Presentation
17 March 2023 Template- and model-based decoding of movie identities with high-density diffuse optical tomography of neural hemodynamics
Zachary E. Markow, Kalyan Tripathy, Jason W. Trobaugh, Alexa M. Svoboda, Mariel L. Schroeder, Sean M. Rafferty, Edward J. Richter, Adam T. Eggebrecht, Mark A. Anastasio, Joseph P. Culver
Author Affiliations +
Proceedings Volume PC12365, Neural Imaging and Sensing 2023; PC1236503 (2023) https://doi.org/10.1117/12.2649294
Event: SPIE BiOS, 2023, San Francisco, California, United States
Abstract
Functional MRI has decoded complex information about naturalistic stimuli using brain responses, but other non-invasive technologies have not achieved similar decoding capabilities. To evaluate feasibility of naturalistic visual decoding with Diffuse Optical Tomography (DOT), a 6.5-mm-spaced optode grid was employed to decode which of four 90-second movies was viewed by human subjects. >90% and >80% average decoding accuracy were achieved using a template-matching decoder within and between sessions, respectively. Average accuracy remained >60% and above chance using a model-based decoder to identify four and 40 clips outside the decoder's training set, respectively. DOT therefore has potential for more-complex neural decoding.
Conference Presentation
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zachary E. Markow, Kalyan Tripathy, Jason W. Trobaugh, Alexa M. Svoboda, Mariel L. Schroeder, Sean M. Rafferty, Edward J. Richter, Adam T. Eggebrecht, Mark A. Anastasio, and Joseph P. Culver "Template- and model-based decoding of movie identities with high-density diffuse optical tomography of neural hemodynamics", Proc. SPIE PC12365, Neural Imaging and Sensing 2023, PC1236503 (17 March 2023); https://doi.org/10.1117/12.2649294
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KEYWORDS
Brain

Diffuse optical tomography

Model-based design

Functional magnetic resonance imaging

Hemodynamics

Electroencephalography

Motion models

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