Abstract

Two analytic traditions characterize fMRI language research. One relies on averaging activations across individuals. This approach has limitations: because of inter-individual variability in the locations of language areas, any given voxel/vertex in a common brain space is part of the language network in some individuals but in others, may belong to a distinct network. An alternative approach relies on identifying language areas in each individual using a functional ‘localizer’. Because of its greater sensitivity, functional resolution, and interpretability, functional localization is gaining popularity, but it is not always feasible, and cannot be applied retroactively to past studies. To bridge these disjoint approaches, we created a probabilistic functional atlas using fMRI data for an extensively validated language localizer in 806 individuals. This atlas enables estimating the probability that any given location in a common space belongs to the language network, and thus can help interpret group-level activation peaks and lesion locations, or select voxels/electrodes for analysis. More meaningful comparisons of findings across studies should increase robustness and replicability in language research.

Measurement(s)

Brain activity measurement

Technology Type(s)

fMRI

Sample Characteristic - Organism

Homo sapiens

Details

Title
Probabilistic atlas for the language network based on precision fMRI data from >800 individuals
Author
Lipkin, Benjamin 1 ; Tuckute, Greta 1 ; Affourtit, Josef 1 ; Small, Hannah 2 ; Mineroff, Zachary 3   VIAFID ORCID Logo  ; Kean, Hope 1 ; Jouravlev, Olessia 4 ; Rakocevic, Lara 1 ; Pritchett, Brianna 1 ; Siegelman, Matthew 5 ; Hoeflin, Caitlyn 6 ; Pongos, Alvincé 7   VIAFID ORCID Logo  ; Blank, Idan A. 8 ; Struhl, Melissa Kline 9 ; Ivanova, Anna 1 ; Shannon, Steven 10 ; Sathe, Aalok 1   VIAFID ORCID Logo  ; Hoffmann, Malte 11   VIAFID ORCID Logo  ; Nieto-Castañón, Alfonso 12 ; Fedorenko, Evelina 13   VIAFID ORCID Logo 

1  Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786); Massachusetts Institute of Technology, McGovern Institute for Brain Research, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786) 
2  Johns Hopkins University, Department of Cognitive Science, Baltimore, USA (GRID:grid.21107.35) (ISNI:0000 0001 2171 9311) 
3  Carnegie Mellon University, Human-computer Interaction Institute, Pittsburgh, USA (GRID:grid.147455.6) (ISNI:0000 0001 2097 0344) 
4  Carleton University, Department of Cognitive Science, Ottawa, Canada (GRID:grid.34428.39) (ISNI:0000 0004 1936 893X) 
5  Columbia University, Department of Psychology, New York, USA (GRID:grid.21729.3f) (ISNI:0000000419368729) 
6  University of Chicago, Harris School of Public Policy, Chicago, USA (GRID:grid.170205.1) (ISNI:0000 0004 1936 7822) 
7  University of California, Department of Bioengineering, Berkeley, USA (GRID:grid.47840.3f) (ISNI:0000 0001 2181 7878) 
8  University of California, Department of Psychology, Los Angeles, USA (GRID:grid.19006.3e) (ISNI:0000 0000 9632 6718) 
9  Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786) 
10  Massachusetts Institute of Technology, McGovern Institute for Brain Research, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786) 
11  Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Cambridge, USA (GRID:grid.32224.35) (ISNI:0000 0004 0386 9924) 
12  Massachusetts Institute of Technology, McGovern Institute for Brain Research, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786); Boston University, Department of Speech, Language, and Hearing Sciences, Boston, USA (GRID:grid.189504.1) (ISNI:0000 0004 1936 7558) 
13  Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786); Massachusetts Institute of Technology, McGovern Institute for Brain Research, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786); Harvard University, Department of Speech, Hearing, Bioscience, and Technology, Cambridge, USA (GRID:grid.38142.3c) (ISNI:000000041936754X) 
Publication year
2022
Publication date
2022
Publisher
Nature Publishing Group
e-ISSN
20524463
Source type
Scholarly Journal
Language of publication
English
DOI
https://doi.org/10.1038/s41597-022-01645-3
ProQuest document ID
2707731856
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.