Convergent functional architecture of the superior parietal lobule unraveled with multimodal neuroimaging approaches

Brain structures with stronger genetic associations are not less associated with family- and state-level economic contexts

We investigate whether neural, cognitive, and psychopathology phenotypes that are more strongly related to genetic differences are less strongly associated with family- and state-level economic contexts (N = 5374 individuals with 1KG-EUR-like genotypes with 870 twins, from the Adolescent Behavior and Cognitive Development study). We estimated the twin- and SNP-based heritability of each phenotype, as well as its association with an educational attainment polygenic index (EA PGI). We further examined associations with family socioeconomic status (SES) and tested whether SES-related differences were moderated by state cost of living and social safety net programs (Medicaid expansion and cash assistance). SES was broadly associated with cognition, psychopathology, brain volumes, and cortical surface areas, even after controlling for the EA PGI. Brain phenotypes that were more heritable or more strongly associated with the EA PGI were not, overall, less related to SES, nor were SES-related differences in these phenotypes less moderated by macroeconomic context and policy. Informing a long-running theoretical debate, and contra to widespread lay beliefs, results suggest that aspects of child brain development that are more strongly related to genetic differences are not, in general, less associated with socioeconomic contexts and policies.

Effects of computerized working memory training on neuroplasticity in healthy individuals: A combined neuroimaging and neurotransmitter study

Working memory (WM) is an essential cognitive function that underpins various higher-order cognitive processes. Improving WM capacity through targeted training interventions has emergered as a potential approach for enhancing cognitive abilities. The present study employed an 8-week regimen of computerized WM training (WMT) to investigate its effect on neuroplasticity in healthy individuals, utilizing neuroimaging data gathered both before and after the training. The key metrics assessed included the amplitude of low-frequency fluctuations (ALFF), voxel-based morphometry (VBM), and the spatial distribution correlations of neurotransmitter. The results indicated that post-training, compared to baseline, there was a reduction in ALFF in the medial superior frontal gyrus and an elevation in ALFF in the left middle occipital gyrus within the training group. In comparison to the control group, the training group also exhibited decreased ALFF in the anterior cingulate cortex, angular gyrus, and superior parietal lobule, along with increased ALFF in the postcentral gyrus post-training. VBM analysis revealed a significant increase in gray matter volume (GMV) in the right dorsal superior frontal gyrus after the training period, compared to the initial baseline measurement. Furthermore, the training group showed GMV increases in the dorsal superior frontal gyrus, Rolandic operculum, precentral gyrus, and postcentral gyrus when compared to the control group. In addition, significant associations were identifed between neuroimaging measurements (AFLL and VBM) and the spatial patterns of neurotransmitters such as serotonin (5-HT), dopamine (DA), and N-methyl-D-aspartate (NMDA), providing insights into the underlying neurochemical processes. These findings clarify the neuroplastic changes caused by WMT, offering a deeper understanding of brain plasticity and highlighting the potential advantages of cognitive training interventions.

Individual large-scale functional network mapping for major depressive disorder with electroconvulsive therapy

Personalized functional connectivity mapping has been demonstrated to be promising in identifying underlying neurophysiological basis for brain disorders and treatment effects. Electroconvulsive therapy (ECT) has been proved to be an effective treatment for major depressive disorder (MDD) while its active mechanisms remain unclear. Here, 46 MDD patients before and after ECT as well as 46 demographically matched healthy controls (HC) underwent resting-state functional magnetic resonance imaging (rs-fMRI) scans. A spatially regularized form of non-negative matrix factorization (NMF) was used to accurately identify functional networks (FNs) in individuals to map individual-level static and dynamic functional network connectivity (FNC) to reveal the underlying neurophysiological basis of therepetical effects of ECT for MDD. Moreover, these static and dynamic FNCs were used as features to predict the clinical treatment outcomes for MDD patients. We found that ECT could modulate both static and dynamic large-scale FNCs at individual level in MDD patients, and dynamic FNCs were closely associated with depression and anxiety symptoms. Importantly, we found that individual FNCs, particularly the individual dynamic FNCs could better predict the treatment outcomes of ECT suggesting that dynamic functional connectivity analysis may be better to link brain functional characteristics with clinical symptoms and treatment outcomes. Taken together, our findings provide new evidence for the active mechanisms and biomarkers for ECT to improve diagnostic accuracy and to guide individual treatment selection for MDD patients.

Early attentional processing and cortical remapping strategies of tactile stimuli in adults with an early and late-onset visual impairment: A cross-sectional study

Neuroplastic changes appear in people with visual impairment (VI) and they show greater tactile abilities. Improvements in performance could be associated with the development of enhanced early attentional processes based on neuroplasticity. Currently, the various early attentional and cortical remapping strategies that are utilized by people with early (EB) and late-onset blindness (LB) remain unclear. Thus, more research is required to develop effective rehabilitation programs and substitution devices. Our objective was to explore the differences in spatial tactile brain processing in adults with EB, LB and a sighted control group (CG). In this cross-sectional study 27 participants with VI were categorized into EB (n = 14) and LB (n = 13) groups. They were then compared with a CG (n = 15). A vibrotactile device and event-related potentials (ERPs) were utilized while participants performed a spatial tactile line recognition task. The P100 latency and cortical areas of maximal activity were analyzed during the task. The three groups had no statistical differences in P100 latency (p>0.05). All subjects showed significant activation in the right superior frontal areas. Only individuals with VI activated the left superior frontal regions. In EB subjects, a higher activation was found in the mid-frontal and occipital areas. A higher activation of the mid-frontal, anterior cingulate cortex and orbitofrontal zones was observed in LB participants. Compared to the CG, LB individuals showed greater activity in the left orbitofrontal zone, while EB exhibited greater activity in the right superior parietal cortex. The EB had greater activity in the left orbitofrontal region compared to the LB. People with VI may not have faster early attentional processing. EB subjects activate the occipital lobe and right superior parietal cortex during tactile stimulation because of an early lack of visual stimuli and a multimodal information processing. In individuals with LB and EB the orbitofrontal area is activated, suggesting greater emotional processing.

The Mediterranean Diet in Pregnancy: Implications for Maternal Brain Morphometry in a Secondary Analysis of the IMPACT BCN Randomized Clinical Trial

INTRODUCTION

A Mediterranean diet has positive effects on the brain in mid-older adults; however, there is scarce information on pregnant individuals. We aimed to evaluate the effect of a structured Mediterranean diet intervention on the cortical structure of the maternal brain during pregnancy.

METHODS

This study was a secondary analysis of the IMPACT BCN, a randomized clinical trial with 1221 high-risk pregnant women randomly allocated into three groups at 19-23 weeks of gestation: Mediterranean diet intervention, a mindfulness-based stress reduction program, or usual care. Maternal brain magnetic resonance imaging was performed during the third trimester of pregnancy in a random subgroup of participants. For this study, data from the Mediterranean diet and usual groups were analyzed. Maternal dietary intake, adherence to the Mediterranean diet and metabolite biomarkers were evaluated using a food frequency questionnaire, a 17-item dietary screener and plasma/urine samples, respectively.

RESULTS

The cluster-wise analysis showed that the Mediterranean diet group participants (n = 34) had significantly larger surface areas in the right precuneus (90%CI: <0.0001-0.0004, p < 0.001) and left superior parietal (90%CI: 0.026-0.033, p = 0.03) lobules compared to the usual care group participants (n = 37). A larger right precuneus area was associated with high improvements in adherence to the Mediterranean diet, a high intake of walnuts and high concentrations of urinary hydroxytyrosol. A larger left superior parietal area was associated with a high intake of walnuts and high concentrations of urinary hydroxytyrosol.

CONCLUSIONS

The promotion of a Mediterranean diet during pregnancy has a significant effect on maternal brain structure.

Delineating abnormal individual structural covariance brain network organization in pediatric epilepsy with unilateral resection of visual cortex

Although several previous studies have used resting-state functional magnetic resonance imaging and diffusion tensor imaging to report topological changes in the brain in epilepsy, it remains unclear whether the individual structural covariance network (SCN) changes in epilepsy, especially in pediatric epilepsy with visual cortex resection but with normal functions. Herein, individual SCNs were mapped and analyzed for seven pediatric patients with epilepsy after surgery and 15 age-matched healthy controls. A whole-brain individual SCN was constructed based on an automated anatomical labeling template, and global and nodal network metrics were calculated for statistical analyses. Small-world properties were exhibited by pediatric patients after brain surgery and by healthy controls. After brain surgery, pediatric patients with epilepsy exhibited a higher shortest path length, lower global efficiency, and higher nodal efficiency in the cuneus than those in healthy controls. These results revealed that pediatric epilepsy after brain surgery, even with normal functions, showed altered topological organization of the individual SCNs, which revealed residual network topological abnormalities and may provide initial evidence for the underlying functional impairments in the brain of pediatric patients with epilepsy after surgery that can occur in the future.

