An empirical evaluation of functional alignment using inter-subject decoding

Autor: Jean-Baptiste Poline, Thomas Bazeille, Bertrand Thirion, Elizabeth DuPre, Hugo Richard
Přispěvatelé: Modelling brain structure, function and variability based on high-field MRI data (PARIETAL), Service NEUROSPIN (NEUROSPIN), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Montreal Neurological Institute and Hospital, McGill University = Université McGill [Montréal, Canada], Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Service NEUROSPIN (NEUROSPIN), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Computer science
Cognitive Neuroscience
Neurosciences. Biological psychiatry. Neuropsychiatry
Machine learning
computer.software_genre
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
03 medical and health sciences
0302 clinical medicine
[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]
Humans
030304 developmental biology
inter-subject variability
0303 health sciences
Brain Mapping
business.industry
fMRI
Brain
Usability
Magnetic Resonance Imaging
Variable (computer science)
Range (mathematics)
functional alignment
Neurology
Scalability
Benchmark (computing)
Piecewise
Artificial intelligence
[INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM]
business
Neural coding
computer
predictive modeling
030217 neurology & neurosurgery
Decoding methods
Algorithms
RC321-571
Zdroj: NeuroImage
NeuroImage, 2021, 245, ⟨10.1016/j.neuroimage.2021.118683⟩
NeuroImage, Vol 245, Iss, Pp 118683-(2021)
NeuroImage, Elsevier, 2021
NeuroImage, Vol. 245
ISSN: 1053-8119
1095-9572
Popis: Inter-individual variability in the functional organization of the brain presents a major obstacle to identifying generalizable neural coding principles. Functional alignment—a class of methods that matches subjects’ neural signals based on their functional similarity—is a promising strategy for addressing this variability. To date, however, a range of functional alignment methods have been proposed and their relative performance is still unclear. In this work, we benchmark five functional alignment methods for inter-subject decoding on four publicly available datasets. Specifically, we consider three existing methods: piecewise Procrustes, searchlight Procrustes, and piecewise Optimal Transport. We also introduce and benchmark two new extensions of functional alignment methods: piecewise Shared Response Modelling (SRM), and intra-subject alignment. We find that functional alignment generally improves inter-subject decoding accuracy though the best performing method depends on the research context. Specifically, SRM and Optimal Transport perform well at both the region-of-interest level of analysis as well as at the whole-brain scale when aggregated through a piecewise scheme. We also benchmark the computational efficiency of each of the surveyed methods, providing insight into their usability and scalability. Taking inter-subject decoding accuracy as a quantification of inter-subject similarity, our results support the use of functional alignment to improve inter-subject comparisons in the face of variable structure-function organization. We provide open implementations of all methods used.
Databáze: OpenAIRE
Externí odkaz: