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.

Case study of the prediction of elective surgery durations in a New Zealand teaching hospital.

We present an elective surgery redesign project involving several New Zealand hospitals that is primarily data-driven. One of the project objectives is to improve the predictions of surgery durations. We address this task by considering two approaches: (a) linear regression modelling, and (b) improvement of the data quality. For (a) we evaluate the accuracy of predictions using two performance measures. These predictions are compared to the surgeons' estimates that may subsequently be adjusted. We demonstrate using the historical surgical lists that the estimates from our prediction techniques improve the scheduling of elective surgeries by minimising the occurrences of list under- and over-runs. For (b), we discuss how the surgical data motivates a review of the surgery procedure classification which takes into account the design of the electronic booking form. The proposed hierarchical classification streamlines the specification of surgery types and therefore retains the potential for improved predictions.

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.

Longitudinal analysis of the developing rhesus monkey brain using magnetic resonance imaging: birth to adulthood.

We have longitudinally assessed normative brain growth patterns in naturalistically reared Macaca mulatta monkeys. Postnatal to early adulthood brain development in two cohorts of rhesus monkeys was analyzed using magnetic resonance imaging. Cohort A consisted of 24 rhesus monkeys (12 male, 12 female) and cohort B of 21 monkeys (11 male, 10 female). All subjects were scanned at 1, 4, 8, 13, 26, 39, and 52 weeks; cohort A had additional scans at 156 weeks (3 years) and 260 weeks (5 years). Age-specific segmentation templates were developed for automated volumetric analyses of the T1-weighted magnetic resonance imaging scans. Trajectories of total brain size as well as cerebral and subcortical subdivisions were evaluated over this period. Total brain volume was about 64 % of adult estimates in the 1-week-old monkey. Brain volume of the male subjects was always, on average, larger than the female subjects. While brain volume generally increased between any two imaging time points, there was a transient plateau of brain growth between 26 and 39 weeks in both cohorts of monkeys. The trajectory of enlargement differed across cortical regions with the occipital cortex demonstrating the most idiosyncratic pattern of maturation and the frontal and temporal lobes showing the greatest and most protracted growth. A variety of allometric measurements were also acquired and body weight gain was most closely associated with the rate of brain growth. These findings provide a valuable baseline for the effects of fetal and early postnatal manipulations on the pattern of abnormal brain growth related to neurodevelopmental disorders.

Hypofractionated stereotactic radiotherapy in medium-sized to large arteriovenous malformations.

We have reviewed treatment results in terms of obliteration and complications in 24 patients with medium to large sized cerebral arteriovenous malformations (AVMs) (mean volume 18.5±8.9cm(3); range: 10-42) treated with hypofractionated stereotactic radiotherapy (HSRT). AVMs are congenital lesions associated with a high morbidity and mortality. Radiosurgery is one option for treatment. However, in larger AVMs with volumes exceeding 10cm(3) obliteration rates are less favourable and radiation induced complications more frequent. For larger AVMs, volume-staged radiosurgery is one option while another option may be the use of HSRT. Patients were treated with 6-7Gy in five fractions to a total dose of 30-35Gy (mean total dose 32.9±1.6Gy [standard error of the mean]). Sixteen patients (69.6%) showed obliteration after a mean time of 35.2±14.8 months (range: 24-60). Only one patient (4.2%) experienced symptomatic radionecrosis. Our treatment with HSRT seems safe and efficient for treatment of medium to large sized AVMs. Treatment results seem to be in line with volume-staged radiosurgery and may be an alternative for AVMs not suitable for single fraction radiosurgery.

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.

Triple aim program: assessing its effectiveness as a hospital management tool.

According to a recent national survey of Hospital chief executive officers, financial challenges are their top concern, especially government reimbursement. Moreover, the patient faces greater deductibles forcing hospitals to prioritize price transparency. The Triple Aim program is a tool available to hospital management to help address these challenges. This study indicates that the Triple Aim is valuable to healthcare providers and patients by reducing medical errors, improving healthcare quality, and reducing costs on a per capita basis. Managerial implications are discussed for hospitals and health systems considering this approach to addressing financial challenges.

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.

Bridging the gap between the human and macaque connectome: a quantitative comparison of global interspecies structure-function relationships and network topology.

Resting state functional connectivity MRI (rs-fcMRI) may provide a powerful and noninvasive "bridge" for comparing brain function between patients and experimental animal models; however, the relationship between human and macaque rs-fcMRI remains poorly understood. Here, using a novel surface deformation process for species comparisons in the same anatomical space (Van Essen, 2004, 2005), we found high correspondence, but also unique hub topology, between human and macaque functional connectomes. The global functional connectivity match between species was moderate to strong (r = 0.41) and increased when considering the top 15% strongest connections (r = 0.54). Analysis of the match between functional connectivity and the underlying anatomical connectivity, derived from a previous retrograde tracer study done in macaques (Markov et al., 2012), showed impressive structure-function correspondence in both the macaque and human. When examining the strongest structural connections, we found a 70-80% match between structural and functional connectivity matrices in both species. Finally, we compare species on two widely used metrics for studying hub topology: degree and betweenness centrality. The data showed topological agreement across the species, with nodes of the posterior cingulate showing high degree and betweenness centrality. In contrast, nodes in medial frontal and parietal cortices were identified as having high degree and betweenness in the human as opposed to the macaque. Our results provide: (1) a thorough examination and validation for a surface-based interspecies deformation process, (2) a strong theoretical foundation for making interspecies comparisons of rs-fcMRI, and (3) a unique look at topological distinctions between the species.

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.

The complications and the position of the Codman MicroSensor™ ICP device: an analysis of 549 patients and 650 Sensors.

BACKGROUND: Complications of and insertion depth of the Codman MicroSensor ICP monitoring device (CMS) is not well studied. OBJECTIVE: To study complications and the insertion depth of the CMS in a clinical setting. METHODS: We identified all patients who had their intracranial pressure (ICP) monitored using a CMS device between 2002 and 2010. The medical records and post implantation computed tomography (CT) scans were analyzed for occurrence of infection, hemorrhage and insertion depth. RESULTS: In all, 549 patients were monitored using 650 CMS. Mean monitoring time was 7.0 ± 4.9 days. The mean implantation depth was 21.3 ± 11.1 mm (0-88 mm). In 27 of the patients, a haematoma was identified; 26 of these were less than 1 ml, and one was 8 ml. No clinically significant bleeding was found. There was no statistically significant increase in the number of hemorrhages in presumed coagulopathic patients. The infection rate was 0.6 % and the calculated infection rate per 1,000 catheter days was 0.8. CONCLUSION: The risk for hemorrhagic and infectious complications when using the CMS for ICP monitoring is low. The depth of insertion varies considerably and should be taken into account if patients are treated with head elevation, since the pressure is measured at the tip of the sensor. To meet the need for ICP monitoring, an intraparenchymal ICP monitoring device should be preferred to the use of an external ventricular drainage (EVD).

Inferring functional connectivity in MRI using Bayesian network structure learning with a modified PC algorithm.

Resting state functional connectivity MRI (rs-fcMRI) is a popular technique used to gauge the functional relatedness between regions in the brain for typical and special populations. Most of the work to date determines this relationship by using Pearson's correlation on BOLD fMRI timeseries. However, it has been recognized that there are at least two key limitations to this method. First, it is not possible to resolve the direct and indirect connections/influences. Second, the direction of information flow between the regions cannot be differentiated. In the current paper, we follow-up on recent work by Smith et al. (2011), and apply PC algorithm to both simulated data and empirical data to determine whether these two factors can be discerned with group average, as opposed to single subject, functional connectivity data. When applied on simulated individual subjects, the algorithm performs well determining indirect and direct connection but fails in determining directionality. However, when applied at group level, PC algorithm gives strong results for both indirect and direct connections and the direction of information flow. Applying the algorithm on empirical data, using a diffusion-weighted imaging (DWI) structural connectivity matrix as the baseline, the PC algorithm outperformed the direct correlations. We conclude that, under certain conditions, the PC algorithm leads to an improved estimate of brain network structure compared to the traditional connectivity analysis based on correlations.

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.

Hypnotic intervention in a 7-year-old thumbsucker: a case study.

Thumbsucking is a common habit among younger children. Usually, the child outgrows this habit by age 6. When a child over the age of 6 continues to suck his or her thumb, it can be a cause of potential harm due to peer pressure, ridicule, and shunning. It can also lead to malocclusions requiring eventual orthodontic interventions. In this case study, the author demonstrates a hypnotic intervention in a 7-year-old girl. Validation of her habit and imaging a role model sucking her thumb were employed in trance. Using this approach, the child was able to end her dependence on thumbsucking in 1 session.