investigation. Our final findings may provide clinicians and users with information about the long-term effects of marijuana use on brain function.

Withdrawn: The altered dynamic community structure for adaptive adjustment in stroke patients with multidomain cognitive impairments: A multilayer network analysis

BackgroundInternal capsule strokes can lead to multidomain cognitive impairments, and while the brain showcases adaptability post-stroke, the interplay between this adaptability and multidomain cognitive function remains elusive. In addition, although most studies indicate that adaptive changes after stroke manifest as brain functional network abnormalities, the changes in dynamic topological features, especially dynamic community structure, required for adaptive adjustment in stroke patients are not yet clear. MethodsResting-state fMRI data were acquired from patients with infarct in left-sided (n = 46, CI_L) and right-sided (n = 45, CI_R) internal capsule and 81 healthy controls (HC). Dynamic network matrices were generated using a sliding-window approach. These matrices were partitioned into communities utilizing a multilayer community detection algorithm. The network switching rate were employed as a key metric to characterize the differences of dynamic community structure between stroke and HC groups, and the correlations between these significant intergroup differences and cognitive performance scores was calculated. ResultsCompared to HC, CI_L patients exhibited an increase in network switching rates across all networks in the whole brain. However, these increases were largely unbeneficial for cognitive recovery; CI_R group show a more limited range of increased network switching rates and a more limited negative correlations with cognitive performance. ConclusionsThis study elucidates that following a stroke, the brain continuously adapts its dynamic community structure in an effort to address multidomain cognitive impairments, but this adaptation is often ineffective, unorganized, and disordered. Moreover, these findings elucidate the lateralized effects of stroke lesions on dynamic reorganization.

Topological Organization of the Brain Network in Patients with Primary Angle-closure Glaucoma Through Graph Theory Analysis.

Primary angle-closure glaucoma (PACG) is a sight-threatening eye condition that leads to irreversible blindness. While past neuroimaging research has identified abnormal brain function in PACG patients, the relationship between PACG and alterations in brain functional networks has yet to be explored. This study seeks to examine the influence of PACG on brain networks, aiming to advance knowledge of its neurobiological processes for better diagnostic and therapeutic approaches utilizing graph theory analysis. A cohort of 44 primary angle-closure glaucoma (PACG) patients and 44 healthy controls participated in this study. Functional brain networks were constructed using fMRI data and the Automated Anatomical Labeling 90 template. Subsequently, graph theory analysis was employed to evaluate global metrics, nodal metrics, modular organization, and network-based statistics (NBS), enabling a comparative analysis between PACG patients and the control group. The analysis of global metrics, including small-worldness and network efficiency, did not exhibit significant differences between the two groups. However, PACG patients displayed elevated nodal metrics, such as centrality and efficiency, in the left frontal superior medial, right frontal superior medial, and right posterior central brain regions, along with reduced values in the right temporal superior gyrus region compared to healthy controls. Furthermore, Module 5 showed notable disparities in intra-module connectivity, while Module 1 demonstrated substantial differences in inter-module connectivity with both Module 7 and Module 8. Noteworthy, the NBS analysis unveiled a significantly altered network when comparing the PACG and healthy control groups. The study proposes that PACG patients demonstrate variations in nodal metrics and modularity within functional brain networks, particularly affecting the prefrontal, occipital, and temporal lobes, along with cerebellar regions. However, an analysis of global metrics suggests that the overall connectivity patterns of the entire brain network remain unaltered in PACG patients. These results have the potential to serve as early diagnostic and differential markers for PACG, and interventions focusing on brain regions with high degree centrality and nodal efficiency could aid in optimizing therapeutic approaches.

