An image-computable model for the stimulus selectivity of gamma oscillations

Dora Hermes, Natalia Petridou, Kendrick N Kay, Jonathan Winawer

Research output: Contribution to journalArticleAcademicpeer-review


Gamma oscillations in visual cortex have been hypothesized to be critical for perception, cognition, and information transfer. However, observations of these oscillations in visual cortex vary widely; some studies report little to no stimulus-induced narrowband gamma oscillations, others report oscillations for only some stimuli, and yet others report large oscillations for most stimuli. To better understand this signal, we developed a model that predicts gamma responses for arbitrary images and validated this model on electrocorticography (ECoG) data from human visual cortex. The model computes variance across the outputs of spatially pooled orientation channels, and accurately predicts gamma amplitude across 86 images. Gamma responses were large for a small subset of stimuli, differing dramatically from fMRI and ECoG broadband (non-oscillatory) responses. We propose that gamma oscillations in visual cortex serve as a biomarker of gain control rather than being a fundamental mechanism for communicating visual information.

Original languageEnglish
Article numbere47035
Publication statusPublished - 8 Nov 2019


Dive into the research topics of 'An image-computable model for the stimulus selectivity of gamma oscillations'. Together they form a unique fingerprint.

Cite this