Sensorimotor dysfunctions as primary features of autism spectrum disorders

Motor impairments in autism spectrum disorders(ASD) have received far less research attention than core social- communication and cognitive features. Yet, behavioral, neurophysiological, neuroimaging and histopathological studies have documented abnormal motor system development in the majority of individuals with ASD suggesting that these deficits may be primary to the disorder. There are several unique advantages to studying motor development in ASD. First, the neurophysiological substrates of motor skills have been well-characterized via animal and human lesion studies. Second, many of the single-gene disorders associated with ASD also are characterized by motor dysfunctions. Third, recent evidence suggests that the onset of motor dysfunctions may precede the emergence of social and communication deficits during the first year of life in ASD. Motor deficits documented in ASD indicate disruptions throughout the neuroaxis affecting cortex, striatum, the cerebellum and brainstem. Questions remain regarding the timing and development of motor system alterations in ASD, their association with defining clinical features, and their potential for parsing heterogeneity in ASD. Pursuing these questions through neurobiologically informed translational research holds great promise for identifying gene-brain pathways associated with ASD.

Artificial intelligence applications in psychoradiology

One important challenge in psychiatric research is to translate findings from brain imaging research studies that identified brain alterations in patient groups into an accurate diagnosis at an early stage of illness,pre-diction of prognosis before treatment,and guidance for selection of effective treatments that target patient-relevant pathophysiological features.This is the primary aim of the field of Psychoradiology.Using databases collected from large samples at multiple centers,sophisticated artificial intelligence(AI)algorithms may be used to develop clinically useful image analysis pipelines that can help physicians diagnose,predict,and make treatment decisions.In this review,we selectively summarize psychoradiological research using magnetic reso-nance imaging of the brain to explore the neural mechanism of psychiatric disorders,and outline progress and the path forward for the combination of psychoradiology and AI for complementing clinical examinations in patients with psychiatric disorders,as well as limitations in the application of AI that should be considered in future translational research.

The inferior frontal gyrus and familial risk for bipolar disorder

Bipolar disorder(BD)is a familial disorder with high heritability.Genetic factors have been linked to the pathogenesis of BD.Relatives of probands with BD who are at familial risk can exhibit brain abnormalities prior to illness onset.Given its involvement in prefrontal cognitive control and in frontolimbic circuitry that regulates emotional reactivity,the inferior frontal gyrus(IFG)has been a focus of research in studies of BD-related pathology and BD-risk mechanism.In this review,we discuss multimodal neuroimaging findings of the IFG based on studies comparing at-risk relatives and low-risk controls.Review of these studies in at-risk cases suggests the presence of both risk and resilience markers related to the IFG.At-risk individuals exhibited larger gray matter volume and increased functional activities in IFG compared with low-risk controls,which might result from an adaptive brain compensation to support emotion regulation as an aspect of psychological resilience.Functional connectivity between IFG and downstream limbic or striatal areas was typically decreased in at-risk individuals relative to controls,which could contribute to risk-related problems of cognitive and emotional control.Large-scale and longitudinal investigations on at-risk individuals will further elucidate the role of IFG and other brain regions in relation to familial risk for BD,and together guide identification of at-risk individuals for primary prevention.

Effect of jet lag on brain white matter functional connectivity

Background:A long-haul flight across more than five time zones may produce a circadian rhythm sleep disorder known as jet lag.Little is known about the effect of jet lag on white matter(WM)functional connectivity(FC).Objective:The present study is to investigate changes in WM FC in subjects due to recovery from jet lag after flying across six time zones.Methods:Here,resting-state functional magnetic resonance imaging was performed in 23 participants within 24 hours of flying and again 50 days later.Gray matter(GM)and WM networks were identified by k-means clustering.WM FC and functional covariance connectivity(FCC)were analyzed.Next,a sliding window method was used to establish dynamic WM FC.WM static and dynamic FC and FCC were compared between when participants had initially completed their journey and 50 days later.Emotion was assessed using the Positive and Negative Affect Schedule and the State Anxiety Inventory.Results:All participants were confirmed to have jet lag symptoms by the Columbian Jet Lag Scale.The static FC strengthes of cingulate network(WM7)-sensorimotor network and ventral frontal network-visual network were lower after the long-haul flight compared with recovery.Corresponding results were obtained for the dynamic FC analysis.The analysis of FCC revealed weakened connections between the WM7 and several other brain networks,especially the precentral/postcentral network.Moreover,a negative correlation was found between emotion scores and the FC between the WM7 and sensorimotor related regions.Conclusions:The results of this study provide further evidence for the existence of WM networks and show that jet lag is associated with alterations in static and dynamic WM FC and FCC,especially in sensorimotor networks.Jet lag is a complex problem that not only is related to sleep rhythm but also influences emotion.