Consistency and functional specialization in the default mode brain network

Prognostic neuroimaging biomarkers of trauma-related psychopathology: resting-state fMRI shortly after trauma predicts future PTSD and depression symptoms in the AURORA study

Neurobiological markers of future susceptibility to posttraumatic stress disorder (PTSD) may facilitate identification of vulnerable individuals in the early aftermath of trauma. Variability in resting-state networks (RSNs), patterns of intrinsic functional connectivity across the brain, has previously been linked to PTSD, and may thus be informative of PTSD susceptibility. The present data are part of an initial analysis from the AURORA study, a longitudinal, multisite study of adverse neuropsychiatric sequalae. Magnetic resonance imaging (MRI) data from 109 recently (i.e., ~2 weeks) traumatized individuals were collected and PTSD and depression symptoms were assessed at 3 months post trauma. We assessed commonly reported RSNs including the default mode network (DMN), central executive network (CEN), and salience network (SN). We also identified a proposed arousal network (AN) composed of a priori brain regions important for PTSD: the amygdala, hippocampus, mamillary bodies, midbrain, and pons. Primary analyses assessed whether variability in functional connectivity at the 2-week imaging timepoint predicted 3-month PTSD symptom severity. Left dorsolateral prefrontal cortex (DLPFC) to AN connectivity at 2 weeks post trauma was negatively related to 3-month PTSD symptoms. Further, right inferior temporal gyrus (ITG) to DMN connectivity was positively related to 3-month PTSD symptoms. Both DLPFC-AN and ITG-DMN connectivity also predicted depression symptoms at 3 months. Our results suggest that, following trauma exposure, acutely assessed variability in RSN connectivity was associated with PTSD symptom severity approximately two and a half months later. However, these patterns may reflect general susceptibility to posttraumatic dysfunction as the imaging patterns were not linked to specific disorder symptoms, at least in the subacute/early chronic phase. The present data suggest that assessment of RSNs in the early aftermath of trauma may be informative of susceptibility to posttraumatic dysfunction, with future work needed to understand neural markers of long-term (e.g., 12 months post trauma) dysfunction. Furthermore, these findings are consistent with neural models suggesting that decreased top-down cortico-limbic regulation and increased network-mediated fear generalization may contribute to ongoing dysfunction in the aftermath of trauma.

Statistical and Machine Learning Link Selection Methods for Brain Functional Networks: Review and Comparison

Network-based representations have introduced a revolution in neuroscience, expanding the understanding of the brain from the activity of individual regions to the interactions between them. This augmented network view comes at the cost of high dimensionality, which hinders both our capacity of deciphering the main mechanisms behind pathologies, and the significance of any statistical and/or machine learning task used in processing this data. A link selection method, allowing to remove irrelevant connections in a given scenario, is an obvious solution that provides improved utilization of these network representations. In this contribution we review a large set of statistical and machine learning link selection methods and evaluate them on real brain functional networks. Results indicate that most methods perform in a qualitatively similar way, with NBS (Network Based Statistics) winning in terms of quantity of retained information, AnovaNet in terms of stability and ExT (Extra Trees) in terms of lower computational cost. While machine learning methods are conceptually more complex than statistical ones, they do not yield a clear advantage. At the same time, the high heterogeneity in the set of links retained by each method suggests that they are offering complementary views to the data. The implications of these results in neuroscience tasks are finally discussed.

A common genetic variant in fatty acid amide hydrolase is linked to alterations in fear extinction neural circuitry in a racially diverse, nonclinical sample of adults

Poor fear extinction learning and recall are linked to the development of fear-based disorders, like posttraumatic stress disorder, and are associated with aberrant activation of fear-related neural circuitry. This includes greater amygdala activation during extinction learning and lesser hippocampal and ventromedial prefrontal cortex (vmPFC) activation during recall. Emerging data indicate that genetic variation in fatty acid amide hydrolase (FAAH C385A; rs324420) is associated with increased peripheral endocannabinoid (eCB) levels and lesser threat-related amygdala reactivity. Preclinical studies link increased eCB signaling to better extinction learning and recall, thus FAAH C385A may protect against the development of trauma-related psychopathology by facilitating extinction learning. However, how this FAAH variant affects fear extinction neural circuitry remains unknown. In the present study, we used a novel, immersive-reality fear extinction paradigm paired with functional neuroimaging to assess FAAH C385A effects on fear-related neural circuitry and conditioned fear responding (US expectancy ratings, subjective units of distress, and skin conductance responding) in healthy adults from an urban area (Detroit, MI; N = 59; C/C = 35, A-carrier = 24). We found lesser amygdala activation in A-allele carriers, compared to C/C homozygotes, during early extinction recall. Likewise, we found lesser dorsal anterior cingulate cortex and greater hippocampus activation in early extinction learning in A-carriers compared to C/C homozygotes. We found no effects of FAAH C385A on vmPFC activation or behavioral fear indices. These data support and extend previous findings that FAAH genetic variation, associated with increased eCB signaling and subsequent enhanced fear extinction, may predict individual differences in successful fear learning.

Audiovisual working memory and association with resting-state regional homogeneity

Multisensory processing is a prevalent research issue. However, multisensory working memory research has received inadequate attention. The present study aimed to investigate the behavioral performance of an audiovisual working memory task and its association with resting-state functional magnetic resonance imaging (fMRI) regional homogeneity (ReHo). A total of 128 healthy participants were enrolled in this study. The participants completed a modified Sternberg working memory task using complex auditory and visual objects as materials involved in different encoding conditions, including semantically congruent audiovisual, semantically incongruent audiovisual, and single modality of auditory or visual object encoding. Two subgroups received resting-state fMRI scans according to their behavioral performances. The results showed that the semantically congruent audiovisual object encoding sped up the later unisensory memory recognition in this task. Moreover, the high behavioral performance (response time, RT) group showed increased ReHo in the executive control network (ECN) and decreased ReHo in the default mode network (DMN) and saline network (SN). In addition, resting-state ReHo values in the ECN nodes (e.g., middle frontal gyrus and superior frontal gyrus) was correlated with RT. These findings suggested that semantically congruent audiovisual processing in working memory was superior to unisensory memory recognition and may be involved in the different functional networks such as ECN.

Safety learning and the Pavlovian conditioned inhibition of fear in humans: Current state and future directions

Safety learning occurs when an otherwise neutral stimulus comes to signal the absence of threat, allowing organisms to use safety information to inhibit fear and anxiety in nonthreatening environments. Although it continues to emerge as a topic of relevance in biological and clinical psychology, safety learning remains inconsistently defined and under-researched. Here, we analyse the Pavlovian conditioned inhibition paradigm and its application to the study of safety learning in humans. We discuss existing studies; address outstanding theoretical considerations; and identify prospects for its further application. Though Pavlovian conditioned inhibition presents a theoretically sound model of safety learning, it has been investigated infrequently, with decade-long interims between some studies, and notable methodological variability. Consequently, we argue that the full potential of conditioned inhibition as a model for human safety learning remains untapped, and propose that it could be revisited as a framework for addressing timely questions in the behavioural and clinical sciences.

Trait self-control mediates the association between resting-state neural correlates and emotional well-being in late adolescence

Trait self-control (TSC), defined as the capacity to alter predominant response to promote desirable long-term goals, has been found to facilitate emotional well-being (EWB). However, the neural correlates underlying this association remain unclear. The present study estimated resting-state brain activity and connectivity with amplitude of low-frequency fluctuations (ALFFs) and resting-state functional connectivity (rsFC) among late adolescents. Whole-brain correlation analysis showed that higher TSC was associated with increased ALFFs in regions within the executive control network (inferior frontal gyrus, IFG) and the salience network (anterior insula, AI) and decreased ALFF in regions (e.g. medial frontal gyrus, MFG; posterior cingulate, PC) within the default-mode network (DMN). TSC was also linked with the integration (e.g. increased IFG-PC connectivity) and segregation (e.g. decreased AI-MFG connectivity) among brain networks. Mediation analysis indicated that TSC totally mediated the links from the IFG and the precuneus, FC of the AI and regions of the DMN (e.g. bilateral PC and MFG), to EWB. Additionally, ALFF in the IFG and the MFG could predict negative affect in the pandemic through TSC. These findings suggest that TSC is involved in several regions and functional organizations within and between brain networks and mediated the association between neural correlates and emotional wellness in adolescence.