Functionality of arousal-regulating brain circuitry at rest predicts human cognitive abilities

Arousal state is regulated by subcortical neuromodulatory nuclei, such as locus coeruleus, which send wide-reaching projections to cortex. Whether higher-order cortical regions have the capacity to recruit neuromodulatory systems to aid cognition is unclear. Here, we hypothesized that select cortical regions activate the arousal system, which, in turn, modulates large-scale brain activity, creating a functional circuit predicting cognitive ability. We utilized the Human Connectome Project 7T functional magnetic resonance imaging dataset (n = 149), acquired at rest with simultaneous eye tracking, along with extensive cognitive assessment for each subject. First, we discovered select frontoparietal cortical regions that drive large-scale spontaneous brain activity specifically via engaging the arousal system. Second, we show that the functionality of the arousal circuit driven by bilateral posterior cingulate cortex (associated with the default mode network) predicts subjects' cognitive abilities. This suggests that a cortical region that is typically associated with self-referential processing supports cognition by regulating the arousal system.

Exploration of neuroanatomical characteristics to differentiate prodromal Alzheimer's disease from cognitively unimpaired amyloid-positive individuals

Differentiating clinical stages based solely on positive findings from amyloid PET is challenging. We aimed to investigate the neuroanatomical characteristics at the whole-brain level that differentiate prodromal Alzheimer's disease (AD) from cognitively unimpaired amyloid-positive individuals (CU A+) in relation to amyloid deposition and regional atrophy. We included 45 CU A+ participants and 135 participants with amyloid-positive prodromal AD matched 1:3 by age, sex, and education. All participants underwent 18F-florbetaben positron emission tomography and 3D structural T1-weighted magnetic resonance imaging. We compared the standardized uptake value ratios (SUVRs) and volumes in 80 regions of interest (ROIs) between CU A+ and prodromal AD groups using independent t-tests, and employed the least absolute selection and shrinkage operator (LASSO) logistic regression model to identify ROIs associated with prodromal AD in relation to amyloid deposition, regional atrophy, and their interaction. After applying False Discovery Rate correction at < 0.1, there were no differences in global and regional SUVR between CU A+ and prodromal AD groups. Regional volume differences between the two groups were observed in the amygdala, hippocampus, entorhinal cortex, insula, parahippocampal gyrus, and inferior temporal and parietal cortices. LASSO logistic regression model showed significant associations between prodromal AD and atrophy in the entorhinal cortex, inferior parietal cortex, both amygdalae, and left hippocampus. The mean SUVR in the right superior parietal cortex (beta coefficient = 0.0172) and its interaction with the regional volume (0.0672) were also selected in the LASSO model. The mean SUVR in the right superior parietal cortex was associated with an increased likelihood of prodromal AD (Odds ratio [OR] 1.602, p = 0.014), particularly in participants with lower regional volume (OR 3.389, p < 0.001). Only regional volume differences, not amyloid deposition, were observed between CU A+ and prodromal AD. The reduced volume in the superior parietal cortex may play a significant role in the progression to prodromal AD through its interaction with amyloid deposition in that region.

The relationship between the resting state functional connectivity and social cognition in schizophrenia: Results from the Italian Network for Research on Psychoses

Deficits in social cognition (SC) interfere with recovery in schizophrenia (SZ) and may be related to resting state brain connectivity. This study aimed at assessing the alterations in the relationship between resting state functional connectivity and the social-cognitive abilities of patients with SZ compared to healthy subjects. We divided the brain into 246 regions of interest (ROI) following the Human Healthy Volunteers Brainnetome Atlas. For each participant, we calculated the resting-state functional connectivity (rsFC) in terms of degree centrality (DC), which evaluates the total strength of the most powerful coactivations of every ROI with all other ROIs during rest. The rs-DC of the ROIs was correlated with five measures of SC assessing emotion processing and mentalizing in 45 healthy volunteers (HVs) chosen as a normative sample. Then, controlling for symptoms severity, we verified whether these significant associations were altered, i.e., absent or of opposite sign, in 55 patients with SZ. We found five significant differences between SZ patients and HVs: in the patients' group, the correlations between emotion recognition tasks and rsFC of the right entorhinal cortex (R-EC), left superior parietal lobule (L-SPL), right caudal hippocampus (R-c-Hipp), and the right caudal (R-c) and left rostral (L-r) middle temporal gyri (MTG) were lost. An altered resting state functional connectivity of the L-SPL, R-EC, R-c-Hipp, and bilateral MTG in patients with SZ may be associated with impaired emotion recognition. If confirmed, these results may enhance the development of non-invasive brain stimulation interventions targeting those cerebral regions to reduce SC deficit in SZ.

Shared Manifold Regularized Joint Feature Selection for Joint Classification and Regression in Alzheimer's Disease Diagnosis

In Alzheimer's disease (AD) diagnosis, joint feature selection for predicting disease labels (classification) and estimating cognitive scores (regression) with neuroimaging data has received increasing attention. In this paper, we propose a model named Shared Manifold regularized Joint Feature Selection (SMJFS) that performs classification and regression in a unified framework for AD diagnosis. For classification, unlike the existing works that build least squares regression models which are insufficient in the ability of extracting discriminative information for classification, we design an objective function that integrates linear discriminant analysis and subspace sparsity regularization for acquiring an informative feature subset. Furthermore, the local data relationships are learned according to the samples' transformed distances to exploit the local data structure adaptively. For regression, in contrast to previous works that overlook the correlations among cognitive scores, we learn a latent score space to capture the correlations and employ the latent space to design a regression model with l2,1 -norm regularization, facilitating the feature selection in regression task. Moreover, the missing cognitive scores can be recovered in the latent space for increasing the number of available training samples. Meanwhile, to capture the correlations between the two tasks and describe the local relationships between samples, we construct an adaptive shared graph to guide the subspace learning in classification and the latent cognitive score learning in regression simultaneously. An efficient iterative optimization algorithm is proposed to solve the optimization problem. Extensive experiments on three datasets validate the discriminability of the features selected by SMJFS.

Functionality of arousal-regulating brain circuitry at rest predicts human cognitive abilities

Arousal state is regulated by subcortical neuromodulatory nuclei, such as locus coeruleus, which send wide-reaching projections to cortex. Whether higher-order cortical regions have the capacity to recruit neuromodulatory systems to aid cognition is unclear. Here, we hypothesized that select cortical regions activate the arousal system, which in turn modulates large-scale brain activity, creating a functional circuit predicting cognitive ability. We utilized the Human Connectome Project 7T functional magnetic resonance imaging dataset (N=149), acquired at rest with simultaneous eye tracking, along with extensive cognitive assessment for each subject. First, we discovered select frontoparietal cortical regions that drive large-scale spontaneous brain activity specifically via engaging the arousal system. Second, we show that the functionality of the arousal circuit driven by bilateral posterior cingulate cortex (associated with the default mode network) predicts subjects' cognitive abilities. This suggests that a cortical region that is typically associated with self-referential processing supports cognition by regulating the arousal system.

Vaping and smoking cue reactivity in young adult electronic cigarette users who have never smoked combustible cigarettes: A functional neuroimaging study

Introduction

The rapid growth in the use of electronic cigarettes (e-cigarettes) among young adults who have never smoked combustible cigarettes is concerning, as it raises the potential for chronic vaping and nicotine addiction. A key characteristic of drug addiction is the elevated neural response to conditioned drug-related cues (i.e., cue reactivity). Generalized reactivity to both vaping and smoking cues may signify an increased risk for smoking initiation in non- smoking vapers. In this study, we used functional magnetic resonance imaging (fMRI) to evaluate brain responses to vaping and smoking cues in young adult never-smoking vapers.

Methods

Sixty-six young adult never-smoking vapers underwent functional MRI while viewing visual cues pertaining to vaping, smoking, and nicotine-unrelated unconditioned reward (i.e., food). A priori region-of-interest analysis combined with exploratory whole-brain analysis was performed to characterize neural reactivity to vaping and smoking cues in comparison to food cues.

Results

The medial prefrontal cortex and the posterior cingulate cortex, regions that play a key role in drug cue reactivity, showed significantly increased neural response to vaping cues compared to food cues. The posterior cingulate cortex additionally showed increased neural responses to smoking cues compared to food cues.

