Individual-specific functional connectivity of the amygdala: A substrate for precision psychiatry

The subcortical default mode network and Alzheimer's disease: a systematic review and meta-analysis

The default mode network is a central cortical brain network suggested to play a major role in several disorders and to be particularly vulnerable to the neuropathological hallmarks of Alzheimer's disease. Subcortical involvement in the default mode network and its alteration in Alzheimer's disease remains largely unknown. We performed a systematic review, meta-analysis and empirical validation of the subcortical default mode network in healthy adults, combined with a systematic review, meta-analysis and network analysis of the involvement of subcortical default mode areas in Alzheimer's disease. Our results show that, besides the well-known cortical default mode network brain regions, the default mode network consistently includes subcortical regions, namely the thalamus, lobule and vermis IX and right Crus I/II of the cerebellum and the amygdala. Network analysis also suggests the involvement of the caudate nucleus. In Alzheimer's disease, we observed a left-lateralized cluster of decrease in functional connectivity which covered the medial temporal lobe and amygdala and showed overlap with the default mode network in a portion covering parts of the left anterior hippocampus and left amygdala. We also found an increase in functional connectivity in the right anterior insula. These results confirm the consistency of subcortical contributions to the default mode network in healthy adults and highlight the relevance of the subcortical default mode network alteration in Alzheimer's disease.

Creative tempo: Spatiotemporal dynamics of the default mode network in improvisational musicians

The intrinsic dynamics of human brain activity display a recurring pattern of anti-correlated activity between the default mode network (DMN), associated with internal processing and mentation, and task positive regions, associated with externally directed attention. In human functional magnetic resonance imaging (fMRI) data, this anti-correlated pattern is detectable on the infraslow timescale (<0.1 Hz) as a quasi-periodic pattern (QPP). While the DMN is implicated in creativity and musicality in traditional time-averaged functional connectivity studies, no one has yet explored how creative training may alter dynamic spatiotemporal patterns involving the DMN such as QPPs. In the present study, we compare the outputs of two QPP detection approaches, sliding window algorithm and complex principal components analysis (cPCA). We apply both methods to an existing dataset of musicians captured with resting state fMRI, grouped as either classical, improvisational, or minimally trained non-musicians. The original time-averaged functional connectivity (FC) analysis of this dataset used improvisation as a proxy for creative thinking and found that the DMN and visual networks (VIS) display higher connectivity in improvisational musicians. We expand upon this dataset's original study and find that QPP analysis detects convergent results at the group level with both methods. In improvisational musicians, dynamic functional correlation in the group-averaged QPP was found to be increased between the DMN-VIS and DMN-FPN for both the QPP algorithm and complex principal components analysis (cPCA) methods. Additionally, we found an unexpected increase in FC in the group-averaged QPP between the dorsal attention network and amygdala in improvisational musicians; this result was not reported in the original seed-based study of this dataset. The current study represents a novel application of two dynamic FC detection methods with results that replicate and expand upon previous seed-based FC findings. The results show the robustness of both the QPP phenomenon and its detection methods. This study also demonstrates the value of dynamic FC methods in reproducing seed-based findings and their promise in detecting group-wise or individual differences that may be missed by traditional seed-based resting state fMRI studies.

Understanding the heterogeneity of anxiety using a translational neuroscience approach

Anxiety disorders affect millions of people worldwide and present a challenge in neuroscience research because of their substantial heterogeneity in clinical presentation. While a great deal of progress has been made in understanding the neurobiology of fear and anxiety, these insights have not led to effective treatments. Understanding the relationship between phenotypic heterogeneity and the underlying biology is a critical first step in solving this problem. We show translation, reverse translation, and computational modeling can contribute to a refined, cross-species understanding of fear and anxiety as well as anxiety disorders. More specifically, we outline how animal models can be leveraged to develop testable hypotheses in humans by using targeted, cross-species approaches and ethologically informed behavioral paradigms. We discuss reverse translational approaches that can guide and prioritize animal research in nontraditional research species. Finally, we advocate for the use of computational models to harmonize cross-species and cross-methodology research into anxiety. Together, this translational neuroscience approach will help to bridge the widening gap between how we currently conceptualize and diagnose anxiety disorders, as well as aid in the discovery of better treatments for these conditions.

Anatomical Organization of the Amygdala: A Brief Visual Review

The amygdala consists of a collection of nuclei that are deep within the medial temporal lobe. Despite its small size, the amygdala is one of the most densely connected structures in the brain, and it plays a role in many superior neural functions, including neurovegetative control, motor control, memory processing, and neuromodulation. Advances in neuroimaging technology for examining brain activity have opened up new ways of understanding the functional contribution of this structure to emotions, learning, and related memories. Many studies have shown that the amygdala plays a key role in the pathophysiology of neuropsychiatric disorders, such as anxiety disorders, depression, aggression, and temporal epilepsy. This article reviews the anatomical structure of the amygdaloid complex and the connectivity among its subdivisions and with other brain structures, which will serve as a basis for understanding the clinical correlations.

Normalization of Fronto-Parietal Activation by Cognitive-Behavioral Therapy in Unmedicated Pediatric Patients With Anxiety Disorders

OBJECTIVE

Anxiety disorders are prevalent among youths and are often highly impairing. Cognitive-behavioral therapy (CBT) is an effective first-line treatment. The authors investigated the brain mechanisms associated with symptom change following CBT.

METHODS

Unmedicated youths diagnosed with an anxiety disorder underwent 12 weeks of CBT as part of two randomized clinical trials testing the efficacy of adjunctive computerized cognitive training. Across both trials, participants completed a threat-processing task during functional MRI before and after treatment. Age-matched healthy comparison youths completed two scans over the same time span. The mean age of the samples was 13.20 years (SD=2.68); 41% were male (youths with anxiety disorders, N=69; healthy comparison youths, N=62). An additional sample including youths at temperamental risk for anxiety (N=87; mean age, 10.51 years [SD=0.43]; 41% male) was utilized to test the stability of anxiety-related neural differences in the absence of treatment. Whole-brain regional activation changes (thresholded at p<0.001) were examined using task-based blood-oxygen-level-dependent response.

RESULTS

Before treatment, patients with an anxiety disorder exhibited altered activation in fronto-parietal attention networks and limbic regions relative to healthy comparison children across all task conditions. Fronto-parietal hyperactivation normalized over the course of treatment, whereas limbic responses remained elevated after treatment. In the at-risk sample, overlapping clusters emerged between regions showing stable associations with anxiety over time and regions showing treatment-related changes.

CONCLUSIONS

Activation in fronto-parietal networks may normalize after CBT in unmedicated pediatric anxiety patients. Limbic regions may be less amenable to acute CBT effects. Findings from the at-risk sample suggest that treatment-related changes may not be attributed solely to the passage of time.

Elevating the field for applying neuroimaging to individual patients in psychiatry

Although neuroimaging has been widely applied in psychiatry, much of the exuberance in decades past has been tempered by failed replications and a lack of definitive evidence to support the utility of imaging to inform clinical decisions. There are multiple promising ways forward to demonstrate the relevance of neuroimaging for psychiatry at the individual patient level. Ultra-high field magnetic resonance imaging is developing as a sensitive measure of neurometabolic processes of particular relevance that holds promise as a new way to characterize patient abnormalities as well as variability in response to treatment. Neuroimaging may also be particularly suited to the science of brain stimulation interventions in psychiatry given that imaging can both inform brain targeting as well as measure changes in brain circuit communication as a function of how effectively interventions improve symptoms. We argue that a greater focus on individual patient imaging data will pave the way to stronger relevance to clinical care in psychiatry. We also stress the importance of using imaging in symptom-relevant experimental manipulations and how relevance will be best demonstrated by pairing imaging with differential treatment prediction and outcome measurement. The priorities for using brain imaging to inform psychiatry may be shifting, which compels the field to solidify clinical relevance for individual patients over exploratory associations and biomarkers that ultimately fail to replicate.