Differences between the child and adult brain in the local functional structure of the cerebral cortex

Imaging studies on neuronal network formation provide relevant information as to how the brain matures during adolescence. We used a novel imaging approach combining well-established MRI measures of local functional connectivity that jointly provide qualitatively different information relating to the functional structure of the cerebral cortex. To investigate the adolescent transition into adulthood, we comparatively assessed 169 preadolescents aged 8-12 years and 121 healthy adults. Whole-brain functional connectivity maps were generated using multi-distance measures of intracortical neural activity coupling defined within iso-distant local areas. Such Iso-Distant Average Correlation (IDAC) measures therefore represent the average temporal correlation of a given brain unit, or voxel, with other units situated at increasingly separated iso-distant intervals. The results indicated that between-group differences in the functional structure of the cerebral cortex are extensive and implicate part of the lateral prefrontal cortex, a medial frontal/anterior cingulate region, the superior parietal lobe extending to the somatosensory strip and posterior cingulate cortex, and local connections within the visual cortex, hippocampus, amygdala and insula. We thus provided detail of the cerebral cortex functional structure maturation during the transition to adulthood, which may serve to establish more accurate links between adolescent performance gains and cerebral cortex maturation. Remarkably, our study provides new information as to the cortical maturation processes in prefrontal areas relevant to executive functioning and rational learning, medial frontal areas playing an active role in the cognitive appraisal of emotion and anxiety, and superior parietal cortices strongly associated with bodily self-consciousness in the context of body image formation.

Largest scale dissociation of brain activity at propofol-induced loss of consciousness

The brain is a functional unit made up of multilevel connected elements showing a pattern of synchronized activity that varies in different states. The wake-sleep cycle is a major variation of brain functional condition that is ultimately regulated by subcortical arousal- and sleep-promoting cell groups. We analyzed the evolution of functional MRI (fMRI) signal in the whole cortex and in a deep region including most sleep- and wake-regulating subcortical nuclei at loss of consciousness induced by the hypnotic agent propofol. Optimal data were obtained in 21 of the 30 healthy participants examined. A dynamic analysis of fMRI time courses on a time-scale of seconds was conducted to characterize consciousness transition, and functional connectivity maps were generated to detail the anatomy of structures showing different dynamics. Inside the magnet, loss of consciousness was marked by the participants ceasing to move their hands. We observed activity synchronization after loss of consciousness within both the cerebral cortex and subcortical structures. However, the evolution of fMRI signal was dissociated, showing a transient reduction of global cortico-subcortical coupling that was restored during the unconscious state. An exception to cortico-subcortical decoupling was a brain network related to self-awareness (i.e. the default mode network) that remained connected to subcortical brain structures. Propofol-induced unconsciousness is thus characterized by an initial, transitory dissociated synchronization at the largest scale of brain activity. Such cortico-subcortical decoupling and subsequent recoupling may allow the brain to detach from waking activity and reorganize into a functionally distinct state.

Differential Modulation of Effective Connectivity in the Brain's Extended Face Processing System by Fearful and Sad Facial Expressions

The processing of emotional facial expressions is underpinned by the integration of information from a distributed network of brain regions. Despite investigations into how different emotional expressions alter the functional relationships within this network, there remains limited research examining which regions drive these interactions. This study investigated effective connectivity during the processing of sad and fearful facial expressions to better understand how these stimuli differentially modulate emotional face processing circuitry. Ninety-eight healthy human adolescents and young adults, aged between 15 and 25 years, underwent an implicit emotional face processing fMRI task. Using dynamic causal modeling (DCM), we examined five brain regions implicated in face processing. These were restricted to the right hemisphere and included the occipital and fusiform face areas, amygdala, and dorsolateral prefrontal cortex (dlPFC) and ventromedial prefrontal cortex (vmPFC). Processing sad and fearful facial expressions were associated with greater positive connectivity from the amygdala to dlPFC. Only the processing of fearful facial expressions was associated with greater negative connectivity from the vmPFC to amygdala. Compared with processing sad faces, processing fearful faces was associated with significantly greater connectivity from the amygdala to dlPFC. No difference was found between the processing of these expressions and the connectivity from the vmPFC to amygdala. Overall, our findings indicate that connectivity from the amygdala and dlPFC appears to be responding to dimensional features which differ between these expressions, likely those relating to arousal. Further research is necessary to examine whether this relationship is also observable for positively valenced emotions.

Resting state functional connectivity in the default mode network: Relationships between cannabis use, gender, and cognition in adolescents and young adults

INTRODUCTION

Cannabis is the most commonly used illicit substance in the United States, and nearly 1 in 4 young adults are current cannabis users. Chronic cannabis use is associated with changes in resting state functional connectivity (RSFC) in the default mode network (DMN) in adolescents and young adults; results are somewhat inconsistent across studies, potentially due to methodological differences. The aims of the present study were to examine potential differences in DMN RSFC between cannabis users and controls, and to examine, as an exploratory analysis, if gender moderated any findings. We further examined whether differences in RSFC related to differences in performance on selected neuropsychological measures.

MATERIALS AND METHODS

Seventy-seven 16-26-year-old participants underwent an MRI scan (including resting state scan), neuropsychological battery, toxicology screening, and drug use interview. Differences in DMN connectivity were examined between groups (cannabis vs. control) and with an exploratory group by gender interaction, using a left posterior cingulate cortex (PCC) seed-based analysis conducted in AFNI.

RESULTS

Cannabis users demonstrated weaker connectivity than controls between the left PCC and various DMN nodes, and the right Rolandic operculum/Heschl's gyrus. Cannabis users demonstrated stronger connectivity between the left PCC and the cerebellum and left supramarginal gyrus. The group by gender interaction was not significantly associated with connectivity differences. Stronger left PCC-cerebellum connectivity was associated with poorer performance on cognitive measures in cannabis users. In controls, intra-DMN connectivity was positively correlated with performance on a speeded selective/sustained attention measure.

DISCUSSION

Consistent with our hypotheses and other studies, cannabis users demonstrated weaker connectivity between the left PCC and DMN nodes. Chronic THC exposure may alter GABA and glutamate concentrations, which may alter brain communication. Future studies should be conducted with a larger sample size and examine gender differences and the mechanism by which these differences may arise.

Network-based functional connectivity predicts response to exposure therapy in unmedicated adults with obsessive-compulsive disorder

Obsessive-compulsive disorder (OCD) is associated with alterations in cortico-striato-thalamo-cortical brain networks, but some resting-state functional magnetic resonance imaging studies report more diffuse alterations in brain connectivity. Few studies have assessed functional connectivity within or between networks across the whole brain in unmedicated OCD patients or how patterns of connectivity predict response to exposure and ritual prevention (EX/RP) therapy, a first-line treatment for OCD. Herein, multiband resting-state functional MRI scans were collected from unmedicated, adult patients with OCD (n = 41) and healthy participants (n = 36); OCD patients were then offered twice weekly EX/RP (17 sessions). A whole-brain-network-based statistic approach was used to identify group differences in resting-state connectivity. We detected altered pre-treatment functional connectivity between task-positive regions in the temporal gyri (middle and superior) and regions of the cingulo-opercular and default networks in individuals with OCD. Signal extraction was performed using a reconstruction independent components analysis and isolated two independent subcomponents (IC1 and IC2) within this altered connectivity. In the OCD group, linear mixed-effects models tested whether IC1 or IC2 values predicted the slope of change in Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) scores across EX/RP treatment. Lower (more different from controls) IC2 score significantly predicted greater symptom reduction with EX/RP (Bonferroni-corrected p = 0.002). Collectively, these findings suggest that an altered balance between task-positive and task-negative regions centered around temporal gyri may contribute to difficulty controlling intrusive thoughts or urges to perform ritualistic behaviors.