Brain structural and functional abnormalities associated with acute post-traumatic headache: iron deposition and functional connectivity

BackgroundThe purpose of this study was to interrogate brain iron accumulation in participants with acute post-traumatic headache (PTH) due to mild traumatic brain injury (mTBI), and to determine if functional connectivity is affected in areas with iron accumulation. We aimed to examine the correlations between iron accumulation and headache frequency, post-concussion symptom severity, number of mTBIs, and time since most recent TBI.MethodsSixty participants with acute PTH and 60 age-matched healthy controls (HC) underwent 3T magnetic resonance imaging including quantitative T2* maps and resting-state functional connectivity imaging. Between group T2* differences were determined using T-tests (p < 0.005, cluster size threshold of 90 voxels). For regions with T2* differences, two analyses were conducted. First, the correlations with clinical variables including headache frequency, number of lifetime mTBIs, time since most recent mTBI, and Sport Concussion Assessment Tool (SCAT) symptom severity scale scores were investigated using linear regression. Second, the functional connectivity of these regions with the rest of the brain was examined (significance of p < 0.05 with family wise error correction for multiple comparisons).ResultsThe acute PTH group consisted of 60 participants (22 male, 38 female) with average age of 42 ± 14 years. The HC group consisted of 60 age-matched controls (17 male, 43 female, average age of 42 ± 13). PTH participants had lower T2* values compared to HC in the left posterior cingulate and the bilateral cuneus. Stronger functional connectivity was observed between bilateral cuneus and right cerebellar areas in PTH compared to HC. Within the PTH group, linear regression showed negative associations of T2* in the left posterior cingulate with SCAT symptom severity score (p = 0.05) and T2* in the left cuneus with headache frequency (p = 0.04).ConclusionsIron accumulation in posterior cingulate and cuneus was observed in those with acute PTH relative to HC; stronger functional connectivity was detected between the bilateral cuneus and the right cerebellum. The correlations of decreased T2* (suggesting higher iron content) with headache frequency and post mTBI symptom severity suggest that the iron accumulation that results from mTBI might reflect the severity of underlying mTBI pathophysiology and associate with post-mTBI symptom severity including PTH.

Repetitive Transcranial Magnetic Stimulation Reversing Abnormal Brain Function in Mood Disorders with Early Life Stress: from preclinical models to clinical applications

BackgroundEarly life stress (ELS) significantly increases the risk of mood disorders and affects the neurodevelopment of the primary cortex. HypothesisModulating the primary cortex through neural intervention can ameliorate the impact of ELS on brain development and consequently alleviate its effects on mood disorders. MethodWe induced the chronic unpredictable mild stress (CUMS) model in adolescent rats, followed by applying repetitive transcranial magnetic stimulation (rTMS) to their primary cortex in early adulthood. To assess the applicability of primary cortex rTMS in humans, we recruited individuals aged 17–25 with mood disorders who had experienced ELS and performed primary cortex rTMS on them. Functional magnetic resonance imaging (fMRI) and depression-related behavioral and clinical symptoms were conducted in both rats and human subjects before and after the rTMS. ResultsIn animals, fMRI analysis revealed increased activation in the primary cortex of CUMS rats and decrease subcortical activation. Following the intervention of primary cortex rTMS, the abnormal functional activity was reversed. Similarly, in mood disorders patients with ELS, increased activation in the primary cortex and decreased activation in the frontal cortex were observed. During rTMS intervention, similar neuroimaging improvements were noted, particularly decreased activation in the primary cortex. This suggests that targeted rTMS in the primary cortex can reverse the abnormal neuroimaging. ConclusionThis cross-species translational study has identified the primary cortex as a key region in mood disorders patients with ELS. Targeting the primary cortex with rTMS can correct abnormal functional activity while improving symptoms. Our study provides translational evidence for therapeutics targeting the ELS factor of mood disorders patients.

Advancements and Future Directions in Prevention Based on Evaluation for Individuals With Clinical High Risk of Psychosis: Insights From the SHARP Study.

This review examines the evolution and future prospects of prevention based on evaluation (PBE) for individuals at clinical high risk (CHR) of psychosis, drawing insights from the SHARP (Shanghai At Risk for Psychosis) study. It aims to assess the effectiveness of non-pharmacological interventions in preventing psychosis onset among CHR individuals. The review provides an overview of the developmental history of the SHARP study and its contributions to understanding the needs of CHR individuals. It explores the limitations of traditional antipsychotic approaches and introduces PBE as a promising framework for intervention. Three key interventions implemented by the SHARP team are discussed: nutritional supplementation based on niacin skin response blunting, precision transcranial magnetic stimulation targeting cognitive and brain functional abnormalities, and cognitive behavioral therapy for psychotic symptoms addressing symptomatology and impaired insight characteristics. Each intervention is evaluated within the context of PBE, emphasizing the potential for tailored approaches to CHR individuals. The review highlights the strengths and clinical applications of the discussed interventions, underscoring their potential to revolutionize preventive care for CHR individuals. It also provides insights into future directions for PBE in CHR populations, including efforts to expand evaluation techniques and enhance precision in interventions.

