Brainhack: developing a culture of open, inclusive, community-driven neuroscience

Abstract

Brainhack is an innovative meeting format that promotes scientific collaboration and education in an open and inclusive environment. Departing from the formats of typical scientific workshops, these events are based on grassroots projects and training, and foster open and reproducible scientific practices. We describe here the multifaceted, lasting benefits of Brainhacks for individual participants, particularly early career researchers. We further highlight the unique contributions that Brainhacks can make to the research community, contributing to scientific progress by complementing opportunities available in conventional formats.

Transcriptional characterization of the glial response due to chronic neural implantation of flexible microprobes

“…Neural interfaces intended to interact with the central nervous system (CNS) are well established within fundamental neuroscience and aim at clinical applications (1–4). Accurate sampling of the electrophysiological activity of the local neuronal population is achieved by implanting penetrating probes into the brain parenchyma, sometimes equipped with a multitude of recording sites (5–7).…”

Cross disorder comparisons of brain structure in schizophrenia, bipolar disorder, major depressive disorder, and 22q11.2 deletion syndrome: A review of ENIGMA findings

“…nidash.org, nda.nih.gov, etc.). [14][15][16][17] The ENIGMA project started in 2009 with the initial aim of aggregating brain imaging and genetic data across research centers in order to identify the predominantly small effects of common genetic variations in the brain. ENIGMA's first imaging genetics publication yielded the first genome-wide significant genetic loci associated with hippocampal and intracranial volumes based on data obtained from 21 151 and 15 782 individuals, in collaboration with the CHARGE (Cohorts of Heart and Aging Research in Genomic Epidemiology) consortium.…”

Group-level inference of information-based measures for the analyses of cognitive brain networks from neurophysiological data

“…Our approach has been implemented in an open-source Python package called Frites 8 ( Framework for Information Theoretical analysis of Electrophysiological data and Statistics ) designed for inferring cognitive brain networks by means of measures of information. The toolbox, partially developed during Brainhack events (Gau et al, 2021), includes an implementation of the proposed group-level statistical pipeline, with fixed- and randomeffect models such as test- and cluster-wise corrections. By default, Frites is using a tensorbased implementation of the GCMI for faster computations.…”