Spontaneous electrical low-frequency oscillations: a possible role in Hydra and all living systems

As one of the first model systems in biology, the basal metazoan Hydra has been revealing fundamental features of living systems since it was first discovered by Antonie van Leeuwenhoek in the early eighteenth century. While it has become well-established within cell and developmental biology, this tiny freshwater polyp is only now being re-introduced to modern neuroscience where it has already produced a curious finding: the presence of low-frequency spontaneous neural oscillations at the same frequency as those found in the default mode network in the human brain. Surprisingly, increasing evidence suggests such spontaneous electrical low-frequency oscillations (SELFOs) are found across the wide diversity of life on Earth, from bacteria to humans. This paper reviews the evidence for SELFOs in diverse phyla, beginning with the importance of their discovery in Hydra, and hypothesizes a potential role as electrical organism organizers, which supports a growing literature on the role of bioelectricity as a 'template' for developmental memory in organism regeneration. This article is part of the theme issue 'Basal cognition: conceptual tools and the view from the single cell'.

The default mode network: where the idiosyncratic self meets the shared social world

The default mode network (DMN) is classically considered an 'intrinsic' system, specializing in internally oriented cognitive processes such as daydreaming, reminiscing and future planning. In this Perspective, we suggest that the DMN is an active and dynamic 'sense-making' network that integrates incoming extrinsic information with prior intrinsic information to form rich, context-dependent models of situations as they unfold over time. We review studies that relied on naturalistic stimuli, such as stories and movies, to demonstrate how an individual's DMN neural responses are influenced both by external information accumulated as events unfold over time and by the individual's idiosyncratic past memories and knowledge. The integration of extrinsic and intrinsic information over long timescales provides a space for negotiating a shared neural code, which is necessary for establishing shared meaning, shared communication tools, shared narratives and, above all, shared communities and social networks.

Altered Frequency-Dependent Brain Activation and White Matter Integrity Associated With Cognition in Characterizing Preclinical Alzheimer's Disease Stages

Background

Subjective cognitive decline (SCD), non-amnestic mild cognitive impairment (naMCI), and amnestic mild cognitive impairment (aMCI) are regarded to be at high risk of converting to Alzheimer's disease (AD). Amplitude of low-frequency fluctuations (ALFF) can reflect functional deterioration while diffusion tensor imaging (DTI) is capable of detecting white matter integrity. Our study aimed to investigate the structural and functional alterations to further reveal convergence and divergence among SCD, naMCI, and aMCI and how these contribute to cognitive deterioration.

Methods

We analyzed ALFF under slow-4 (0.027-0.073 Hz) and slow-5 (0.01-0.027 Hz) bands and white matter fiber integrity among normal controls (CN), SCD, naMCI, and aMCI groups. Correlation analyses were further utilized among paired DTI alteration, ALFF deterioration, and cognitive decline.

Results

For ALFF calculation, ascended ALFF values were detected in the lingual gyrus (LING) and superior frontal gyrus (SFG) within SCD and naMCI patients, respectively. Descended ALFF values were presented mainly in the LING, SFG, middle frontal gyrus, and precuneus in aMCI patients compared to CN, SCD, and naMCI groups. For DTI analyses, white matter alterations were detected within the uncinate fasciculus (UF) in aMCI patients and within the superior longitudinal fasciculus (SLF) in naMCI patients. SCD patients presented alterations in both fasciculi. Correlation analyses revealed that the majority of these structural and functional alterations were associated with complicated cognitive decline. Besides, UF alterations were correlated with ALFF deterioration in the SFG within aMCI patients.

Conclusions

SCD shares structurally and functionally deteriorative characteristics with aMCI and naMCI, and tends to convert to either of them. Furthermore, abnormalities in white matter fibers may be the structural basis of abnormal brain activation in preclinical AD stages. Combined together, it suggests that structural and functional integration may characterize the preclinical AD progression.

Frontoparietal and default mode network connectivity varies with age and intelligence

Background

Anticorrelated resting state connectivity between task-positive and task-negative networks in adults supports flexible shifting between externally focused attention and internal thought. Findings suggest that children show positive correlations between task-positive (frontoparietal; FP) and task-negative (default mode; DMN) networks. FP-DMN connectivity also associates with intellectual functioning across the lifespan. We investigated whether FP-DMN connectivity in healthy children varied with age and intelligence quotient (IQ).

Methods

We utilized network-based statistics (NBS) to examine resting state functional connectivity between FP and DMN seeds in N = 133 7−25-year-olds (M_age = 15.80). Linear regression evaluated FP-DMN associations with IQ.

Results

We detected NBS subnetworks containing both within- and between-network connections that were inversely associated with age. Four FP-DMN connections showed more negative connectivity between FP (inferior frontal gyrus and precentral gyrus) and DMN regions (frontal medial cortex, precuneus, and frontal pole) among older participants. Frontal pole-precentral gyrus connectivity inversely associated with IQ.

Conclusions

FP-DMN connectivity was more anticorrelated at older ages, potentially indicating dynamic network segregation of these circuits from childhood to early adulthood. Youth with more mature (i.e., anticorrelated) FP-DMN connectivity demonstrated higher IQ. Our findings add to the growing body of literature examining neural network development and its association with IQ.

Feelings of shame and guilt are associated with distinct neural activation in youth

Shame and guilt are moral emotions that play an important role in social functioning. There is limited knowledge about the neural underpinnings of these emotions, particularly in young people. In the current study, 36 healthy females (mean age 18.8 ± 1.9 years) underwent functional Magnetic Resonance Imaging, during which they reflected on their decisions about social moral dilemmas, and subsequently received negative or positive peer feedback. Ratings of shame and guilt were used as parametric modulators of brain activity. Shame was associated with decreased activity in the superior temporal sulcus and precentral gyrus during reflection. Guilt was associated with decreased activity in the precuneus during positive feedback, and in the hippocampus and supramarginal gyrus during negative feedback. Results suggest that shame and guilt are associated with activity in brain regions involved in social cognition and emotion regulation; however, they have distinct underlying neural circuitry that may be differentiated based on social evaluation.

Machine Learning-Based Electroencephalographic Phenotypes of Schizophrenia and Major Depressive Disorder

Background: Psychiatric diagnosis is formulated by symptomatic classification; disease-specific neurophysiological phenotyping could help with its fundamental treatment. Here, we investigated brain phenotyping in patients with schizophrenia (SZ) and major depressive disorder (MDD) by using electroencephalography (EEG) and conducted machine-learning-based classification of the two diseases by using EEG components. Materials and Methods: We enrolled healthy controls (HCs) (n = 30) and patients with SZ (n = 34) and MDD (n = 33). An auditory P300 (AP300) task was performed, and the N1 and P3 components were extracted. Two-group classification was conducted using linear discriminant analysis (LDA) and support vector machine (SVM) classifiers. Positive and negative symptoms and depression and/or anxiety symptoms were evaluated. Results: Considering both the results of statistical comparisons and machine learning-based classifications, patients and HCs showed significant differences in AP300, with SZ and MDD showing lower N1 and P3 than HCs. In the sum of amplitudes and cortical sources, the findings for LDA with classification accuracy (SZ vs. HCs: 71.31%, MDD vs. HCs: 74.55%), sensitivity (SZ vs. HCs: 77.67%, MDD vs. HCs: 79.00%), and specificity (SZ vs. HCs: 64.00%, MDD vs. HCs: 69.67%) supported these results. The SVM classifier showed reasonable scores between SZ and HCs and/or MDD and HCs. The comparison between SZ and MDD showed low classification accuracy (59.71%), sensitivity (65.08%), and specificity (54.83%). Conclusions: Patients with SZ and MDD showed deficiencies in N1 and P3 components in the sum of amplitudes and cortical sources, indicating attentional dysfunction in both early and late sensory/cognitive gating input. The LDA and SVM classifiers in the AP300 are useful to distinguish patients with SZ and HCs and/or MDD and HCs.