Social cognitive regions of human association cortex are selectively connected to the amygdala

Reasoning about someone's thoughts and intentions - i.e., forming a theory of mind - is an important aspect of social cognition that relies on association areas of the brain that have expanded disproportionately in the human lineage. We recently showed that these association zones comprise parallel distributed networks that, despite occupying adjacent and interdigitated regions, serve dissociable functions. One network is selectively recruited by theory of mind processes. What circuit properties differentiate these parallel networks? Here, we show that social cognitive association areas are intrinsically and selectively connected to regions of the anterior medial temporal lobe that are implicated in emotional learning and social behaviors, including the amygdala at or near the basolateral complex and medial nucleus. The results suggest that social cognitive functions emerge through coordinated activity between amygdala circuits and a distributed association network, and indicate the medial nucleus may play an important role in social cognition in humans.

Fetal development of the human amygdala

The intricate development of the human amygdala involves a complex interplay of diverse processes, varying in speed and duration. In humans, transient cytoarchitectural structures deliquesce, leading to the formation of functionally distinct nuclei as a result of multiple interdependent developmental events. This study compares the amygdala's cytoarchitectural development in conjunction with specific antibody reactivity for neuronal, glial, neuropil, and radial glial fibers, synaptic, extracellular matrix, and myelin components in 39 fetal human brains. We recognized that the early fetal period, as a continuation of the embryonic period, is still dominated by relatively uniform histogenetic processes. The typical appearance of ovoid cell clusters in the lateral nucleus during midfetal period is most likely associated with the cell migration and axonal growth processes in the developing human brain. Notably, synaptic markers are firstly detected in the corticomedial group of nuclei, while immunoreactivity for the panaxonal neurofilament marker SMI 312 is found dorsally. The late fetal period is characterized by a protracted migration process evidenced by the presence of doublecortin and SOX-2 immunoreactivity ventrally, in the prospective paralaminar nucleus, reinforced by vimentin immunoreactivity in the last remaining radial glial fibers. Nearing the term period, SMI 99 immunoreactivity indicates that perinatal myelination becomes prominent primarily along major axonal pathways, laying the foundation for more pronounced functional maturation. This study comprehensively elucidates the rate and sequence of maturational events in the amygdala, highlighting the key role of prenatal development in its behavioral, autonomic, and endocrine regulation, with subsequent implications for both normal functioning and psychiatric disorders.

Novel mechanism-based treatments for pediatric anxiety and depressive disorders

Pediatric anxiety and depressive disorders are common, can be highly impairing, and can persist despite the best available treatments. Here, we review research into novel treatments for childhood anxiety and depressive disorders designed to target underlying cognitive, emotional, and neural circuit mechanisms. We highlight three novel treatments lying along a continuum relating to clinical impact of the disorder and the intensity of clinical management required. We review cognitive training, which involves the lowest risk and may be applicable for problems with mild to moderate impact; psychotherapy, which includes a higher level of clinical involvement and may be sufficient for problems with moderate impact; and brain stimulation, which has the highest potential risks and is therefore most appropriate for problems with high impact. For each treatment, we review the specific underlying cognitive, emotional, and brain circuit mechanisms that are being targeted, whether treatments modify those underlying mechanisms, and efficacy in reducing symptoms. We conclude by highlighting future directions, including the importance of work that leverages developmental windows of high brain plasticity to time interventions to the specific epochs in childhood that have the largest and most enduring life-long impact.

Cerebellar mutism is linked to midbrain volatility and desynchronization from speech cortices

Cerebellar mutism syndrome is a disorder of speech, movement and affect that can occur after tumour removal from the posterior fossa. Projections from the fastigial nuclei to the periaqueductal grey area were recently implicated in its pathogenesis, but the functional consequences of damaging these projections remain poorly understood. Here, we examine functional MRI data from patients treated for medulloblastoma to identify functional changes in key brain areas that comprise the motor system for speech, which occur along the timeline of acute speech impairment in cerebellar mutism syndrome. One hundred and twenty-four participants, all with medulloblastoma, contributed to the study: 45 with cerebellar mutism syndrome, 11 patients with severe postoperative deficits other than mutism, and 68 without either (asymptomatic). We first performed a data-driven parcellation to spatially define functional nodes relevant to the cohort that align with brain regions critical for the motor control of speech. We then estimated functional connectivity between these nodes during the initial postoperative imaging sessions to identify functional deficits associated with the acute phase of the disorder. We further analysed how functional connectivity changed over time within a subset of participants that had suitable imaging acquired over the course of recovery. Signal dispersion was also measured in the periaqueductal grey area and red nuclei to estimate activity in midbrain regions considered key targets of the cerebellum with suspected involvement in cerebellar mutism pathogenesis. We found evidence of periaqueductal grey dysfunction in the acute phase of the disorder, with abnormal volatility and desynchronization with neocortical language nodes. Functional connectivity with periaqueductal grey was restored in imaging sessions that occurred after speech recovery and was further shown to be increased with left dorsolateral prefrontal cortex. The amygdalae were also broadly hyperconnected with neocortical nodes in the acute phase. Stable connectivity differences between groups were broadly present throughout the cerebrum, and one of the most substantial differences-between Broca's area and the supplementary motor area-was found to be inversely related to cerebellar outflow pathway damage in the mutism group. These results reveal systemic changes in the speech motor system of patients with mutism, centred on limbic areas tasked with the control of phonation. These findings provide further support for the hypothesis that periaqueductal grey dysfunction (following cerebellar surgical injury) contributes to the transient postoperative non-verbal episode commonly observed in cerebellar mutism syndrome but highlights a potential role of intact cerebellocortical projections in chronic features of the disorder.

Effects of acute stress and depression on functional connectivity between prefrontal cortex and the amygdala

Stress is known to be a significant risk factor for the development of Major Depressive Disorder (MDD), yet the neural mechanisms that underlie this risk are poorly understood. Prior work has heavily implicated the corticolimbic system in the pathophysiology of MDD. In particular, the prefrontal cortex (PFC) and amygdala play a central role in regulating the response to stress, with dorsal PFC and ventral PFC exhibiting reciprocal excitatory and inhibitory influences on amygdala subregions. However, it remains unclear how best to disentangle the impact of stress from the impact of current MDD symptoms on this system. Here, we examined stress-induced changes in resting state functional connectivity (rsFC) within an a priori corticolimbic network in MDD patients and healthy controls (total n = 80) before and after an acute stressor or a "no stress" control condition. Using graph theoretic analysis, we found that connectivity between basolateral amygdala and dorsal prefrontal nodes of the corticolimbic network had a negative association with individual differences in chronic perceived stress at baseline. Following the acute stressor, healthy individuals showed a reduction of the amygdala node strength, while MDD patients exhibited little change. Finally, dorsal PFC-particularly dorsomedial PFC- connectivity to the basolateral amygdala was associated with the strength of the basolateral amygdala responses to loss feedback during a reinforcement learning task. These findings highlight attenuated connectivity between basolateral amygdala and prefrontal cortex in patients with MDD. In healthy individuals, acute stress exposure was found to push the corticolimbic network to a "stress-phenotype" that may be chronically present in patients with current depression and high levels of perceived stress. In sum, these results help to identify circuit mechanisms underlying the effects of acute stress and their role in mood disorders.

Substructure of the brain's Cingulo-Opercular network

The Cingulo-Opercular network (CON) is an executive network of the human brain that regulates actions. CON is composed of many widely distributed cortical regions that are involved in top-down control over both lower-level (i.e., motor) and higher-level (i.e., cognitive) functions, as well as in processing of painful stimuli. Given the topographical and functional heterogeneity of the CON, we investigated whether subnetworks within the CON support separable aspects of action control. Using precision functional mapping (PFM) in 15 participants with > 5 hours of resting state functional connectivity (RSFC) and task data, we identified three anatomically and functionally distinct CON subnetworks within each individual. These three distinct subnetworks were linked to Decisions, Actions, and Feedback (including pain processing), respectively, in convergence with a meta-analytic task database. These Decision, Action and Feedback subnetworks represent pathways by which the brain establishes top-down goals, transforms those goals into actions, implemented as movements, and processes critical action feedback such as pain.

