Effects of social subordination and oestradiol on resting-state amygdala functional connectivity in adult female rhesus monkeys.

Preclinical studies demonstrate that chronic stress modulates the effects of oestradiol (E2) on behaviour through the modification of the amygdala and the medial prefrontal cortex (mPFC) neuronal structure. Clinical studies suggest that alterations in amygdala functional connectivity (FC) with the mPFC may be associated with stress-related phenotypes, including mood and anxiety disorders. Thus, identifying the effects of stress and E2 on amygdala-mPFC circuits is critical for understanding the neurobiology underpinning the vulnerability to stress-related disorders in women. In the present study, we used a well-validated rhesus monkey model of chronic psychosocial stress (subordinate social rank) to examine effects of E2 on subordinate (SUB) (i.e. high stress) and dominant (DOM) (i.e. low stress) female resting-state amygdala FC with the mPFC and with the whole-brain. In the non-E2 treatment control condition, SUB was associated with stronger left amygdala FC to subgenual cingulate (Brodmann area [BA] 25: BA25), a region implicated in several psychopathologies in people. In SUB females, E2 treatment strengthened right amygdala-BA25 FC, induced a net positive amygdala-visual cortex FC that was positively associated with frequency of submissive behaviours, and weakened positive amygdala-para/hippocampus FC. Our findings show that subordinate social rank alters amygdala FC and the impact of E2 on amygdala FC with BA25 and with regions involved in visual processing and memory encoding.

Exploring the limits of network topology estimation using diffusion-based tractography and tracer studies in the macaque cortex.

Reconstructing the anatomical pathways of the brain to study the human connectome has become an important endeavour for understanding brain function and dynamics. Reconstruction of the cortico-cortical connectivity matrix in vivo often relies on noninvasive diffusion-weighted imaging (DWI) techniques but the extent to which they can accurately represent the topological characteristics of structural connectomes remains unknown. We addressed this question by constructing connectomes using DWI data collected from macaque monkeys in vivo and with data from published invasive tracer studies. We found the strength of fiber tracts was well estimated from DWI and topological properties like degree and modularity were captured by tractography-based connectomes. Rich-club/core-periphery type architecture could also be detected but the classification of hubs using betweenness centrality, participation coefficient and core-periphery identification techniques was inaccurate. Our findings indicate that certain aspects of cortical topology can be faithfully represented in noninvasively-obtained connectomes while other network analytic measures warrant cautionary interpretations.

Heritability of the human connectome: A connectotyping study.

Recent progress in resting-state neuroimaging demonstrates that the brain exhibits highly individualized patterns of functional connectivity-a "connectotype." How these individualized patterns may be constrained by environment and genetics is unknown. Here we ask whether the connectotype is familial and heritable. Using a novel approach to estimate familiality via a machine-learning framework, we analyzed resting-state fMRI scans from two well-characterized samples of child and adult siblings. First we show that individual connectotypes were reliably identified even several years after the initial scanning timepoint. Familial relationships between participants, such as siblings versus those who are unrelated, were also accurately characterized. The connectotype demonstrated substantial heritability driven by high-order systems including the fronto-parietal, dorsal attention, ventral attention, cingulo-opercular, and default systems. This work suggests that shared genetics and environment contribute toward producing complex, individualized patterns of distributed brain activity, rather than constraining local aspects of function. These insights offer new strategies for characterizing individual aberrations in brain function and evaluating heritability of brain networks.

Correlated Gene Expression and Anatomical Communication Support Synchronized Brain Activity in the Mouse Functional Connectome.

Cognition and behavior depend on synchronized intrinsic brain activity that is organized into functional networks across the brain. Research has investigated how anatomical connectivity both shapes and is shaped by these networks, but not how anatomical connectivity interacts with intra-areal molecular properties to drive functional connectivity. Here, we present a novel linear model to explain functional connectivity by integrating systematically obtained measurements of axonal connectivity, gene expression, and resting-state functional connectivity MRI in the mouse brain. The model suggests that functional connectivity arises from both anatomical links and inter-areal similarities in gene expression. By estimating these effects, we identify anatomical modules in which correlated gene expression and anatomical connectivity support functional connectivity. Along with providing evidence that not all genes equally contribute to functional connectivity, this research establishes new insights regarding the biological underpinnings of coordinated brain activity measured by BOLD fMRI.SIGNIFICANCE STATEMENT Efforts at characterizing the functional connectome with fMRI have risen exponentially over the last decade. Yet despite this rise, the biological underpinnings of these functional measurements are still primarily unknown. The current report begins to fill this void by investigating the molecular underpinnings of the functional connectome through an integration of systematically obtained structural information and gene expression data throughout the rodent brain. We find that both white matter connectivity and similarity in regional gene expression relate to resting-state functional connectivity. The current report furthers our understanding of the biological underpinnings of the functional connectome and provides a linear model that can be used to streamline preclinical animal studies of disease.

Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature.