Effect of Methylphenidate on Resting-State Connectivity in Adolescents With a Disruptive Behavior Disorder: A Double-Blind Randomized Placebo-Controlled fMRI Study

Some studies suggest that methylphenidate (MPH) might be an effective treatment for antisocial and aggressive behavior in adolescence. However, little is known about the mechanism of action of MPH in adolescents with this kind of psychopathology. MPH is a dopamine and norepinephrine reuptake inhibitor and thus it is likely to affect dopaminergic mesocorticolimbic pathways. This is the first study to investigate the effect of MPH on resting-state connectivity of three mesolimbic seed regions with the rest of the brain in clinical referred male adolescents with a disruptive behavior disorder (DBD). Thirty-six male DBD adolescents and 31 male healthy controls (HCs) were included. DBD subjects were randomly allocated to a single dose of MPH (DBD-MPH, n = 20) or placebo (DBD-PCB, n = 16). Seed-based resting-state functional connectivity of the nucleus accumbens (NAcc), amygdala, and ventral tegmental area (VTA) with the rest of the brain was compared between groups. The NAcc seed showed increased connectivity in DBD-PCB compared to HC with the occipital cortex, posterior cingulate cortex (PCC), precuneus, and inferior parietal lobule (IPL) and increased connectivity in DBD-PCB compared to DBD-MPH with occipital cortex, IPL, and medial frontal gyrus. The amygdala seed showed increased connectivity in DBD-PCB compared to HC with the precuneus and PCC. The VTA seed showed increased connectivity in the DBD-MPH compared to the DBD-PCB group with a cluster in the postcentral gyrus and a cluster in the supplementary motor cortex/superior frontal gyrus. Both NAcc and amygdala seeds showed no connectivity differences in the DBD-MPH compared to the HC group, indicating that MPH normalizes the increased functional connectivity of mesolimbic seed regions with areas involved in moral decision making, visual processing, and attention.

Personode: A Toolbox for ICA Map Classification and Individualized ROI Definition

Canonical resting state networks (RSNs) can be obtained through independent component analysis (ICA). RSNs are reproducible across subjects but also present inter-individual differences, which can be used to individualize regions-of-interest (ROI) definition, thus making fMRI analyses more accurate. Unfortunately, no automatic tool for defining subject-specific ROIs exists, making the classification of ICAs as representatives of RSN time-consuming and largely dependent on visual inspection. Here, we present Personode, a user-friendly and open source MATLAB-based toolbox that semi-automatically performs the classification of RSN and allows for defining subject- and group-specific ROIs. To validate the applicability of our new approach and to assess potential improvements compared to previous approaches, we applied Personode to both task-related activation and resting-state data. Our analyses show that for task-related activation analyses, subject-specific spherical ROIs defined with Personode produced higher activity contrasts compared to ROIs derived from single-study and meta-analytic coordinates. We also show that subject-specific irregular ROIs defined with Personode improved ROI-to-ROI functional connectivity analyses.Hence, Personode might be a useful toolbox for ICA map classification into RSNs and group- as well as subject-specific ROI definitions, leading to improved analyses of task-related activation and functional connectivity.

Source-based morphometry reveals gray matter differences related to suicidal behavior in criminal offenders

Relative to the general population, criminal offenders have a higher risk of suicide. Neurobiological deficits related to suicidal behavior have been identified in the general population, but unexamined in offenders to date. We examined the association between brain morphology and suicidal behavior in adult male criminal offenders. Brain morphology was examined using voxel-based morphometry (VBM) and source-based morphometry (SBM), a multivariate alternative to VBM which analyzes brain volume in between-subject spatially independent networks. Results showed that offenders with past suicide attempts (n = 19), relative to offenders without past suicide attempts (n = 19) and non-offenders (n = 26), had reduced gray matter in an SBM component that comprised the posterior cingulate, dorsal prefrontal cortex, and amygdala. The SBM source weights were significantly associated with suicide attempts independent of other suicide risk variables (e.g., depression). VBM results were similar to the SBM results but less robust. The results reveal a potential neurobiological marker of vulnerability to suicidal behavior among criminal offenders and illustrate the utility of multivariate methods of gray matter analyses.

Functional parcellation of the default mode network: a large-scale meta-analysis

The default mode network (DMN) consists of several regions that selectively interact to support distinct domains of cognition. Of the various sites that partake in DMN function, the posterior cingulate cortex (PCC), temporal parietal junction (TPJ), and medial prefrontal cortex (MPFC) are frequently identified as key contributors. Yet, it remains unclear whether these subcomponents of the DMN make unique contributions to specific cognitive processes and health conditions. To address this issue, we applied a meta-analytic parcellation approach used in prior work. This approach used the Neurosynth database and classification methods to quantify the association between PCC, TPJ, and MPFC activation and specific topics related to cognition and health (e.g., decision making and smoking). Our analyses replicated prior observations that the PCC, TPJ, and MPFC collectively support multiple cognitive functions such as decision making, memory, and awareness. To gain insight into the functional organization of each region, we parceled each region based on its coactivation pattern with the rest of the brain. This analysis indicated that each region could be further subdivided into functionally distinct subcomponents. Taken together, we further delineate DMN function by demonstrating the relative strengths of association among subcomponents across a range of cognitive processes and health conditions. A continued attentiveness to the specialization within the DMN allows future work to consider the nuances in sub-regional contributions necessary for healthy cognition, as well as create the potential for more targeted treatment protocols in various health conditions.

Brain functional network alterations caused by a strong desire to void in healthy adults: a graph theory analysis study

PURPOSE

This resting-state functional magnetic resonance imaging (fMRI) study determined the functional connectivity (FC) changes and topologic property alterations of the brain functional network provoked by a strong desire to void in healthy adults using a graph theory analysis (GTA).

MATERIALS AND METHODS

Thirty-four healthy, right-handed subjects filled their bladders by drinking water. The subjects were scanned under an empty bladder and a strong desire to void states. The Pearson's correlation coefficients were calculated among 90 brain regions in the automated anatomical labeling (AAL) atlas to construct the brain functional network. A paired t test (P < .05, after false discovery rate [FDR] correction) was used to detect significant differences in the FC, topologic properties (small-world parameters [gamma, sigma], C_p, L_p, E_glob, E_loc, and E_nodal) between the two states in all subjects.

RESULTS

Both the two states showed small-world network properties. The clustering coefficient (C_p) and local efficiency (E_loc) in the whole brain network decreased, while the FC within the default mode network (DMN) increased during the strong desire to void compared with the empty bladder state. Moreover, an increased nodal efficiency (E_nodal) was detected in the basal ganglia (BG), DMN, sensorimotor-related network (SMN), and visual network (VN).

CONCLUSION

We detected FC changes and topologic property alterations in brain functional networks caused by a strong desire to void in healthy and suggest that the micturition control may be a process dominated by DMN and coordinated by multiple sub-networks (such as, BG, SMN, and VN), which could serve as a baseline for understanding the pathologic process underlying bladder dysfunction and be useful to improve targeted therapy in the future.