Controversies and progress on standardization of large-scale brain network nomenclature

Progress in scientific disciplines is accompanied by standardization of terminology. Network neuroscience, at the level of macroscale organization of the brain, is beginning to confront the challenges associated with developing a taxonomy of its fundamental explanatory constructs. The Workgroup for HArmonized Taxonomy of NETworks (WHATNET) was formed in 2020 as an Organization for Human Brain Mapping (OHBM)-endorsed best practices committee to provide recommendations on points of consensus, identify open questions, and highlight areas of ongoing debate in the service of moving the field toward standardized reporting of network neuroscience results. The committee conducted a survey to catalog current practices in large-scale brain network nomenclature. A few well-known network names (e.g., default mode network) dominated responses to the survey, and a number of illuminating points of disagreement emerged. We summarize survey results and provide initial considerations and recommendations from the workgroup. This perspective piece includes a selective review of challenges to this enterprise, including (1) network scale, resolution, and hierarchies; (2) interindividual variability of networks; (3) dynamics and nonstationarity of networks; (4) consideration of network affiliations of subcortical structures; and (5) consideration of multimodal information. We close with minimal reporting guidelines for the cognitive and network neuroscience communities to adopt.

Echoes from Intrinsic Connectivity Networks in the Subcortex

Decades of research have greatly improved our understanding of intrinsic human brain organization in terms of functional networks and the transmodal hubs within the cortex at which they converge. However, substrates of multinetwork integration in the human subcortex are relatively uncharted. Here, we leveraged recent advances in subcortical atlasing and ultra-high field (7 T) imaging optimized for the subcortex to investigate the functional architecture of 14 individual structures in healthy adult males and females with a fully data-driven approach. We revealed that spontaneous neural activity in subcortical regions can be decomposed into multiple independent subsignals that correlate with, or "echo," the activity in functional networks across the cortex. Distinct subregions of the thalamus, striatum, claustrum, and hippocampus showed a varied pattern of echoes from attention, control, visual, somatomotor, and default mode networks, demonstrating evidence for a heterogeneous organization supportive of functional integration. Multiple network activity furthermore converged within the globus pallidus externa, substantia nigra, and ventral tegmental area but was specific to one subregion, while the amygdala and pedunculopontine nucleus preferentially affiliated with a single network, showing a more homogeneous topography. Subregional connectivity of the globus pallidus interna, subthalamic nucleus, red nucleus, periaqueductal gray, and locus coeruleus did not resemble patterns of cortical network activity. Together, these finding describe potential mechanisms through which the subcortex participates in integrated and segregated information processing and shapes the spontaneous cognitive dynamics during rest.SIGNIFICANCE STATEMENT Despite the impact of subcortical dysfunction on brain health and cognition, large-scale functional mapping of subcortical structures severely lags behind that of the cortex. Recent developments in subcortical atlasing and imaging at ultra-high field provide new avenues for studying the intricate functional architecture of the human subcortex. With a fully data-driven analysis, we reveal subregional connectivity profiles of a large set of noncortical structures, including those rarely studied in fMRI research. The results have implications for understanding how the functional organization of the subcortex facilitates integrative processing through cross-network information convergence, paving the way for future work aimed at improving our knowledge of subcortical contributions to intrinsic brain dynamics and spontaneous cognition.

Functional connectomics in depression: insights into therapies

Depression is a common mental disorder characterized by heterogeneous cognitive and behavioral symptoms. The emerging research paradigm of functional connectomics has provided a quantitative theoretical framework and analytic tools for parsing variations in the organization and function of brain networks in depression. In this review, we first discuss recent progress in depression-associated functional connectome variations. We then discuss treatment-specific brain network outcomes in depression and propose a hypothetical model highlighting the advantages and uniqueness of each treatment in relation to the modulation of specific brain network connectivity and symptoms of depression. Finally, we look to the future promise of combining multiple treatment types in clinical practice, using multisite datasets and multimodal neuroimaging approaches, and identifying biological depression subtypes.

Toward reframing brain-social dynamics: current assumptions and future challenges

Evolutionary analyses suggest that the human social brain and sociality appeared together. The two fundamental tools that accelerated the concurrent emergence of the social brain and sociality include learning and plasticity. The prevailing core idea is that the primate brain and the cortex in particular became reorganised over the course of evolution to facilitate dynamic adaptation to ongoing changes in physical and social environments. Encouraged by computational or survival demands or even by instinctual drives for living in social groups, the brain eventually learned how to learn from social experience via its massive plastic capacity. A fundamental framework for modeling these orchestrated dynamic responses is that social plasticity relies upon neuroplasticity. In the present article, we first provide a glimpse into the concepts of plasticity, experience, with emphasis on social experience. We then acknowledge and integrate the current theoretical concepts to highlight five key intertwined assumptions within social neuroscience that underlie empirical approaches for explaining the brain-social dynamics. We suggest that this epistemological view provides key insights into the ontology of current conceptual frameworks driving future research to successfully deal with new challenges and possible caveats in favour of the formulation of novel assumptions. In the light of contemporary societal challenges, such as global pandemics, natural disasters, violent conflict, and other human tragedies, discovering the mechanisms of social brain plasticity will provide new approaches to support adaptive brain plasticity and social resilience.

Neurobiology of Treatment in Pediatric Anxiety Disorders

Both pharmacologic and psychotherapeutic treatment-related changes increase activity in brain regions implicated in prefrontal regulatory circuits, and the functional connectivity of these regions with the amygdala is enhanced following pharmacological treatment. This may suggest overlapping mechanisms of action across therapeutic modalities. The existing literature is best viewed as a partially constructed scaffold on which to construct a vigorous understanding of biomarkers in pediatric anxiety syndromes. As the field approaches leveraging "fingerprints" in neuroimaging with "outputs" in neuropsychiatric tasks and scale, we can move beyond one-size-fits-all selection of psychiatric interventions toward more nuanced therapeutic strategies that recognize individual differences.

Increased functional connectivity of amygdala subregions in patients with drug-naïve panic disorder and without comorbidities

BACKGROUND

Amygdala plays an important role in the neurobiological basis of panic disorder (PD), and the amygdala contains different subregions, which may play different roles in PD. The aim of the present study was to examine whether there are common or distinct patterns of functional connectivity of the amygdala subregions in PD using resting-state functional magnetic resonance imaging and to explore the relationship between the abnormal spontaneous functional connectivity patterns of the regions of interest (ROIs) and the clinical symptoms of PD patients.

METHODS

Fifty-three drug-naïve, non-comorbid PD patients and 70 healthy controls (HCs) were recruited. Seed-based resting-state functional connectivity (rsFC) analyses were conducted using the bilateral amygdalae and its subregions as the ROI seed. Two samples t test was performed for the seed-based Fisher's z -transformed correlation maps. The relationship between the abnormal spontaneous functional connectivity patterns of the ROIs and the clinical symptoms of PD patients was investigated by Pearson correlation analysis.

RESULTS

PD patients showed increased rsFC of the bilateral amygdalae and almost all the amygdala subregions with the precuneus/posterior cingulate gyrus compared with the HC group (left amygdala [lAMY]: t  = 4.84, P  <0.001; right amygdala [rAMY]: t  = 4.55, P  <0.001; left centromedial amygdala [lCMA]: t  = 3.87, P  <0.001; right centromedial amygdala [rCMA]: t  = 3.82, P  = 0.002; left laterobasal amygdala [lBLA]: t  = 4.33, P  <0.001; right laterobasal amygdala [rBLA]: t  = 4.97, P  <0.001; left superficial amygdala [lSFA]: t  = 3.26, P  = 0.006). The rsFC of the lBLA with the left angular gyrus/inferior parietal lobule remarkably increased in the PD group ( t  = 3.70, P  = 0.003). And most of the altered rsFCs were located in the default mode network (DMN). A significant positive correlation was observed between the severity of anxiety and the rsFC between the lSFA and the left precuneus in PD patients ( r  = 0.285, P  = 0.039).

