1. Non-invasive real-time access to spatial attention information from 3T fMRI BOLD signals
- Author
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Carine De Sousa Ferreira, Suliann Ben Hamed, Simon Clavagnier, Danielle Ibarrola, Franck Lamberton, Celia Loriette, Impact de l'environnement chimique sur la santé humaine - ULR 4483 (IMPECS), Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Centre d'Etude et de Recherche Multimodal Et Pluridisciplinaire en imagerie du vivant (CERMEP - imagerie du vivant), Centre Hospitalier Universitaire de Saint-Etienne [CHU Saint-Etienne] (CHU ST-E)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-CHU Grenoble-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Institut des sciences cognitives Marc Jeannerod - Centre de neuroscience cognitive - UMR5229 (ISC-MJ), Université Claude Bernard Lyon 1 (UCBL), and Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)
- Subjects
Cued speech ,Computer science ,business.industry ,media_common.quotation_subject ,[SCCO.NEUR]Cognitive science/Neuroscience ,Cognition ,Pattern recognition ,Local field potential ,computer.software_genre ,Covert ,Voxel ,Contrast (vision) ,Artificial intelligence ,Neurofeedback ,business ,computer ,Decoding methods ,media_common - Abstract
Access to higher cognitive functions in real-time remains very challenging, because these functions are internally driven and their assessment is based onto indirect measures. In addition, recent finding show that these functions are highly dynamic. Previous studies using intra-cortical recordings in monkeys, succeed to access the (x,y) position of covert spatial attention, in real-time, using classification methods applied to monkey prefrontal multi-unit activity and local field potentials. In contrast, the direct access to attention with non-invasive methods is limited to predicting the attention localisation based on a quadrant classification. Here, we demonstrate the feasibility to track covert spatial attention localization using non-invasive fMRI BOLD signals, with an unprecedented spatial resolution. We further show that the errors produced by the decoder are not randomly distributed but concentrate on the locations neighbouring the cued location and that behavioral errors correlate with weaker decoding performance. Last, we also show that the voxels contributing to the decoder precisely match the visual retinotopic organization of the occipital cortex and that single trial access to attention is limited by the intrinsic dynamics of spatial attention. Taken together, these results open the way to the development of remediation and enhancement neurofeedback protocols targeting the attentional function.
- Published
- 2022