The Functional Role of Large-scale Brain Network Coordination in Placebo-induced Anxiolysis

Anxiety reduction through mere expectation of anxiolytic treatment effects (placebo anxiolysis) has enormous clinical importance. Recent behavioral and electrophysiological data suggest that placebo anxiolysis involves reduced vigilance and enhanced internalization of attention; however, the underlying neurobiological mechanisms are not yet clear. Given the fundamental function of intrinsic connectivity networks (ICNs) in basic cognitive processes, we investigated ICN activity patterns associated with externally and internally directed mental states under the influence of an anxiolytic placebo medication. Based on recent findings, we specifically analyzed the functional role of the rostral anterior cingulate cortex (rACC) in coordinating placebo-dependent cue-related (phasic) and cue-unrelated (sustained) network activity. Under placebo, we observed a down-regulation of the entire salience network (SN), particularly in response to threatening cues. The rACC exhibited enhanced cue-unrelated functional connectivity (FC) with the SN, which correlated with reductions in tonic arousal and anxiety. Hence, apart from the frequently reported modulation of aversive cue responses, the rACC appears to be crucially involved in exerting a tonically dampening control over salience-responsive structures. In line with a more internally directed mental state, we also found enhanced FC within the default mode network (DMN), again predicting reductions in anxiety under placebo.

Callous-unemotional traits and reduced default mode network connectivity within a community sample of children

Callous-unemotional (CU) traits characterize a subset of youth at risk for persistent and serious antisocial behavior. Differences in resting state connectivity in the default mode network (DMN) have been associated with CU traits in forensic and clinical samples of adolescents and with deficient interpersonal/affective traits (often operationalized as Factor 1 psychopathy traits) in adults. It is unclear whether these brain-behavior associations extend to community-based children. Using mixed model analyses, we tested the associations between CU traits and within-network resting-state connectivity of seven task-activated networks and the DMN using data from 9,636 9-11-year-olds in the Adolescent Brain Cognitive Development (ABCD) study. Even after accounting for comorbid externalizing problems, higher levels of CU traits were associated with reduced connectivity within the DMN. This finding is consistent with prior literature surrounding psychopathy and CU traits in clinically and forensically based populations, suggesting the correlation likely exists on a spectrum, can be detected in childhood, and is not restricted to children with significant antisocial behavior.

Association of ovarian hormones with mapping concept of self and others in the brain's default mode network

The brain's default mode network (DMN) has become closely associated with self-referential mental activity, particularly in the resting-state. Prior reports point that the sex hormones are potent modulators of brain plasticity and functional connectivity. However, it is uncertain whether changes in ovarian hormones, as occur during the monthly menstrual cycle, substantially affects the functional connectivity of DMN. Here, we employed a Self-Awareness Scale (SAS) and the resting-state functional MRI in the late follicular phase and the mid-luteal phase to investigate the effect of the estradiol (E2) and progesterone on the SAS and DMN. On the behavioral level, increased progesterone facilitated women's other-focused attention. The regions of interest-based resting-state functional connectivity analyses continued to demonstrate a negative correlation of the relative progesterone and the medial prefrontal cortex-inferior temporal gyrus (mPFC-ITG) functional connectivity, and a facilitated effect of relative E2 on the mPFC-inferior parietal lobule functional connectivity in the DMN. Furthermore, as a core hub of the 'theory of mind', the functional connectivity between the ITG and thalamus was found negatively correlated with the relative E2. Meanwhile, the mid-luteal phase, which had significantly lower relative E2 levels, was indicated had stronger ITG-thalamus functional connectivity during the resting state. These results demonstrated an opposite effect of E2 and progesterone on the DMN and the other-focused preference in the mid-luteal phase, extended previous evidence of the potentially adaptive psychological effects of ovarian hormones on mapping self and others in the brain networks.

Altered network connectivity predicts response to cognitive-behavioral therapy in pediatric obsessive-compulsive disorder

Obsessive-compulsive disorder (OCD) is commonly associated with alterations in cortico-striato-thalamo-cortical brain networks. Yet, recent investigations of large-scale brain networks suggest that more diffuse alterations in brain connectivity may underlie its pathophysiology. Few studies have assessed functional connectivity within or between networks across the whole brain in pediatric OCD or how patterns of connectivity associate with treatment response. Resting-state functional magnetic resonance imaging scans were acquired from 25 unmedicated, treatment-naive children and adolescents with OCD (12.8 ± 2.9 years) and 23 matched healthy control (HC) participants (11.0 ± 3.3 years) before participants with OCD completed a course of cognitive-behavioral therapy (CBT). Participants were re-scanned after 12-16 weeks. Whole-brain connectomic analyses were conducted to assess baseline group differences and group-by-time interactions, corrected for multiple comparisons. Relationships between functional connectivity and OCD symptoms pre- and post-CBT were examined using longitudinal cross-lagged panel modeling. Reduced connectivity in OCD relative to HC participants was detected between default mode and task-positive network regions. Greater (less altered) connectivity between left angular gyrus and left frontal pole predicted better response to CBT in the OCD group. Altered connectivity between task-positive and task-negative networks in pediatric OCD may contribute to the impaired control over intrusive thoughts early in the illness. This is the first study to show that altered connectivity between large-scale network regions may predict response to CBT in pediatric OCD, highlighting the clinical relevance of these networks as potential circuit-based targets for the development of novel treatments.

Brain Network Modularity During a Sustained Working-Memory Task

Spontaneous oscillations of the blood oxygenation level-dependent (BOLD) signal are spatially synchronized within specific brain networks and are thought to reflect synchronized brain activity. Networks are modulated by the performance of a task, even if the exact features and degree of such modulations are still elusive. The presence of networks showing anticorrelated fluctuations lend initially to suppose that a competitive relationship between the default mode network (DMN) and task positive networks (TPNs) supports the efficiency of brain processing. However, more recent results indicate that cooperative and competitive dynamics between networks coexist during task performance. In this study, we used graph analysis to assess the functional relevance of the topological reorganization of brain networks ensuing the execution of a steady state working-memory (WM) task. Our results indicate that the performance of an auditory WM task is associated with a switching between different topological configurations of several regions of specific networks, including frontoparietal, ventral attention, and dorsal attention areas, suggesting segregation of ventral attention regions in the presence of increased overall integration. However, the correct execution of the task requires integration between components belonging to all the involved networks.

Impaired Structural Network Properties Caused by White Matter Hyperintensity Related to Cognitive Decline

Purpose: There is a high correlation between white matter hyperintensity (WMH) and cognitive impairment (CI) in elderly people. However, not all WMH will develop into CI, and the potential mechanism of WMH-related CI is still unclear. This study aimed to investigate the topological properties of white matter structural network in WMH-related CI.

Methods: Forty-one WMH subjects with CI (WMH-CI), 42 WMH subjects without CI (WMH-no-CI), and 52 elderly healthy controls (HC) were recruited. Diffusion tensor imaging (DTI) fiber tractography and graph theoretical analysis were applied to construct the structural network. We compared network properties and clinical features among the three groups. Multiple linear regression analysis was performed to investigate the relationships among WMH volumes, impaired network properties, and cognitive functions in the WMH-CI group.

Results: Compared with the controls, both WMH groups showed decreased network strength, global efficiency, and increased characteristic path length (Lp) at the level of the whole brain. The WMH-CI group displayed more profound impairments of nodal efficiency and nodal path length (NLp) within multiple regions including precentral, cingulate, and medial temporal gyrus. The disrupted network properties were associated with CI and WMH burdens in the WMH-CI group. Furthermore, a mediation effect of NLp in the left inferior frontal gyrus was observed for the association between periventricular WMH (PWMH) and memory deficit.

Conclusions: Brain structural network in WMH-CI is significantly disturbed, and this disturbance is related to the severity of WMH and CI. Increased NLp in the left opercular part of inferior frontal gyrus (IFGoperc.L) was shown to be a mediation framework between PWMH and WMH-related memory, which shed light on investigating the underlying mechanisms of CI caused by WMH.