Conclusions

Despite never having smoked combustible cigarettes, young adult vapers exhibited heightened neural susceptibility to both vaping and smoking cues within brain systems associated with cue reactivity. The findings shed light on the mechanisms underlying nicotine addiction and smoking initiation risk in this critical population and may contribute to the development of science-based interventions and regulatory measures in the future.

IMPLICATIONS

The escalating vaping prevalence among US never-smoking young adults is alarming, due to its potential ramifications for nicotine addiction development. Nicotine addiction is characterized by elevated neural response to conditioned nicotine-related cues. Using functional neuroimaging, we showed that young adult non-smoking vapers exhibited heightened neural susceptibility to both vaping and smoking cues within brain systems previously associated with cue reactivity. Such cross-reactivity to both types of nicotine cues may serve as the mechanism underlying nicotine addiction and smoking initiation risk in this population. Our findings may contribute to the development of science-based interventions and regulatory measures addressing the vaping epidemic.

The association between cortical gyrification and sleep in adolescents and young adults

STUDY OBJECTIVES

Healthy sleep is important for adolescent neurodevelopment, and relationships between brain structure and sleep can vary in strength over this maturational window. Although cortical gyrification is increasingly considered a useful index for understanding cognitive and emotional outcomes in adolescence, and sleep is also a strong predictor of such outcomes, we know relatively little about associations between cortical gyrification and sleep. We aimed to identify developmentally invariant (stable across age) or developmentally specific (observed only during discrete age intervals) gyrification-sleep relationships in young people.

METHODS

A total of 252 Neuroimaging and Pediatric Sleep Databank participants (9-26 years; 58.3% female) completed wrist actigraphy and a structural MRI scan. Local gyrification index (lGI) was estimated for 34 bilateral brain regions. Naturalistic sleep characteristics (duration, timing, continuity, and regularity) were estimated from wrist actigraphy. Regularized regression for feature selection was used to examine gyrification-sleep relationships.

RESULTS

For most brain regions, greater lGI was associated with longer sleep duration, earlier sleep timing, lower variability in sleep regularity, and shorter time awake after sleep onset. lGI in frontoparietal network regions showed associations with sleep patterns that were stable across age. However, in default mode network regions, lGI was only associated with sleep patterns from late childhood through early-to-mid adolescence, a period of vulnerability for mental health disorders.

CONCLUSIONS

We detected both developmentally invariant and developmentally specific ties between local gyrification and naturalistic sleep patterns. Default mode network regions may be particularly susceptible to interventions promoting more optimal sleep during childhood and adolescence.

Familial Risk for Schizophrenia vs Bipolar Disorder and Task-Based Neural Activation: A functional Magnetic Resonance Imaging Meta-Analysis

BACKGROUND AND HYPOTHESIS

Individuals at familial risk for developing schizophrenia (FRSZ) or bipolar disorder (FRBD) have shared and unique genetic risks. Few studies have compared neural activation between these two groups. Therefore, the present meta-analysis investigated functional brain similarities and differences between FRSZ and FRBD individuals.

STUDY DESIGN

A systematic literature review was conducted of articles that compared FRSZ or FRBD individuals to healthy controls (31 FRSZ and 22 FRBD). Seed-based d mapping was used to conduct the meta-analysis. Analyses included comparisons of FRSZ to controls, FRBD to controls, and both relative groups to each other.

STUDY RESULTS

Using a highly conservative family-wise error rate correction, there were no significant findings. Using a less conservative threshold, FRSZ compared to controls had lower activation in the left precuneus (Puncorrected = .02) across all studies and in the left middle frontal gyrus (Puncorrected = .03) in nonsocial cognition studies. FRBD compared to controls had lower activation in the left superior parietal gyrus (Puncorrected = .03) and right angular gyrus (Puncorrected = .03) in nonsocial cognition studies, and higher activation in the left superior frontal gyrus (Puncorrected = .01) in social tasks. Differences between FRSZ and FRBD were not significant.

CONCLUSIONS

There were few robust differences between FRSZ or FRBD compared to controls. This suggests only weak support for neural activation differences between individuals at genetic risk for schizophrenia or bipolar disorder and controls. The tentative findings observed were in different brain regions for FRSZ and FRBD, with no strong evidence for shared effects between schizophrenia and bipolar genetic risk on neural activation.

Identifying structural brain markers of resilience to adversity in young people using voxel-based morphometry

There is increasing evidence that resilience in youth may have a neurobiological basis. However, the existing literature lacks a consistent way of operationalizing resilience, often relying on arbitrary judgments or narrow definitions (e.g., not developing PTSD) to classify individuals as resilient. Therefore, this study used data-driven, continuous resilience scores based on adversity and psychopathology to investigate associations between resilience and brain structure in youth. Structural MRI data from 298 youth aged 9-18 years (Mage = 13.51; 51% female) who participated in the European multisite FemNAT-CD study were preprocessed using SPM12 and analyzed using voxel-based morphometry. Resilience scores were derived by regressing data on adversity exposure against current/lifetime psychopathology and quantifying each individual's distance from the regression line. General linear models tested for associations between resilience and gray matter volume (GMV) and examined whether associations between resilience and GMV differed by sex. Resilience was positively correlated with GMV in the right inferior frontal and medial frontal gyri. Sex-by-resilience interactions were observed in the middle temporal and middle frontal gyri. These findings demonstrate that resilience in youth is associated with volume in brain regions implicated in executive functioning, emotion regulation, and attention. Our results also provide evidence for sex differences in the neurobiology of resilience.

Molecular mechanisms underlying resting-state brain functional correlates of behavioral inhibition

Previous literature has established the presence of sex differences in behavioral inhibition as well as its neural substrates and related disease risk. However, there is limited evidence that speaks directly to the question of whether or not there are sex-dependent associations between behavioral inhibition and resting-state brain function and, if so, how they are modulated by the underlying molecular mechanisms. We computed functional connectivity density (FCD) using resting-state functional MRI data to examine their associations with behavioral inhibition ability measured using a Go/No-Go task across a large cohort of 510 healthy young adults. Then, we examined the spatial relationships of the FCD correlates of behavioral inhibition with gene expression and neurotransmitter atlases to explore their potential genetic architecture and neurochemical basis. A significant negative correlation between behavioral inhibition and FCD in the left superior parietal lobule was found in females but not males. Further spatial correlation analyses demonstrated that the identified neural correlates of behavioral inhibition were associated with expression of gene categories predominantly implicating essential components of the cerebral cortex (glial cell, neuron, axon, dendrite, and synapse) and ion channel activity, as well as were linked to the serotonergic system. Our findings may not only yield important insights into the molecular mechanisms underlying the female-specific neural substrates of behavioral inhibition, but also provide a critical context for understanding how biological sex might contribute to variation in behavioral inhibition and its related disease risk.

Neural correlates of the sound facilitation effect in the modified Simon task in older adults

Introduction

The ability to resolve interference declines with age and is attributed to neurodegeneration and reduced cognitive function and mental alertness in older adults. Our previous study revealed that task-irrelevant but environmentally meaningful sounds improve performance on the modified Simon task in older adults. However, little is known about neural correlates of this sound facilitation effect.

Methods

Twenty right-handed older adults [mean age = 72 (SD = 4), 11 female] participated in the fMRI study. They performed the modified Simon task in which the arrows were presented either in the locations matching the arrow direction (congruent trials) or in the locations mismatching the arrow direction (incongruent trials). A total of 50% of all trials were accompanied by task-irrelevant but environmentally meaningful sounds.

Results

Participants were faster on the trials with concurrent sounds, independently of whether trials were congruent or incongruent. The sound effect was associated with activation in the distributed network of auditory, posterior parietal, frontal, and limbic brain regions. The magnitude of the behavioral facilitation effect due to sound was associated with the changes in activation of the bilateral auditory cortex, cuneal cortex, and occipital fusiform gyrus, precuneus, left superior parietal lobule (SPL) for No Sound vs. Sound trials. These changes were associated with the corresponding changes in reaction time (RT). Older adults with a recent history of falls showed greater activation in the left SPL than those without falls history.

Conclusion

Our findings are consistent with the dedifferentiation hypothesis of cognitive aging. The facilitatory effect of sound could be achieved through recruitment of excessive neural resources, which allows older adults to increase attention and mental alertness during task performance. Considering that the SPL is critical for integration of multisensory information, individuals with slower task responses and those with a history of falls may need to recruit this region more actively than individuals with faster responses and those without a fall history to overcome increased difficulty with interference resolution. Future studies should examine the relationship among activation in the SPL, the effect of sound, and falls history in the individuals who are at heightened risk of falls.

