Zachary E. Markow,1 Kalyan Tripathy,2 Jason W. Trobaugh,1 Alexa M. Svoboda,3 Mariel L. Schroeder,4 Sean M. Rafferty,1 Edward J. Richter,1 Adam T. Eggebrechthttps://orcid.org/0000-0002-6320-2676,2 Mark A. Anastasio,5 Joseph P. Culver1
1Washington Univ. in St. Louis (United States) 2Washington Univ. in St Louis (United States) 3Univ. of Cincinnati (United States) 4Purdue Univ. (United States) 5Univ. of Illinois (United States)
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
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.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
The alert did not successfully save. Please try again later.
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, "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