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Brain dynamics and temporal trajectories during task and naturalistic processing

Manasij Venkatesh, Joseph Jaja, Luiz Pessoa
doi: https://doi.org/10.1101/380402
Manasij Venkatesh
1Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, USA
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Joseph Jaja
1Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, USA
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Luiz Pessoa
1Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, USA
2Department of Psychology and Maryland Neuroimaging Center, University of Maryland, College Park MD, USA
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Abstract

Human functional Magnetic Resonance Imaging (fMRI) data are acquired while participants engage in diverse perceptual, motor, cognitive, and emotional tasks. Although data are acquired temporally, they are most often treated in a quasi-static manner. Yet, a fuller understanding of the mechanisms that support mental functions necessitates the characterization of dynamic properties. Here, we describe an approach employing a class of recurrent neural networks called reservoir computing, and show the feasibility and potential of using it for the analysis of temporal properties of brain data. We show that reservoirs can be used effectively both for classification and for characterizing lower-dimensional “trajectories” of temporal data. Classification accuracy was approximately 85% for short clips of “social interactions” and above 70% for clips extracted from movie segments. Data representations with 10 or fewer dimensions (from an original space with over 300) attained classification accuracy within 5% of the full data. We hypothesize that such low-dimensional trajectories may provide “signatures” that can be associated with tasks and/or mental states. The approach was applied across participants (that is, training in one set of participants, and testing in a separate group), showing that representations generalized well to unseen participants. Taken together, we believe the present approach provides a promising framework to characterize dynamic fMRI information during both tasks and naturalistic conditions.

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  • manasij{at}umd.edu

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted July 30, 2018.
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Brain dynamics and temporal trajectories during task and naturalistic processing
Manasij Venkatesh, Joseph Jaja, Luiz Pessoa
bioRxiv 380402; doi: https://doi.org/10.1101/380402
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Brain dynamics and temporal trajectories during task and naturalistic processing
Manasij Venkatesh, Joseph Jaja, Luiz Pessoa
bioRxiv 380402; doi: https://doi.org/10.1101/380402

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