Local-Global Parcellation of the Human Cerebral Cortex from Intrinsic Functional Connectivity MRI

A central goal in systems neuroscience is the parcellation of the cerebral cortex into discrete neurobiological "atoms". Resting-state functional magnetic resonance imaging (rs-fMRI) offers the possibility of in vivo human cortical parcellation. Almost all previous parcellations relied on 1 of 2 approaches. The local gradient approach detects abrupt transitions in functional connectivity patterns. These transitions potentially reflect cortical areal boundaries defined by histology or visuotopic fMRI. By contrast, the global similarity approach clusters similar functional connectivity patterns regardless of spatial proximity, resulting in parcels with homogeneous (similar) rs-fMRI signals. Here, we propose a gradient-weighted Markov Random Field (gwMRF) model integrating local gradient and global similarity approaches. Using task-fMRI and rs-fMRI across diverse acquisition protocols, we found gwMRF parcellations to be more homogeneous than 4 previously published parcellations. Furthermore, gwMRF parcellations agreed with the boundaries of certain cortical areas defined using histology and visuotopic fMRI. Some parcels captured subareal (somatotopic and visuotopic) features that likely reflect distinct computational units within known cortical areas. These results suggest that gwMRF parcellations reveal neurobiologically meaningful features of brain organization and are potentially useful for future applications requiring dimensionality reduction of voxel-wise fMRI data. Multiresolution parcellations generated from 1489 participants are publicly available (https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/brain_parcellation/Schaefer2018_LocalGlobal).

The Human Brainnetome Atlas: A New Brain Atlas Based on Connectional Architecture

The human brain atlases that allow correlating brain anatomy with psychological and cognitive functions are in transition from ex vivo histology-based printed atlases to digital brain maps providing multimodal in vivo information. Many current human brain atlases cover only specific structures, lack fine-grained parcellations, and fail to provide functionally important connectivity information. Using noninvasive multimodal neuroimaging techniques, we designed a connectivity-based parcellation framework that identifies the subdivisions of the entire human brain, revealing the in vivo connectivity architecture. The resulting human Brainnetome Atlas, with 210 cortical and 36 subcortical subregions, provides a fine-grained, cross-validated atlas and contains information on both anatomical and functional connections. Additionally, we further mapped the delineated structures to mental processes by reference to the BrainMap database. It thus provides an objective and stable starting point from which to explore the complex relationships between structure, connectivity, and function, and eventually improves understanding of how the human brain works. The human Brainnetome Atlas will be made freely available for download at http://atlas.brainnetome.org, so that whole brain parcellations, connections, and functional data will be readily available for researchers to use in their investigations into healthy and pathological states.

The neural architecture of the language comprehension network: converging evidence from lesion and connectivity analyses

While traditional models of language comprehension have focused on the left posterior temporal cortex as the neurological basis for language comprehension, lesion and functional imaging studies indicate the involvement of an extensive network of cortical regions. However, the full extent of this network and the white matter pathways that contribute to it remain to be characterized. In an earlier voxel-based lesion-symptom mapping analysis of data from aphasic patients (Dronkers et al., 2004), several brain regions in the left hemisphere were found to be critical for language comprehension: the left posterior middle temporal gyrus, the anterior part of Brodmann's area 22 in the superior temporal gyrus (anterior STG/BA22), the posterior superior temporal sulcus (STS) extending into Brodmann's area 39 (STS/BA39), the orbital part of the inferior frontal gyrus (BA47), and the middle frontal gyrus (BA46). Here, we investigated the white matter pathways associated with these regions using diffusion tensor imaging from healthy subjects. We also used resting-state functional magnetic resonance imaging data to assess the functional connectivity profiles of these regions. Fiber tractography and functional connectivity analyses indicated that the left MTG, anterior STG/BA22, STS/BA39, and BA47 are part of a richly interconnected network that extends to additional frontal, parietal, and temporal regions in the two hemispheres. The inferior occipito-frontal fasciculus, the arcuate fasciculus, and the middle and inferior longitudinal fasciculi, as well as transcallosal projections via the tapetum were found to be the most prominent white matter pathways bridging the regions important for language comprehension. The left MTG showed a particularly extensive structural and functional connectivity pattern which is consistent with the severity of the impairments associated with MTG lesions and which suggests a central role for this region in language comprehension.

