The Spatial Dimensions of Electrically Coupled Networks of Interneurons in the Neocortex

Brain Mapping Lysine Models, Neurological Action Potentials Gap Junctions Cell Count Neocortex Neural Inhibition Somatosensory Cortex In Vitro Techniques Immunohistochemistry Synaptic Transmission Rats Rats, Sprague-Dawley 03 medical and health sciences Parvalbumins 0302 clinical medicine Interneurons Animals Neural Networks, Computer Nerve Net Somatostatin
DOI: 10.1523/jneurosci.22-10-04142.2002 Publication Date: 2018-04-04T23:40:38Z
ABSTRACT
Inhibitory interneurons of the neocortex are electrically coupled to cells of the same type through gap junctions. We studied the spatial organization of two types of interneurons in the rat somatosensory cortex: fast-spiking (FS) parvalbumin-immunoreactive (PV+) cells, and low threshold-spiking (LTS) somatostatin-immunoreactive (SS+) cells. Paired recordings in layer 4 demonstrated that both the probability of coupling and the coupling coefficient drop steeply with intersomatic distance, reaching zero beyond 200 μm. The dendritic arbors of FS and LTS cells were reconstructed from electrophysiologically characterized, biocytin-filled cells; the two cell types had only minor differences in the number and span of their dendrites. However, there was a markedly higher density of PV+ cells than SS+ cells. PV+ cells were densest in layer 4, while SS+ cell density peaked in the subgranular layers. From these data we estimate that there is measurable electrical coupling (directly or indirectly via intermediary cells) between each interneuron and 20–50 others. The large number of electrical synapses implies that each interneuron participates in a large, continuous syncytium. To evaluate the functional significance of these findings, we examined several simple architectures of coupled networks analytically. We present a mathematical method to estimate the average summated coupling conductance that each cell receives from all of its neighbors, and the average leak conductance of individual cells, and we suggest that these have the same order of magnitude. These quantitative results have important implications for the effects of electrical coupling on the dynamic behavior of interneuron networks.
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