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341 An intracranial EEG map of naturalistic images in the human brain
Published online by Cambridge University Press: 19 April 2022
Abstract
OBJECTIVES/GOALS: Our overall goal is to identify the processes used by the human visual system to encode visual stimuli into perceptual representations. In this project, our objective is (i) to collect a dataset of human neural activity in response to 1000 naturalistic color images and (ii) to determine how image parameters drive different parts of the human brain. METHODS/STUDY POPULATION: We recorded iEEG data in 4 human subjects who had been implanted for epilepsy monitoring. Each subject was presented 10 sets of 100 naturalistic stimuli, taken from the Natural Scenes Dataset (Allen et al., 2021), on a screen for 1 second each with 1 second rest intervals between stimuli. The subjects were instructed to fixate on a red dot at the center of the screen and were prompted to recall whether they had seen 3 additional test stimuli at the end of each set to encourage attentiveness. We calculated significant neural responses at each electrode by comparing evoked potentials and high frequency power changes during each stimulus vs. rest. Electrodes with significant responses were then mapped to anatomic locations in each subjects brain and then collectively to a standard brain. RESULTS/ANTICIPATED RESULTS: The natural image set elicited significant evoked potentials and high frequency responses at electrodes in each subject. Response latencies, from 80 to 300 ms after stimulus onset, portrayed the evolution of visual processing along the visual pathways, through key sites such as the early visual cortex, ventral temporal cortex, intraparietal sulcus, and frontal eye field. These responses differed significantly from those elicited by simple patterns, which drove early visual cortex but less so in later regions. DISCUSSION/SIGNIFICANCE: These data show that the human brain responds differently to more complex images. Determining the human brains response to naturalistic images is essential for encoding models that describe the processing in the human visual system. These models may further future efforts for electrical neurostimulation therapies such as for restoring vision.
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- This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
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- © The Author(s), 2022. The Association for Clinical and Translational Science