A review of brain regions and associated post-concussion symptoms

The human brain is an exceptionally complex organ that is comprised of billions of neurons. Therefore, when a traumatic event such as a concussion occurs, somatic, cognitive, behavioral, and sleep impairments are the common outcome. Each concussion is unique in the sense that the magnitude of biomechanical forces and the direction, rotation, and source of those forces are different for each concussive event. This helps to explain the unpredictable nature of post-concussion symptoms that can arise and resolve. The purpose of this narrative review is to connect the anatomical location, healthy function, and associated post-concussion symptoms of some major cerebral gray and white matter brain regions and the cerebellum. As a non-exhaustive description of post-concussion symptoms nor comprehensive inclusion of all brain regions, we have aimed to amalgamate the research performed for specific brain regions into a single article to clarify and enhance clinical and research concussion assessment. The current status of concussion diagnosis is highly subjective and primarily based on self-report of symptoms, so this review may be able to provide a connection between brain anatomy and the clinical presentation of concussions to enhance medical imaging assessments. By explaining anatomical relevance in terms of clinical concussion symptom presentation, an increased understanding of concussions may also be achieved to improve concussion recognition and diagnosis.

Altered neurovascular coupling in patients with vascular cognitive impairment: a combined ASL-fMRI analysis

Background and objective

This study aims to examine the role of neurovascular coupling (NVC) in vascular cognitive impairment (VCI) by investigating the relationship between white matter lesion (WML) burden, NVC, and cognitive deficits. Additionally, we aim to explore the potential of NVC as a tool for understanding the neural mechanisms underlying VCI.

Methods

This study included thirty-eight small vessel disease cognitive impairment (SVCI) patients, 34 post-stroke cognitive impairment (PSCI) patients, and 43 healthy controls (HC). Comprehensive assessments, including neuroimaging and neuropsychological testing, were conducted to evaluate cognitive function. WML burden was measured and correlated with NVC coefficients to examine the relationship between white matter pathology and NVC. Mediation analysis was employed to explore the link relationship between NVC, WML burden, and cognitive function.

Results

The present study showed that NVC was significantly reduced in the SVCI and PSCI groups compared with HCs at both whole-brain and brain region level. The analysis revealed notable findings regarding NVC in relation to WML burden and cognitive function in VCI patients. Specifically, reduced NVC coefficients were observed within higher order brain systems responsible for cognitive control and emotion regulation. Mediation analysis demonstrated that NVC played a mediating role in the relationship between WML burden and cognitive impairment.

Conclusion

This study reveals the mediating role of NVC in the relationship between WML burden and cognitive function in VCI patients. The results demonstrate the potential of the NVC as an accurate measure of cognitive impairment and its ability to identify specific neural circuits affected by WML burden.

Influence of Strenuous Physical Activity and Cardiorespiratory Fitness on Age-Related Differences in Brain Activations During Varieties of Cognitive Control

While there is extensive literature on the beneficial effects of physical activity on age differences in cognitive control, limited research exists on comparing the contributions of strenuous physical activity (sPA) and cardiorespiratory fitness (CRF) to fluctuations in the blood oxygen level-dependent (BOLD) signals during varieties of cognitive control. The current study addresses this gap in knowledge by investigating BOLD signal differences between high-fit and low-fit older adults, determined by their sPA or CRF, during a novel fMRI task with a hybrid block and event-related design that included transient activations (during switching, updating and their combination trials) and sustained activations (during proactive and reactive control blocks). fBOLD signals from older (n = 25) were compared to more functionally efficient younger (n = 15) adults. High-sPA old showed higher task accuracy than Low-sPA old and similar accuracy as young. Whole-brain fMRI analyses identified higher BOLD activations (esp. dlPFC/MFG) in high-fit old during updating and combination trials that were similar to young, suggesting maintenance of BOLD signals in higher fit older adults during working memory updating. Additionally, both High-sPA and High-CRF related compensatory overactivation were observed in left parietal and occipital areas during sustained activations, which were positively correlated with older adults' accuracy. These results suggest that physical fitness is a modifier of age-related changes in BOLD signal modulation elicited in response to increasing cognitive control demands, with higher fitness in old contributing to both compensatory overactivations and maintenance of task-related brain activations during cognitive control, whereas lower fitness contributed to maladaptive overactivations during lower cognitive demands.

Decoding and geometry of ten finger movements in human posterior parietal cortex and motor cortex

Objective. Enable neural control of individual prosthetic fingers for participants with upper-limb paralysis.Approach. Two tetraplegic participants were each implanted with a 96-channel array in the left posterior parietal cortex (PPC). One of the participants was additionally implanted with a 96-channel array near the hand knob of the left motor cortex (MC). Across tens of sessions, we recorded neural activity while the participants attempted to move individual fingers of the right hand. Offline, we classified attempted finger movements from neural firing rates using linear discriminant analysis with cross-validation. The participants then used the neural classifier online to control individual fingers of a brain-machine interface (BMI). Finally, we characterized the neural representational geometry during individual finger movements of both hands.Main Results. The two participants achieved 86% and 92% online accuracy during BMI control of the contralateral fingers (chance = 17%). Offline, a linear decoder achieved ten-finger decoding accuracies of 70% and 66% using respective PPC recordings and 75% using MC recordings (chance = 10%). In MC and in one PPC array, a factorized code linked corresponding finger movements of the contralateral and ipsilateral hands.Significance. This is the first study to decode both contralateral and ipsilateral finger movements from PPC. Online BMI control of contralateral fingers exceeded that of previous finger BMIs. PPC and MC signals can be used to control individual prosthetic fingers, which may contribute to a hand restoration strategy for people with tetraplegia.

Nicotine dependence and insula subregions: functional connectivity and cue-induced activation

Nicotine dependence is a major predictor of relapse in people with Tobacco Use Disorder (TUD). Accordingly, therapies that reduce nicotine dependence may promote sustained abstinence from smoking. The insular cortex has been identified as a promising target in brain-based therapies for TUD, and has three major sub-regions (ventral anterior, dorsal anterior, and posterior) that serve distinct functional networks. How these subregions and associated networks contribute to nicotine dependence is not well understood, and therefore was the focus of this study. Sixty individuals (28 women; 18-45 years old), who smoked cigarettes daily, rated their level of nicotine dependence (on the Fagerström Test for Nicotine Dependence) and, after abstaining from smoking overnight (~12 h), underwent functional magnetic resonance imaging (fMRI) in a resting state. A subset of these participants (N = 48) also completing a cue-induced craving task during fMRI. Correlations between nicotine dependence and resting-state functional connectivity (RSFC) and cue-induced activation of the major insular sub-regions were evaluated. Nicotine dependence was negatively correlated with connectivity of the left and right dorsal, and left ventral anterior insula with regions within the superior parietal lobule (SPL), including the left precuneus. No relationship between posterior insula connectivity and nicotine dependence was found. Cue-induced activation in the left dorsal anterior insula was positively associated with nicotine dependence and negatively associated with RSFC of the same region with SPL, suggesting that craving-related responsivity in this subregion was greater among participants who were more dependent. These results may inform therapeutic approaches, such as brain stimulation, which may elicit differential clinical outcomes (e.g., dependence, craving) depending on the insular subnetwork that is targeted.

Disrupted functional connectivity of the cerebellum with default mode and frontoparietal networks in young adults with major depressive disorder

Cerebellar dysconnectivity has repeatedly been documented in major depressive disorder (MDD). The cerebellum is composed of multiple functionally distinct subunits, and whether those subunits show similar or distinct dysconnectivity patterns with the cerebrum in MDD, is still unclear and needs to be further clarified. In this study, 91 MDD patients (23 male and 68 female) and 59 demographically matched healthy controls (22 male and 37 female) were enrolled to explore the cerebellar-cerebral dysconnectivity pattern in MDD by using the cutting-edge cerebellar partition atlas. Results showed that MDD patients exhibit decreased cerebellar connectivity with cerebral regions of default mode (DMN), frontoparietal networks (FPN), and visual areas. The dysconnectivity pattern was statistically similar across cerebellar subunits, with no significant diagnosis-by-subunit interactions. Correlation analyzes showed that cerebellar-dorsal lateral prefrontal cortex (DLPFC) connectivity is significantly correlated with anhedonia in MDD patients. Such dysconnectivity pattern was not affected by sex, which, however, should be further replicated in larger samples. These findings suggest a generalized disrupted cerebellar-cerebral connectivity pattern in MDD across all cerebellar subunits, which partially accounts for depressive symptoms in MDD, thus highlighting the pivotal role of the disrupted connectivity of cerebellum with DMN and FPN in the neuropathology of depression.