Spatial Topography of Individual-Specific Cortical Networks Predicts Human Cognition, Personality, and Emotion

Resting-state functional magnetic resonance imaging (rs-fMRI) offers the opportunity to delineate individual-specific brain networks. A major question is whether individual-specific network topography (i.e., location and spatial arrangement) is behaviorally relevant. Here, we propose a multi-session hierarchical Bayesian model (MS-HBM) for estimating individual-specific cortical networks and investigate whether individual-specific network topography can predict human behavior. The multiple layers of the MS-HBM explicitly differentiate intra-subject (within-subject) from inter-subject (between-subject) network variability. By ignoring intra-subject variability, previous network mappings might confuse intra-subject variability for inter-subject differences. Compared with other approaches, MS-HBM parcellations generalized better to new rs-fMRI and task-fMRI data from the same subjects. More specifically, MS-HBM parcellations estimated from a single rs-fMRI session (10 min) showed comparable generalizability as parcellations estimated by 2 state-of-the-art methods using 5 sessions (50 min). We also showed that behavioral phenotypes across cognition, personality, and emotion could be predicted by individual-specific network topography with modest accuracy, comparable to previous reports predicting phenotypes based on connectivity strength. Network topography estimated by MS-HBM was more effective for behavioral prediction than network size, as well as network topography estimated by other parcellation approaches. Thus, similar to connectivity strength, individual-specific network topography might also serve as a fingerprint of human behavior.

Age-related reorganizational changes in modularity and functional connectivity of human brain networks

The human brain undergoes both morphological and functional modifications across the human lifespan. It is important to understand the aspects of brain reorganization that are critical in normal aging. To address this question, one approach is to investigate age-related topological changes of the brain. In this study, we developed a brain network model using graph theory methods applied to the resting-state functional magnetic resonance imaging data acquired from two groups of normal healthy adults classified by age. We found that brain functional networks demonstrated modular organization in both groups with modularity decreased with aging, suggesting less distinct functional divisions across whole brain networks. Local efficiency was also decreased with aging but not with global efficiency. Besides these brain-wide observations, we also observed consistent alterations of network properties at the regional level in the elderly, particularly in two major functional networks-the default mode network (DMN) and the sensorimotor network. Specifically, we found that measures of regional strength, local and global efficiency of functional connectivity were increased in the sensorimotor network while decreased in the DMN with aging. These results indicate that global reorganization of brain functional networks may reflect overall topological changes with aging and that aging likely alters individual brain networks differently depending on the functional properties. Moreover, these findings highly correspond to the observation of decline in cognitive functions but maintenance of primary information processing in normal healthy aging, implying an underlying compensation mechanism evolving with aging to support higher-level cognitive functioning.

Clinical and neural effects of six-week administration of oxytocin on core symptoms of autism

Autism spectrum disorder is a prevalent neurodevelopmental disorder with no established pharmacological treatment for its core symptoms. Although previous literature has shown that single-dose administration of oxytocin temporally mitigates autistic social behaviours in experimental settings, it remains in dispute whether such potentially beneficial responses in laboratories can result in clinically positive effects in daily life situations, which are measurable only in long-term observations of individuals with the developmental disorder undergoing continual oxytocin administration. Here, to address this issue, we performed an exploratory, randomized, double-blind, placebo-controlled, crossover trial including 20 high-functional adult males with autism spectrum disorder. Data obtained from 18 participants who completed the trial showed that 6-week intranasal administration of oxytocin significantly reduced autism core symptoms specific to social reciprocity, which was clinically evaluated by Autism Diagnostic Observation Scale (P = 0.034, PFDR < 0.05, Cohen's d = 0.78). Critically, the improvement of this clinical score was accompanied by oxytocin-induced enhancement of task-independent resting-state functional connectivity between anterior cingulate cortex and dorso-medial prefrontal cortex (rho = -0.60, P = 0.011), which was measured by functional magnetic resonance imaging. Moreover, using the same social-judgement task as used in our previous single-dose oxytocin trial, we confirmed that the current continual administration also significantly mitigated behavioural and neural responses during the task, both of which were originally impaired in autistic individuals (judgement tendency: P = 0.019, d = 0.62; eye-gaze effect: P = 0.03, d = 0.56; anterior cingulate activity: P = 0.00069, d = 0.97; dorso-medial prefrontal activity: P = 0.0014, d = 0.92; all, PFDR < 0.05). Furthermore, despite its longer administration, these effect sizes of the 6-week intervention were not larger than those seen in our previous single-dose intervention. These findings not only provide the evidence for clinically beneficial effects of continual oxytocin administration on the core social symptoms of autism spectrum disorder with suggesting its underlying biological mechanisms, but also highlight the necessity to seek optimal regimens of continual oxytocin treatment in future studies.

