Anatomical and Electrophysiological Clustering of Superficial Medial Entorhinal Cortex Interneurons

Abstract

Local GABAergic interneurons regulate the activity of spatially-modulated principal cells in the medial entorhinal cortex (MEC), mediating stellate-to-stellate connectivity and possibly enabling grid formation via recurrent inhibitory circuitry. Despite the important role interneurons seem to play in the MEC cortical circuit, the combination of low cell counts and functional diversity has made systematic electrophysiological studies of these neurons difficult. For these reasons, there remains a paucity of knowledge on the electrophysiological profiles of superficial MEC interneuron populations. Taking advantage of glutamic acid decarboxylase 2 (GAD2)-IRES-tdTomato and PV-tdTomato transgenic mice, we targeted GABAergic interneurons for whole-cell patch-clamp recordings and characterized their passive membrane features, basic input/output properties and action potential (AP) shape. These electrophysiologically characterized cells were then anatomically reconstructed, with emphasis on axonal projections and pial depth. K-means clustering of interneuron anatomical and electrophysiological data optimally classified a population of 106 interneurons into four distinct clusters. The first cluster is comprised of layer 2- and 3-projecting, slow-firing interneurons. The second cluster is comprised largely of PV+ fast-firing interneurons that project mainly to layers 2 and 3. The third cluster contains layer 1- and 2-projecting interneurons, and the fourth cluster is made up of layer 1-projecting horizontal interneurons. These results, among others, will provide greater understanding of the electrophysiological characteristics of MEC interneurons, help guide future in vivo studies, and may aid in uncovering the mechanism of grid field formation.

A Corticothalamic Circuit for Refining Tactile Encoding

“…The Gad2-cre mouse line was used to target ChR2-expression to GABAergic interneurons, to thus achieve a non-specific activation of GABAergic interneurons. (Katzel et al, 2011, Taniguchi et al, 2011, Harris et al, 2014, Martinez et al, 2017. Virus mediated expression of ChR2-mCherry in the BC showed bright fluorescence from somata and neuropil in all layers of BC ( Figure 3F and Figure S9).…”

Shunting Inhibition Improves Synchronization in Heterogeneous Inhibitory Interneuronal Networks with Type 1 Excitability Whereas Hyperpolarizing Inhibition Is Better for Type 2 Excitability

“…However, within regions, the excitability type of FS interneurons seems to be consistent. For example, all FS cells in the striatum (Sciamanna and Wilson, 2011) and MEC (Martínez et al, 2017) appear to be type 2, whereas those in CA1 (Wang and Buzsáki, 1996;Ferguson et al, 2013) and dentate gyrus (Vida et al, 2006) seem to be uniformly type 1. Therefore, we compared networks of uniform excitability type within the network.…”

“…We varied the slope of the f/I curve for type 1 neurons and both the cutoff frequency and slope for the type2 neurons by rescaling the temporal dynamics. The cutoff frequency for fast spiking PV+ basket cells (Martínez et al, 2017) had an estimated standard deviation of 40%. Thus, the 10-60 Hz range in cutoff frequencies explored should map onto biologically plausible distributions of cutoff frequencies.…”

Morphological Cell Types Projecting from V1 Layer 4B to V2 Thick and Thin Stripes

“…The software uses a convex hull analysis to quantify dendritic field perimeter and area, and computes dendritic complexity according the following formula: (Sum of the terminal orders ϩ Number of terminals) ϫ (Dendritic length/ Number of primary dendrites). Because of the mathematical relationships between some variables (e.g., soma area and soma perimeter), and correlations between all variables, we used principal component analysis (PCA) to control for correlations in the dataset, and to investigate factors that may be driving differences between samples in an unbiased way (Martínez et al, 2017). Stellate and pyramidal cells were analyzed separately, although combining all data yielded very similar results.…”