Interregional synchrony of visuomotor tracking: perturbation effects and individual differences

The present study evaluated the neural and behavioural correlates associated with a visuomotor tracking task during which a sensory perturbation was introduced that created a directional bias between moving hand and cursor position. The results revealed that trajectory error increased as a result of the perturbation in conjunction with a dynamic neural reorganization of cluster patterns that reflected distinct processing. In particular, a negatively activated cluster, characterizing the degraded information processing due to the perturbation, involved both hemispheres as well as midline area. Conversely, a positively activated cluster, indicative of compensatory processing was strongly confined to the left (dominant) hemisphere. In addition, a brain-behavioural association of good vs. poor performing participants enabled to localize a neural circuit within the left hemisphere and midline area that linked with successful performance. Overall, these data reinforce the functional significance of interregional synchrony in defining response output and behavioural success

Brain Dynamics across levels of Organization

After presenting evidence that the electrical activity recorded from the brain surface can reflect metastable state transitions of neuronal configurations at the mesoscopic level, I will suggest that their patterns may correspond to the distinctive spatio-temporal activity in the Dynamic Core (DC) and the Global Neuronal Workspace (GNW), respectively, in the models of the Edelman group on the one hand, and of Dehaene-Changeux, on the other. In both cases, the recursively reentrant activity flow in intra-cortical and cortical-subcortical neuron loops plays an essential and distinct role. Reasons will be given for viewing the temporal characteristics of this activity flow as signature of Self-Organized Criticality (SOC), notably in reference to the dynamics of neuronal avalanches. This point of view enables the use of statistical Physics approaches for exploring phase transitions, scaling and universality properties of DC and GNW, with relevance to the macroscopic electrical activity in EEG and EMG

Disruption to control network function correlates with altered dynamic connectivity in the wider autism spectrum.

Autism is a common developmental condition with a wide, variable range of co-occurring neuropsychiatric symptoms. Contrasting with most extant studies, we explored whole-brain functional organization at multiple levels simultaneously in a large subject group reflecting autism's clinical diversity, and present the first network-based analysis of transient brain states, or dynamic connectivity, in autism. Disruption to inter-network and inter-system connectivity, rather than within individual networks, predominated. We identified coupling disruption in the anterior-posterior default mode axis, and among specific control networks specialized for task start cues and the maintenance of domain-independent task positive status, specifically between the right fronto-parietal and cingulo-opercular networks and default mode network subsystems. These appear to propagate downstream in autism, with significantly dampened subject oscillations between brain states, and dynamic connectivity configuration differences. Our account proposes specific motifs that may provide candidates for neuroimaging biomarkers within heterogeneous clinical populations in this diverse condition

Dynamic fluctuations coincide with periods of high and low modularity in resting-state functional brain networks

We investigate the relationship of resting-state fMRI functional connectivity estimated over long periods of time with time-varying functional connectivity estimated over shorter time intervals. We show that using Pearson's correlation to estimate functional connectivity implies that the range of fluctuations of functional connections over short time scales is subject to statistical constraints imposed by their connectivity strength over longer scales. We present a method for estimating time-varying functional connectivity that is designed to mitigate this issue and allows us to identify episodes where functional connections are unexpectedly strong or weak. We apply this method to data recorded from $N=80$ participants, and show that the number of unexpectedly strong/weak connections fluctuates over time, and that these variations coincide with intermittent periods of high and low modularity in time-varying functional connectivity. We also find that during periods of relative quiescence regions associated with default mode network tend to join communities with attentional, control, and primary sensory systems. In contrast, during periods where many connections are unexpectedly strong/weak, default mode regions dissociate and form distinct modules. Finally, we go on to show that, while all functional connections can at times manifest stronger (more positively correlated) or weaker (more negatively correlated) than expected, a small number of connections, mostly within the visual and somatomotor networks, do so a disproportional number of times. Our statistical approach allows the detection of functional connections that fluctuate more or less than expected based on their long-time averages and may be of use in future studies characterizing the spatio-temporal patterns of time-varying functional connectivityComment: 47 Pages, 8 Figures, 4 Supplementary Figure

Combined EEG-fMRI and tractography to visualise propagation of epileptic activity

In a patient with refractory temporal lobe epilepsy, EEG-fMRI showed activation in association with left anterior temporal interictal discharges, in the left temporal, parietal and occipital lobes. Dynamic causal modelling suggested propagation of neural activity from the temporal focus to the area of occipital activation. Tractography showed connections from the site of temporal lobe activation to the site of occipital activation. This demonstrates the principle of combining EEG-fMRI and tractography to delineate the pathways of propagation of epileptic activity