Virtual reality (VR) environments simulating height offer a unique platform to investigate neural adaptations to emotionally salient contexts during locomotion. These simulations allow for controlled analysis of motor‐cognitive interactions under perceived ...
Teravoxel-scale, cellular-resolution images of cleared rodent brains acquired with light-sheet fluorescence microscopy have transformed the way we study the brain. Realizing the potential of this technology requires computational pipelines that generalize ...
Understanding the brain requires studying its multiscale interactions from molecules to networks. The increasing availability of large-scale datasets detailing brain circuit composition, connectivity, and activity is transforming neuroscience. However, int ...
Resting-state fMRI has spurred an impressive amount of methods development, among which dynamic functional connectivity (dFC) is one important branch. However, the relevance of time-varying and time-resolved features has led to debate, to which we want to ...
Implantable neuroprosthetic devices such as electrocorticography (ECoG) and intracortical microelectrodes have the potential to restore neurological functions in disabled individuals. They constitute the direct interface with the body and require long term ...
Relating behavior to brain activity in animals is a fundamental goal in neuroscience, with practical applications in building robust brain-machine interfaces. However, the domain gap between individuals is a major issue that prevents the training of genera ...
Recently, the complexity analysis of brain activity has shown the possibility to provide additional information to discriminate between rest and motion in real-time. In this work, we propose a novel entropy-based machine learning method to classify between ...
