Error-driven Global Transition in a Competitive Population on a Network

We show, both analytically and numerically, that erroneous data transmission generates a global transition within a competitive population playing the Minority Game on a network. This transition, which resembles a phase transition, is driven by a `temporal symmetry breaking' in the global outcome series. The phase boundary, which is a function of the network connectivity $p$ and the error probability $q$, is described quantitatively by the Crowd-Anticrowd theory.Comment: 4 pages, 3 figure

Investigating White Matter Lesion Load, Intrinsic Functional Connectivity, and Cognitive Abilities in Older Adults

Changes to the while matter of the brain disrupt neural communication between spatially distributed brain regions and are associated with cognitive changes in later life. While approximately 95% of older adults experience these brain changes, not everyone who has significant white matter damage displays cognitive impairment. Few studies have investigated the association between white matter changes and cognition in the context of functional brain network integrity. This study used a data-driven, multivariate analytical model to investigate intrinsic functional connectivity patterns associated with individual variability in white matter lesion load as related to fluid and crystallized intelligence in a sample of healthy older adults (n = 84). Several primary findings were noted. First, a reliable pattern emerged associating whole-brain resting-state functional connectivity with individual variability in measures of white matter lesion load, as indexed by total white matter lesion volume and number of lesions. Secondly, white matter lesion load was associated with increased network disintegration and dedifferentiation. Specifically, lower white matter lesion load was associated with greater within- versus between-network connectivity. Higher white matter lesion load was associated with greater between-network connectivity compared to within. These associations between intrinsic functional connectivity and white matter lesion load were not reliably associated with crystallized and fluid intelligence performance. These results suggest that changes to the white matter of the brain in typically aging older adults are characterized by increased functional brain network dedifferentiation. The findings highlight the role of white matter lesion load in altering the functional network architecture of the brain

PROCESS BASED CLASSIFICATION OF SEDIMENT CONNECTIVITY AT THE RIVER BASIN SCALE.

Novel modelling approaches allow to trace the fate of sediment contributions from individual river reaches throughout the river network and to assess the resulting sediment connectivity at the basin scale. The derived information is an unprecedented source of information to assess from where and over which times a downstream river reach recruits its sediment. This information links strongly to the reach sensitivity to anthropic disturbance or restoration efforts. In this paper, we demonstrate how to make the complex data-sets resulting from basin scale connectivity models accessible for river basin management applications. We introduce the concept of “connectivity signatures” that epitomizes the timing, magnitude, and quality (grain size) domain of connectivity at the reach scale. We use data driven classification techniques to identify a reduced set of typical connectivity classes. Spatial distribution of connectivity classes reveals that these classes represent specific, functional “connectivity styles” with specific locations and functions for sediment routing in the river network. Results concretize the interpretation of sediment connectivity from an operational perspective and open the way for its application to large river basins

Data-Driven Approach to Dynamic Resting State Functional Connectivity in Post-Traumatic Stress Disorder

Posttraumatic stress disorder (PTSD) is a heterogenous psychological disorder that may result from exposure to a traumatic event. Using functional magnetic resonance imaging (fMRI), symptoms of PTSD have been associated with aberrations in brain networks that emerge in the absence of a given cognitive demand or task, called resting state networks. Most previous research in resting state networks and PTSD has focused on aberrations in the static functional connectivity among specific regions of interest (ROI) in the brain and within canonical networks constrained by a priori hypotheses. However, dynamic fMRI, an approach that examines changes in brain network characteristics over time, may provide a more sensitive measure to understand the network properties underlying dysfunction in PTSD. In addition, a data-driven analytic approach may reveal the contribution of other larger network disturbances beyond those revealed by hypothesis-driven examinations of ROIs or canonical networks. Therefore, the current study used a data-driven approach to characterize and subsequently compare brain network dynamics and recurrent connectivity states in a large sample of trauma exposed individuals (1,000+) with and without PTSD from the ENIGMA-PGC-PTSD workgroup. Static functional connectivity results showed those with PTSD had lower network efficiencies than Controls within and between sensorimotor and visual subnetworks. Further, network dynamics showed increased network efficiencies through the course of the scan for both groups, except in the visual subnetwork where those with PTSD showed blunted efficiencies through time. Those with PTSD also had fewer individual-level connectivity states, especially in the second half of the scan, compared to Controls suggesting a degree of stochasticity in the network over time. Finally, there were no group differences in dwell time or number of transitions of group-level connectivity states. Together, results suggest aberrancies in large-scale brain networks related to PTSD diagnosis beyond the most common analyzed ROIs. Unsurprisingly, in a large and heterogenous trauma sample, larger scale group results were not as robust compared to similar analyses in smaller homogenous trauma samples. Heterogeneity of PTSD, especially within diffuse brain networks, cannot be captured by evaluating only diagnostic groups, further work should be done to evaluate brain network dynamics with respect to specific symptoms and trauma types

Investigating human audio-visual object perception with a combination of hypothesis-generating and hypothesis-testing fMRI analysis tools

Primate multisensory object perception involves distributed brain regions. To investigate the network character of these regions of the human brain, we applied data-driven group spatial independent component analysis (ICA) to a functional magnetic resonance imaging (fMRI) data set acquired during a passive audio-visual (AV) experiment with common object stimuli. We labeled three group-level independent component (IC) maps as auditory (A), visual (V), and AV, based on their spatial layouts and activation time courses. The overlap between these IC maps served as definition of a distributed network of multisensory candidate regions including superior temporal, ventral occipito-temporal, posterior parietal and prefrontal regions. During an independent second fMRI experiment, we explicitly tested their involvement in AV integration. Activations in nine out of these twelve regions met the max-criterion (A < AV > V) for multisensory integration. Comparison of this approach with a general linear model-based region-of-interest definition revealed its complementary value for multisensory neuroimaging. In conclusion, we estimated functional networks of uni- and multisensory functional connectivity from one dataset and validated their functional roles in an independent dataset. These findings demonstrate the particular value of ICA for multisensory neuroimaging research and using independent datasets to test hypotheses generated from a data-driven analysis