Structural and functional brain abnormalities in children with schizotypal disorder: a pilot study

Schizotypal disorder lies in the schizophrenia spectrum and is widely studied in adult populations. Schizotypal disorder in children (SDc) is less well described. This study examined brain morphological and functional connectivity abnormalities in SDc (12 SDc and 9 typically developing children), focusing on the default mode and executive control brain networks. Results indicated that SDc is associated with reduced grey matter volume (GMV) in superior and medial frontal gyri, and increased resting-state functional connectivity between the superior frontal gyrus and inferior parietal lobule, compared to typically developing children (cluster-level FWE-corrected p < 0.05). The brain structure abnormality (GMV in left superior frontal gyrus) was correlated with clinical symptoms in SDc (r = −0.66, p = 0.026) and functional connectivity abnormality was correlated with extra-dimensional shifting impairments in all participants (r = 0.62, p = 0.011), suggesting their contribution to the underlying mechanisms of clinical presentation. These preliminary results motivate further work to characterize the neural basis of SDc and its significance as a risk factor for later psychosis.

The developmental trajectory of fronto-temporoparietal connectivity as a proxy of the default mode network: a longitudinal fNIRS investigation

The default mode network (DMN) is a network of brain regions that is activated while we are not engaged in any particular task. While there is a large volume of research documenting functional connectivity within the DMN in adults, knowledge of the development of this network is still limited. There is some evidence for a gradual increase in the functional connections within the DMN during the first 2 years of life, in contrast to other functional resting‐state networks that support primary sensorimotor functions, which are online from very early in life. Previous studies that investigated the development of the DMN acquired data from sleeping infants using fMRI. However, sleep stages are known to affect functional connectivity. In the current longitudinal study, fNIRS was used to measure spontaneous fluctuations in connectivity within fronto‐temporoparietal areas—as a proxy for the DMN—in awake participants every 6 months from 11 months till 36 months. This study validates a method for recording resting‐state data from awake infants, and presents a data analysis pipeline for the investigation of functional connections with infant fNIRS data, which will be beneficial for researchers in this field. A gradual development of fronto‐temporoparietal connectivity was found, supporting the idea that the DMN develops over the first years of life. Functional connectivity reached its maximum peak at about 24 months, which is consistent with previous findings showing that, by 2 years of age, DMN connectivity is similar to that observed in adults.

A randomized trial of stereotactic versus conventional radiotherapy in young patients with low-grade brain tumors: occupational therapy-based neurocognitive data

BACKGROUND

Radiotherapy for brain tumors in young patients is not only associated with improved survival but also long-term neurocognitive sequelae. We aimed to compare group differences in the executive neurocognitive outcomes in young patients with low-grade brain tumors treated with stereotactic conformal radiotherapy (SCRT) and conventional RT (ConvRT) techniques.

METHODS

This a phase 3 randomized trial that enrolled 200 young patients with benign brain tumors and low-grade gliomas. Patients were randomly allocated (1:1) to either SCRT or ConvRT arms and treated to a dose of 54 Gy in 30 fractions over 6 weeks. Lowenstein Occupational Therapy Cognitive Assessment battery was performed at preradiotherapy baseline, 6 months, and annually thereafter until 5 years. Executive functions measures included orientation, visual perception, spatial perception, motor praxis, visuomotor organization, thinking operations, and attention and concentration. The trajectory of these parameters was compared between the treatment arms over 5 years.

RESULTS

Two hundred patients were enrolled in the study (SCRT: 104 and ConvRT: 96). The median age was 13 years (interquartile range: 9-17); mean total neurocognitive scores over 5 years were significantly superior in SCRT arm as compared to ConvRT (difference in slope: 2.27, P = .024). Outcomes improved in the SCRT arm vis-à-vis ConvRT for the subdomain of visuomotor organization (difference in slope: 0.66, P < .001). Visuomotor organization scores significantly improved in majority of the substratification groups. Spatial perception improved in craniopharyngioma patients with SCRT technique as opposed to ConvRT.

CONCLUSIONS

SCRT achieved superior outcomes compared to ConvRT in certain executive neurocognitive functional domains. We provide high level of evidence in favor of SCRT. Trial Registration. ClinicalTrials.gov Identifier: NCT00517959.

A Connectomic Atlas of the Human Cerebrum-Chapter 4: The Medial Frontal Lobe, Anterior Cingulate Gyrus, and Orbitofrontal Cortex

In this supplement, we build on work previously published under the Human Connectome Project. Specifically, we show a comprehensive anatomic atlas of the human cerebrum demonstrating all 180 distinct regions comprising the cerebral cortex. The location, functional connectivity, and structural connectivity of these regions are outlined, and where possible a discussion is included of the functional significance of these areas. In part 4, we specifically address regions relevant to the medial frontal lobe, anterior cingulate gyrus, and orbitofrontal cortex.

A Connectomic Atlas of the Human Cerebrum-Chapter 17: Tractographic Description of the Cingulum

In this supplement, we show a comprehensive anatomic atlas of the human cerebrum demonstrating all 180 distinct regions comprising the cerebral cortex. The location, functional connectivity, and structural connectivity of these regions are outlined, and where possible a discussion is included of the functional significance of these areas. In this chapter, we specifically address regions integrating to form the cingulum.

A Connectomic Atlas of the Human Cerebrum-Chapter 8: The Posterior Cingulate Cortex, Medial Parietal Lobe, and Parieto-Occipital Sulcus

In this supplement, we build on work previously published under the Human Connectome Project. Specifically, we seek to show a comprehensive anatomic atlas of the human cerebrum demonstrating all 180 distinct regions comprising the cerebral cortex. The location, functional connectivity, and structural connectivity of these regions are outlined, and where possible a discussion is included of the functional significance of these areas. In part 8, we specifically address regions relevant to the posterior cingulate cortex, medial parietal lobe, and the parieto-occipital sulcus.

Fronto-temporoparietal connectivity and self-awareness in 18-month-olds: A resting state fNIRS study

How and when a concept of the 'self' emerges has been the topic of much interest in developmental psychology. Self-awareness has been proposed to emerge at around 18 months, when toddlers start to show evidence of physical self-recognition. However, to what extent physical self-recognition is a valid indicator of being able to think about oneself, is debated. Research in adult cognitive neuroscience has suggested that a common network of brain regions called Default Mode Network (DMN), including the temporo-parietal junction (TPJ) and the medial prefrontal cortex (mPFC), is recruited when we are reflecting on the self. We hypothesized that if mirror self-recognition involves self-awareness, toddlers who exhibit mirror self-recognition might show increased functional connectivity between frontal and temporoparietal regions of the brain, relative to those toddlers who do not yet show mirror self-recognition. Using fNIRS, we collected resting-state data from 18 Recognizers and 22 Non-Recognizers at 18 months of age. We found significantly stronger fronto-temporoparietal connectivity in Recognizers compared to Non-Recognizers, a finding which might support the hypothesized relationship between mirror-self recognition and self-awareness in infancy.

Synchronous brain networks for passive auditory perception in depressive states: A pilot study

Recent studies have revealed a strong relationship between the default mode network (DMN) and major depression disorder (MDD). The DMN consists of several areas in the brain where activity simultaneously increases during the resting state and is suppressed during cognitive tasks (i.e., DMN suppression). Although the DMN has been evaluated in patients with MDD, it has not been studied in people with self-measured depressive symptoms without medication. Although most studies have used high-demand cognitive tasks, the relationships between MDD and passive sensory tasks remain unclear. Here, we recorded electroencephalograph (EEG) data under two sessions: a resting session and an auditory session. Moreover, we assessed depressive states with a Self-Rating Depression Scale (SDS) score. To reveal the DMN suppression mechanism in the depressive states, we used EEG time-frequency analysis. As a result, the alpha-band phase synchronization in the DMN increased during the resting session and decreased during the auditory session. The results suggest that participants in a depressive state have both an abnormal DMN connectivity and a suppressed DMN connectivity via a passive stimulus. Moreover, we were able to estimate the DMN suppression mechanism during the depressive states: (1) the beta-band phase resetting was found in the auditory and parietal areas via the auditory stimulus; (2) the beta-band transfer entropy from the auditory area to the parietal area was high as information flow among these area; and (3) the beta-band systems (information flow) were synchronized with the alpha-band DMN systems. Although the sample size was small, these results suggest that the DMN systems may already be altered during self-measured depressive symptoms like the early stages of the depressive states.

