Reference : Mapping human temporal and parietal neuronal population activity and functional coupl...
Scientific journals : Article
Social & behavioral sciences, psychology : Neurosciences & behavior
http://hdl.handle.net/2268/204348
Mapping human temporal and parietal neuronal population activity and functional coupling during mathematical cognition
English
Daitch, Amy []
Foster, Brett []
Schrouff, Jessica mailto [Université de Liège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation >]
Rangarajan, Vinitha []
Kasikci, Itir []
Gattas, Sandra []
Parvizi, Josef []
2016
Proceedings of the National Academy of Sciences of the United States of America
National Academy of Sciences
113
46
Yes (verified by ORBi)
International
0027-8424
1091-6490
Washington
DC
[en] numerical processing ; ECoG
[en] Brain areas within the lateral parietal cortex (LPC) and ventral temporal cortex (VTC) have been shown to code for abstract quantity representations and for symbolic numerical representations, respectively. To explore the fast dynamics of activity within each region and the interaction between them, we used electrocorticography recordings from 16 neurosurgical subjects implanted with grids of electrodes over these two regions and tracked the activity within and between the regions as subjects performed three different numerical tasks. Although our results reconfirm the presence of math-selective hubs within the VTC and LPC, we report here a remarkable heterogeneity of neural responses within each region at both millimeter and millisecond scales. Moreover, we show that the heterogeneity of response profiles within each hub mirrors the distinct patterns of functional coupling between them. Our results support the existence of multiple bidirectional functional loops operating between discrete populations of neurons within the VTC and LPC during the visual processing of numerals and the performance of arithmetic functions. These findings reveal information about the dynamics of numerical processing in the brain and also provide insight into the fine-grained functional architecture and connectivity within the human brain
Commission européenne : Direction générale de la Recherche
http://hdl.handle.net/2268/204348
10.1073/pnas.1608434113
H2020 ; 654038 - DecoMP_ECoG - Decoding memory processing from experimental and spontaneous human brain activity using intracranial electrophysiological recordings and machine learning based methods.

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