CONCLUSIONS

Our research suggested that the increased rsFC of amygdala subregions with DMN plays an important role in the pathogenesis of PD. Future studies may further explore whether the rsFC of amygdala subregions, especially with the regions in DMN, can be used as a biological marker of PD.

Regional superficial amygdala resting-state functional connectivity in adults infers childhood maltreatment severity

Background

Childhood maltreatment (CM) is a potential risk factor for some neuropsychiatric disorders in adulthood (e.g. depression and anxiety) and alters trajectories of brain development. Accumulating evidence suggests that functional connectivity of the limbic system, especially the amygdala, is highly associated with childhood maltreatment, although not all studies have found this. These inconsistent results may be due to differential alterations of amygdala resting-state functional connectivity (rsFC) following childhood maltreatment.

Objective

Our aim was to investigate the relationship between the rsFC of amygdala subregions and CM severity, as well as to develop a stable rsFC-based model for inferring the severity of CM.

Methods

In this study, we employed the Childhood Trauma Questionnaire (CTQ) to assess CM severity in each individual. We explored the relationship between the rsFC of amygdala subregions (i.e. centromedial -CMA, basolateral -BLA, superficial-SFA amygdala) and CM experience in a discovery dataset of n = 110 healthy Chinese participants by linear multiple regression analysis. Subsequent dimensional and categorical approach were performed to elucidate the relationship between rsFCs and CM severity and CM subtypes, respectively. A support vector regression model was then conducted to validate the associations between rsFCs and total CTQ scores. Moreover, we also verified the model into another independent replication dataset (n = 38).

Results

Our findings suggested that childhood maltreatment was negatively associated with rsFC between the right superficial amygdala and perigenual anterior cingulate cortex (pgACC)/postcentral gyrus (PCG) but not the other two amygdala subregions. Moreover, SFA-pgACC coupling was more associated with physical neglect whereas the SFA-PCG was more related to emotional neglect. In addition, supervised machine learning confirmed that using these two rsFCs as predictors could stably estimate continuous maltreatment severity in both discovery and replication datasets.

Conclusion

The current study supports that the rsFCs of superficial amygdala are related to childhood maltreatment and which may be a potential biomarker for the effects of childhood maltreatment-related psychiatric disorders (i.e. depression and anxiety).

Using synthetic MR images for distortion correction

Functional MRI (fMRI) data acquired using echo-planar imaging (EPI) are highly distorted by magnetic field inhomogeneities. Distortion and differences in image contrast between EPI and T1-weighted and T2-weighted (T1w/T2w) images makes their alignment a challenge. Typically, field map data are used to correct EPI distortions. Alignments achieved with field maps can vary greatly and depends on the quality of field map data. However, many public datasets lack field map data entirely. Additionally, reliable field map data is often difficult to acquire in high-motion pediatric or developmental cohorts. To address this, we developed Synth, a software package for distortion correction and cross-modal image registration that does not require field map data. Synth combines information from T1w and T2w anatomical images to construct an idealized undistorted synthetic image with similar contrast properties to EPI data. This synthetic image acts as an effective reference for individual-specific distortion correction. Using pediatric (ABCD: Adolescent Brain Cognitive Development) and adult (MSC: Midnight Scan Club; HCP: Human Connectome Project) data, we demonstrate that Synth performs comparably to field map distortion correction approaches, and often outperforms them. Field map-less distortion correction with Synth allows accurate and precise registration of fMRI data with missing or corrupted field map information.

Functional Connectivity Mapping for rTMS Target Selection in Depression

OBJECTIVE

Repetitive transcranial magnetic stimulation (rTMS) protocols increasingly use subgenual anterior cingulate cortex (sgACC) functional connectivity to individualize treatment targets. However, the efficacy of this approach is unclear, with conflicting findings and varying effect sizes across studies. Here, the authors investigated the effect of the stimulation site's functional connectivity with the sgACC (sgACC-StimFC) on treatment outcome to rTMS in 295 patients with major depression.

METHODS

The reliability and accuracy of estimating sgACC functional connectivity were validated with data from individuals who underwent extensive functional MRI testing. Electric field modeling was used to analyze associations between sgACC-StimFC and clinical improvement using standardized assessments and to evaluate sources of heterogeneity.

RESULTS

An imputation-based method provided reliable and accurate sgACC functional connectivity estimates. Treatment responses weakly but robustly correlated with sgACC-StimFC (r=-0.16), but only when the stimulated cortex was identified using electric field modeling. Surprisingly, this association was driven by patients with strong global signal fluctuations stemming from a specific periodic respiratory pattern (r=-0.49).

CONCLUSIONS

Functional connectivity between the sgACC and the stimulated cortex was correlated with individual differences in treatment outcomes, but the association was weaker than those observed in previous studies and was accentuated in a subgroup of patients with distinct, respiration-related signal patterns in their scans. These findings indicate that in a large representative sample of patients with major depressive disorder, individual differences in sgACC-StimFC explained only ∼3% of the variance in outcomes, which may limit the utility of existing sgACC-based targeting protocols. However, these data also provide strong evidence for a true-albeit small-effect and highlight opportunities for incorporating additional functional connectivity measures to generate models of rTMS response with enhanced predictive power.

Network-specific selectivity of functional connections in the neonatal brain

The adult human brain is organized into functional brain networks, groups of functionally connected segregated brain regions. A key feature of adult functional networks is long-range selectivity, the property that spatially distant regions from the same network have higher functional connectivity than spatially distant regions from different networks. Although it is critical to establish the status of functional networks and long-range selectivity during the neonatal period as a foundation for typical and atypical brain development, prior work in this area has been mixed. Although some studies report distributed adult-like networks, other studies suggest that neonatal networks are immature and consist primarily of spatially isolated regions. Using a large sample of neonates (n = 262), we demonstrate that neonates have long-range selective functional connections for the default mode, fronto-parietal, and dorsal attention networks. An adult-like pattern of functional brain networks is evident in neonates when network-detection algorithms are tuned to these long-range connections, when using surface-based registration (versus volume-based registration), and as per-subject data quantity increases. These results help clarify factors that have led to prior mixed results, establish that key adult-like functional network features are evident in neonates, and provide a foundation for studies of typical and atypical brain development.

Morphological Features of Human Dendritic Spines

Dendritic spine features in human neurons follow the up-to-date knowledge presented in the previous chapters of this book. Human dendrites are notable for their heterogeneity in branching patterns and spatial distribution. These data relate to circuits and specialized functions. Spines enhance neuronal connectivity, modulate and integrate synaptic inputs, and provide additional plastic functions to microcircuits and large-scale networks. Spines present a continuum of shapes and sizes, whose number and distribution along the dendritic length are diverse in neurons and different areas. Indeed, human neurons vary from aspiny or "relatively aspiny" cells to neurons covered with a high density of intermingled pleomorphic spines on very long dendrites. In this chapter, we discuss the phylogenetic and ontogenetic development of human spines and describe the heterogeneous features of human spiny neurons along the spinal cord, brainstem, cerebellum, thalamus, basal ganglia, amygdala, hippocampal regions, and neocortical areas. Three-dimensional reconstructions of Golgi-impregnated dendritic spines and data from fluorescence microscopy are reviewed with ultrastructural findings to address the complex possibilities for synaptic processing and integration in humans. Pathological changes are also presented, for example, in Alzheimer's disease and schizophrenia. Basic morphological data can be linked to current techniques, and perspectives in this research field include the characterization of spines in human neurons with specific transcriptome features, molecular classification of cellular diversity, and electrophysiological identification of coexisting subpopulations of cells. These data would enlighten how cellular attributes determine neuron type-specific connectivity and brain wiring for our diverse aptitudes and behavior.

