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Slow Rhythms In Sensory Cortices And The Encoding Of Acoustic Information


Kayser,  C
Research Group Physiology of Sensory Integration, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Kayser, C. (2012). Slow Rhythms In Sensory Cortices And The Encoding Of Acoustic Information. Talk presented at 8th Forum of European Neuroscience (FENS 2012). Barcelona, Spain.

Oscillations are pervasive in encephalographic (EEG/MEG) signals and are considered an important marker or even a causal mechanism for cognitive processes and sensory representations. While the relation between oscillation amplitude (power) and sensory cognitive variables has been extensively studied, recent work revealed that the dynamic oscillation signature (the temporal phase pattern) can carry information about such processes to a degree greater than the amplitude. Especially in the auditory system it was realized that slow rhythms entrain to the dynamic signature of naturalistic sounds. To elucidate the direct neural correlates of such oscillatory phase patterns we compared the stimulus selectivity of auditory driven neural firing rates and of EEG oscillations generated by these. We studied the encoding of natural sounds in auditory cortex by employing the same naturalistic sound stimuli in experiments recording scalp EEGs in human subjects and in experiments recording intracortical field potentials and single neurons in macaque auditory cortex. Using stimulus decoding techniques we show that stimulus selective firing patterns imprint on the phase structure rather than the amplitude of slow (mostly theta band) oscillations. Importantly, we found that stimuli which can be discriminated by firing rates can also be discriminated by oscillatory phase patterns but not by oscillation amplitude, directly demonstrating a neural basis for stimulus selective EEG phase patterns. This work reveals a level of interrelation between encephalographic signals and neural firing beyond simple amplitude co-variations and enhance the possibilities to interpret EEG based studies towards dynamic signatures of sensory processing.