Association of Brain Microstructure and Functional Connectivity With Cognitive Outcomes and Postnatal Growth Among Early School-Aged Children Born With Extremely Low Birth Weight

Importance

Postnatal growth may be associated with longitudinal brain development in children born preterm.

Objective

To compare brain microstructure and functional connectivity strength with cognitive outcomes in association with postnatal growth among early school-aged children born preterm with extremely low birth weight.

Design, Setting, and Participants

This single-center cohort study prospectively enrolled 38 children 6 to 8 years of age born preterm with extremely low birth weight: 21 with postnatal growth failure (PGF) and 17 without PGF. Children were enrolled, past records were retrospectively reviewed, and imaging data and cognitive assessments occurred from April 29, 2013, through February 14, 2017. Image processing and statistical analyses were conducted through November 2021.

Exposure

Postnatal growth failure in the early neonatal period.

Main Outcomes and Measures

Diffusion tensor images and resting-state functional magnetic resonance images were analyzed. Cognitive skills were tested using the Wechsler Intelligence Scale; executive function was assessed based on a composite score calculated from the synthetic composite of the Children's Color Trails Test, STROOP Color and Word Test, and Wisconsin Card Sorting Test; attention function was evaluated using the Advanced Test of Attention (ATA); and the Hollingshead Four Factor Index of Social Status-Child was estimated.

Results

Twenty-one children born preterm with PGF (14 girls [66.7%]), 17 children born preterm without PGF (6 girls [35.3%]), and 44 children born full term (24 girls [54.5%]) were recruited. Attention function was less favorable in children with PGF than those without PGF (mean [SD] ATA score: children with PGF, 63.5 [9.4]; children without PGF, 55.7 [8.0]; P = .008). Significantly lower mean (SD) fractional anisotropy in the forceps major of the corpus callosum (0.498 [0.067] vs 0.558 [0.044] vs 0.570 [0.038]) and higher mean (SD) mean diffusivity in the left superior longitudinal fasciculus-parietal bundle (8.312 [0.318] vs 7.902 [0.455] vs 8.083 [0.393]; originally calculated as millimeter squared per second and rescaled 10 000 times as mean diffusivity × 10 000) were seen among children with PGF compared with children without PGF and controls, respectively. Decreased resting-state functional connectivity strength was observed in the children with PGF. The mean diffusivity of the forceps major of the corpus callosum significantly correlated with the attention measures (r = 0.225; P = .047). Functional connectivity strength between the left superior lateral occipital cortex and both superior parietal lobules correlated with cognitive outcomes of intelligence (right superior parietal lobule, r = 0.262; P = .02; and left superior parietal lobule, r = 0.286; P = .01) and executive function (right superior parietal lobule, r = 0.367; P = .002; and left superior parietal lobule, r = 0.324; P = .007). The ATA score was positively correlated with functional connectivity strength between the precuneus and anterior division of the cingulate gyrus (r = 0.225; P = .048); however, it was negatively correlated with functional connectivity strength between the posterior cingulate gyrus and both superior parietal lobules (the right superior parietal lobule [r = -0.269; P = .02] and the left superior parietal lobule [r = -0.338; P = .002]).

Conclusions and Relevance

This cohort study suggests that the forceps major of the corpus callosum and the superior parietal lobule were vulnerable regions in preterm infants. Preterm birth and suboptimal postnatal growth could have negative associations with brain maturation, including altered microstructure and functional connectivity. Postnatal growth may be associated with differences in long-term neurodevelopment among children born preterm.

Cortical and subcortical morphological alterations in motor subtypes of Parkinson's disease

Parkinson's disease (PD) can be classified into an akinetic-rigid (AR) and a tremor-dominant (TD) subtype based on predominant motor symptoms. Patients with different motor subtypes often show divergent clinical manifestations; however, the underlying neural mechanisms remain unclear. This study aimed to characterize the cortical and subcortical morphological alterations in motor subtypes of PD. T1-weighted MRI images were obtained for 90 patients with PD (64 with the AR subtype and 26 with the TD subtype) and 56 healthy controls (HCs). Cortical surface area, sulcal depth (measured by Freesurfer's Sulc index), and subcortical volume were computed to identify the cortical and subcortical morphological alterations in the two motor subtypes. Compared with HCs, we found widespread surface area reductions in the AR subtype yet sparse surface area reductions in the TD subtype. We found no significant Sulc change in the AR subtype yet increased Sulc in the right supramarginal gyrus in the TD subtype. The hippocampal volumes in both subtypes were lower than those of HCs. In PD patients, the surface area of left posterior cingulate cortex was positively correlated with Mini-Mental State Examination (MMSE) score, while the Sulc value of right middle frontal gyrus was positively correlated with severity of motor impairments. Additionally, the hippocampal volumes were positively correlated with MMSE and Montreal Cognitive Assessment scores and negatively correlated with severity of motor impairments and Hoehn & Yahr scores. Taken together, these findings may contribute to a better understanding of the neural substrates underlying the distinct symptom profiles in the two PD subtypes.

Inhibition, Shifting and Updating: Inter and intra-domain commonalities and differences from an executive functions activation likelihood estimation meta-analysis

Executive functions are higher-order mental processes that support goal-directed behavior. Among these processes, Inhibition, Updating, and Shifting have been considered core executive domains. In this meta-analysis, we comprehensively investigate the neural networks of these executive domains and we synthesize for the first time the neural convergences and divergences among the most frequently used executive paradigms within those domains. A systematic search yielded 1055 published neuroimaging studies (including 26,191 participants in total). Our study revealed that a fronto-parietal network was shared by the three main domains. Furthermore, we executed conjunction analyses among the paradigms of the same domain to extract the core distinctive components of the main executive domains. This approach showed that Inhibition and Shifting are characterized by a strongly lateralized neural activation in the right and left hemisphere, respectively. In addition, both networks overlapped with the Updating network but not with each other. Remarkably, our study detected heterogeneity among the paradigms from the same domain. More specifically, analysis of Inhibition tasks revealed differing activations for Response Inhibition compared to Interference Control paradigms, suggesting that Inhibition encompasses relatively heterogeneous sub-functions. Shifting analyses revealed a bilateral overlap of the Wisconsin Card Sorting Task with the Updating network, but this pattern was absent for Rule Switching and Dual Task paradigms. Moreover, our Updating meta-analyses revealed the neural signatures associated with the specific modules of the Working Memory model from Baddeley and Hitch. To our knowledge, this is the most comprehensive meta-analysis of executive functions to date. Its paradigm-driven analyses provide a unique contribution to a better understanding of the neural convergences and divergences among executive processes that are relevant for clinical applications, such as cognitive enhancement and neurorehabilitation interventions.

Surface-Based Cortical Measures in Multimodal Association Brain Regions Predict Chess Expertise

The complex structure of the brain supports high-order cognition, which is crucial for mastering chess. Surface-based measures, including the fractional dimension (FD) and gyrification index (GI), may be more sensitive in detecting cortical changes relative to volumetric indexes. For this reason, structural magnetic resonance imaging data from 29 chess experts and 29 novice participants were analyzed using the CAT12 toolbox. FD and GI for each brain region were compared between the groups. A multivariate model was used to identify surface-based brain measures that can predict chess expertise. In chess experts, FD is increased in the left frontal operculum (p < 0.01), and this change correlates with the starting age of chess practice (ρ = −0.54, p < 0.01). FD is decreased in the right superior parietal lobule (p < 0.01). Chess expertise is predicted by the FD in a network of fronto-parieto-temporal regions and is associated with GI changes in the middle cingulate gyrus (p < 0.01) and the superior temporal sulcus (p < 0.01). Our findings add to the evidence that chess expertise is based on the complex properties of the brain surface of a network of transmodal association areas important for flexible high-level cognitive functions. Interestingly, these changes are associated with long-lasting practice, suggesting that neuroplastic effects develop over time.

Performance in information processing speed is associated with parietal white matter tract integrity in multiple sclerosis

Background

The Symbol Digit Modalities Test (SDMT) is most frequently used to test processing speed in patients with multiple sclerosis (MS). Functional imaging studies emphasize the importance of frontal and parietal areas for task performance, but the influence of frontoparietal tracts has not been thoroughly studied. We were interested in tract-specific characteristics and their association with processing speed in MS patients.

