Decoupling action potential bias from cortical local field potentials

Stephen David, Nicolas Malaval, Shihab A. Shamma

Research output: Contribution to journalArticle

16 Citations (Scopus)

Abstract

Neurophysiologists have recently become interested in studying neuronal population activity through local field potential (LFP) recordings during experiments that also record the activity of single neurons. This experimental approach differs from early LFP studies because it uses high impendence electrodes that can also isolate single neuron activity. A possible complication for such studies is that the synaptic potentials and action potentials of the small subset of isolated neurons may contribute disproportionately to the LFP signal, biasing activity in the larger nearby neuronal population to appear synchronous and cotuned with these neurons. To address this problem, we used linear filtering techniques to remove features correlated with spike events from LFP recordings. This filtering procedure can be applied for well-isolated single units or multiunit activity. We illustrate the effects of this correction in simulation and on spike data recorded from primary auditory cortex. We find that local spiking activity can explain a significant portion of LFP power at most recording sites and demonstrate that removing the spike-correlated component can affect measurements of auditory tuning of the LFP.

Original languageEnglish (US)
Article number393019
JournalComputational Intelligence and Neuroscience
Volume2010
DOIs
StatePublished - 2010
Externally publishedYes

Fingerprint

Action Potential
Local Field
Decoupling
Action Potentials
Neurons
Neuron
Spike
Synaptic Potentials
Auditory Cortex
Population
Linear Filtering
Electrodes
Tuning
Cortex
Complications
Electrode
Filtering
Unit
Subset
Experiments

ASJC Scopus subject areas

  • Computer Science(all)
  • Mathematics(all)
  • Neuroscience(all)

Cite this

Decoupling action potential bias from cortical local field potentials. / David, Stephen; Malaval, Nicolas; Shamma, Shihab A.

In: Computational Intelligence and Neuroscience, Vol. 2010, 393019, 2010.

Research output: Contribution to journalArticle

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