Publication Title

PLoS Computational Biology

Document Type

Article

Department or Program

Neuroscience

Publication Date

9-1-2021

Abstract

A number of neuroimaging techniques have been employed to understand how visual information is transformed along the visual pathway. Although each technique has spatial and temporal limitations, they can each provide important insights into the visual code. While the BOLD signal of fMRI can be quite informative, the visual code is not static and this can be obscured by fMRI’s poor temporal resolution. In this study, we leveraged the high temporal resolution of EEG to develop an encoding technique based on the distribution of responses generated by a population of real-world scenes. This approach maps neural signals to each pixel within a given image and reveals location-specific transformations of the visual code, providing a spatiotemporal signature for the image at each electrode. Our analyses of the mapping results revealed that scenes undergo a series of nonuniform transformations that prioritize different spatial frequencies at different regions of scenes over time. This mapping technique offers a potential avenue for future studies to explore how dynamic feedforward and recurrent processes inform and refine high-level representations of our visual world.

PubMed ID

34570753

Copyright Note

This is the publisher's version of the work. This publication appears in Bates College's institutional repository by permission of the copyright owner for personal use, not for redistribution.

Required Publisher's Statement

Original version is available from the publisher at: https://doi.org/10.1371/journal.pcbi.1009456

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