The Resting Brain of Alcoholics

Chronic alcohol consumption affects multiple cognitive processes supported by far-reaching cerebral networks. To identify neurofunctional mechanisms underlying selective deficits, 27 sober alcoholics and 26 age-matched controls underwent resting-state functional magnetic resonance imaging and neuropsychological testing. Functional connectivity analysis assessed the default mode network (DMN); integrative executive control (EC), salience (SA), and attention (AT) networks; primary somatosensory, auditory, and visual (VI) input networks; and subcortical reward (RW) and emotion (EM) networks. The groups showed an extensive overlap of intrinsic connectivity in all brain networks examined, suggesting overall integrity of large-scale functional networks. Despite these similar patterns, connectivity analyses identified network-specific differences of weaker within-network connectivity and expanded connectivity to regions outside the main networks in alcoholics compared with controls. For AT and VI networks, better task performance was related to expanded connectivity in alcoholism, supporting the concept of network expansion as a neural mechanism for functional compensation. For default mode, SA, RW, and EC networks, both weaker within-network and expanded outside-network connectivity correlated with poorer performance and mood. Current smoking contributed to some of these abnormalities in connectivity. The observed pattern of resting-state connectivity might reflect neural vulnerability of intrinsic networking in alcoholics and suggests a mechanism to explain signature impairments in EM, RW evaluation, and EC ability.

Ventral tegmental area/midbrain functional connectivity and response to antipsychotic medication in schizophrenia

Medication management in schizophrenia is a lengthy process, as the lack of clinical response can only be confirmed after at least 4 weeks of antipsychotic treatment at a therapeutic dose. Thus, there is a clear need for the discovery of biomarkers that have the potential to accelerate the management of treatment. Using resting-state functional MRI, we examined the functional connectivity of the ventral tegmental area (VTA), the origin of the mesocorticolimbic dopamine projections, in 21 healthy controls and 21 unmedicated patients with schizophrenia at baseline (pre-treatment) and after 1 week of treatment with the antipsychotic drug risperidone (1-week post-treatment). Group-level functional connectivity maps were obtained and group differences in connectivity were assessed on the groups' participant-level functional connectivity maps. We also examined the relationship between pre-treatment/1-week post-treatment functional connectivity and treatment response. Compared with controls, patients exhibited significantly reduced pre-treatment VTA/midbrain connectivity to multiple cortical and subcortical regions, including the dorsal anterior cingulate cortex (dACC) and thalamus. After 1 week of treatment, VTA/midbrain connectivity to bilateral regions of the thalamus was re-established. Pre-treatment VTA/midbrain connectivity strength to dACC was positively correlated with good response to a 6-week course of risperidone, whereas pre-treatment VTA/midbrain connectivity strength to the default mode network was negatively correlated. Our findings suggest that VTA/midbrain resting-state connectivity may be a useful biomarker for the prediction of treatment response.

Network dysfunction in Alzheimer's disease: refining the disconnection hypothesis

Much effort in recent years has focused on understanding the effects of Alzheimer's disease (AD) on neural function. This effort has resulted in an enormous number of papers describing different facets of the functional derangement seen in AD. A particularly important tool for these investigations has been resting-state functional connectivity. Attempts to comprehensively synthesize resting-state functional connectivity results have focused on the potential utility of functional connectivity as a biomarker for disease risk, disease staging, or prognosis. While these are all appropriate uses of this technique, the purpose of this review is to examine how functional connectivity disruptions inform our understanding of AD pathophysiology. Here, we examine the rationale and methodological considerations behind functional connectivity studies and then provide a critical review of the existing literature. In conclusion, we propose a hypothesis regarding the development and spread of functional connectivity deficits seen in AD.

Individual-Specific Areal-Level Parcellations Improve Functional Connectivity Prediction of Behavior

Resting-state functional magnetic resonance imaging (rs-fMRI) allows estimation of individual-specific cortical parcellations. We have previously developed a multi-session hierarchical Bayesian model (MS-HBM) for estimating high-quality individual-specific network-level parcellations. Here, we extend the model to estimate individual-specific areal-level parcellations. While network-level parcellations comprise spatially distributed networks spanning the cortex, the consensus is that areal-level parcels should be spatially localized, that is, should not span multiple lobes. There is disagreement about whether areal-level parcels should be strictly contiguous or comprise multiple noncontiguous components; therefore, we considered three areal-level MS-HBM variants spanning these range of possibilities. Individual-specific MS-HBM parcellations estimated using 10 min of data generalized better than other approaches using 150 min of data to out-of-sample rs-fMRI and task-fMRI from the same individuals. Resting-state functional connectivity derived from MS-HBM parcellations also achieved the best behavioral prediction performance. Among the three MS-HBM variants, the strictly contiguous MS-HBM exhibited the best resting-state homogeneity and most uniform within-parcel task activation. In terms of behavioral prediction, the gradient-infused MS-HBM was numerically the best, but differences among MS-HBM variants were not statistically significant. Overall, these results suggest that areal-level MS-HBMs can capture behaviorally meaningful individual-specific parcellation features beyond group-level parcellations. Multi-resolution trained models and parcellations are publicly available (https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/brain_parcellation/Kong2022_ArealMSHBM).