Alterations in spatiotemporal characteristics of dynamic networks in juvenile myoclonic epilepsy.

Juvenile myoclonic epilepsy (JME) is characterized by altered patterns of brain functional connectivity (FC). However, the nature and extent of alterations in the spatiotemporal characteristics of dynamic FC in JME patients remain elusive. Dynamic networks effectively encapsulate temporal variations in brain imaging data, offering insights into brain network abnormalities and contributing to our understanding of the seizure mechanisms and origins. Resting-state functional magnetic resonance imaging (rs-fMRI) data were procured from 37 JME patients and 37 healthy counterparts. Forty-seven network nodes were identified by group-independent component analysis (ICA) to construct the dynamic network. Ultimately, patients' and controls' spatiotemporal characteristics, encompassing temporal clustering and variability, were contrasted at the whole-brain, large-scale network, and regional levels. Our findings reveal a marked reduction in temporal clustering and an elevation in temporal variability in JME patients at the whole-brain echelon. Perturbations were notably pronounced in the default mode network (DMN) and visual network (VN) at the large-scale level. Nodes exhibiting anomalous were predominantly situated within the DMN and VN. Additionally, there was a significant correlation between the severity of JME symptoms and the temporal clustering of the VN. Our findings suggest that excessive temporal changes in brain FC may affect the temporal structure of dynamic brain networks, leading to disturbances in brain function in patients with JME. The DMN and VN play an important role in the dynamics of brain networks in patients, and their abnormal spatiotemporal properties may underlie abnormal brain function in patients with JME in the early stages of the disease.

Structural and functional brain alterations in subthreshold depression: A multimodal coordinate-based meta-analysis.

Imaging studies of subthreshold depression (StD) have reported structural and functional abnormalities in a variety of spatially diverse brain regions. However, there is no consensus among different studies. In the present study, we applied a multimodal meta-analytic approach, the Activation Likelihood Estimation (ALE), to test the hypothesis that StD exhibits spatially convergent structural and functional brain abnormalities compared to healthy controls. A total of 31 articles with 25 experiments were included, collectively representing 1001 subjects with StD. We found consistent differences between StD and healthy controls mainly in the left insula across studies with various neuroimaging methods. Further exploratory analyses found structural atrophy and decreased functional activities in the right pallidum and thalamus in StD, and abnormal spontaneous activity converged to the middle frontal gyrus. Coordinate-based meta-analysis found spatially convergent structural and functional impairments in StD. These findings provide novel insights for understanding the neural underpinnings of subthreshold depression and enlighten the potential targets for its early screening and therapeutic interventions in the future.

Brain functional magnetic resonance imaging in ICU patients who developed delirium

