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Tuning to sound frequency in auditory field potentials

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons84006

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;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84136

Petkov,  CI
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84063

Logothetis,  NK
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Zitation

Kayser, C., Petkov, C., & Logothetis, N. (2007). Tuning to sound frequency in auditory field potentials. Journal of Neurophysiology, 98(3), 1806-1809. doi:10.1152/jn.00358.2007.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0013-CBC7-B
Zusammenfassung
Neurons in auditory cortex are selective for the frequency content of acoustical stimuli. Classically, this response selectivity is studied at the single neuron level. However, current research often employs functional imaging techniques to investigate the organization of auditory cortex. The signals underlying the imaging data arise from neural mass action and reflect the properties of populations of neurons. For example, the signal used for functional magnetic resonance imaging (fMRI-BOLD) was shown to correlate with the oscillatory activity quantified by local field potentials (LFP). This raises the questions of how the frequency selectivity in neuronal population signals compares to the tuning of spiking responses. To address this, we quantified tuning properties of auditory evoked potentials (AEP), different frequency bands of the LFP, analog multi-unit (AMUA) and spike-sorted single- and multi-unit activity in auditory cortex. The AMUA showed a close correspondence in frequency tuning to the spike-sorted activity. In contrast, for the LFP we found a clear dissociation of high and low frequency bands: there was a gradual increase of tuning-curve similarity, tuning specificity and information about the stimulus with increasing LFP frequency. While properties of the high frequency LFP matched those of spiking activity, the lower frequency bands differed considerably, as did the AEP. These results demonstrate that electrophysiological population responses exhibit varying degrees of frequency tuning and suggest that those functional imaging methods that are related to high frequency oscillatory activity should well reflect the neuronal processing of sound frequency.