Methods

Diffusion tensor imaging was obtained in 100 MS patients and 24 healthy matched controls to compare seed-based tract characteristics descending from the superior parietal lobule [Brodman area 7A (BA7A)], atlas-based tract characteristics from the superior longitudinal fasciculus (SLF), and control tract characteristics from the corticospinal tract (CST) and their respective association with ability on the SDMT.

Results

Patients had decreased performance on the SDMT and decreased white matter volume (each p &lt; 0.05). The mean fractional anisotropy (FA) for the BA7A tract and CST (p &lt; 0.05), but not the SLF, differed between MS patients and controls. Furthermore, only the FA of the SLF was positively associated with SDMT performance even after exclusion of the lesions within the tract (r = 0.25, p &lt; 0.05). However, only disease disability and total white matter volume were associated with information processing speed in a linear regression model.

Conclusions

Processing speed in MS is associated with the structural integrity of frontoparietal white matter tracts.

Distinct connectivity patterns in human medial parietal cortices: Evidence from standardized connectivity map using cortico-cortical evoked potential

The medial parietal cortices are components of the default mode network (DMN), which are active in the resting state. The medial parietal cortices include the precuneus and the dorsal posterior cingulate cortex (dPCC). Few studies have mentioned differences in the connectivity in the medial parietal cortices, and these differences have not yet been precisely elucidated. Electrophysiological connectivity is essential for understanding cortical function or functional differences. Since little is known about electrophysiological connections from the medial parietal cortices in humans, we evaluated distinct connectivity patterns in the medial parietal cortices by constructing a standardized connectivity map using cortico-cortical evoked potential (CCEP). This study included nine patients with partial epilepsy or a brain tumor who underwent chronic intracranial electrode placement covering the medial parietal cortices. Single-pulse electrical stimuli were delivered to the medial parietal cortices (38 pairs of electrodes). Responses were standardized using the z-score of the baseline activity, and a response density map was constructed in the Montreal Neurological Institutes (MNI) space. The precuneus tended to connect with the inferior parietal lobule (IPL), the occipital cortex, superior parietal lobule (SPL), and the dorsal premotor area (PMd) (the four most active regions, in descending order), while the dPCC tended to connect to the middle cingulate cortex, SPL, precuneus, and IPL. The connectivity pattern differs significantly between the precuneus and dPCC stimulation (p<0.05). Regarding each part of the medial parietal cortices, the distributions of parts of CCEP responses resembled those of the functional connectivity database. Based on how the dPCC was connected to the medial frontal area, SPL, and IPL, its connectivity pattern could not be explained by DMN alone, but suggested a mixture of DMN and the frontoparietal cognitive network. These findings improve our understanding of the connectivity profile within the medial parietal cortices. The electrophysiological connectivity is the basis of propagation of electrical activities in patients with epilepsy. In addition, it helps us to better understand the epileptic network arising from the medial parietal cortices.

Altered functional association and couplings: Effective diagnostic neuromarkers for Alzheimer’s disease

Alzheimer’s disease (AD) is a common neurodegenerative disorder causing dementia in the elderly population. Functional disconnection of brain is considered to be the main cause of AD. In this study, we applied a newly developed association (Asso) mapping approach to directly quantify the functional disconnections and to explore the diagnostic effects for AD with resting-state functional magnetic resonance imaging data from 36 AD patients and 42 age-, gender-, and education-matched healthy controls (HC). We found that AD patients showed decreased Asso in left dorsoanterior insula (INS) while increased functional connections of INS with right medial prefrontal cortex (MPFC) and left posterior cingulate cortex (PCC). The changed Asso and functional connections were closely associated with cognitive performances. In addition, the reduced Asso and increased functional connections could serve as effective neuromarkers to distinguish AD patients from HC. Our research provided new evidence for functional disconnections in AD and demonstrated that functional disconnections between cognition-memory networks may be potential early biomarkers for AD.

How musical rhythm training improves short-term memory for faces

Playing a musical instrument engages numerous cognitive abilities, including sensory perception, selective attention, and short-term memory. Mounting evidence indicates that engaging these cognitive functions during musical training will improve performance of these same functions. Yet, it remains unclear the extent these benefits may extend to nonmusical tasks, and what neural mechanisms may enable such transfer. Here, we conducted a preregistered randomized clinical trial where nonmusicians underwent 8 wk of either digital musical rhythm training or word search as control. Only musical rhythm training placed demands on short-term memory, as well as demands on visual perception and selective attention, which are known to facilitate short-term memory. As hypothesized, only the rhythm training group exhibited improved short-term memory on a face recognition task, thereby providing important evidence that musical rhythm training can benefit performance on a nonmusical task. Analysis of electroencephalography data showed that neural activity associated with sensory processing and selective attention were unchanged by training. Rather, rhythm training facilitated neural activity associated with short-term memory encoding, as indexed by an increased P3 of the event-related potential to face stimuli. Moreover, short-term memory maintenance was enhanced, as evidenced by increased two-class (face/scene) decoding accuracy. Activity from both the encoding and maintenance periods each highlight the right superior parietal lobule (SPL) as a source for training-related changes. Together, these results suggest musical rhythm training may improve memory for faces by facilitating activity within the SPL to promote how memories are encoded and maintained, which can be used in a domain-general manner to enhance performance on a nonmusical task.

Corresponding anatomical of the macaque superior parietal lobule areas 5 (PE) subdivision reveal similar connectivity patterns with humans

Using the animal brain as a cross-species tool for human brain research based on imaging features can provide more potential to reveal comprehensive human brain analysis. Previous studies have shown that human Brodmann area 5 (BA5) and macaque PE are homologous regions. They are both involved in processes depth and direction information during the touch process in the arm movement. However, recent studies show that both BA5 and PE are not homogeneous. According to the cytoarchitecture, BA5 is subdivided into three different subregions, and PE can be subdivided into PEl, PEla, and PEm. The species homologous relationship among the subregions is not clear between BA5 and PE. At the same time, the subdivision of PE based on the anatomical connection of white matter fiber bundles needs more verification. This research subdivided the PE of macaques based on the anatomical connection of white matter fiber bundles. Two PE subregions are defined based on probabilistic fiber tracking, one on the anterior side and the other on the dorsal side. Finally, the research draws connectivity fingerprints with predefined homologous target areas for the BA5 and PE subregions to reveal the characteristics of structure and functions and gives the homologous correspondence identified.

Resting-state neural signal variability in women with depressive disorders

Aberrant activity and connectivity in default mode (DMN), frontoparietal (FPN), and salience (SN) network regions is well-documented in depression. Recent neuroimaging research suggests that altered variability in the blood oxygen level-dependent (BOLD) signal may disrupt normal network integration and be an important novel predictor of psychopathology. However, no studies have yet determined the relationship between resting-state BOLD signal variability and depressive disorders nor applied BOLD signal variability features to the classification of depression history using machine learning (ML). We collected resting-state fMRI data for 79 women with different depression histories: no history, past history, and current depressive disorder. We tested voxelwise differences in BOLD signal variability related to depression group and severity. We also investigated whether BOLD signal variability of DMN, FPN, and SN regions could predict depression history group using a supervised random forest ML model. Results indicated that individuals with any history of depression had significantly decreased BOLD signal variability in the left and right cerebellum and right parietal cortex (pFWE <0.05). Furthermore, greater depression severity was also associated with reduced BOLD signal variability in the cerebellum. A random forest model classified participant depression history with 74% accuracy, with the ventral anterior cingulate cortex of the DMN as the most important variable in the model. These findings provide novel support for resting-state BOLD signal variability as a marker of neural dysfunction in depression and implicate decreased neural signal variability in the pathophysiology of depression.

Resting-state functional connectivity of the amygdala in major depressive disorder with suicidal ideation

Suicide is a common issue among major depressive disorder (MDD) patients and suicidal ideation (SI) is the first step toward it. There are no definitive objective biomarkers of SI relative to MDD. In this study, a seed-based correlation analysis was performed among 36 MDD patients with SI, 66 MDD patients without SI (NSI), and 57 healthy controls (HCs) using amygdala resting-state functional connectivity (RSFC). Furthermore, the correlation between amygdala RSFC and clinical features was examined in the SI group. When compared to the NSI group, SI group exhibited increased RSFC between the left amygdala seed and left medial superior frontal gyrus (SFGmed) as well as left middle frontal gyrus (MFG). In turn, a decreased RSFC was observed between the left amygdala seed and the following brain regions including the left inferior parietal lobule (IPL), right precentral gyrus (PrCG), and left superior parietal lobule (SPL) in SI group compared to NSI group. Moreover, the SI group exhibited increased RSFC of the right amygdala with left middle temporal gyrus (MTG); In addition, the RSFC of the left amygdala with left MFG was negatively associated with learning and memory (VSM), speed of processing (SOP). The RSFC of the amygdala is distinct between MDD patients with SI and without SI. Our findings reveal the neurobiological characteristics of MDD with respect to SI and provide new clues regarding vulnerability to mental illness. It is necessary to carry out repeated and more longitudinal researches using multimodal approaches on SI in the future.

