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Predicting stimulus-locked single unit spiking from cortical local field potentials.


ABSTRACT: The rapidly increasing use of the local field potential (LFP) has motivated research to better understand its relation to the gold standard of neural activity, single unit (SU) spiking. We addressed this in an in vivo, awake, restrained mouse auditory cortical electrophysiology preparation by asking whether the LFP could actually be used to predict stimulus-evoked SU spiking. Implementing a Bayesian algorithm to predict the likelihood of spiking on a trial by trial basis from different representations of the despiked LFP signal, we were able to predict, with high quality and fine temporal resolution (2 ms), the time course of a SU's excitatory or inhibitory firing rate response to natural species-specific vocalizations. Our best predictions were achieved by representing the LFP by its wide-band Hilbert phase signal, and approximating the statistical structure of this signal at different time points as independent. Our results show that each SU's action potential has a unique relationship with the LFP that can be reliably used to predict the occurrence of spikes. This "signature" interaction can reflect both pre- and post-spike neural activity that is intrinsic to the local circuit rather than just dictated by the stimulus. Finally, the time course of this "signature" may be most faithful when the full bandwidth of the LFP, rather than specific narrow-band components, is used for representation.

SUBMITTER: Galindo-Leon EE 

PROVIDER: S-EPMC2935517 | biostudies-literature | 2010 Dec

REPOSITORIES: biostudies-literature

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Predicting stimulus-locked single unit spiking from cortical local field potentials.

Galindo-Leon Edgar E EE   Liu Robert C RC  

Journal of computational neuroscience 20100209 3


The rapidly increasing use of the local field potential (LFP) has motivated research to better understand its relation to the gold standard of neural activity, single unit (SU) spiking. We addressed this in an in vivo, awake, restrained mouse auditory cortical electrophysiology preparation by asking whether the LFP could actually be used to predict stimulus-evoked SU spiking. Implementing a Bayesian algorithm to predict the likelihood of spiking on a trial by trial basis from different represent  ...[more]

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