Inter- and intra-animal variation in the integrative properties of stellate cells in the medial entorhinal cortex.

Hugh Pastoll,Derek L Garden,Gülşen Sürmeli,Matthew F Nolan,Ioannis Papastathopoulos

doi:10.7554/elife.52258

Abstract

Distinctions between cell types underpin organizational principles for nervous system function. Functional variation also exists between neurons of the same type. This is exemplified by correspondence between grid cell spatial scales and the synaptic integrative properties of stellate cells (SCs) in the medial entorhinal cortex. However, we know little about how functional variability is structured either within or between individuals. Using ex-vivo patch-clamp recordings from up to 55 SCs per mouse, we found that integrative properties vary between mice and, in contrast to the modularity of grid cell spatial scales, have a continuous dorsoventral organization. Our results constrain mechanisms for modular grid firing and provide evidence for inter-animal phenotypic variability among neurons of the same type. We suggest that neuron type properties are tuned to circuit-level set points that vary within and between animals.

Highlights

The concept of cell types provides a general organising principle for understanding biological structures including the brain (Regev et al, 2017; Zeng and Sanes, 2017)
Because tests of whether data arise from modular as opposed to continuous distributions have received less general attention, to facilitate detection of modularity using relatively few observations we introduce a modification of the gap statistic algorithm (Tibshirani et al, 2001)that estimates the number of modes in a dataset while controlling for observations expected by chance
Our results suggest that set points for individual features of a neuronal cell type are established at a population level, differ between animals and follow a continuous organisation

Summary

Introduction

The concept of cell types provides a general organising principle for understanding biological structures including the brain (Regev et al, 2017; Zeng and Sanes, 2017). Correlations between the functional organisation of sensory, motor and cognitive circuits and electrophysiological properties of individual neuronal cell types suggest that this feature variability underlies key neural computations (Adamson et al, 2002; Angelo et al, 2012; Fletcher and Williams, 2018; Garden et al, 2008; Giocomo et al, 2007; Kuba et al, 2005; O’Donnell and Nolan, 2011). