Peter T. Bell

The Dynamics of Functional Brain Networks: Integrated Network States during Cognitive Task Performance

Higher brain function relies upon the ability to flexibly integrate information across specialized communities of macroscopic brain regions, but it is unclear how this mechanism manifests over time. Here we characterized patterns of time-resolved functional connectivity using resting state and task fMRI data from a large cohort of unrelated subjects. Our results demonstrate that dynamic fluctuations in network structure during the resting state reflect transitions between states of integrated and segregated network topology. These patterns were altered during task performance, demonstrating a higher level of network integration that tracked with the complexity of the task and correlated with effective behavioral performance. Replication analysis demonstrated that these results were reproducible across sessions, sample populations and datasets. Together these results provide insight into the brains coordination between integration and segregation and highlight key principles underlying the reorganization of the network architecture of the brain during both rest and behavior.

A hierarchy of timescales explains distinct effects of local inhibition of primary visual cortex and frontal eye fields

Within the primate visual system, areas at lower levels of the cortical hierarchy process basic visual features, whereas those at higher levels, such as the frontal eye fields (FEF), are thought to modulate sensory processes via feedback connections. Despite these functional exchanges during perception, there is little shared activity between early and late visual regions at rest. How interactions emerge between regions encompassing distinct levels of the visual hierarchy remains unknown. Here we combined neuroimaging, non-invasive cortical stimulation and computational modelling to characterize changes in functional interactions across widespread neural networks before and after local inhibition of primary visual cortex or FEF. We found that stimulation of early visual cortex selectively increased feedforward interactions with FEF and extrastriate visual areas, whereas identical stimulation of the FEF decreased feedback interactions with early visual areas. Computational modelling suggests that these opposing effects reflect a fast-slow timescale hierarchy from sensory to association areas. DOI: http://dx.doi.org/10.7554/eLife.15252.001

Dopaminergic basis for impairments in functional connectivity across subdivisions of the striatum in Parkinson's disease.

The pathological hallmark of Parkinsons disease is the degeneration of dopaminergic nigrostriatal neurons, leading to depletion of striatal dopamine. Recent neuroanatomical work has identified pathways for communication across striatal subdivisions, suggesting that the striatum provides a platform for integration of information across parallel corticostriatal circuits. The aim of this study was to investigate whether dopaminergic dysfunction in Parkinsons disease was associated with impairments in functional connectivity across striatal subdivisions, which could potentially reflect reduced integration across corticostriatal circuits. Utilizing resting‐state functional magnetic resonance imaging (fMRI), we analyzed functional connectivity in 39 patients with Parkinsons disease, both “on” and “off” their regular dopaminergic medications, along with 40 age‐matched healthy controls. Our results demonstrate widespread impairments in connectivity across subdivisions of the striatum in patients with Parkinsons disease in the “off” state. The administration of dopaminergic medication significantly improved connectivity across striatal subdivisions in Parkinsons disease, implicating dopaminergic deficits in the pathogenesis of impaired striatal interconnectivity. In addition, impaired striatal interconnectivity in the Parkinsons disease “off” state was associated with pathological decoupling of the striatum from the thalamic and sensorimotor (SM) networks. Specifically, we found that although the strength of striatal interconnectivity was positively correlated with both (i) the strength of internal thalamic connectivity, and (ii) the strength of internal SM connectivity, in both healthy controls and the Parkinsons disease “on” state, these relationships were absent in Parkinsons disease when in the “off” state. Taken together our findings emphasize the central role of dopamine in integrated striatal function and the pathological consequences of striatal dopamine denervation in Parkinsons disease. Hum Brain Mapp 36:1278–1291, 2015.