Neural traces of stress: cortisol related sustained enhancement of amygdala-hippocampal functional connectivity

Stressful experiences modulate neuro-circuitry function, and the temporal trajectory of these alterations, elapsing from early disturbances to late recovery, heavily influences resilience and vulnerability to stress. Such effects of stress may depend on processes that are engaged during resting-state, through active recollection of past experiences and anticipation of future events, all known to involve the default mode network (DMN). By inducing social stress and acquiring resting-state functional magnetic resonance imaging (fMRI) before stress, immediately following it, and 2 h later, we expanded the time-window for examining the trajectory of the stress response. Throughout the study repeated cortisol samplings and self-reports of stress levels were obtained from 51 healthy young males. Post-stress alterations were investigated by whole brain resting-state functional connectivity (rsFC) of two central hubs of the DMN: the posterior cingulate cortex (PCC) and hippocampus. Results indicate a ’recovery’ pattern of DMN connectivity, in which all alterations, ascribed to the intervening stress, returned to pre-stress levels. The only exception to this pattern was a stress-induced rise in amygdala-hippocampal connectivity, which was sustained for as long as 2 h following stress induction. Furthermore, this sustained enhancement of limbic connectivity was inversely correlated to individual stress-induced cortisol responsiveness (AUCi) and characterized only the group lacking such increased cortisol (i.e., non-responders). Our observations provide evidence of a prolonged post-stress response profile, characterized by both the comprehensive balance of most DMN functional connections and the distinct time and cortisol dependent ascent of intra-limbic connectivity. These novel insights into neuro-endocrine relations are another milestone in the ongoing search for individual markers in stress-related psychopathologies.

Resting-state functional connectivity and nicotine addiction: prospects for biomarker development

Given conceptual frameworks of addiction as a disease of intercommunicating brain networks, examinations of network interactions may provide a holistic characterization of addiction-related dysfunction. One such methodological approach is the examination of resting-state functional connectivity, which quantifies correlations in low-frequency fluctuations of the blood oxygen level-dependent magnetic resonance imaging signal between disparate brain regions in the absence of task performance. Here, evidence of differentiated effects of chronic nicotine exposure, which reduces the efficiency of network communication across the brain, and acute nicotine exposure, which increases connectivity within specific limbic circuits, is discussed. Several large-scale resting networks, including the salience, default, and executive control networks, have also been implicated in nicotine addiction. The dynamics of connectivity changes among and between these large-scale networks during nicotine withdrawal and satiety provide a heuristic framework with which to characterize the neurobiological mechanism of addiction. The ability to simultaneously quantify effects of both chronic (trait) and acute (state) nicotine exposure provides a platform to develop a neuroimaging-based addiction biomarker. While such development remains in its early stages, evidence of coherent modulations in resting-state functional connectivity at various stages of nicotine addiction suggests potential network interactions on which to focus future addiction biomarker development.

Intrinsic functional network organization in high-functioning adolescents with autism spectrum disorder

Converging theories and data suggest that atypical patterns of functional and structural connectivity are a hallmark neurobiological feature of autism. However, empirical studies of functional connectivity, or, the correlation of MRI signal between brain regions, have largely been conducted during task performance and/or focused on group differences within one network [e.g., the default mode network (DMN)]. This narrow focus on task-based connectivity and single network analyses precludes investigation of whole-brain intrinsic network organization in autism. To assess whole-brain network properties in adolescents with autism, we collected resting-state functional connectivity MRI (rs-fcMRI) data from neurotypical (NT) adolescents and adolescents with autism spectrum disorder (ASD). We used graph theory metrics on rs-fcMRI data with 34 regions of interest (i.e., nodes) that encompass four different functionally defined networks: cingulo-opercular, cerebellar, fronto-parietal, and DMN (Fair etal., 2009). Contrary to our hypotheses, network analyses revealed minimal differences between groups with one exception. Betweenness centrality, which indicates the degree to which a seed (or node) functions as a hub within and between networks, was greater for participants with autism for the right lateral parietal (RLatP) region of the DMN. Follow-up seed-based analyses demonstrated greater functional connectivity in ASD than NT groups between the RLatP seed and another region of the DMN, the anterior medial prefrontal cortex. Greater connectivity between these regions was related to lower ADOS (Autism Diagnostic Observation Schedule) scores (i.e., lower impairment) in autism. These findings do not support current theories of underconnectivity in autism, but, rather, underscore the need for future studies to systematically examine factors that can influence patterns of intrinsic connectivity such as autism severity, age, and head motion.