Human amygdala compared to orbitofrontal cortex connectivity, and emotion

The amygdala and orbitofrontal cortex have been implicated in emotion. To understand these regions better in humans, their effective connectivity with 360 cortical regions was measured in 171 humans from the Human Connectome Project, and complemented with functional connectivity and diffusion tractography. The human amygdala has effective connectivity from few cortical regions compared to the orbitofrontal cortex: primarily from auditory cortex A5 and the related superior temporal gyrus and temporal pole regions; the piriform (olfactory) cortex; the lateral orbitofrontal cortex 47m; somatosensory cortex; the hippocampus, entorhinal cortex, perirhinal cortex, and parahippocampal TF; and from the cholinergic nucleus basalis. The amygdala has effective connectivity to the hippocampus, entorhinal and perirhinal cortex; to the temporal pole; and to the lateral orbitofrontal cortex. The orbitofrontal cortex has effective connectivity from gustatory, olfactory, and temporal visual, auditory and pole cortex, and to the pregenual anterior and posterior cingulate cortex, hippocampal system, and prefrontal cortex, and provides for rewards and punishers to be used in reported emotions, and memory and navigation to goals. Given the paucity of amygdalo-neocortical connectivity in humans, it is proposed that the human amygdala is involved primarily in autonomic and conditioned responses via brainstem connectivity, rather than in reported (declarative) emotion.

Individualized Functional Connectome Identified Replicable Biomarkers for Dysphoric Symptoms in First-Episode Medication-Naïve Patients With Major Depressive Disorder

BACKGROUND

Major depressive disorder (MDD) is a heterogeneous syndrome and can be conceptualized as a mixture of dimensional abnormalities across several specific brain circuits. The neural underpinnings of different symptom dimensions in MDD are not well understood. We aimed to identify robust, generalizable, functional connectivity (FC)-based biomarkers for different symptom dimensions in MDD using individualized functional connectomes.

METHODS

Patterns of FC associated with symptom severity were identified using a novel, individualized, functional network parcellation analysis in conjunction with hierarchical clustering. Dimension-specific prediction models were trained to estimate symptom severity in first-episode medication-naïve patients (discovery dataset, n = 95) and replicated in an independent validation dataset (n = 94). The correlation between FC changes and symptom changes was further explored in a treatment dataset (n = 55).

RESULTS

Two distinct symptom clusters previously identified in patients with MDD, namely dysphoric and anxiosomatic clusters, were robustly replicated in our data. A connectivity biomarker associated with dysphoric symptoms was identified, which mainly involved the default, dorsal attention, and limbic networks. Critically, this brain-symptom association was confirmed in the validation dataset. Moreover, the marker also tracked dysphoric symptom improvement following a 2-week antidepressant treatment. For comparison, we repeated our analyses using a nonindividualized approach and failed to identify replicable brain-symptom biomarkers. Further quantitative analysis indicated that the generalizability of the connectivity-symptom association was hampered when functional regions were not localized in individuals.

CONCLUSIONS

This work reveals robust, replicable FC biomarkers for dysphoric symptoms in MDD, demonstrates the advantage of individual-oriented approach, and emphasizes the importance of independent validation in psychiatric neuroimaging analysis.

Contributions of human amygdala nuclei to resting-state networks

The amygdala is a brain region with a complex internal structure that is associated with psychiatric disease. Methodological limitations have complicated the study of the internal structure of the amygdala in humans. In the current study we examined the functional connectivity between nine amygdaloid nuclei and existing resting-state networks using a high spatial-resolution fMRI dataset. Using data-driven analysis techniques we found that there were three main clusters inside the amygdala that correlated with the somatomotor, ventral attention and default mode networks. In addition, we found that each resting-state networks depended on a specific configuration of amygdaloid nuclei. Finally, we found that co-activity in the cortical-nucleus increased with the severity of self-rated fear in participants. These results highlight the complex nature of amygdaloid connectivity that is not confined to traditional large-scale divisions, implicates specific configurations of nuclei with certain resting-state networks and highlights the potential clinical relevance of the cortical-nucleus in future studies of the human amygdala.

Linking Individual Differences in Personalized Functional Network Topography to Psychopathology in Youth

BACKGROUND

The spatial layout of large-scale functional brain networks differs between individuals and is particularly variable in the association cortex, implicated in a broad range of psychiatric disorders. However, it remains unknown whether this variation in functional topography is related to major dimensions of psychopathology in youth.

METHODS

The authors studied 790 youths ages 8 to 23 years who had 27 minutes of high-quality functional magnetic resonance imaging data as part of the Philadelphia Neurodevelopmental Cohort. Four correlated dimensions were estimated using a confirmatory correlated traits factor analysis on 112 item-level clinical symptoms, and one overall psychopathology factor with 4 orthogonal dimensions were extracted using a confirmatory factor analysis. Spatially regularized nonnegative matrix factorization was used to identify 17 individual-specific functional networks for each participant. Partial least square regression with split-half cross-validation was conducted to evaluate to what extent the topography of personalized functional networks encodes major dimensions of psychopathology.

RESULTS

Personalized functional network topography significantly predicted unseen individuals' major dimensions of psychopathology, including fear, psychosis, externalizing, and anxious-misery. Reduced representation of association networks was among the most important features for the prediction of all 4 dimensions. Further analysis revealed that personalized functional network topography predicted overall psychopathology (r = 0.16, permutation testing p < .001), which drove prediction of the 4 correlated dimensions.

CONCLUSIONS

These results suggest that individual differences in functional network topography in association networks is related to overall psychopathology in youth. Such results underscore the importance of considering functional neuroanatomy for personalized diagnostics and therapeutics in psychiatry.

Perceived danger associated with a property modulates cross category generalization

Identifying projectable predicates is a key issue in understanding inductive inference. It is proposed that looking into the evolutionary psychology literature for adaptive properties may be one useful approach. One hypothesis that emerges from this literature is that properties that signal danger or harm should be more salient than properties that do not. Two studies are carried out to test this hypothesis. In study 1 participants were presented with a scenario involving the discovery of novel animals, for which there was incomplete information. Three types of properties (a harmful property, a neutral property, a beneficial property) were associated with animals in one (base) category and participants were asked to indicate strength of generalization of the property to a target within the category, and to a target across to another category. In the second experiment, the procedure was repeated, but in addition, subjects were also explicitly asked to indicate whether the base and target belonged to the same or different categories. Study 1 showed that the harmful property was more projectable compared to the beneficial and neutral properties. Study 2 reconfirmed this and further showed that it also promoted excessive generalization across categories. The results suggest that examination of adaptations identified by evolutionary psychologists may be a useful source of insight in the study of inductive inference.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-022-09793-3.

Human cortical amygdala dendrites and spines morphology under open‐source three‐dimensional reconstruction procedures

Visualizing nerve cells has been fundamental for the systematic description of brain structure and function in humans and other species. Different approaches aimed to unravel the morphological features of neuron types and diversity. The inherent complexity of the human nervous tissue and the need for proper histological processing have made studying human dendrites and spines challenging in postmortem samples. In this study, we used Golgi data and open-source software for 3D image reconstruction of human neurons from the cortical amygdaloid nucleus to show different dendrites and pleomorphic spines at different angles. Procedures required minimal equipment and generated high-quality images for differently shaped cells. We used the "single-section" Golgi method adapted for the human brain to engender 3D reconstructed images of the neuronal cell body and the dendritic ramification by adopting a neuronal tracing procedure. In addition, we elaborated 3D reconstructions to visualize heterogeneous dendritic spines using a supervised machine learning-based algorithm for image segmentation. These tools provided an additional upgrade and enhanced visual display of information related to the spatial orientation of dendritic branches and for dendritic spines of varied sizes and shapes in these human subcortical neurons. This same approach can be adapted for other techniques, areas of the central or peripheral nervous system, and comparative analysis between species.

