TY - JOUR
T1 - Spatiotemporal dynamics of neocortical excitation and inhibition during human sleep
AU - Peyrache, Adrien
AU - Dehghani, Nima
AU - Eskandar, Emad N.
AU - Madsen, Joseph R.
AU - Anderson, William S.
AU - Donoghue, Jacob A.
AU - Hochberg, Leigh R.
AU - Halgren, Eric
AU - Cash, Sydney S.
AU - Destexhe, Alain
PY - 2012/1/31
Y1 - 2012/1/31
N2 - Intracranial recording is an important diagnostic method routinely used in a number of neurological monitoring scenarios. In recent years, advancements in such recordings have been extended to include unit activity of an ensemble of neurons. However, a detailed functional characterization of excitatory and inhibitory cells has not been attempted in human neocortex, particularly during the sleep state. Here, we report that such feature discrimination is possible from high-density recordings in the neocortex by using 2D multielectrode arrays. Successful separation of regular-spiking neurons (or bursting cells) from fast-spiking cells resulted inwell-defined clusters that each showed unique intrinsic firing properties. The high density of the array, which allowed recording from a large number of cells (up to 90), helped us to identify apparentmonosynaptic connections, confirming the excitatory and inhibitory nature of regular-spiking and fast-spiking cells, thus categorized as putative pyramidal cells and interneurons, respectively. Finally,we investigated the dynamics of correlations within each class. A marked exponential decay with distancewas observed in the case of excitatory but not for inhibitory cells. Although the amplitude of that decline depended on the timescale at which the correlations were computed, the spatial constant did not. Furthermore, this spatial constant is compatible with the typical size of human columnar organization. These findings provide a detailed characterization of neuronal activity, functional connectivity at the microcircuit level, and the interplay of excitation and inhibition in the human neocortex.
AB - Intracranial recording is an important diagnostic method routinely used in a number of neurological monitoring scenarios. In recent years, advancements in such recordings have been extended to include unit activity of an ensemble of neurons. However, a detailed functional characterization of excitatory and inhibitory cells has not been attempted in human neocortex, particularly during the sleep state. Here, we report that such feature discrimination is possible from high-density recordings in the neocortex by using 2D multielectrode arrays. Successful separation of regular-spiking neurons (or bursting cells) from fast-spiking cells resulted inwell-defined clusters that each showed unique intrinsic firing properties. The high density of the array, which allowed recording from a large number of cells (up to 90), helped us to identify apparentmonosynaptic connections, confirming the excitatory and inhibitory nature of regular-spiking and fast-spiking cells, thus categorized as putative pyramidal cells and interneurons, respectively. Finally,we investigated the dynamics of correlations within each class. A marked exponential decay with distancewas observed in the case of excitatory but not for inhibitory cells. Although the amplitude of that decline depended on the timescale at which the correlations were computed, the spatial constant did not. Furthermore, this spatial constant is compatible with the typical size of human columnar organization. These findings provide a detailed characterization of neuronal activity, functional connectivity at the microcircuit level, and the interplay of excitation and inhibition in the human neocortex.
KW - Ensemble recordings
KW - Functional dynamics
KW - Single unit
KW - Spontaneous activity
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U2 - 10.1073/pnas.1109895109
DO - 10.1073/pnas.1109895109
M3 - Article
C2 - 22307639
AN - SCOPUS:84857132925
SN - 0027-8424
VL - 109
SP - 1731
EP - 1736
JO - Proceedings of the National Academy of Sciences of the United States of America
JF - Proceedings of the National Academy of Sciences of the United States of America
IS - 5
ER -