ObjectiveTo detect brain alterations in intensive care unit (ICU) patients who develop delirium using functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) and to determine their predictive value.MethodsFifty-two patients who were admitted to the ICU of the Affiliated Hospital of Zunyi Medical University between June 2021 and June 2022 were enrolled. Fifteen patients who were diagnosed with delirium by the Intensive Care Delirium Screening Checklist (ICDSC) after MRI were selected as the delirium group, and 15 healthy volunteers who were examined during the same period served as the control group. Both groups underwent fMRI and DTI. Quantitative fMRI and DTI data were compared between the two groups to detect abnormal structural and functional brain damage. The relationships between MRI outliers and clinical indicators in the delirium group were also assessed.ResultsDemographic characteristics and imaging indicators before delirium were not correlated with ICDSC scores after delirium. Compared with the healthy control group, the delirium group had significantly lower regional homogeneity (ReHo) values in the left caudate nucleus and frontal lobe on fMRI. The amplitude of the low-frequency fluctuations (ALFF) values of the delirium group were significantly increased in the hippocampus but significantly decreased in the frontal lobe. Compared with the healthy control group, the delirium group showed reduced mean diffusivity (MD) values, mainly in the right cerebellum and right middle temporal gyrus; reduced radial diffusivity (RD) values, mainly in the anterior cerebellum and right middle temporal gyrus; reduced fractional anisotropy (FA) values, only in the corpus callosum; and reduced axial diffusivity (AD) values, mainly in the anterior cerebellar lobe, right middle temporal gyrus, and left middle frontal gyrus on DTI. The statistical thresholds for quantitative DTI measurements were p &amp;lt; 0.005 at the voxel level and a cluster size &amp;gt; 5.ConclusionAbnormal resting-state brain activity in the left superior frontal gyrus and structural changes in the frontal lobe, temporal lobe, corpus callosum, hippocampus, and cerebellum were observed in ICU patients who developed delirium during hospitalization. Early-brain fMRI and DTI examinations are recommended for the prediction of delirium according to unique quantitative indicators to facilitate early intervention for critically ill patients, reduce the length of hospital stay, and improve patient prognosis.

Altered Functional Connectivity of Temporoparietal Lobe in Obstructive Sleep Apnea: A Resting-State fNIRS Study.

Obstructive Sleep Apnea (OSA), a sleep disorder with high prevalence, is normally accompanied by affective, autonomic, and cognitive abnormalities, and is deemed to be linked to functional brain alterations. To investigate alterations in brain functional connectivity properties in patients with OSA, a comparative analysis of global and local topological properties of brain networks was conducted between patients with OSA and healthy controls (HCs), utilizing functional near-infrared spectroscopy (fNIRS) imaging. A total of 148 patients with OSA and 150 healthy individuals were involved. Firstly, quantitative alterations in blood oxygen concentration, changes in functional connectivity, and variations in graph theory-based network topological characteristics were assessed. Then, with Mann-Whitney statistics, this study compared whether there are significant differences in the above characteristics between patients with OSA and HCs. Lastly, the study further examined the correlation between the altered characteristics and the apnea hypopnea index (AHI) using linear regression. Results revealed a higher mean and standard deviation of hemoglobin concentration in the superior temporal gyrus among patients with OSA compared to HCs. Resting-state functional connectivity (RSFC) exhibited a slight increase between the superior temporal gyrus and other specific areas in patients with OSA. Notably, neither patients with OSA nor HCs demonstrated significant small-world network properties. Patients with OSA displayed an elevated clustering coefficient (p < 0.05) and local efficiency (p < 0.05). Additionally, patients with OSA exhibited a tendency towards increased nodal betweenness centrality (p < 0.05) and degree centrality (p < 0.05) in the right supramarginal gyrus, as well as a trend towards higher betweenness centrality (p < 0.05) in the right precentral gyrus. The results of multiple linear regressions indicate that the influence of the AHI on RSFC between the right precentral gyrus and right superior temporal gyrus (p < 0.05), as well as between the right precentral gyrus and right supramarginal gyrus (p < 0.05), are statistically significant. These findings suggest that OSA may compromise functional brain connectivity and network topological properties in affected individuals, serving as a potential neurological mechanism underlying the observed abnormalities in brain function associated with OSA.

Uremic toxins and the brain in chronic kidney disease.

Chronic kidney disease (CKD) patients have an increased risk for cognitive impairment compared to the general population. The risk is much higher in CKD patients who progress to end-stage kidney disease (ESKD) and require hemodialysis or peritoneal dialysis. Multiple factors maycontribute to cognitive impairment in CKD patients and in patients on chronic dialysis. However, the observation that, after kidney transplantation, there is an improvement in several cognitive performance markers and that some structural and functional brain abnormalities mayimprove suggests that cognitive deficits in patients on dialysis may be at least partially reversible. Recent evidence supports the hypothesis that uremic toxins may disrupt the blood brain barrier and damage the brain cells. Such brain toxicity should prompt efforts to lower the burden of uremic toxins through dialytic and non-dialytic strategies.