Automated optimization of TMS coil placement for personalized functional network engagement

Transcranial magnetic stimulation (TMS) is used to treat multiple psychiatric and neurological conditions by manipulating activity in particular brain networks and circuits, but individual responses are highly variable. In clinical settings, TMS coil placement is typically based on either group average functional maps or scalp heuristics. Here, we found that this approach can inadvertently target different functional networks in depressed patients due to variability in their functional brain organization. More precise TMS targeting should be feasible by accounting for each patient's unique functional neuroanatomy. To this end, we developed a targeting approach, termed targeted functional network stimulation (TANS). The TANS approach improved stimulation specificity in silico in 8 highly sampled patients with depression and 6 healthy individuals and in vivo when targeting somatomotor functional networks representing the upper and lower limbs. Code for implementing TANS and an example dataset are provided as a resource.

Person-specific and precision neuroimaging: Current methods and future directions

Most neuroimaging studies of brain function analyze data in normalized space to identify regions of common activation across participants. These studies treat interindividual differences in brain organization as noise, but this approach can obscure important information about the brain's functional architecture. Recently, a number of studies have adopted a person-specific approach that aims to characterize these individual differences and explore their reliability and implications for behavior. A subset of these studies has taken a precision imaging approach that collects multiple hours of data from each participant to map brain function on a finer scale. In this review, we provide a broad overview of how person-specific and precision imaging techniques have used resting-state measures to examine individual differences in the brain's organization and their impact on behavior, followed by how task-based activity continues to add detail to these discoveries. We argue that person-specific and precision approaches demonstrate substantial promise in uncovering new details of the brain's functional organization and its relationship to behavior in many areas of cognitive neuroscience. We also discuss some current limitations in this new field and some new directions it may take.

Greater interruption of visual processing and memory encoding by visceral than somatic pain in healthy volunteers - An fMRI study

Visceral pain is regarded as more salient than somatic pain. It has greater affective and emotional components, i.e., it elicits higher levels of pain-related fear and is perceived as more unpleasant than somatic pain. In this fMRI study, we examined the neural effects of painful visceral as compared to painful somatic stimulation on visual processing and memory encoding in a visual categorization and surprise recognition task in healthy volunteers. During the categorization task, participants received either rectal distensions or heat stimuli applied to the forearm, with stimuli being individually matched for unpleasantness. Behaviorally, visceral pain reduced memory encoding as compared to somatic pain (Kleine-Borgmann et al., 2021). Imaging analyses now revealed that visceral pain was associated with reduced activity (i.e., greater pain-related interruption) in neural areas typically involved in visual processing and memory encoding. These include the parahippocampal gyrus, fusiform gyrus, striatum, occipital cortex, insula, and the amygdala. Moreover, reduced engagement of the lateral occipital complex during visual categorization under visceral pain was associated with higher visceral pain-related fear. These findings obtained in healthy volunteers shed light on the neural circuitry underlying the interruptive effect of visceral pain and pave the way for future studies in patient samples.

Associations between early-life stress exposure and internalizing symptomatology during the COVID-19 pandemic: Assessing the role of neurobehavioral mediators

Background

The ongoing COVID-19 pandemic is a major stressor that has been associated with increased risk for psychiatric illness in the general population. Recent work has highlighted that experiences of early-life stress (ELS) may impact individuals' psychological functioning and vulnerability for developing internalizing psychopathology in response to pandemic-related stress. However, little is known about the neurobehavioral factors that may mediate the association between ELS exposure and COVID-related internalizing symptomatology. The current study sought to examine the mediating roles of pre-pandemic resting-state frontoamygdala connectivity and concurrent emotion regulation (ER) in the association between ELS and pandemic-related internalizing symptomatology.

Methods

Retrospective life-stress histories, concurrent self-reported ER strategies (i.e., reappraisal and suppression), concurrent self-reported internalizing symptomatology (i.e., depression- and anxiety-related symptomatology), and resting-state functional connectivity data from a sample of adults (N = 64, M age = 22.12, female = 68.75%) were utilized.

Results

There were no significant direct associations between ELS and COVID-related internalizing symptomatology. Neither frontoamygdala functional connectivity nor ER strategy use mediated an association between ELS and COVID-related internalizing symptomatology (ps > 0.05). Exploratory analyses identified a significant moderating effect of reappraisal use on the association between ELS and internalizing symptomatology (β = -0.818, p = 0.047), such that increased reappraisal use buffered the impact of ELS on psychopathology.

Conclusions

While frontoamygdala connectivity and ER do not appear to mediate the association between ELS and COVID-related internalizing symptomatology, our findings suggest that the use of reappraisal may buffer against the effect of ELS on mental health during the pandemic.

Immature excitatory neurons in the amygdala come of age during puberty

The human amygdala is critical for emotional learning, valence coding, and complex social interactions, all of which mature throughout childhood, puberty, and adolescence. Across these ages, the amygdala paralaminar nucleus (PL) undergoes significant structural changes including increased numbers of mature neurons. The PL contains a large population of immature excitatory neurons at birth, some of which may continue to be born from local progenitors. These progenitors disappear rapidly in infancy, but the immature neurons persist throughout childhood and adolescent ages, indicating that they develop on a protracted timeline. Many of these late-maturing neurons settle locally within the PL, though a small subset appear to migrate into neighboring amygdala subnuclei. Despite its prominent growth during postnatal life and possible contributions to multiple amygdala circuits, the function of the PL remains unknown. PL maturation occurs predominately during late childhood and into puberty when sex hormone levels change. Sex hormones can promote developmental processes such as neuron migration, dendritic outgrowth, and synaptic plasticity, which appear to be ongoing in late-maturing PL neurons. Collectively, we describe how the growth of late-maturing neurons occurs in the right time and place to be relevant for amygdala functions and neuropsychiatric conditions.

Accuracy and reliability of diffusion imaging models

Diffusion imaging aims to non-invasively characterize the anatomy and integrity of the brain's white matter fibers. We evaluated the accuracy and reliability of commonly used diffusion imaging methods as a function of data quantity and analysis method, using both simulations and highly sampled individual-specific data (927-1442 diffusion weighted images [DWIs] per individual). Diffusion imaging methods that allow for crossing fibers (FSL's BedpostX [BPX], DSI Studio's Constant Solid Angle Q-Ball Imaging [CSA-QBI], MRtrix3's Constrained Spherical Deconvolution [CSD]) estimated excess fibers when insufficient data were present and/or when the data did not match the model priors. To reduce such overfitting, we developed a novel Bayesian Multi-tensor Model-selection (BaMM) method and applied it to the popular ball-and-stick model used in BedpostX within the FSL software package. BaMM was robust to overfitting and showed high reliability and the relatively best crossing-fiber accuracy with increasing amounts of diffusion data. Thus, sufficient data and an overfitting resistant analysis method enhance precision diffusion imaging. For potential clinical applications of diffusion imaging, such as neurosurgical planning and deep brain stimulation (DBS), the quantities of data required to achieve diffusion imaging reliability are lower than those needed for functional MRI.

Temporally and anatomically specific contributions of the human amygdala to threat and safety learning

Pavlovian threat learning is a primary translational model for understanding the brain systems that underlie anxiety and trauma-related psychopathology. The amygdala has traditionally played a central role in this important form of learning across species. However, recent human neuroimaging work has revealed inconsistent findings regarding the role of human amygdala in threat and safety learning. To address this discrepancy, we examined amygdala responses to threat-predictive cues in a large sample of human participants. We found robust evidence for amygdala responses during threat conditioning and, further, that these responses occurred in a temporally and anatomically specific manner. Our results reveal clear evidence of human amygdala involvement in associative learning and offer insight into why some neuroimaging work has yielded equivocal findings.

