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01.10.2014 | Ausgabe 2/2014 Open Access

Journal of Computational Neuroscience 2/2014

Impact of correlated inputs to neurons: modeling observations from in vivo intracellular recordings

Zeitschrift:
Journal of Computational Neuroscience > Ausgabe 2/2014
Autoren:
Man Yi Yim, Arvind Kumar, Ad Aertsen, Stefan Rotter
Wichtige Hinweise
Action Editor: Alain Destexhe
The present work was supported by the German Federal Ministry of Education and Research (BMBF Grant No. 01GQ0420 to “BCCN Freiburg” and BMBF Grant No. 01GW0730 “Impulse Control”) and the EU (INTERREG-V Grant to Neurex: TriNeuron)
An erratum to this article can be found at http://​dx.​doi.​org/​10.​1007/​s10827-014-0509-5.

Conflict of interest

The authors declare that they have no conflict of interest.

Abstract

In vivo recordings in rat somatosensory cortex suggest that excitatory and inhibitory inputs are often correlated during spontaneous and sensory-evoked activity. Using a computational approach, we study how the interplay of input correlations and timing observed in experiments controls the spiking probability of single neurons. Several correlation-based mechanisms are identified, which can effectively switch a neuron on and off. In addition, we investigate the transfer of input correlation to output correlation in pairs of neurons, at the spike train and the membrane potential levels, by considering spike-driving and non-spike-driving inputs separately. In particular, we propose a plausible explanation for the in vivo finding that membrane potentials in neighboring neurons are correlated, but the spike-triggered averages of membrane potentials preceding a spike are not: Neighboring neurons possibly receive an ongoing bombardment of correlated subthreshold background inputs, and occasionally uncorrelated spike-driving inputs.
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