The development of human cognition results from the emergence of coordinated activity between distant brain areas. Network science, combined with non-invasive functional imaging, has generated unprecedented insights regarding the adult brain's functional organization, and promises to help elucidate the development of functional architectures supporting complex behavior. Here we review what is known about functional network development from birth until adulthood, particularly as understood through the use of resting-state functional connectivity MRI (rs-fcMRI). We attempt to synthesize rs-fcMRI findings with other functional imaging techniques, with macro-scale structural connectivity, and with knowledge regarding the development of micro-scale structure. We highlight a number of outstanding conceptual and technical barriers that need to be addressed, as well as previous developmental findings that may need to be revisited. Finally, we discuss key areas ripe for future research in order to (1) better characterize normative developmental trajectories, (2) link these trajectories to biologic mechanistic events, as well as component behaviors and (3) better understand the clinical implications and pathophysiological basis of aberrant network development.

Network Structure among Brain Systems in Adult ADHD is Uniquely Modified by Stimulant Administration.

Current research in connectomics highlights that self-organized functional networks or "communities" of cortical areas can be detected in the adult brain. This perspective may provide clues to mechanisms of treatment response in psychiatric conditions. Here we examine functional brain community topology based on resting-state fMRI in adult Attention-Deficit/Hyperactivity Disorder (ADHD; n = 22) and controls (n = 31). We sought to evaluate ADHD patterns in adulthood and their modification by short term stimulants administration. Participants with ADHD were scanned one or two weeks apart, once with medication and once without; comparison participants were scanned at one time-point. Functional connectivity was estimated from these scans and community detection applied to determine cortical network topology. Measures of change in connectivity profile were calculated via a graph measure, termed the Node Dissociation Index (NDI). Compared to controls, several cortical networks had atypical connectivity in adults with ADHD when withholding stimulants, as measured by NDI. In most networks stimulants significantly reduced, but did not eliminate, differences in the distribution of connections between key brain systems relative to the control sample. These findings provide an enriched model of connectivity in ADHD and demonstrate how stimulants may exert functional effects by altering connectivity profiles in the brain.

The Rhesus Monkey Connectome Predicts Disrupted Functional Networks Resulting from Pharmacogenetic Inactivation of the Amygdala.

Contemporary research suggests that the mammalian brain is a complex system, implying that damage to even a single functional area could have widespread consequences across the system. To test this hypothesis, we pharmacogenetically inactivated the rhesus monkey amygdala, a subcortical region with distributed and well-defined cortical connectivity. We then examined the impact of that perturbation on global network organization using resting-state functional connectivity MRI. Amygdala inactivation disrupted amygdalocortical communication and distributed corticocortical coupling across multiple functional brain systems. Altered coupling was explained using a graph-based analysis of experimentally established structural connectivity to simulate disconnection of the amygdala. Communication capacity via monosynaptic and polysynaptic pathways, in aggregate, largely accounted for the correlational structure of endogenous brain activity and many of the non-local changes that resulted from amygdala inactivation. These results highlight the structural basis of distributed neural activity and suggest a strategy for linking focal neuropathology to remote neurophysiological changes.

Feedback-driven trial-by-trial learning in autism spectrum disorders.

OBJECTIVE: Impairments in learning are central to autism spectrum disorders. The authors investigated the cognitive and neural basis of these deficits in young adults with autism spectrum disorders using a well-characterized probabilistic reinforcement learning paradigm. METHOD: The probabilistic selection task was implemented among matched participants with autism spectrum disorders (N=22) and with typical development (N=25), aged 18-40 years, using rapid event-related functional MRI. Participants were trained to choose the correct stimulus in high-probability (AB), medium-probability (CD), and low-probability (EF) pairs, presented with valid feedback 80%, 70%, and 60% of the time, respectively. Whole-brain voxel-wise and parametric modulator analyses examined early and late learning during the stimulus and feedback epochs of the task. RESULTS: The groups exhibited comparable performance on medium- and low-probability pairs. Typically developing persons showed higher accuracy on the high-probability pair, better win-stay performance (selection of the previously rewarded stimulus on the next trial of that type), and more robust recruitment of the anterior and medial prefrontal cortex during the stimulus epoch, suggesting development of an intact reward-based working memory for recent stimulus values. Throughout the feedback epoch, individuals with autism spectrum disorders exhibited greater recruitment of the anterior cingulate and orbito-frontal cortices compared with individuals with typical development, indicating continuing trial-by-trial activity related to feedback processing. CONCLUSIONS: Individuals with autism spectrum disorders exhibit learning deficits reflecting impaired ability to develop an effective reward-based working memory to guide stimulus selection. Instead, they continue to rely on trial-by-trial feedback processing to support learning dependent upon engagement of the anterior cingulate and orbito-frontal cortices.

Structural and functional connectivity of the human brain in autism spectrum disorders and attention-deficit/hyperactivity disorder: A rich club-organization study.

