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In Vivo Measurement of Cortical Impedance Spectrum in Monkeys: Implications for Signal Propagation

MPG-Autoren
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;

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/persons84733

Oeltermann,  A
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Zitation

Logothetis, N., Kayser, C., & Oeltermann, A. (2007). In Vivo Measurement of Cortical Impedance Spectrum in Monkeys: Implications for Signal Propagation. Neuron, 55(5), 809-823. doi:10.1016/j.neuron.2007.07.027.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0013-CBB9-B
Zusammenfassung
To combine insights obtained from electric field potentials (LFP) and neuronal spiking activity (MUA) we need a better understanding of the relative spatial summation of these indices of neuronal activity. Compared to MUA, the LFP has greater spatial coherence, resulting in lower spatial specificity and lower stimulus selectivity. A differential propagation of low- and high-frequency electric signals supposedly underlies this phenomenon, which could result from cortical tissue specifically attenuating higher frequencies, i.e. from a frequency-dependent impedance spectrum. Here we directly measure the cortical impedance spectrum in vivo in monkey primary visual cortex. Our results show that impedance is independent of frequency, is homogeneous, tangentially isotropic within gray matter and can be theoretically predicted assuming a pure-resistive conductor. We propose that the spatial summation of LFP and MUA is determined by the size of these signals’ generators and the nature of neural events underlying them , rather than by biophysical properties of gray matter.