GABAergic neuroactive steroids and resting-state functional connectivity in postpartum depression: a preliminary study

Postpartum depression (PPD) affects up to 1 in 8 women. The early postpartum period is characterized by a downward physiological shift from relatively elevated levels of sex steroids during pregnancy to diminished levels after parturition. Sex steroids influence functional brain connectivity in healthy non-puerperal subjects. This study tests the hypothesis that PPD is associated with attenuation of resting-state functional connectivity (rs-fc) within corticolimbic regions implicated in depression and alterations in neuroactive steroid concentrations as compared to healthy postpartum women. Subjects (n = 32) were prospectively evaluated during pregnancy and in the postpartum with repeated plasma neuroactive steroid measurements and mood and psychosocial assessments. Healthy comparison subjects (HCS) and medication-free subjects with unipolar PPD (PPD) were examined using functional magnetic resonance imaging (fMRI) within 9 weeks of delivery. We performed rs-fc analysis with seeds placed in the anterior cingulate cortex (ACC), and bilateral amygdala (AMYG), hippocampi (HIPP) and dorsolateral prefrontal cortices (DLPFCs). Postpartum rs-fc and perinatal neuroactive steroid plasma concentrations, quantified by liquid chromatography/mass spectrometry, were compared between groups. PPD subjects showed attenuation of connectivity for each of the tested regions (i.e. ACC, AMYG, HIPP and DLPFC) and between corticocortical and corticolimbic regions vs. HCS. Perinatal concentrations of pregnanolone, allopregnanolone and pregnenolone were not different between groups. This is the first report of a disruption in the rs-fc patterns in medication-free subjects with PPD. This disruption may contribute to the development of PPD, at a time of falling neuroactive steroid concentrations.

Default-mode network functional connectivity is closely related to metabolic activity

Over the last decade, the brain's default‐mode network (DMN) and its function has attracted a lot of attention in the field of neuroscience. However, the exact underlying mechanisms of DMN functional connectivity, or more specifically, the blood‐oxygen level‐dependent (BOLD) signal, are still incompletely understood. In the present study, we combined 2‐deoxy‐2‐[¹⁸F]fluoroglucose positron emission tomography (FDG‐PET), proton magnetic resonance spectroscopy (¹H‐MRS), and resting‐state functional magnetic resonance imaging (rs‐fMRI) to investigate more directly the association between local glucose consumption, local glutamatergic neurotransmission and DMN functional connectivity during rest. The results of the correlation analyzes using the dorsal posterior cingulate cortex (dPCC) as seed region showed spatial similarities between fluctuations in FDG‐uptake and fluctuations in BOLD signal. More specifically, in both modalities the same DMN areas in the inferior parietal lobe, angular gyrus, precuneus, middle, and medial frontal gyrus were positively correlated with the dPCC. Furthermore, we could demonstrate that local glucose consumption in the medial frontal gyrus, PCC and left angular gyrus was associated with functional connectivity within the DMN. We did not, however, find a relationship between glutamatergic neurotransmission and functional connectivity. In line with very recent findings, our results lend further support for a close association between local metabolic activity and functional connectivity and provide further insights towards a better understanding of the underlying mechanism of the BOLD signal. Hum Brain Mapp 36:2027–2038, 2015. © 2015 Wiley Periodicals, Inc.

Frontostriatal circuits, resting state functional connectivity and cognitive control in internet gaming disorder

Converging evidence has identified cognitive control deficits in internet gaming disorder (IGD). Recently, mounting evidence had revealed that resting state functional connectivity (RSFC) and structural connectivity of frontostriatal circuits could modulate cognitive control in healthy individuals. Unfortunately, relatively little is known about the thoroughly circuit-level characterization of the frontostriatal pathways (both the dorsal and ventral striatum) during resting-state and their association with cognitive control in IGD. In the current study, the differences of striatum volume and RSFC networks were investigated between 43 young IGD individuals and 44 healthy controls. Meanwhile, cognitive control deficits were assessed by Stroop task performances. The neuroimaging findings were then correlated with the Stroop task behaviors. In IGD subjects, we demonstrated an increased volume of right caudate and nucleus accumbens (NAc) as well as reduced RSFC strength of dorsal prefrontal cortex (DLPFC)-caudate and orbitofrontal cortex (OFC)-NAc. NAc volumes were positively correlated with internet addiction test scores in IGD. The caudate volume and DLPFC-caudate RSFC was correlated with the impaired cognitive control (more incongruent errors in Stroop task) in IGD. Consistent with substance use disorder (SUD) findings, we detected striatum volume and frontostriatal circuits RSFC differences between IGD and healthy controls, which provided evidence of some degree of the similarity between IGD and SUD. More importantly, the cognitive control deficits in IGD were correlated with the reduced frontostrital RSFC strength. It is hoped that our results could shed insight on the neurobiological mechanisms of IGD and suggest potential novel therapeutic targets for treatment.

