Characterizing interneuron and pyramidal cells in the human medial temporal lobe in vivo using extracellular recordings

Indre V. Viskontas, Arne D. Ekstrom, Charles L. Wilson, Itzhak Fried

Research output: Contribution to journalArticlepeer-review

49 Scopus citations


The goal of this study was to characterize the electrophysiological features of single neurons recorded deep within the medial temporal lobes in humans. Using three physiological criteria to distinguish principal cells and interneurons (firing rate, burst propensity, and action potential waveform) and a large data set of human single neurons (585) from thirteen patients, we show that single neurons in the human MTL separate into two distinct classes comparable to the pyramidal cell and interneuron classes described in animals. We also find that the four different MTL brain regions that we examined (amygdala, hippocampus, entorhinal cortex, and posterior parahippocampal cortex) show unique action potential characteristics, which may in turn relate to the role that neurons from these regions play in behavior. A subset of cells were recorded while patients engaged in both slow-wave (SWS) and rapid-eye movement (REM) sleep and a comparison of the electrophysiological features during these different sleep stages showed that interneurons tended to burst more during SWS compared to REM, while only principal cells in the EC and hippocampus showed a greater propensity for bursting during SWS. Together, our results support the idea that human single neurons have electrophysiologically identifiable cell types, similar to those observed in other mammals, and provide insight into regional and functional differences in spike-wave characteristics relevant to considerations about neural populations in the human brain.

Original languageEnglish (US)
Pages (from-to)49-57
Number of pages9
Issue number1
StatePublished - 2007
Externally publishedYes


  • Action potential
  • Depth electrode
  • Epilepsy
  • Hippocampus

ASJC Scopus subject areas

  • Cognitive Neuroscience


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