Abstract The Human Connectome Project (HCP) was launched in 2010 as an ambitious
effort to accelerate advances in human neuroimaging, particularly for measures of brain …

Decoding, ie prediction from brain images or signals, calls for empirical evaluation of its
predictive power. Such evaluation is achieved via cross-validation, a method also used to …

Speech neuroprostheses have the potential to restore communication to people living with
paralysis, but naturalistic speed and expressivity are elusive. Here we use high-density …

A spinal cord injury interrupts the communication between the brain and the region of the
spinal cord that produces walking, leading to paralysis,. Here, we restored this …

Considerable progress has recently been made in natural language processing: deep
learning algorithms are increasingly able to generate, summarize, translate and classify …

Decoding speech from brain activity is a long-awaited goal in both healthcare and
neuroscience. Invasive devices have recently led to major milestones in this regard: deep …

NeuroKit2 is an open-source, community-driven, and user-centered Python package for
neurophysiological signal processing. It provides a comprehensive suite of processing …

Loss of consciousness is associated with the disruption of long-range thalamocortical and
corticocortical brain communication. We tested the hypothesis that deep brain stimulation …

Neural oscillations are ubiquitous across recording methodologies and species, broadly
associated with cognitive tasks, and amenable to computational modelling that investigates …

Cluster‐based permutation tests are gaining an almost universal acceptance as inferential
procedures in cognitive neuroscience. They elegantly handle the multiple comparisons …