Down-regulation of amygdala and insula functional circuits by varenicline and nicotine in abstinent cigarette smokers

BACKGROUND

Although the amygdala and insula are regarded as critical neural substrates perpetuating cigarette smoking, little is known about their circuit-level interactions with interconnected regions during nicotine withdrawal or following pharmacotherapy administration. To elucidate neurocircuitry associated with early smoking abstinence, we examined the impact of varenicline and nicotine, two modestly efficacious pharmacologic cessation aids, on amygdala- and insula-centered circuits using resting-state functional connectivity (rsFC).

METHODS

In a functional magnetic resonance imaging study employing a two-drug, placebo-controlled design, 24 overnight-abstinent smokers and 20 nonsmokers underwent ∼17 days of varenicline and placebo pill administration and were scanned, on different days under each condition, wearing a transdermal nicotine or placebo patch. We examined the impact of varenicline and nicotine (both alone and in combination) on amygdala- and insula-centered rsFC using seed-based assessments.

RESULTS

Beginning with a functionally defined amygdala seed, we observed that rsFC strength in an amygdala-insula circuit was down-regulated by varenicline and nicotine in abstinent smokers. Using this identified insula region as a new seed, both drugs similarly decreased rsFC between the insula and constituents of the canonical default-mode network (posterior cingulate cortex, ventromedial/dorsomedial prefrontal cortex, parahippocampus). Drug-induced rsFC modulations were critically linked with nicotine withdrawal, as similar effects were not detected in nonsmokers.

CONCLUSIONS

These results suggest that nicotine withdrawal is associated with elevated amygdala-insula and insula-default-mode network interactions. As these potentiated interactions were down-regulated by two pharmacotherapies, this effect may be a characteristic shared by pharmacologic agents promoting smoking cessation. Decreased rsFC in these circuits may contribute to amelioration of subjective withdrawal symptoms.

Classification of ADHD children through multimodal magnetic resonance imaging

Attention deficit/hyperactivity disorder (ADHD) is one of the most common diseases in school-age children. To date, the diagnosis of ADHD is mainly subjective and studies of objective diagnostic method are of great importance. Although many efforts have been made recently to investigate the use of structural and functional brain images for the diagnosis purpose, few of them are related to ADHD. In this paper, we introduce an automatic classification framework based on brain imaging features of ADHD patients and present in detail the feature extraction, feature selection, and classifier training methods. The effects of using different features are compared against each other. In addition, we integrate multimodal image features using multi-kernel learning (MKL). The performance of our framework has been validated in the ADHD-200 Global Competition, which is a world-wide classification contest on the ADHD-200 datasets. In this competition, our classification framework using features of resting-state functional connectivity (FC) was ranked the 6th out of 21 participants under the competition scoring policy and performed the best in terms of sensitivity and J-statistic.

I remember you: a role for memory in social cognition and the functional neuroanatomy of their interaction

Remembering events from the personal past (autobiographical memory) and inferring the thoughts and feelings of other people (mentalizing) share a neural substrate. The shared functional neuroanatomy of these processes has been demonstrated in a meta-analysis of independent task domains (Spreng, Mar & Kim, 2009) and within subjects performing both tasks (Rabin, Gilboa, Stuss, Mar, & Rosenbaum, 2010; Spreng & Grady, 2010). Here, we examine spontaneous low-frequency fluctuations in fMRI BOLD signal during rest from two separate regions key to memory and mentalizing, the left hippocampus and right temporal parietal junction, respectively. Activity in these two regions was then correlated with the entire brain in a resting-state functional connectivity analysis. Although the left hippocampus and right temporal parietal junction were not correlated with each other, both were correlated with a distributed network of brain regions. These regions were consistent with the previously observed overlap between autobiographical memory and mentalizing evoked brain activity found in past studies. Reliable patterns of overlap included the superior temporal sulcus, anterior temporal lobe, lateral inferior parietal cortex (angular gyrus), posterior cingulate cortex, dorsomedial and ventral prefrontal cortex, inferior frontal gyrus, and the amygdala. We propose that the functional overlap facilitates the integration of personal and interpersonal information and provides a means for personal experiences to become social conceptual knowledge. This knowledge, in turn, informs strategic social behavior in support of personal goals. In closing, we argue for a new perspective within social cognitive neuroscience, emphasizing the importance of memory in social cognition.