Brain functional connectivity correlates of coping styles

Coping abilities represent the individual set of mental and behavioral strategies adopted when facing stress or traumatic experiences. Coping styles related to avoidance have been linked to a disposition to develop psychiatric disorders such as PTSD, anxiety, and major depression, whereas problem-oriented coping skills have been positively correlated with well-being and high quality of life. Even though coping styles constitute an important determinant of resilience and can impact many aspects of everyday living, no study has investigated their brain functional connectivity underpinnings in humans. Here we analyzed both psychometric scores of coping and resting-state fMRI data from 102 healthy adult participants. Controlling for personality and problem-solving abilities, we identified significant links between the propensity to adopt different coping styles and the functional connectivity profiles of regions belonging to the default mode (DMN) and anterior salience (AS) networks-namely, the anterior cingulate cortex, left frontopolar cortex, and left angular gyrus. Also, a reduced negative correlation between AS and DMN nodes explained variability in one specific coping style, related to avoiding problems while focusing on the emotional component of the stressor at hand, instead of relying on cognitive resources. These results might be integrated with current neurophysiological models of resilience and individual responses to stress, in order to understand the propensity to develop clinical conditions (e.g., PTSD) and predict the outcomes of psychotherapeutic interventions.

Anterior Cingulate Glutamate and GABA Associations on Functional Connectivity in Schizophrenia

BACKGROUND

The underlying neurobiological mechanism for abnormal functional connectivity in schizophrenia (SCZ) remains unknown. This project investigated whether glutamate and GABA, 2 metabolites that contribute to excitatory and inhibitory functions, may influence functional connectivity in SCZ.

METHODS

Resting-state functional magnetic resonance imaging and proton magnetic resonance spectroscopy were acquired from 58 SCZ patients and 61 healthy controls (HC). Seed-based connectivity maps were extracted between the anterior cingulate cortex (ACC) spectroscopic voxel and all other brain voxels. Magnetic resonance spectroscopy (MRS) spectra were processed to quantify glutamate and GABA levels. Regression analysis was performed to describe relationships between functional connectivity and glutamate and GABA levels.

RESULTS

Reduced ACC functional connectivity in SCZ was found in regions associated with several neural networks including the default mode network (DMN) compared to HC. In the HC, positive correlations were found between glutamate and both ACC-right inferior frontal gyrus functional connectivity and ACC-bilateral superior temporal gyrus functional connectivity. A negative correlation between GABA and ACC-left posterior cingulate functional connectivity was also observed in HC. These same relationships were not statistically significant in SCZ.

CONCLUSIONS

The present investigation is one of the first studies to examine links between functional connectivity and glutamate and GABA levels in SCZ. Results indicate that glutamate and GABA play an important role in the functional connectivity modulation in the healthy brain. The absence of glutamate and GABA correlations in areas where SCZ showed significantly reduced functional connectivity may suggest that this chemical-functional relationship is disrupted in SCZ.

Neurodevelopmental correlates of the emerging adult self

The self-concept – the set of beliefs that a person has about themselves – shows significant development from adolescence to early adulthood, in parallel with brain development over the same period. We sought to investigate how age-related changes in self-appraisal processes corresponded with brain network segregation and integration in healthy adolescents and young adults. We scanned 88 participants (46 female), aged from 15 to 25 years, as they performed a self-appraisal task. We first examined their patterns of activation to self-appraisal, and replicated prior reports of reduced dorsomedial prefrontal cortex activation with older age, with similar reductions in precuneus, right anterior insula/operculum, and a region extending from thalamus to striatum. We used independent component analysis to identify distinct anterior and posterior components of the default mode network (DMN), which were associated with the self-appraisal and rest-fixation parts of the task, respectively. Increasing age was associated with reduced functional connectivity between the two components. Finally, analyses of task-evoked interactions between pairs of nodes within the DMN identified a subnetwork that demonstrated reduced connectivity with increasing age. Decreased network integration within the DMN appears to be an important higher-order maturational process supporting the emerging adult self.

The relationship of anxious and depressive symptoms in Parkinson's disease with voxel-based neuroanatomical and functional connectivity measures

BACKGROUND

Anxiety and depression are two frequent comorbidities of Parkinson's disease (PD). However, the underlying neural mechanism is still unclear and the studies on their neural correlates were insufficient.

METHODS

Using voxel-based neuroanatomical and functional connectivity (FC) measures, i.e. grey matter volume, fractional anisotropy, and weighted degree centrality (WD), we examined their correlations with the severity levels of anxious and depressive symptoms in 36 PD patients.

RESULTS

Positive correlations were shown between anxiety and the WDs in the left amygdala, and between depression and short-ranged WDs in the left parahippocampal gyrus. Using these two regions as the seeds, we found that the severity levels of anxiety and depression were positively correlated with the FCs between the two seeds and the areas in the default mode network (DMN), while negatively correlated with the FCs between the two seeds and the prefrontal and superior temporal cortices. Anxiety was also positively correlated with the FC between the amygdala and the superior parietal lobule.

LIMITATIONS

The severity levels of anxious and depressive symptoms of our participants is relatively mild than some previous studies. The cross-sectional design of this study cannot clarify the etiological relationship between PD and two comorbidities.

CONCLUSIONS

Our results were in line with the key roles of the amygdala and parahippocampal gyrus in anxiety and depression, and reflected the distinct effects of the DMN, prefrontal and superior temporal cortices, and sensory-motor regions on emotional regulation. The identification of these neural substrates might assist clinical monitoring mood disturbances in PD.

Stochastic Rank Aggregation for the Identification of Functional Neuromarkers

The main challenge in analysing functional magnetic resonance imaging (fMRI) data from extended samples of subject (N > 100) is to extract as much relevant information as possible from big amounts of noisy data. When studying neurodegenerative diseases with resting-state fMRI, one of the objectives is to determine regions with abnormal background activity with respect to a healthy brain and this is often attained with comparative statistical models applied to single voxels or brain parcels within one or several functional networks. In this work, we propose a novel approach based on clustering and stochastic rank aggregation to identify parcels that exhibit a coherent behaviour in groups of subjects affected by the same disorder and apply it to default-mode network independent component maps from resting-state fMRI data sets. Brain voxels are partitioned into parcels through k-means clustering, then solutions are enhanced by means of consensus techniques. For each subject, clusters are ranked according to their median value and a stochastic rank aggregation method, TopKLists, is applied to combine the individual rankings within each class of subjects. For comparison, the same approach was tested on an anatomical parcellation. We found parcels for which the rankings were different among control subjects and subjects affected by Parkinson's disease and amyotrophic lateral sclerosis and found evidence in literature for the relevance of top ranked regions in default-mode brain activity. The proposed framework represents a valid method for the identification of functional neuromarkers from resting-state fMRI data, and it might therefore constitute a step forward in the development of fully automated data-driven techniques to support early diagnoses of neurodegenerative diseases.

