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An image-computable model for the stimulus selectivity of gamma oscillations
Dora Hermes1,2, Natalia Petridou3, Kendrick N Kay4
1Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, United States.
Elife
|November 9, 2019
Summary
Gamma oscillations in the visual cortex are not fundamental for information transfer. A new model suggests these gamma responses act as a biomarker for gain control, varying significantly with specific stimuli.
Area of Science:
- Neuroscience
- Computational Neuroscience
- Visual Perception
Background:
- Gamma oscillations in the visual cortex are theorized to be crucial for perception and cognition.
- Existing research shows inconsistent findings regarding the presence and magnitude of stimulus-induced gamma oscillations.
Purpose of the Study:
- To develop and validate a predictive model for gamma responses in the human visual cortex.
- To investigate the functional role of gamma oscillations in visual processing.
Main Methods:
- A computational model was created to predict gamma responses based on image properties.
- The model's predictions were validated using electrocorticography (ECoG) data from human subjects.
- The model calculates variance across spatially pooled orientation channels.
Main Results:
- The model accurately predicted gamma oscillation amplitudes for 86 different images.
- Gamma responses were substantial only for a limited set of stimuli.
- These gamma responses differed markedly from broadband (non-oscillatory) ECoG and fMRI signals.
Conclusions:
- Gamma oscillations in the visual cortex may not be a primary mechanism for visual information transfer.
- Gamma oscillations are proposed to function as a biomarker for neural gain control in the visual system.