Subcortical contributions to large-scale network communication

Higher brain function requires integration of distributed neuronal activity across large-scale brain networks. Recent scientific advances at the interface of subcortical brain anatomy and network science have highlighted the possible contribution of subcortical structures to large-scale network communication. We begin our review by examining neuroanatomical literature suggesting that diverse neural systems converge within the architecture of the basal ganglia and thalamus. These findings dovetail with those of recent network analyses that have demonstrated that the basal ganglia and thalamus belong to an ensemble of highly interconnected network hubs. A synthesis of these findings suggests a new view of the subcortex, in which the basal ganglia and thalamus form part of a core circuit that supports large-scale integration of functionally diverse neural signals. Finally, we close with an overview of some of the major opportunities and challenges facing subcortical-inclusive descriptions of large-scale network communication in the human brain.

Dopamine depletion impairs gait automaticity by altering cortico-striatal and cerebellar processing in Parkinson's disease

ABSTRACT Impairments in motor automaticity cause patients with Parkinsons disease to rely on attentional resources during gait, resulting in greater motor variability and a higher risk of falls. Although dopaminergic circuitry is known to play an important role in motor automaticity, little evidence exists on the neural mechanisms underlying the breakdown of locomotor automaticity in Parkinsons disease. This impedes clinical management and is in great part due to mobility restrictions that accompany the neuroimaging of gait. This study therefore utilized a virtual reality gait paradigm in conjunction with functional MRI to investigate the role of dopaminergic medication on lower limb motor automaticity in 23 patients with Parkinsons disease that were measured both on and off dopaminergic medication. Participants either operated foot pedals to navigate a corridor (‘walk’ condition) or watched the screen while a researcher operated the paradigm from outside the scanner (‘watch’ condition), a setting that controlled for the non‐motor aspects of the task. Step time variability during walk was used as a surrogate measure for motor automaticity (where higher variability equates to reduced automaticity), and patients demonstrated a predicted increase in step time variability during the dopaminergic “off” state. During the “off” state, subjects showed an increased blood oxygen level‐dependent response in the bilateral orbitofrontal cortices (walk>watch). To estimate step time variability, a parametric modulator was designed that allowed for the examination of brain regions associated with periods of decreased automaticity. This analysis showed that patients on dopaminergic medication recruited the cerebellum during periods of increasing variability, whereas patients off medication instead relied upon cortical regions implicated in cognitive control. Finally, a task‐based functional connectivity analysis was conducted to examine the manner in which dopamine modulates large‐scale network interactions during gait. A main effect of medication was found for functional connectivity within an attentional motor network and a significant condition by medication interaction for functional connectivity was found within the striatum. Furthermore, functional connectivity within the striatum correlated strongly with increasing step time variability during walk in the off state (r=0.616, p=0.002), but not in the on state (r=−0.233, p=0.284). Post‐hoc analyses revealed that functional connectivity in the dopamine depleted state within an orbitofrontal‐striatal limbic circuit was correlated with worse step time variability (r=0.653, p<0.001). Overall, this study demonstrates that dopamine ameliorates gait automaticity in Parkinsons disease by altering striatal, limbic and cerebellar processing, thereby informing future therapeutic avenues for gait and falls prevention. HighlightsParkinsons disease patients performed a virtual reality gait task during fMRI.The role of dopamine on gait automaticity impairments was investigated.Limbic interference and poor striatal and cerebellar processing impair automaticity.Dopamine ameliorates gait automaticity impairments in Parkinsons disease.

Adsorption and microbial degradation of organic compounds in oil shale retort water

Abstract Studies were conducted to investigate the mechanisms of removal (adsorption and biodegradation) of organic compounds of environmental concern in a continuous retort water treatment cell (RWTC), in which a bed of solid wastes was irrigated with the retort water. The adsorption mechanisms were investigated in batch experiments. The results show that initial adsorption (40–90%) occurs very rapidly and is followed by slower adsorption (10–60%) until equilibrium is achieved after 200–300 h, the actual period depending on the initial concentration of total organic carbon (TOC) and the solid:solution ratio. The microbial species responsible for aerobic biodegradation within the treatment cell were identified. Fungi were dominant in the upper part of the cell. Bacteria of the genera Pseudomonas, Agrobacterium and Bacillus were dominant in the lower parts.