Functional connectivity in autosomal dominant and late-onset Alzheimer disease

IMPORTANCE

Autosomal dominant Alzheimer disease (ADAD) is caused by rare genetic mutations in 3 specific genes in contrast to late-onset Alzheimer disease (LOAD), which has a more polygenetic risk profile.

OBJECTIVE

To assess the similarities and differences in functional connectivity changes owing to ADAD and LOAD.

DESIGN, SETTING, AND PARTICIPANTS

We analyzed functional connectivity in multiple brain resting state networks (RSNs) in a cross-sectional cohort of participants with ADAD (n = 79) and LOAD (n = 444), using resting-state functional connectivity magnetic resonance imaging at multiple international academic sites.

MAIN OUTCOMES AND MEASURES

For both types of AD, we quantified and compared functional connectivity changes in RSNs as a function of dementia severity measured by the Clinical Dementia Rating Scale. In ADAD, we qualitatively investigated functional connectivity changes with respect to estimated years from onset of symptoms within 5 RSNs.

RESULTS

A decrease in functional connectivity with increasing Clinical Dementia Rating scores were similar for both LOAD and ADAD in multiple RSNs. Ordinal logistic regression models constructed in one type of Alzheimer disease accurately predicted clinical dementia rating scores in the other, further demonstrating the similarity of functional connectivity loss in each disease type. Among participants with ADAD, functional connectivity in multiple RSNs appeared qualitatively lower in asymptomatic mutation carriers near their anticipated age of symptom onset compared with asymptomatic mutation noncarriers.

CONCLUSIONS AND RELEVANCE

Resting-state functional connectivity magnetic resonance imaging changes with progressing AD severity are similar between ADAD and LOAD. Resting-state functional connectivity magnetic resonance imaging may be a useful end point for LOAD and ADAD therapy trials. Moreover, the disease process of ADAD may be an effective model for the LOAD disease process.

Brain Events Underlying Episodic Memory Changes in Aging: A Longitudinal Investigation of Structural and Functional Connectivity

Episodic memories are established and maintained by close interplay between hippocampus and other cortical regions, but degradation of a fronto-striatal network has been suggested to be a driving force of memory decline in aging. We wanted to directly address how changes in hippocampal-cortical versus striatal-cortical networks over time impact episodic memory with age. We followed 119 healthy participants (20-83 years) for 3.5 years with repeated tests of episodic verbal memory and magnetic resonance imaging for quantification of functional and structural connectivity and regional brain atrophy. While hippocampal-cortical functional connectivity predicted memory change in young, changes in cortico-striatal functional connectivity were related to change in recall in older adults. Within each age group, effects of functional and structural connectivity were anatomically closely aligned. Interestingly, the relationship between functional connectivity and memory was strongest in the age ranges where the rate of reduction of the relevant brain structure was lowest, implying selective impacts of the different brain events on memory. Together, these findings suggest a partly sequential and partly simultaneous model of brain events underlying cognitive changes in aging, where different functional and structural events are more or less important in various time windows, dismissing a simple uni-factorial view on neurocognitive aging.

Early life stress modulates amygdala-prefrontal functional connectivity: implications for oxytocin effects

Recent evidence suggests that early life stress (ELS) changes stress reactivity via reduced resting state functional connectivity (rs-FC) between amygdala and the prefrontal cortex. Oxytocin (OXT) modulates amygdala connectivity and attenuates responses to psychosocial stress, but its effect appears to be moderated by ELS. Here we first investigate the effect of ELS on amygdala-prefrontal rs-FC, and examine whether ELS-associated changes of rs-FC in this neural circuit predict its response to psychosocial stress. Secondly, we explore the joint effect of OXT and ELS on the amygdala-prefrontal circuit. Eighteen healthy young males participated in a resting-state fMRI study of OXT effects using a double-blind, randomized, placebo-controlled, within-subject crossover design. We measured the rs-FC to bilateral amygdalae and subsequently assessed changes of state anxiety and prefrontal responses to psychosocial stress. Multiple linear regressions showed that ELS, specifically emotional abuse, predicted reduced rs-FC between the right amygdala and pregenual anterior cingulate cortex (pgACC), which in turn predicted elevated state anxiety after psychosocial stress. In subjects with lower ELS scores, stronger pgACC-amygdala rs-FC predicted stronger pgACC deactivation during the psychosocial stress task, and this rest-task interaction was attenuated by OXT. In subjects with higher ELS scores however, the rest-task interaction was altered and OXT showed no significant effect. These findings highlight that ELS reduces pgACC-amygdala rs-FC and alters how rs-FC of this circuit predicts its stress responsiveness. Such changes in pgACC-amygdala functional dynamics may underlie the altered sensitivity to the effects of OXT after ELS.

