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Modulation of Induced Gamma Band Responses in a Perceptual Learning Task in the Human EEG

University of Liverpool, UK

Andreas Keil

University of Konstanz, Germany

Fragmented pictures of an object, which appear meaningless when seen for the first time, can easily be identified after the presentation of an unfragmented version of the same picture. The neuronal mechanism for such a rapid perceptual learning phenomenon is largely unknown. Recently, induced gamma band responses (GBRs) have been discussed as a possible physiological correlate of activity in cell assemblies formed by learning. The present study was designed to investigate the modulation of induced GBRs in a perceptual learning task by using a 128-channel EEG montage. In the first sequence of the experiment, fragmented pictures from the Snodgrass and Vandervart inventory were presented. The fragmentation of the pictures was selected that subjects were unable to identify them. In the second experimental sequence—the perceptual learning sequence—half of the pictures were displayed in their unfragmented version. In the third sequence, all pictures were presented again in the fragmented version. Now, subjects had to rate whether or not they could identify the images. Results showed an increase in spectral gamma power at parietal electrode sites for identified pictures. In addition, neural activity in the gamma band was highly synchronized between posterior electrodes. For pictures not presented in their complete version, we found no such pattern in the third sequence. From our results, we concluded that induced GBRs might represent a signature of synchronized neural activity in a Hebbian cell assembly, activated by the fragmented picture after perceptual learning took place. No difference between identified and unidentified pictures was found in the visual evoked potential in the same time range and in the evoked GBR in the same frequency range as the induced response.

Key Words: Human high-density EEG • Induced gamma band response • Synchrony • Perceptual learning • Vision

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