The contribution of brain imaging to the understanding of psychopathy

Psychopathy is a personality type characterized by both callous emotional dysfunction and deviant behavior that affects society in the form of actions that harm others. Historically, researchers have been concerned with seeking data and arguments to support a neurobiological foundation of psychopathy. In the past few years, increasing research has begun to reveal brain alterations putatively underlying the enigmatic psychopathic personality. In this review, we describe the brain anatomical and functional features that characterize psychopathy from a synthesis of available neuroimaging research and discuss how such brain anomalies may account for psychopathic behavior. The results are consistent in showing anatomical alterations involving primarily a ventral system connecting the anterior temporal lobe to anterior and ventral frontal areas, and a dorsal system connecting the medial frontal lobe to the posterior cingulate cortex/precuneus complex and, in turn, to medial structures of the temporal lobe. Functional imaging data indicate that relevant emotional flow breakdown may occur in both these brain systems and suggest specific mechanisms via which emotion is anomalously integrated into cognition in psychopathic individuals during moral challenge. Directions for future research are delineated emphasizing, for instance, the relevance of further establishing the contribution of early life stress to a learned blockage of emotional self-exposure, and the potential role of androgenic hormones in the development of cortical anomalies.

A Systematic Literature Review of Neuroimaging of Psychopathic Traits

INTRODUCTION

Core psychopathy is characterized by grandiosity, callousness, manipulativeness, and lack of remorse, empathy, and guilt. It is often comorbid with conduct disorder and antisocial personality disorder (ASPD). Psychopathy is present in forensic as well as prison and general populations. In recent years, an increasing amount of neuroimaging studies has been conducted in order to elucidate the obscure neurobiological etiology of psychopathy. The studies have yielded heterogenous results, and no consensus has been reached.

AIMS

This study systematically reviewed and qualitatively summarized functional and structural neuroimaging studies conducted on individuals with psychopathic traits. Furthermore, this study aimed to evaluate whether the findings from different MRI modalities could be reconciled from a neuroanatomical perspective.

MATERIALS AND METHODS

After the search and auditing processes, 118 neuroimaging studies were included in this systematic literature review. The studies consisted of structural, functional, and diffusion tensor MRI studies.

RESULTS

Psychopathy was associated with numerous neuroanatomical abnormalities. Structurally, gray matter anomalies were seen in frontotemporal, cerebellar, limbic, and paralimbic regions. Associated gray matter volume (GMV) reductions were most pronounced particularly in most of the prefrontal cortex, and temporal gyri including the fusiform gyrus. Also decreased GMV of the amygdalae and hippocampi as well the cingulate and insular cortices were associated with psychopathy, as well as abnormal morphology of the hippocampi, amygdala, and nucleus accumbens. Functionally, psychopathy was associated with dysfunction of the default mode network, which was also linked to poor moral judgment as well as deficient metacognitive and introspective abilities. Second, reduced white matter integrity in the uncinate fasciculus and dorsal cingulum were associated with core psychopathy. Third, emotional detachment was associated with dysfunction of the posterior cerebellum, the human mirror neuron system and the Theory of Mind denoting lack of empathy and persistent failure in integrating affective information into cognition.

CONCLUSIONS

Structural and functional aberrancies involving the limbic and paralimbic systems including reduced integrity of the uncinate fasciculus appear to be associated with core psychopathic features. Furthermore, this review points towards the idea that ASPD and psychopathy might stem from divergent biological processes.

Spatial parcellations, spectral filtering, and connectivity measures in fMRI: Optimizing for discrimination

The analysis of Functional Connectivity (FC) is a key technique of fMRI, having been used to distinguish brain states and conditions. While many approaches to calculating FC are available, there have been few assessments of their differences, making it difficult to choose approaches, and compare results. Here, we assess the impact of methodological choices on discriminability, using a fully controlled data set of continuous active states involving basic visual and motor tasks, providing robust localized FC changes. We tested a range of anatomical and functional parcellations, including the AAL atlas, parcellations derived from the Human Connectome Project and Independent Component Analysis (ICA) of many dimensionalities. We measure amplitude, covariance, correlation, and regularized partial correlation under different temporal filtering choices. We evaluate features derived from these methods for discriminating states using MVPA. We find that multidimensional parcellations derived from functional data performed similarly, outperforming an anatomical atlas, with correlation and partial correlation (p < .05, FDR). Partial correlation, with appropriate regularization, outperformed correlation. Amplitude and covariance generally discriminated less well, although gave good results with high‐dimensionality ICA. We found that discriminative FC properties are frequency specific; higher frequencies performed surprisingly well under certain configurations of atlas choices and dependency measures, with ICA‐based parcellations revealing greater discriminability at high frequencies compared to other parcellations. Methodological choices in FC analyses can have a profound impact on results and can be selected to optimize accuracy, interpretability, and sharing of results. This work contributes to a basis for consistent selection of approaches to estimating and analyzing FC.

Task-evoked functional connectivity does not explain functional connectivity differences between rest and task conditions

During complex tasks, patterns of functional connectivity differ from those in the resting state. However, what accounts for such differences remains unclear. Brain activity during a task reflects an unknown mixture of spontaneous and task-evoked activities. The difference in functional connectivity between a task state and the resting state may reflect not only task-evoked functional connectivity, but also changes in spontaneously emerging networks. Here, we characterized the differences in apparent functional connectivity between the resting state and when human subjects were watching a naturalistic movie. Such differences were marginally explained by the task-evoked functional connectivity involved in processing the movie content. Instead, they were mostly attributable to changes in spontaneous networks driven by ongoing activity during the task. The execution of the task reduced the correlations in ongoing activity among different cortical networks, especially between the visual and non-visual sensory or motor cortices. Our results suggest that task-evoked activity is not independent from spontaneous activity, and that engaging in a task may suppress spontaneous activity and its inter-regional correlation.

Principal States of Dynamic Functional Connectivity Reveal the Link Between Resting-State and Task-State Brain: An fMRI Study

Task-related reorganization of functional connectivity (FC) has been widely investigated. Under classic static FC analysis, brain networks under task and rest have been demonstrated a general similarity. However, brain activity and cognitive process are believed to be dynamic and adaptive. Since static FC inherently ignores the distinct temporal patterns between rest and task, dynamic FC may be more a suitable technique to characterize the brain’s dynamic and adaptive activities. In this study, we adopted [Formula: see text]-means clustering to investigate task-related spatiotemporal reorganization of dynamic brain networks and hypothesized that dynamic FC would be able to reveal the link between resting-state and task-state brain organization, including broadly similar spatial patterns but distinct temporal patterns. In order to test this hypothesis, this study examined the dynamic FC in default-mode network (DMN) and motor-related network (MN) using Blood-Oxygenation-Level-Dependent (BOLD)-fMRI data from 26 healthy subjects during rest (REST) and a hand closing-and-opening (HCO) task. Two principal FC states in REST and one principal FC state in HCO were identified. The first principal FC state in REST was found similar to that in HCO, which appeared to represent intrinsic network architecture and validated the broadly similar spatial patterns between REST and HCO. However, the second FC principal state in REST with much shorter “dwell time” implied the transient functional relationship between DMN and MN during REST. In addition, a more frequent shifting between two principal FC states indicated that brain network dynamically maintained a “default mode” in the motor system during REST, whereas the presence of a single principal FC state and reduced FC variability implied a more temporally stable connectivity during HCO, validating the distinct temporal patterns between REST and HCO. Our results further demonstrated that dynamic FC analysis could offer unique insights in understanding how the brain reorganizes itself during rest and task states, and the ways in which the brain adaptively responds to the cognitive requirements of tasks.

Techniques of Neutralization: A Brain Network Perspective

Sykes and Matza introduced neutralization theory in 1957 to explain how juvenile delinquents retain a positive self-image when engaging in delinquent acts. Since then, aspects of neutralization theory have been incorporated into sociological and criminological theories to explain socially deviant behavior. Functional brain mapping research utilizing advanced magnetic resonance imaging techniques has identified complex, intrinsically organized, large-scale brain networks. Higher order operations commonly attributed to three brain networks (default mode network [DMN], central executive network [CEN], salience network [SN]) align closely with neutralization theory. This article briefly discusses brain networks in general and the DMN, CEN, and SN specifically. It also discusses how these networks are involved when engaging in the use of techniques of neutralization and offers implications for future research.