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1 Institute for Theoretical Biology, Humboldt-University Berlin, D-10115 Berlin, Germany
2 Institute for Theoretical Biology, Humboldt-University Berlin, D-10115 Berlin, Germany; Johannes Mueller Institute for Physiology, Charite, D-10117 Berlin, Germany; Unite de Neurosciences Integratives et Computationnelles, Institut de Neurobiologie Alfred Fessard, F-91198 Gif-sur-Ivette, France
3 Johannes Mueller Institute for Physiology, Charite, D-10117 Berlin, Germany
* To whom correspondence should be addressed. E-mail: s.schreiber{at}biologie.hu-berlin.de.
Neurons integrate subthreshold inputs in a frequency-dependent manner. For sinusoidal stimuli, response amplitudes thus vary with stimulus frequency. Neurons in entorhinal cortex show two types of such resonance behavior: Stellate cells in layer II exhibit a prominent peak in the resonance profile at stimulus frequencies of 5-16 Hz. Pyramidal cells in layer III show only a small impedance peak at low frequencies (1-5 Hz) or a maximum at 0 Hz followed by a monotonic decrease of the impedance. Whether the specific frequency selectivity for periodic stimuli also governs the integration of non-periodic stimuli has been questioned recently. Using frozen-noise stimuli with different distributions of power over frequencies, we provide experimental evidence that the integration of non-periodic subthreshold stimuli is determined by the same subthreshold frequency selectivity as that of periodic stimuli. Differences between the integration of noise stimuli in stellate and pyramidal cells can be fully explained by the resonance properties of each cell type. Response power thus reflects stimulus power in a frequency-selective way. Theoretical predictions based on linear system's theory as well as on conductance-based model neurons support this hypothesis. We also find that the frequency selectivity in the subthreshold range extends to suprathreshold responses in terms of firing rate. Cells in entorhinal cortex are representative examples of cells with resonant or low-pass filter impedance profiles. It is therefore likely that neurons with similar frequency selectivity will process input signals according to the same simple principles.
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