Brain network dynamics in the alpha band during a complex postural control task

Creative Commons Attribution license.Objective.To decipher brain network dynamic remodeling from electroencephalography (EEG) during a complex postural control (PC) task combining virtual reality and a moving platform.Approach.EEG (64 electrodes) data from 158 healthy subjects were acquired. The experiment is divided into several phases, and visual and motor stimulation is applied progressively. We combined advanced source-space EEG networks with clustering algorithms to decipher the brain networks states (BNSs) that occurred during the task.Main results.The results show that BNS distribution describes the different phases of the experiment with specific transitions between visual, motor, salience, and default mode networks coherently. We also showed that age is a key factor that affects the dynamic transition of BNSs in a healthy cohort.Significance.This study validates an innovative approach, based on a robust methodology and a consequent cohort, to quantify the brain networks dynamics in the BioVRSea paradigm. This work is an important step toward a quantitative evaluation of brain activities during PC and could lay the foundation for developing brain-based biomarkers of PC-related disorders.Peer reviewe

Computational paradigm for dynamic logic-gates in neuronal activity

In 1943 McCulloch and Pitts suggested that the brain is composed of reliable logic-gates similar to the logic at the core of today's computers. This framework had a limited impact on neuroscience, since neurons exhibit far richer dynamics. Here we propose a new experimentally corroborated paradigm in which the truth tables of the brain's logic-gates are time dependent, i.e. dynamic logicgates (DLGs). The truth tables of the DLGs depend on the history of their activity and the stimulation frequencies of their input neurons. Our experimental results are based on a procedure where conditioned stimulations were enforced on circuits of neurons embedded within a large-scale network of cortical cells in-vitro. We demonstrate that the underlying biological mechanism is the unavoidable increase of neuronal response latencies to ongoing stimulations, which imposes a nonuniform gradual stretching of network delays. The limited experimental results are confirmed and extended by simulations and theoretical arguments based on identical neurons with a fixed increase of the neuronal response latency per evoked spike. We anticipate our results to lead to better understanding of the suitability of this computational paradigm to account for the brain's functionalities and will require the development of new systematic mathematical methods beyond the methods developed for traditional Boolean algebra.Comment: 32 pages, 14 figures, 1 tabl

Dance and emotion in posterior parietal cortex: a low-frequency rTMS study

Background: The neural bases of emotion are most often studied using short non-natural stimuli and assessed using correlational methods. Here we use a brain perturbation approach to make causal inferences between brain activity and emotional reaction to a long segment of dance. <p>Objective/Hypothesis: We aimed to apply offline rTMS over the brain regions involved in subjective emotional ratings to explore whether this could change the appreciation of a dance performance.</p> <p>Methods: We first used functional magnetic resonance imaging (fMRI) to identify regions correlated with fluctuating emotional rating during a 4-minutes dance performance, looking at both positive and negative correlation. Identified regions were further characterized using meta-data interrogation. Low frequency repetitive TMS was applied over the most important node in a different group of participants prior to them rating the same dance performance as in the fMRI session.</p> <p>Results: FMRI revealed a negative correlation between subjective emotional judgment and activity in the right posterior parietal cortex. This region is commonly involved in cognitive tasks and not in emotional task. Parietal rTMS had no effect on the general affective response, but it significantly (p<0.05 using exact t-statistics) enhanced the rating of the moment eliciting the highest positive judgments.</p> <p>Conclusion: These results establish a direct link between posterior parietal cortex activity and emotional reaction to dance. They can be interpreted in the framework of competition between resources allocated to emotion and resources allocated to cognitive functions. They highlight potential use of brain stimulation in neuro-æsthetic investigations.</p&gt

Functional connectivity in relation to motor performance and recovery after stroke.

Plasticity after stroke has traditionally been studied by observing changes only in the spatial distribution and laterality of focal brain activation during affected limb movement. However, neural reorganization is multifaceted and our understanding may be enhanced by examining dynamics of activity within large-scale networks involved in sensorimotor control of the limbs. Here, we review functional connectivity as a promising means of assessing the consequences of a stroke lesion on the transfer of activity within large-scale neural networks. We first provide a brief overview of techniques used to assess functional connectivity in subjects with stroke. Next, we review task-related and resting-state functional connectivity studies that demonstrate a lesion-induced disruption of neural networks, the relationship of the extent of this disruption with motor performance, and the potential for network reorganization in the presence of a stroke lesion. We conclude with suggestions for future research and theories that may enhance the interpretation of changing functional connectivity. Overall findings suggest that a network level assessment provides a useful framework to examine brain reorganization and to potentially better predict behavioral outcomes following stroke