Exploring key genes and pathways associated with sex differences in autism spectrum disorder: integrated bioinformatic analysis.

Autism spectrum disorder (ASD) is a heterogenous neurodevelopmental disorder marked by functional abnormalities in brain that causes social and linguistic difficulties. The incidence of ASD is more prevalent in males compared to females, but the underlying mechanism, as well as molecular indications for identifying sex-specific differences in ASD symptoms remain unknown. Thus, impacting the development of personalized strategy towards pharmacotherapy of ASD. The current study employs an integrated bioinformatic approach to investigate the genes and pathways uniquely associated with sex specific differences in autistic individuals. Based on microarray dataset (GSE6575) extracted from the gene expression omnibus, the dysregulated genes between the autistic and the neurotypical individuals for both sexes were identified. Gene set enrichment analysis was performed to ascertain biological activities linked to the dysregulated genes. Protein-protein interaction network analysis was carried out to identify hub genes. The identified hub genes were examined to determine their functions and involvement in the associated pathways using Enrichr. Additionally, hub genes were validated from autism-associated databases and the potential small molecules targeting the hub genes were identified. The present study utilized whole blood transcriptomic gene expression analysis data and identified 2211 and 958 differentially expressed unique genes in males and females respectively. The functional enrichment analysis revealed that male hub genes were functionally associated with RNA polymerase II mediated transcriptional regulation whereas female hub genes were involved in intracellular signal transduction and cell migration. The top male hub genes exhibited functional enrichment in tyrosine kinase signalling pathway. The pathway enrichment analysis of male hub genes indicates the enrichment of papillomavirus infection. Female hub genes were enriched in androgen receptor signalling pathway and functionally enriched in focal adhesion specific excision repair. Identified drug like candidates targeting these genes may serve as a potential sex specific therapeutics. Wortmannin for males, 5-Fluorouracil for females had the highest scores. Targeted and sex-specific pharmacotherapies may be created for the management of ASD. The current investigation identifies sex-specific molecular signatures derived from whole blood which may serve as a potential peripheral sex-specific biomarkers for ASD. The study also uncovers the possible pharmacological interventions against the selected genes/pathway, providing support in development of therapeutic strategies to mitigate ASD. However, experimental proofs on biological systems are warranted.

Intrinsic Mechanisms of Facial Expression Recognition Defects in Children with Autism

The difficulty of facial expression recognition in autistic children mainly includes the inability to accurately understand the emotions and intentions of others, and shows the lack of facial expression response in social interaction. This defect has caused problems with their adaptation and understanding of others in social communication. Multiple hypotheses have been proposed about the intrinsic mechanism of facial expression recognition defects in children with autism. Children with autism may lack the development of psychological theory, causing them to correctly interpret and understand facial expressions with emotional[1]. Neurobiological factors may influence the areas of facial expression processing in the brain of autistic children, leading to their abnormalities in the transmission of neural circuits. In addition, children with autism may have abnormalities in brain function, making it difficult for them to effectively process and interpret information about facial expressions. Therefore, it is very important to further investigate the intrinsic mechanism of facial expression recognition defects in autistic children and the development of related treatments, which can help to improve the social communication ability and improve their quality of life of autistic children.

Stress-induced failure of embodied cognition: A general model

We derive the classic, ubiquitous, but enigmatic Yerkes–Dodson effect of applied stress on real-world performance in a highly natural manner from fundamental assumptions on cognition and its dynamics, as constrained by the asymptotic limit theorems of information and control theories. We greatly extend the basic approach by showing how differences in an underlying probability model can affect the dynamics of decision across a broad range of cognitive enterprise. Most particularly, however, this development may help inform our understanding of the different expressions of human psychopathology. A ‘thin tailed’ underlying distribution appears to characterize expression of ‘ordinary’ situational depression/anxiety symptoms of conditions like burnout induced by toxic stress. A ‘fat tailed’ underlying distribution appears to be associated with brain structure and function abnormalities leading to serious mental illness and poor decision making where symptoms are not only emerging in the setting of severe stress but may also appear in a highly punctuated manner at relatively lower levels of stress. A simple hierarchical optimization shows how environmental ‘shadow price’ constraints can buffer or aggravate the effects of stress and arousal. Extension of the underlying theory to other patterns of pathology, like immune disorders and premature aging, seems apt. Applications to the punctuated dynamics of institutional cognition under stress also appear possible. Ultimately, the probability models studied here can be converted to new statistical tools for the analysis of observational and experimental data.