Attention-deficit/hyperactive disorder (ADHD) and autism spectrum disorders (ASD) are two of the most common and vexing neurodevelopmental disorders among children. Although the two disorders share many behavioral and neuropsychological characteristics, most MRI studies examine only one of the disorders at a time. Using graph theory combined with structural and functional connectivity, we examined the large-scale network organization among three groups of children: a group with ADHD (8-12 years, n = 20), a group with ASD (7-13 years, n = 16), and typically developing controls (TD) (8-12 years, n = 20). We apply the concept of the rich-club organization, whereby central, highly connected hub regions are also highly connected to themselves. We examine the brain into two different network domains: (1) inside a rich-club network phenomena and (2) outside a rich-club network phenomena. The ASD and ADHD groups had markedly different patterns of rich club and non rich-club connections in both functional and structural data. The ASD group exhibited higher connectivity in structural and functional networks but only inside the rich-club networks. These findings were replicated using the autism brain imaging data exchange dataset with ASD (n = 85) and TD (n = 101). The ADHD group exhibited a lower generalized fractional anisotropy and functional connectivity inside the rich-club networks, but a higher number of axonal fibers and correlation coefficient values outside the rich club. Despite some shared biological features and frequent comorbity, these data suggest ADHD and ASD exhibit distinct large-scale connectivity patterns in middle childhood.

Dietary omega-3 fatty acids modulate large-scale systems organization in the rhesus macaque brain.

Omega-3 fatty acids are essential for healthy brain and retinal development and have been implicated in a variety of neurodevelopmental disorders. This study used resting-state functional connectivity MRI to define the large-scale organization of the rhesus macaque brain and changes associated with differences in lifetime ω-3 fatty acid intake. Monkeys fed docosahexaenoic acid, the long-chain ω-3 fatty acid abundant in neural membranes, had cortical modular organization resembling the healthy human brain. In contrast, those with low levels of dietary ω-3 fatty acids had decreased functional connectivity within the early visual pathway and throughout higher-order associational cortex and showed impairment of distributed cortical networks. Our findings illustrate the similarity in modular cortical organization between the healthy human and macaque brain and support the notion that ω-3 fatty acids play a crucial role in developing and/or maintaining distributed, large-scale brain systems, including those essential for normal cognitive function.

Structural and functional rich club organization of the brain in children and adults.

Recent studies using Magnetic Resonance Imaging (MRI) have proposed that the brain's white matter is organized as a rich club, whereby the most highly connected regions of the brain are also highly connected to each other. Here we use both functional and diffusion-weighted MRI in the human brain to investigate whether the rich club phenomena is present with functional connectivity, and how this organization relates to the structural phenomena. We also examine whether rich club regions serve to integrate information between distinct brain systems, and conclude with a brief investigation of the developmental trajectory of rich-club phenomena. In agreement with prior work, both adults and children showed robust structural rich club organization, comprising regions of the superior medial frontal/dACC, medial parietal/PCC, insula, and inferior temporal cortex. We also show that these regions were highly integrated across the brain's major networks. Functional brain networks were found to have rich club phenomena in a similar spatial layout, but a high level of segregation between systems. While no significant differences between adults and children were found structurally, adults showed significantly greater functional rich club organization. This difference appeared to be driven by a specific set of connections between superior parietal, insula, and supramarginal cortex. In sum, this work highlights the existence of both a structural and functional rich club in adult and child populations with some functional changes over development. It also offers a potential target in examining atypical network organization in common developmental brain disorders, such as ADHD and Autism.

Reward circuit connectivity relates to delay discounting in children with attention-deficit/hyperactivity disorder.

Attention-deficit/hyperactivity disorder (ADHD) is a prevalent psychiatric disorder that has poor long-term outcomes and remains a major public health concern. Recent theories have proposed that ADHD arises from alterations in multiple neural pathways. Alterations in reward circuits are hypothesized as one core dysfunction, leading to altered processing of anticipated rewards. The nucleus accumbens (NAcc) is particularly important for reward processes; task-based fMRI studies have found atypical activation of this region while the participants performed a reward task. Understanding how reward circuits are involved with ADHD may be further enhanced by considering how the NAcc interacts with other brain regions. Here we used the technique of resting-state functional connectivity MRI (rs-fcMRI) to examine the alterations in the NAcc interactions and how they relate to impulsive decision making in ADHD. Using rs-fcMRI, this study: examined differences in functional connectivity of the NAcc between children with ADHD and control children; correlated the functional connectivity of NAcc with impulsivity, as measured by a delay discounting task; and combined these two initial segments to identify the atypical NAcc connections that were associated with impulsive decision making in ADHD. We found that functional connectivity of NAcc was atypical in children with ADHD and the ADHD-related increased connectivity between NAcc and the prefrontal cortex was associated with greater impulsivity (steeper delayed-reward discounting). These findings are consistent with the hypothesis that atypical signaling of the NAcc to the prefrontal cortex in ADHD may lead to excessive approach and failure in estimating future consequences; thus, leading to impulsive behavior.