Neural plasticity in subareas of the rodent amygdala is widely known to be essential for Pavlovian threat conditioning and safety learning. However, less consistent results have been observed in human neuroimaging studies. Here, we identify and test three important factors that may contribute to these discrepancies: the temporal profile of amygdala response in threat conditioning, the anatomical specificity of amygdala responses during threat conditioning and safety learning, and insufficient power to identify these responses. We combined data across multiple studies using a well-validated human threat conditioning paradigm to examine amygdala involvement during threat conditioning and safety learning. In 601 humans, we show that two amygdala subregions tracked the conditioned stimulus with aversive shock during early conditioning while only one demonstrated delayed responding to a stimulus not paired with shock. Our findings identify cross-species similarities in temporal- and anatomical-specific amygdala contributions to threat and safety learning, affirm human amygdala involvement in associative learning and highlight important factors for future associative learning research in humans.

Individualized Functional Subnetworks Connect Human Striatum and Frontal Cortex

The striatum and cerebral cortex are interconnected via multiple recurrent loops that play a major role in many neuropsychiatric conditions. Primate corticostriatal connections can be precisely mapped using invasive tract-tracing. However, noninvasive human research has not mapped these connections with anatomical precision, limited in part by the practice of averaging neuroimaging data across individuals. Here we utilized highly sampled resting-state functional connectivity MRI for individual-specific precision functional mapping (PFM) of corticostriatal connections. We identified ten individual-specific subnetworks linking cortex-predominately frontal cortex-to striatum, most of which converged with nonhuman primate tract-tracing work. These included separable connections between nucleus accumbens core/shell and orbitofrontal/medial frontal gyrus; between anterior striatum and dorsomedial prefrontal cortex; between dorsal caudate and lateral prefrontal cortex; and between middle/posterior putamen and supplementary motor/primary motor cortex. Two subnetworks that did not converge with nonhuman primates were connected to cortical regions associated with human language function. Thus, precision subnetworks identify detailed, individual-specific, neurobiologically plausible corticostriatal connectivity that includes human-specific language networks.

Generalized Connectivity Matrix Response Regression with Applications in Brain Connectivity Studies

Multiple-subject network data are fast emerging in recent years, where a separate connectivity matrix is measured over a common set of nodes for each individual subject, along with subject covariates information. In this article, we propose a new generalized matrix response regression model, where the observed network is treated as a matrix-valued response and the subject covariates as predictors. The new model characterizes the population-level connectivity pattern through a low-rank intercept matrix, and the effect of subject covariates through a sparse slope tensor. We develop an efficient alternating gradient descent algorithm for parameter estimation, and establish the non-asymptotic error bound for the actual estimator from the algorithm, which quantifies the interplay between the computational and statistical errors. We further show the strong consistency for graph community recovery, as well as the edge selection consistency. We demonstrate the efficacy of our method through simulations and two brain connectivity studies.

Dissociable multi-scale patterns of development in personalized brain networks

The brain is organized into networks at multiple resolutions, or scales, yet studies of functional network development typically focus on a single scale. Here, we derive personalized functional networks across 29 scales in a large sample of youths (n = 693, ages 8-23 years) to identify multi-scale patterns of network re-organization related to neurocognitive development. We found that developmental shifts in inter-network coupling reflect and strengthen a functional hierarchy of cortical organization. Furthermore, we observed that scale-dependent effects were present in lower-order, unimodal networks, but not higher-order, transmodal networks. Finally, we found that network maturation had clear behavioral relevance: the development of coupling in unimodal and transmodal networks are dissociably related to the emergence of executive function. These results suggest that the development of functional brain networks align with and refine a hierarchy linked to cognition.

Altered centromedial amygdala functional connectivity in adults is associated with childhood emotional abuse and predicts levels of depression and anxiety

BACKGROUND

Childhood maltreatment is significantly associated with greater occurrence of mental disorders in adulthood such as depression and anxiety. As a key node of the limbic system, the amygdala is engaged in emotional processing and regulation and is dysfunctional in many psychiatric disorders. The present study aimed at exploring the association between childhood maltreatment and amygdala-based functional networks and their potential contributions to depression and anxiety.

METHODS

Totally 90 Chinese healthy volunteers participated in a resting-state fMRI experiment. Levels of childhood maltreatment experience were assessed using the Childhood Trauma Questionnaire (CTQ-SF) as well as levels of depression and anxiety. Associations between CTQ-SF scores and bilateral amygdala gray matter volume and resting-state functional connectivity (RSFC) of the amygdala and selected regions of interest were analyzed using multiple regression analyses with sex and age as covariates. A subsequent moderation analysis was performed to identify whether associations were predictive of depression and anxiety levels.

RESULTS

Childhood maltreatment was significantly negatively associated with RSFC between left amygdala and anterior insula. Further sub-region analyses revealed that this negative association only occurred for the left centromedial amygdala subregion, which subsequently moderated the relationship between levels of childhood emotional abuse and depression / anxiety.

LIMITATIONS

No psychiatric patients were involved and specific neural associations with different childhood maltreatment subtypes need to be examined in future studies.

CONCLUSION

The present findings provide evidence for altered RSFC of centromedial amygdala and the anterior insula associated with childhood maltreatment and which moderate levels of depression and anxiety in adulthood.

A neuroimaging study of interpersonal distance in identical and fraternal twins

Keeping appropriate interpersonal distance is an evolutionary conserved behavior that can be adapted based on learning. Detailed knowledge on how interpersonal space is represented in the brain and whether such representation is genetically influenced is lacking. We measured brain function using functional magnetic resonance imaging in 294 twins (71 monozygotic, 76 dizygotic pairs) performing a distance task where neural responses to human figures were compared to cylindrical blocks. Proximal viewing distance of human figures was compared to cylinders facilitated responses in the occipital face area (OFA) and the superficial part of the amygdala, which is consistent with these areas playing a role in monitoring interpersonal distance. Using the classic twin method, we observed a genetic influence on interpersonal distance related activation in the OFA, but not in the amygdala. Results suggest that genetic factors may influence interpersonal distance monitoring via the OFA whereas the amygdala may play a role in experience‐dependent adjustments of interpersonal distance.

Neurocircuitry of Treatment in Anxiety Disorders

Background:

Methods:

Results:

Conclusions:

Decoding cognition from spontaneous neural activity

In human neuroscience, studies of cognition are rarely grounded in non-task-evoked, 'spontaneous' neural activity. Indeed, studies of spontaneous activity tend to focus predominantly on intrinsic neural patterns (for example, resting-state networks). Taking a 'representation-rich' approach bridges the gap between cognition and resting-state communities: this approach relies on decoding task-related representations from spontaneous neural activity, allowing quantification of the representational content and rich dynamics of such activity. For example, if we know the neural representation of an episodic memory, we can decode its subsequent replay during rest. We argue that such an approach advances cognitive research beyond a focus on immediate task demand and provides insight into the functional relevance of the intrinsic neural pattern (for example, the default mode network). This in turn enables a greater integration between human and animal neuroscience, facilitating experimental testing of theoretical accounts of intrinsic activity, and opening new avenues of research in psychiatry.

Putting the "mental" back in "mental disorders": a perspective from research on fear and anxiety

Mental health problems often involve clusters of symptoms that include subjective (conscious) experiences as well as behavioral and/or physiological responses. Because the bodily responses are readily measured objectively, these have come to be emphasized when developing treatments and assessing their effectiveness. On the other hand, the subjective experience of the patient reported during a clinical interview is often viewed as a weak correlate of psychopathology. To the extent that subjective symptoms are related to the underlying problem, it is often assumed that they will be taken care of if the more objective behavioral and physiological symptoms are properly treated. Decades of research on anxiety disorders, however, show that behavioral and physiological symptoms do not correlate as strongly with subjective experiences as is typically assumed. Further, the treatments developed using more objective symptoms as a marker of psychopathology have mostly been disappointing in effectiveness. Given that "mental" disorders are named for, and defined by, their subjective mental qualities, it is perhaps not surprising, in retrospect, that treatments that have sidelined mental qualities have not been especially effective. These negative attitudes about subjective experience took root in psychiatry and allied fields decades ago when there were few avenues for scientifically studying subjective experience. Today, however, cognitive neuroscience research on consciousness is thriving, and offers a viable and novel scientific approach that could help achieve a deeper understanding of mental disorders and their treatment.

