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Updated: Jul 16, 2026

Stimulus-specific Cortical Visual Evoked Potential Morphological Patterns
Published on: May 12, 2019
Stimuli of varying spatial scale induce gamma activity with distinct temporal characteristics in human visual cortex
Avgis Hadjipapas1, Peyman Adjamian, Jennifer B Swettenham
1The Wellcome Trust Laboratory for MEG Studies, Neurosciences, School of Life and Health Sciences, Aston University, Birmingham B4 7ET, UK. hadjipaa@aston.ac.uk
Abstract:
Gamma activity to stationary grating stimuli was studied non-invasively using MEG recordings in humans. Using a spatial filtering technique, we localized gamma activity to primary visual cortex. We tested the hypothesis that spatial frequency properties of visual stimuli may be related to the temporal frequency characteristics of the associated cortical responses. We devised a method to assess temporal frequency differences between stimulus-related responses that typically exhibit complex spectral shapes. We applied this methodology to either single-trial (induced) or time-averaged (evoked) responses in four frequency ranges (0-40, 20-60, 40-80 and 60-100 Hz) and two time windows (either the entire duration of stimulus presentation or the first second following stimulus onset). Our results suggest that stimuli of varying spatial frequency induce responses that exhibit significantly different temporal frequency characteristics. These effects were particularly accentuated for induced responses in the classical gamma frequency band (20-60 Hz) analyzed over the entire duration of stimulus presentation. Strikingly, examining the first second of the responses following stimulus onset resulted in significant loss in stimulus specificity, suggesting that late signal components contain functionally relevant information. These findings advocate a functional role of gamma activity in sensory representation. We suggest that stimulus specific frequency characteristics of MEG signals can be mapped to processes of neuronal synchronization within the framework of coupled dynamical systems.
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