A multimodal encoding model applied to imaging decision-related neural cascades in the human brain
Perception and cognition in the brain are naturally characterized as spatiotemporal processes. Decision-making, for example, depends on coordinated patterns of neural activity cascading across the brain, running in time from stimulus to response and in space from primary sensory regions to the front...
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Published in | NeuroImage (Orlando, Fla.) Vol. 180; no. Pt A; pp. 211 - 222 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Elsevier Inc
15.10.2018
Elsevier Limited |
Subjects | |
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Abstract | Perception and cognition in the brain are naturally characterized as spatiotemporal processes. Decision-making, for example, depends on coordinated patterns of neural activity cascading across the brain, running in time from stimulus to response and in space from primary sensory regions to the frontal lobe. Measuring this cascade is key to developing an understanding of brain function. Here we report on a novel methodology that employs multi-modal imaging for inferring this cascade in humans at unprecedented spatiotemporal resolution. Specifically, we develop an encoding model to link simultaneously measured electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) signals to infer high-resolution spatiotemporal brain dynamics during a perceptual decision. After demonstrating replication of results from the literature, we report previously unobserved sequential reactivation of a substantial fraction of the pre-response network whose magnitude correlates with a proxy for decision confidence. Our encoding model, which temporally tags BOLD activations using time localized EEG variability, identifies a coordinated and spatially distributed neural cascade that is associated with a perceptual decision. In general the methodology illuminates complex brain dynamics that would otherwise be unobservable using fMRI or EEG acquired separately.
•An encoding model method is proposed that links simultaneously measured EEG and fMRI.•The method temporally tags BOLD activations using time localized EEG variability.•The method is applied to EEG/fMRI acquired during a perceptual decision making task.•Results include a previously unobserved reactivation of a pre-response network.•The magnitude of the reactivation correlates with a proxy for decision confidence. |
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AbstractList | Perception and cognition in the brain are naturally characterized as spatiotemporal processes. Decision-making, for example, depends on coordinated patterns of neural activity cascading across the brain, running in time from stimulus to response and in space from primary sensory regions to the frontal lobe. Measuring this cascade is key to developing an understanding of brain function. Here we report on a novel methodology that employs multi-modal imaging for inferring this cascade in humans at unprecedented spatiotemporal resolution. Specifically, we develop an encoding model to link simultaneously measured electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) signals to infer high-resolution spatiotemporal brain dynamics during a perceptual decision. After demonstrating replication of results from the literature, we report previously unobserved sequential reactivation of a substantial fraction of the pre-response network whose magnitude correlates with a proxy for decision confidence. Our encoding model, which temporally tags BOLD activations using time localized EEG variability, identifies a coordinated and spatially distributed neural cascade that is associated with a perceptual decision. In general the methodology illuminates complex brain dynamics that would otherwise be unobservable using fMRI or EEG acquired separately. Perception and cognition in the brain are naturally characterized as spatiotemporal processes. Decision-making, for example, depends on coordinated patterns of neural activity cascading across the brain, running in time from stimulus to response and in space from primary sensory regions to the frontal lobe. Measuring this cascade is key to developing an understanding of brain function. Here we report on a novel methodology that employs multi-modal imaging for inferring this cascade in humans at unprecedented spatiotemporal resolution. Specifically, we develop an encoding model to link simultaneously measured electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) signals to infer high-resolution spatiotemporal brain dynamics during a perceptual decision. After demonstrating replication of results from the literature, we report previously unobserved sequential reactivation of a substantial fraction of the pre-response network whose magnitude correlates with a proxy for decision confidence. Our encoding model, which temporally tags BOLD activations using time localized EEG variability, identifies a coordinated and spatially distributed neural cascade that is associated with a perceptual decision. In general the methodology illuminates complex brain dynamics that would otherwise be unobservable using fMRI or EEG acquired separately. •An encoding model method is proposed that links simultaneously measured EEG and fMRI.•The method temporally tags BOLD activations using time localized EEG variability.•The method is applied to EEG/fMRI acquired during a perceptual decision making task.•Results include a previously unobserved reactivation of a pre-response network.•The magnitude of the reactivation correlates with a proxy for decision confidence. |
Author | Conroy, Bryan Muraskin, Jordan Tu, Tao Walz, Jennifer M. Sajda, Paul Brown, Truman R. Goldman, Robin I. |
AuthorAffiliation | e Center for Healthy Minds, University of Wisconsin-Madison, Madison, WI, USA, 53705 a Department of Biomedical Engineering, Columbia University, New York, NY, USA 10027 b Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA, 29425 d Philips Research, Cambridge, MA USA, 02141 c Florey Institute of Neuroscience and Mental Health, Melbourne, Australia |
AuthorAffiliation_xml | – name: b Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA, 29425 – name: a Department of Biomedical Engineering, Columbia University, New York, NY, USA 10027 – name: c Florey Institute of Neuroscience and Mental Health, Melbourne, Australia – name: e Center for Healthy Minds, University of Wisconsin-Madison, Madison, WI, USA, 53705 – name: d Philips Research, Cambridge, MA USA, 02141 |
Author_xml | – sequence: 1 givenname: Jordan surname: Muraskin fullname: Muraskin, Jordan email: jordan.muraskin@gmail.com organization: Department of Biomedical Engineering, Columbia University, New York, NY 10027, USA – sequence: 2 givenname: Truman R. surname: Brown fullname: Brown, Truman R. organization: Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC 29425, USA – sequence: 3 givenname: Jennifer M. surname: Walz fullname: Walz, Jennifer M. organization: Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA – sequence: 4 givenname: Tao surname: Tu fullname: Tu, Tao organization: Department of Biomedical Engineering, Columbia University, New York, NY 10027, USA – sequence: 5 givenname: Bryan surname: Conroy fullname: Conroy, Bryan organization: Philips Research, Cambridge, MA 02141, USA – sequence: 6 givenname: Robin I. surname: Goldman fullname: Goldman, Robin I. organization: Center for Healthy Minds, University of Wisconsin-Madison, Madison, WI 53705, USA – sequence: 7 givenname: Paul surname: Sajda fullname: Sajda, Paul email: psajda@columbia.edu organization: Department of Biomedical Engineering, Columbia University, New York, NY 10027, USA |
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SubjectTerms | Adult Brain Brain - physiology Brain mapping Brain Mapping - methods Cognition Confidence Decision making Decision Making - physiology EEG Electroencephalography Electroencephalography - methods Female fMRI Frontal lobe Functional magnetic resonance imaging Humans Hypotheses Magnetic Resonance Imaging - methods Male Models, Neurological Multimodal Imaging - methods Neuroimaging Simultaneous acquisition Young Adult |
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