Disrupted functional connectivity patterns of the left inferior frontal gyrus subregions in benign childhood epilepsy with centrotemporal spikes

BACKGROUND

Benign epilepsy with centrotemporal spikes (BECTS) is one of the most common pediatric epileptic syndromes. Recent studies have shown that BECTS can lead to significant language dysfunction. Although research supports the role of the left inferior frontal gyrus (LIFG) in BECTS, it is unclear whether the subregions of the LIFG show different change patterns in patients with this syndrome.

METHODS

Using resting-state functional magnetic resonance imaging (fMRI) data in a group of 49 BECTS patients and 49 healthy controls, we investigated whether the BECTS patients show abnormal connectivity patterns of the LIFG subregions.

RESULTS

Compared with healthy controls, the BECTS patients exhibited higher connectivity between the following: the inferior frontal sulcus (IFS) and the right anterior cingulate cortex (ACC), and the ventral area 44 (A44v) region and the left hippocampus/parahippocampus. Also, a decreased connectivity was found between the IFS and the left inferior temporal gyrus (ITG). No other significant differences in functional connectivity were found in the other 4 functional subregions of the LIFG in the BECTS.

CONCLUSIONS

These findings provide evidence for BECTS-related functional connectivity patterns of the LIFG subregions and suggest that different subregions may be involved in different neural circuits associated with language function in the BECTS.

Enhanced Resting-State Functional Connectivity of the Nucleus Accumbens in First-Episode, Medication-Naïve Patients With Early Onset Schizophrenia

There is abundant evidence that early onset schizophrenia (EOS) is associated with abnormalities in widespread regions, including the cortical, striatal, and limbic areas. As a main component of the ventral striatum, the nucleus accumbens (NAc) is implicated in the pathology of schizophrenia. However, functional connection patterns of NAc in patients with schizophrenia, especially EOS, are seldom explored. A total of 78 first-episode, medication-naïve patients with EOS and 90 healthy controls were recruited in the present study, and resting-state, seed-based functional connectivity (FC) analyses were performed to investigate temporal correlations between NAc and the rest of the brain in the two groups. Additionally, correlation analyses were done between regions showing group differences in NAc functional integration and clinical features of EOS. Group comparison found enhanced FC of the NAc in the EOS group relative to the HCs with increased FC in the right superior temporal gyrus and left superior parietal gyrus with the left NAc region of interest (ROI) and elevated FC in left middle occipital gyrus with the right NAc ROI. No significant associations were found between FC strength and symptom severity as well as the age of the patients. Our findings reveal abnormally enhanced FC of the NAc with regions located in the temporal, parietal, and occipital areas, which were implicated in auditory/visual processing, sensorimotor integration, and cognitive functions. The results suggest disturbed relationships between regions subserving reward, salience processing, and regions subserving sensory processing as well as cognitive functions, which may deepen our understanding of the role of NAc in the pathology of EOS.

Disassociated and concurrent structural and functional abnormalities in the drug-naïve first-episode early onset schizophrenia

Schizophrenia which is an abnormally developmental disease has been widely reported to show abnormal brain structure and function. Enhanced functional integration is a predominant neural marker for brain mature. Abnormal development of structure and functional integration may be a biomarker for early diagnosis of schizophrenia. Fifty-five patients with early onset schizophrenia (EOS) and 79 healthy controls were enrolled in this study. Voxel-based morphometry (VBM) and functional connectivity density (FCD) were performed to explore gray matter volume (GMV) lesion, abnormal functional integration, and concurrent structural and functional abnormalities in the brain. Furthermore, the relationships between abnormalities structural and function and clinical characteristics were evaluated in EOS. Compared with healthy controls, EOS showed significantly decreased GMV in the bilateral OFC, frontal, temporal, occipital, parietal and limbic system. EOS also showed decreased FCD in precuneus and increased FCD in cerebellum. Moreover, we found concurrent changes of structure and function in left lateral orbitofrontal cortex (lOFC). Finally, correlation analyses did not find significant correlation between abnormal neural measurements and clinical characteristic in EOS. The results reveal disassociated and bound structural and functional abnormalities patterns in EOS suggesting structural and functional measurements play different roles in delineating the abnormal patterns of EOS. The concurrent structural and functional changes in lOFC may be a biomarker for early diagnosis of schizophrenia. Our findings will deepen our understanding of the pathophysiological mechanisms in EOS.

7T ultra-high-field neuroimaging for mental health: an emerging tool for precision psychiatry?

Given the huge symptom diversity and complexity of mental disorders, an individual approach is the most promising avenue for clinical transfer and the establishment of personalized psychiatry. However, due to technical limitations, knowledge about the neurobiological basis of mental illnesses has, to date, mainly been based on findings resulting from evaluations of average data from certain diagnostic groups. We postulate that this could change substantially through the use of the emerging ultra-high-field MRI (UHF-MRI) technology. The main advantages of UHF-MRI include high signal-to-noise ratio, resulting in higher spatial resolution and contrast and enabling individual examinations of single subjects. Thus, we used this technology to assess changes in the properties of resting-state networks over the course of therapy in a naturalistic study of two depressed patients. Significant changes in several network property measures were found in regions corresponding to prior knowledge from group-level studies. Moreover, relevant parameters were already significantly divergent in both patients at baseline. In summary, we demonstrate the feasibility of UHF-MRI for capturing individual neurobiological correlates of mental diseases. These could serve as a tool for therapy monitoring and pave the way for a truly individualized and predictive clinical approach in psychiatric care.

Resting-State Functional Connectivity Associated With Extraversion and Agreeableness in Adolescence

Although adolescence is a period in which developmental changes occur in brain connectivity, personality formation, and peer interaction, few studies have examined the neural correlates of personality dimensions related to social behavior within adolescent samples. The current study aims to investigate whether adolescents’ brain functional connectivity is associated with extraversion and agreeableness, personality dimensions linked to peer acceptance, social network size, and friendship quality. Considering sex-variant neural maturation in adolescence, we also examined sex-specific associations between personality and functional connectivity. Using resting-state functional magnetic resonance imaging (fMRI) data from a community sample of 70 adolescents aged 12–15, we examined associations between self-reported extraversion and agreeableness and seed-to-whole brain connectivity with the amygdala as a seed region of interest. Then, using 415 brain regions that correspond to 8 major brain networks and subcortex, we explored neural connectivity within brain networks and across the whole-brain. We conducted group-level multiple regression analyses with the regressors of extraversion, agreeableness, and their interactions with sex. Results demonstrated that amygdala connectivity with the postcentral gyrus, middle temporal gyrus, and the temporal pole is positively associated with extraversion in girls and negatively associated with extraversion in boys. Agreeableness was positively associated with amygdala connectivity with the middle occipital cortex and superior parietal cortex, in the same direction for boys and girls. Results of the whole-brain connectivity analysis revealed that the connectivity of the postcentral gyrus, located in the dorsal attention network, with regions in default mode network (DMN), salience/ventral attention network, and control network (CON) was associated with extraversion, with most connections showing positive associations in girls and negative associations in boys. For agreeableness, results of the within-network connectivity analysis showed that connections within the limbic network were positively associated with agreeableness in boys while negatively associated with or not associated with agreeableness in girls. Results suggest that intrinsic functional connectivity may contribute to adolescents’ individual differences in extraversion and agreeableness and highlights sex-specific neural connectivity patterns associated with the two personality dimensions. This study deepens our understanding of the neurobiological correlates of adolescent personality that may lead to different developmental trajectories of social experience.

Abnormal degree centrality in first-episode medication-free adolescent depression at rest: A functional magnetic resonance imaging study and support vector machine analysis

BACKGROUND

Depression in adolescents is more heterogeneous and less often diagnosed than depression in adults. At present, reliable approaches to differentiating between adolescents who are and are not affected by depression are lacking. This study was designed to assess voxel-level whole-brain functional connectivity changes associated with adolescent depression in an effort to define an imaging-based biomarker associated with this condition.

MATERIALS AND METHODS

In total, 71 adolescents affected by major depressive disorder (MDD) and 71 age-, sex-, and education level-matched healthy controls were subjected to resting-state functional magnetic resonance imaging (rs-fMRI) based analyses of brain voxel-wise degree centrality (DC), with a support vector machine (SVM) being used for pattern classification analyses.