Functional reorganization of intra- and internetwork connectivity in major depressive disorder after electroconvulsive therapy

Electroconvulsive therapy (ECT) is an effective and rapid treatment for major depressive disorder (MDD). However, the neurobiological underpinnings of ECT are still largely unknown. Recent studies have identified dysregulated brain networks in MDD. Therefore, we hypothesized that ECT may improve MDD symptoms through reorganizing these networks. To test this hypothesis, we used resting-state functional connectivity to investigate changes to the intra- and internetwork architecture of five reproducible resting-state networks: the default mode network (DMN), dorsal attention network (DAN), executive control network (CON), salience network (SAL), and sensory-motor network. Twenty-three MDD patients were assessed before and after ECT, along with 25 sex-, age-, and education-matched healthy controls. At the network level, enhanced intranetwork connectivities were found in the CON in MDD patients after ECT. Furthermore, enhanced internetwork connectivities between the DMN and SAL, and between the CON and DMN, DAN, and SAL were also identified. At the nodal level, the posterior cingulate cortex had increased connections with the left posterior cerebellum, right posterior intraparietal sulcus (rpIPS), and right anterior prefrontal cortex. The rpIPS had increased connections with the medial PFC (mPFC) and left anterior cingulate cortex. The left lateral parietal had increased connections with the dorsal mPFC (dmPFC), left anterior prefrontal cortex, and right anterior cingulate cortex. The dmPFC had increased connection with the left anterolateral prefrontal cortex. Our findings indicate that enhanced interactions in intra- and internetworks may contribute to the ECT response in MDD patients. These findings provide novel and important insights into the neurobiological mechanisms underlying ECT.

Migraine classification using magnetic resonance imaging resting-state functional connectivity data

Background This study used machine-learning techniques to develop discriminative brain-connectivity biomarkers from resting-state functional magnetic resonance neuroimaging ( rs-fMRI) data that distinguish between individual migraine patients and healthy controls. Methods This study included 58 migraine patients (mean age = 36.3 years; SD = 11.5) and 50 healthy controls (mean age = 35.9 years; SD = 11.0). The functional connections of 33 seeded pain-related regions were used as input for a brain classification algorithm that tested the accuracy of determining whether an individual brain MRI belongs to someone with migraine or to a healthy control. Results The best classification accuracy using a 10-fold cross-validation method was 86.1%. Resting functional connectivity of the right middle temporal, posterior insula, middle cingulate, left ventromedial prefrontal and bilateral amygdala regions best discriminated the migraine brain from that of a healthy control. Migraineurs with longer disease durations were classified more accurately (>14 years; 96.7% accuracy) compared to migraineurs with shorter disease durations (≤14 years; 82.1% accuracy). Conclusions Classification of migraine using rs-fMRI provides insights into pain circuits that are altered in migraine and could potentially contribute to the development of a new, noninvasive migraine biomarker. Migraineurs with longer disease burden were classified more accurately than migraineurs with shorter disease burden, potentially indicating that disease duration leads to reorganization of brain circuitry.

Delineating functional segregations of the human middle temporal gyrus with resting-state functional connectivity and coactivation patterns

Although the middle temporal gyrus (MTG) has been parcellated into subregions with distinguished anatomical connectivity patterns, whether the structural topography of MTG can inform functional segregations of this area remains largely unknown. Accumulating evidence suggests that the brain's underlying organization and function can be directly and effectively delineated with resting-state functional connectivity (RSFC) by identifying putative functional boundaries between cortical areas. Here, RSFC profiles were used to explore functional segregations of the MTG and defined four subregions from anterior to posterior in two independent datasets, which showed a similar pattern with MTG parcellation scheme obtained using anatomical connectivity. The functional segregations of MTG were further supported by whole brain RSFC, coactivation, and specific RFSC, and coactivation mapping. Furthermore, the fingerprint with predefined 10 networks and functional characterizations of each subregion using meta-analysis also identified functional distinction between subregions. The specific connectivity analysis and functional characterization indicated that the bilateral most anterior subregions mainly participated in social cognition and semantic processing; the ventral middle subregions were involved in social cognition in left hemisphere and auditory processing in right hemisphere; the bilateral ventro-posterior subregions participated in action observation, whereas the left subregion was also involved in semantic processing; both of the dorsal subregions in superior temporal sulcus were involved in language, social cognition, and auditory processing. Taken together, our findings demonstrated MTG sharing similar structural and functional topographies and provide more detailed information about the functional organization of the MTG, which may facilitate future clinical and cognitive research on this area.