Estimating Large-Scale Network Convergence in the Human Functional Connectome

The study of resting-state networks provides an informative paradigm for understanding the functional architecture of the human brain. Although investigating specialized resting-state networks has led to significant advances in our understanding of brain organization, the manner in which information is integrated across these networks remains unclear. Here, we have developed and validated a data-driven methodology for describing the topography of resting-state network convergence in the human brain. Our results demonstrate the importance of an ensemble of cortical and subcortical regions in supporting the convergence of multiple resting-state networks, including the rostral anterior cingulate, precuneus, posterior cingulate cortex, posterior parietal cortex, dorsal prefrontal cortex, along with the caudate head, anterior claustrum, and posterior thalamus. In addition, we have demonstrated a significant correlation between voxel-wise network convergence and global brain connectivity, emphasizing the importance of resting-state network convergence in facilitating global brain communication. Finally, we examined the convergence of systems within each of the individual resting-state networks in the brain, revealing the heterogeneity by which individual resting-state networks balance the competing demands of specialized processing against the integration of information. Together, our results suggest that the convergence of resting-state networks represents an important organizational principle underpinning systems-level integration in the human brain.

Striatal dysfunction during dual-task performance in Parkinson's disease

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The Dynamics of Functional Brain Networks: Integrated Network States during Cognitive Function

Higher brain function relies upon the ability to flexibly integrate information across specialized communities of macroscopic brain regions, but it is unclear how this mechanism manifests over time. Here we characterized patterns of time-resolved functional connectivity using resting state and task fMRI data from a large cohort of unrelated subjects. Our results demonstrate that dynamic fluctuations in network structure during the resting state reflect transitions between states of integrated and segregated network topology. These patterns were altered during task performance, demonstrating a higher level of network integration that tracked with the complexity of the task and correlated with effective behavioral performance. Replication analysis demonstrated that these results were reproducible across sessions, sample populations and datasets. Together these results provide insight into the brains coordination between integration and segregation and highlight key principles underlying the reorganization of the network architecture of the brain during both rest and behavior.

The low dimensional dynamic and integrative core of cognition in the human brain

The human brain seamlessly integrates innumerable cognitive functions into a coherent whole, shifting with fluidity between changing task demands. To test the hypothesis that the brain contains a core dynamic network that integrates specialized regions across a range of unique task demands, we investigated whether brain activity across multiple cognitive tasks could be embedded within a relatively low dimensional, dynamic manifold. Analysis of task-related fMRI data from the Human Connectome Project revealed a core brain system that fluctuates in accordance with cognitive demands, bringing new brain systems on-line in accordance with changing task demands, while maximizing temporal information processing complexity. Regional differences in noradrenergic neurotransmitter receptor density align with this integrative core, providing a biologically plausible mechanism for the control of global brain dynamics. Our results advance a unique window into functional brain organization that emphasizes the confluence between low dimensional neural activity, network topology, neuromodulator systems and cognitive function.The human brain integrates diverse cognitive processes into a coherent whole, shifting fluidly as a function of changing environmental demands. Despite recent progress, the neurobiological mechanisms responsible for this dynamic system-level integration remain poorly understood. Here, we used multi-task fMRI data from the Human Connectome Project to examine the spatiotemporal architecture of cognition in the human brain. By investigating the spatial, dynamic and molecular signatures of system-wide neural activity across a range of cognitive tasks, we show that large-scale neuronal activity converges onto a low dimensional manifold that facilitates the dynamic execution of diverse task states. Flow within this attractor space is associated with dissociable cognitive functions, and with unique patterns of network-level topology and information processing complexity. The axes of the low-dimensional neurocognitive architecture align with regional differences in the density of neuromodulatory receptors, which in turn relate to distinct signatures of network controllability estimated from the structural connectome. These results advance our understanding of functional brain organization by emphasizing the interface between low dimensional neural activity, network topology, neuromodulatory systems and cognitive function. One Sentence Summary A diverse set of neuromodulators facilitates the formation of a dynamic, low-dimensional integrative core in the brain that is recruited by diverse cognitive demands