Application of machine learning techniques in the diagnostic approach of PTSD using MRI neuroimaging data: A systematic review

BackgroundAt present, the diagnosis of post-traumatic stress disorder（PTSD） mainly relies on clinical symptoms and psychological scales, and finding objective indicators that are helpful for diagnosis has always been a challenge in clinical practice and academic research. Neuroimaging is a useful and powerful tool for discovering the biomarkers of PTSD,especially functional MRI (fMRI), structural MRI (sMRI) and Diffusion Weighted Imaging（DTI）are the most commonly used technologies, which can provide multiple perspectives on brain function, structure and its connectivity. Machine learning (ML) is an emerging and potentially powerful method, which has aroused people's interest because it is used together with neuroimaging data to define brain structural and functional abnormalities related to diseases, and identify phenotypes, such as helping physicians make early diagnosis. ObjectivesAccording to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) declaration, a systematic review was conducted to assess its accuracy in distinguishing between PTSD patients, TEHC(Trauma-Exposed Healthy Controls), and HC(healthy controls). MethodsWe searched PubMed, Embase, and Web of Science using common words for ML methods and PTSD until June 2023, with no language or time limits. This review includes 13 studies, with sensitivity, specificity, and accuracy taken from each publication or acquired directly from the authors. ResultsAll ML techniques have an diagnostic accuracy rate above 70%，and support vector machine（SVM） are the most commonly used techniques. This series of studies has revealed significant neurobiological differences in key brain regions among individuals with PTSD, TEHC, and HC. The connectivity patterns of regions such as the Insula and Amygdala hold particular significance in distinguishing these groups. TEHC exhibits more normal connectivity patterns compared to PTSD, providing valuable insights for the application of machine learning in PTSD diagnosis. ConclusionIn contrast to any currently available assessment and clinical diagnosis, ML techniques can be used as an effective and non-invasive support for early identification and detection of patients as well as for early screening of high-risk populations.

Brain function abnormalities and neuroinflammation in people living with HIV-associated anxiety disorders.

People living with HIV (PLWH) exhibits an increased susceptibility to anxiety disorders, concomitant with heightened vulnerability to aberrant immune activation and inflammatory responses, and endocrine dysfunction. There exists a dearth of scholarly investigations pertaining to the neurological, immune, and endocrine dimensions of HIV-associated anxiety disorders. This study aimed to compare a group of 16 individuals diagnosed with HIV-associated anxiety disorders (HIV ANXs) according to the Diagnostic and statistical manual of mental disorders (5th ed.), with a HIV individual control group (HIV control) of 49 PLWH without mental disorders. Muti-modal magnetic resonance was employed to assess the brain function and structure of both groups. Seed-based functional connectivity (FC) was used to assess the regional intrinsic brain activity and the influence of regional disturbances on FC with other brain regions. Peripheral blood cytokines and chemokines concentrations were measured using liquid chip and ELISA. Amplitude of low-frequency fluctuations in the right inferior temporal gyrus (ITG) was increased. There is a significant decreased regional homogeneity in HIV ANXs in the right superior occipital gyrus (SOG). The right ITG and the right SOG were separately set as the seed brain region of interest (ROI 1 and ROI 2) to be analyzed the FC. FC decreased in HIV ANXs between ROI1 and the right middle occipital gyrus, the right SOG, FC between ROI2 and left ITG increased in HIV ANXs. No significant structural difference was found between two groups. Pro-inflammatory chemokines showed higher levels in the HIV ANXs. Pro-inflammatory cytokines, neurotrophic factors, and endocrine factors were significantly correlated with alterations in brain function. This study suggests that patients with HIV-associated anxiety disorders may exhibit abnormalities in neurologic, immune, and endocrine functioning. Consequently, it is imperative to implement additional screening and intervention measures for anxiety disorders among PLWH.