Associations between testosterone, estradiol, and androgen receptor genotype with amygdala subregions in adolescents

Much is known about the development of the whole amygdala, but less is known about its structurally and functionally diverse subregions. One notable distinguishing feature is their wide range of androgen and estrogen receptor densities. Given the rise in pubertal hormones during adolescence, sex steroid levels as well as receptor sensitivity could influence age-related subregion volumes. Therefore, our goal was to evaluate the associations between the total amygdala and its subregion volumes in relation to sex hormones - estradiol and free testosterone (FT) - as a function of age and genetic differences in androgen receptor (AR) sensitivity in a sample of 297 adolescents (46% female). In males, we found small effects of FT-by-age interactions in the total amygdala, portions of the basolateral complex, and the cortical and medial nuclei (CMN), with the CMN effects being moderated by AR sensitivity. For females, small effects were seen with increased genetic AR sensitivity relating to smaller basolateral complexes. However, none of these small effects passed multiple comparisons. Future larger studies are necessary to replicate these small, yet possibly meaningful effects of FT-by-age associations and modulation by AR sensitivity on amygdala development to ultimately determine if they contribute to known sex differences in emotional neurodevelopment.

Prefrontal cortex interactions with the amygdala in primates

This review addresses functional interactions between the primate prefrontal cortex (PFC) and the amygdala, with emphasis on their contributions to behavior and cognition. The interplay between these two telencephalic structures contributes to adaptive behavior and to the evolutionary success of all primate species. In our species, dysfunction in this circuitry creates vulnerabilities to psychopathologies. Here, we describe amygdala-PFC contributions to behaviors that have direct relevance to Darwinian fitness: learned approach and avoidance, foraging, predator defense, and social signaling, which have in common the need for flexibility and sensitivity to specific and rapidly changing contexts. Examples include the prediction of positive outcomes, such as food availability, food desirability, and various social rewards, or of negative outcomes, such as threats of harm from predators or conspecifics. To promote fitness optimally, these stimulus-outcome associations need to be rapidly updated when an associative contingency changes or when the value of a predicted outcome changes. We review evidence from nonhuman primates implicating the PFC, the amygdala, and their functional interactions in these processes, with links to experimental work and clinical findings in humans where possible.

Patients with chronic pain exhibit individually unique cortical signatures of pain encoding

Chronic pain is characterised by an ongoing and fluctuating intensity over time. Here, we investigated how the trajectory of the patients' endogenous pain is encoded in the brain. In repeated functional MRI (fMRI) sessions, 20 patients with chronic back pain and 20 patients with chronic migraine were asked to continuously rate the intensity of their endogenous pain. Linear mixed effects models were used to disentangle cortical processes related to pain intensity and to pain intensity changes. At group level, we found that the intensity of pain in patients with chronic back pain is encoded in the anterior insular cortex, the frontal operculum, and the pons; the change of pain in chronic back pain and chronic migraine patients is mainly encoded in the anterior insular cortex. At the individual level, we identified a more complex picture where each patient exhibited their own signature of endogenous pain encoding. The diversity of the individual cortical signatures of chronic pain encoding results bridge between clinical observations and neuroimaging; they add to the understanding of chronic pain as a complex and multifaceted disease.

The diversity and multiplexity of edge communities within and between brain systems

The human brain is composed of functionally specialized systems that support cognition. Recently, we proposed an edge-centric model for detecting overlapping communities. It remains unclear how these communities and brain systems are related. Here, we address this question using data from the Midnight Scan Club and show that all brain systems are linked via at least two edge communities. We then examine the diversity of edge communities within each system, finding that heteromodal systems are more diverse than sensory systems. Next, we cluster the entire cortex to reveal it according to the regions' edge-community profiles. We find that regions in heteromodal systems are more likely to form their own clusters. Finally, we show that edge communities are personalized. Our work reveals the pervasive overlap of edge communities across the cortex and their relationship with brain systems. Our work provides pathways for future research using edge-centric brain networks.

Associations among negative life events, changes in cortico-limbic connectivity, and psychopathology in the ABCD Study

Adversity exposure is a risk factor for psychopathology, which most frequently onsets during adolescence, and prior research has demonstrated that alterations in cortico-limbic connectivity may account in part for this association. In a sample of youth from the Adolescent Brain Cognitive Development (ABCD) Study (N = 4006), we tested a longitudinal structural equation model to examine the indirect effect of adversity exposure (negative life events) on later psychopathology via changes in cortico-limbic resting-state functional connectivity (rsFC). We also examined the potential protective effects of parental acceptance. Generally, cortico-limbic connectivity became more strongly negative between baseline and year 2 follow-up, suggesting that stronger negative correlations within these cortico-limbic networks may reflect a more mature phenotype. Exposure to a greater number of negative life events was associated with stronger negative cortico-limbic rsFC which, in turn, was associated with lower internalizing (but not externalizing) symptoms. The indirect effect of negative life events on internalizing symptoms via cortico-limbic rsFC was significant. Parental acceptance did not moderate the association between negative life events and rsFC. Our findings highlight how stressful childhood experiences may accelerate neurobiological maturation in specific cortico-limbic connections, potentially reflecting an adaptive process that protects against internalizing problems in the context of adversity.

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Childhood adversity shapes cortico-limbic connectivity and mental health.

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In the ABCD Study, cortico-limbic functional connectivity changed over time.

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These changes explain the association between adversity and internalizing symptoms.

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Adversity exposure may accelerate corticolimbic development.

Acute Neurofunctional Effects of Escitalopram in Pediatric Anxiety: A Double-Blind, Placebo-Controlled Trial

OBJECTIVE

Amygdala-ventrolateral prefrontal cortex (VLPFC) circuitry is disrupted in pediatric anxiety disorders, yet how selective serotonin reuptake inhibitors (SSRIs) affect this circuitry is unknown. We examined the impact of the SSRI escitalopram on functional connectivity (FC) within this circuit, and whether early FC changes predicted treatment response in adolescents with generalized anxiety disorder (GAD).

METHOD

Resting-state functional magnetic resonance (MR) images were acquired before and after 2 weeks of treatment in 41 adolescents with GAD (12-17 years of age) who received double-blind escitalopram or placebo for 8 weeks. Change in amygdala-based whole-brain FC and anxiety severity were analyzed.

RESULTS

Controlling for age, sex, and pretreatment anxiety, escitalopram increased amygdala-VLPFC connectivity compared to placebo (F = 17.79, p = .002 FWE-corrected). This early FC change predicted 76.7% of the variability in improvement trajectory in patients who received escitalopram (p < .001) but not placebo (p = .169); the predictive power of early amygdala-VLPFC FC change significantly differed between placebo and escitalopram (p = .013). Furthermore, this FC change predicted improvement better than baseline FC or clinical/demographic characteristics. Exploratory analyses of amygdala subfields' FC revealed connectivity of left basolateral amygdala (BLA) -VLPFC (F = 19.64, p < .001 FWE-corrected) and superficial amygdala-posterior cingulate cortex (F = 22.92, p = .001 FWE-corrected) were also increased by escitalopram, but only BLA-VLPFC FC predicted improvement in anxiety over 8 weeks of treatment.

CONCLUSION

In adolescents with GAD, escitalopram increased amygdala-prefrontal connectivity within the first 2 weeks of treatment, and the magnitude of this change predicted subsequent clinical improvement. Early normalization of amygdala-VLPFC circuitry might represent a useful tool for identifying future treatment responders as well as a promising biomarker for drug development.

CLINICAL TRIAL REGISTRATION INFORMATION

Neurofunctional Predictors of Escitalopram Treatment Response in Adolescents With Anxiety; https://www.clinicaltrials.gov/; NCT02818751.