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EEG signals are informative for individual cue-response combinations in a visuomotor task

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http://pubman.mpdl.mpg.de/cone/persons/resource/persons84278

Venkatesh,  V
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84179

Rulla,  S
Research Group Neural Population Imaging, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons83940

Gotthardt,  S
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84966

Panzeri,  S
Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84098

Munk,  M
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Citation

Venkatesh, V., Rulla, S., Gotthardt, S., Panzeri, S., & Munk, M. (2011). EEG signals are informative for individual cue-response combinations in a visuomotor task. Poster presented at 41st Annual Meeting of the Society for Neuroscience (Neuroscience 2011), Washington, DC, USA.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0013-B934-6
Abstract
The execution of complex behavior requires the coordinated action of discrete neural populations. The dynamic interaction of distributed populations are studied by mesoscopic and macroscopic measures of brain activity such as LFP and EEG signals which reflect the summated responses of neural groups to cognitive events. We wanted to investigate if a quantitative measure of modulations in oscillatory components with specific task components and demands can be derived. A sensorimotor task paradigm was implemented where distinct visual cues indicate distinct motor responses to determine if modulations in oscillations can be tuned to specific cue-response combinations. Two monkeys were trained to perform a visuo-motor task which involved moving a lever with their right hand cued by moving visual stimuli. Movement direction and velocity of sine wave gratings were trained to be associated with a target position of the manipulandum. Multi-area EEG signals were acquired from implanted electrodes above visual, parietal, sensorimotor and premotor areas. The time frequency spectra of the EEG signals was characterized by continuous wavelet transform. The time frequency spectrum displays dominant power in the 10-30 Hz bands although significant modulation is also present in 1-10 Hz and 45 - 80 Hz bands. We investigated the stimulus and motor response specificity of oscillations by computing mutual information between the cue or motor response and specific frequency components of the oscillatory signal. We find that information is higher in left hemisphere electrodes above sites related to the task such as visual and sensorimotor electrodes (statistically significant for the 1-8 Hz and 45-60 Hz band), reflecting the usage of the right hand for motor response. The peak mutual information was found in the lower frequency bands such as the 1-8 Hz band with a mean value of 0.16 bits averaged across channels and timebins. The higher frequency bands such as the 45-60 Hz band also carry information about the cues although at a lower magnitude (mean value of 0.04 bits). We found that cues can be distinguished based on the differences in spectral power in certain channels activated by the task. Information about cue or task attributes is carried in discrete frequency bands with the lower frequency bands being most informative. Estimating mutual information can provide a quantitative measure of tuning of defined frequency components of EEG to stimulus or task attributes. EEG signals which reflect the coherent activity of many neural populations carry information in their frequency structure about how stimulus processing- behavior production drives activation of multiple brain areas.