output
20122026
most citedUnraveling the Hidden Environmental Impacts of AI Solutions for Environment

180 citations

Showing 2023Show all

6 papers · 1 filter

eess.IV2023★ 15 cited

FetMRQC: a robust quality control system for multi-centric fetal brain MRI

Thomas Sanchez, Oscar Esteban, Yvan Gomez +8

Fetal brain MRI is becoming an increasingly relevant complement to neurosonography for perinatal diagnosis, allowing fundamental insights into fetal brain development throughout ge…

stat.ML2023

Comprehensive analysis of synthetic learning applied to neonatal brain MRI segmentation

R Valabregue, F Girka, A Pron +2

Brain segmentation from neonatal MRI images is a very challenging task due to large changes in the shape of cerebral structures and variations in signal intensities reflecting the…

q-bio.OT2023★ 60 cited

The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)

Russell A. Poldrack, Christopher J. Markiewicz, Stefan Appelhoff +111

The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is mean…

q-bio.NC2023★ 2 cited

Accurate Detection of Spiking Motifs by Learning Heterogeneous Delays of a Spiking Neural Network

Laurent U Perrinet

Recently, interest has grown in exploring the hypothesis that neural activity conveys information through precise spiking motifs. To investigate this phenomenon, various algorithms…

physics.soc-ph2023★ 15 cited

An integrative dynamical perspective for graph theory and the study of complex networks

Gorka Zamora-López, Matthieu Gilson

Built upon the shoulders of graph theory, the field of complex networks has become a central tool for studying real systems across various fields of research. Represented as graphs…

q-bio.NC2023

Beyond sparse coding in V1

Ilias Rentzeperis, Luca Calatroni, Laurent Perrinet +1

Growing evidence indicates that only a sparse subset from a pool of sensory neurons is active for the encoding of visual stimuli at any instant in time. Traditionally, to replicate…