RESULTS

DC patterns derived from 16-min rs-fMRI analyses were able to effectively differentiate between adolescent MDD patients and healthy controls with 95.1% accuracy (136/143), and with respective sensitivity and specificity values of 92.1% (70/76) and 98.5% (66/67) based upon DC abnormalities detected in the right cerebellum. Specifically, increased DC was evident in the bilateral insula and left lingual area of MDD patients, together with reductions in the DC values in the right cerebellum and bilateral superior parietal lobe. DC values were not significantly correlated with disease severity or duration in these patients following correction for multiple comparisons.

CONCLUSION

These results suggest that whole-brain network centrality abnormalities may be present in many brain regions in adolescent depression patients. Accordingly, these DC maps may hold value as candidate neuroimaging biomarkers capable of differentiating between adolescents who are and are not affected by MDD, although further validation of these results will be critical.

Dynamic changes of large-scale resting-state functional networks in major depressive disorder

Sliding window method is widely used to study the functional connectivity dynamics in brain networks. A key issue of this method is how to choose the window length and number of clusters across different window length. Here, we introduced a universal method to determine the optimal window length and number of clusters and applied it to study the dynamic functional network connectivity (FNC) in major depressive disorder (MDD). Specifically, we first extracted the resting-state networks (RSNs) in 27 medication-free MDD patients and 54 healthy controls using group independent component analysis (ICA), and constructed the dynamic FNC patterns for each subject in the window range of 10-80 repetition times (TRs) using sliding window method. Then, litekmeans algorithm was utilized to cluster the FNC patterns corresponding to each window length into 2-20 clusters. The optimal number of clusters was determined by voting method and the optimal window length was determined by identifying the most representative window length. Finally, 8 recurring FNC patterns regarded as FNC states were captured for further analyzing the dynamic attributes. Our results revealed that MDD patients showed increased mean dwell time and fraction of time spent in state #5, and the mean dwell time is correlated with depression symptom load. Additionally, compared with healthy controls, MDD patients had significantly reduced FNC within FPN in state #7. Our study reported a new approach to determine the optimal window length and number of clusters, which may facilitate the future study of the functional dynamics. These findings about MDD using dynamic FNC analyses provide new evidence to better understand the neuropathology of MDD.

A Multidimensional Examination of Psychopathy Traits and Gray Matter Volume in Adults

Uncovering the neurobiological abnormalities that may contribute to the manifestation of psychopathic traits is an important step toward understanding the etiology of this disorder. Although many studies have examined gray matter volume (GMV) in relation to psychopathy, few have examined how dimensions of psychopathic traits interactively relate to GMV, an approach that holds promise for parsing heterogeneity in neurobiological risk factors for this disorder. The aim of this study was to investigate the affective-interpersonal (Factor 1) and impulsive-antisocial (Factor 2) dimensions of psychopathy in relation to cortical surface and subcortical GMV in a mixed-gender, high-risk community sample with significant justice-system involvement (N = 156, 50.0% men). Cortex-wide analysis indicated that (i) the Factor 1 traits correlated negatively with GMV in two cortical clusters, one in the right rostral middle frontal region and one in the occipital lobe, and (ii) the interaction of the affective-interpersonal and impulsive-antisocial traits was negatively associated with GMV bilaterally in the parietal lobe, such that individuals high on both trait dimensions evidenced reduced GMV relative to individuals high on only one psychopathy factor. An interactive effect also emerged for bilateral amygdalar and hippocampal GMV, such that Factor 1 psychopathic traits were significantly negatively associated with GMV only at high (but not low) levels of Factor 2 traits. Results extend prior research by demonstrating the neurobiological correlates of psychopathy differ based on the presentation of Factor 1 and 2 traits.

Altered Brain Structure and Spontaneous Functional Activity in Children With Concomitant Strabismus

Strabismus occurs in about 2% of children and may result in amblyopia or lazy eyes and loss of depth perception. However, whether/how long-term strabismus shapes the brain structure and functions in children with concomitant strabismus (CS) is still unclear. In this study, a total of 26 patients with CS and 28 age-, sex-, and education-matched healthy controls (HCs) underwent structural and resting-state functional magnetic resonance imaging examination. The cortical thickness and amplitude of low-frequency fluctuation (ALFF) were calculated to assess the structural and functional plasticity in children with CS. Compared with HCs group, patients with CS showed increased cortical thickness in the precentral gyrus and angular gyrus while decreased cortical thickness in the left intraparietal sulcus, parieto-occipital sulcus, superior and middle temporal gyrus, right ventral premotor cortex, anterior insula, orbitofrontal cortex, and paracentral lobule. Meanwhile, CS patients exhibited increased ALFF in the prefrontal cortex and superior temporal gyrus, and decreased ALFF in the caudate and hippocampus. These results show that children with CS have abnormal structure and function in brain regions subserving eye movement, controls, and high-order cognitive functions. Our findings revealed the structural and functional abnormalities induced by CS and may provide new insight into the underlying neural mechanisms for CS.

Analyses of microstructural variation in the human striatum using non-negative matrix factorization

The striatum is a major subcortical connection hub that has been heavily implicated in a wide array of motor and cognitive functions. Here, we developed a normative multimodal, data-driven microstructural parcellation of the striatum using non-negative matrix factorization (NMF) based on multiple magnetic resonance imaging-based metrics (mean diffusivity, fractional anisotropy, and the ratio between T1- and T2-weighted structural scans) from the Human Connectome Project Young Adult dataset (n = 329 unrelated participants, age range: 22-35, F/M: 185/144). We further explored the biological and functional relationships of this parcellation by relating our findings to motor and cognitive performance in tasks known to involve the striatum as well as demographics. We identified 5 spatially distinct striatal components for each hemisphere. We also show the gain in component stability when using multimodal versus unimodal metrics. Our findings suggest distinct microstructural patterns in the human striatum that are largely symmetric and that relate mostly to age and sex. Our work also highlights the putative functional relevance of these striatal components to different designations based on a Neurosynth meta-analysis.

Voxel-Wise Quantitative Mapping of the Brain Association Ability

The association cortices of the brain are essential for integrating multimodal information that subserves complex and high-order cognitive functions. To delineate the changing pattern of associative cortices can provide critical insight into brain development, aging, plasticity, and disease-triggered functional abnormalities. However, how to quantitatively characterize the association capability of the brain is elusive. Here, we developed a new method of association index (Asso) at the voxel level to quantitatively characterize the brain association ability. Using the Asso method, we found high Asso values in association cortical networks, and low values in visual and limbic networks, suggesting a pattern of significant gradient distribution in neural functions. The spatial distribution patterns of Asso show high similarities across different thresholds suggesting that Asso mapping is a threshold-free method. In addition, compared with functional connectivity strength, i.e., degree centrality method, Asso mapping showed different patterns for association cortices and primary cortices. Finally, the Asso method was applied to investigate aging effects and identified similar findings with previous studies. All these results indicated that Asso can characterize the brain association patterns effectively and open a new avenue to reveal a neural basis for development, aging, and brain disorders.

Establishment of Effective Biomarkers for Depression Diagnosis With Fusion of Multiple Resting-State Connectivity Measures

Major depressive disorder (MDD) is a severe mental disorder and is lacking in biomarkers for clinical diagnosis. Previous studies have demonstrated that functional abnormalities of the unifying triple networks are the underlying basis of the neuropathology of depression. However, whether the functional properties of the triple network are effective biomarkers for the diagnosis of depression remains unclear. In our study, we used independent component analysis to define the triple networks, and resting-state functional connectivities (RSFCs), effective connectivities (EC) measured with dynamic causal modeling (DCM), and dynamic functional connectivity (dFC) measured with the sliding window method were applied to map the functional interactions between subcomponents of triple networks. Two-sample t-tests with p < 0.05 with Bonferroni correction were used to identify the significant differences between healthy controls (HCs) and MDD. Compared with HCs, the MDD showed significantly increased intrinsic FC between the left central executive network (CEN) and salience network (SAL), increased EC from the right CEN to left CEN, decreased EC from the right CEN to the default mode network (DMN), and decreased dFC between the right CEN and SAL, DMN. Moreover, by fusion of the changed RSFC, EC, and dFC as features, support vector classification could effectively distinguish the MDD from HCs. Our results demonstrated that fusion of the multiple functional connectivities measures of the triple networks is an effective way to reveal functional disruptions for MDD, which may facilitate establishing the clinical diagnosis biomarkers for depression.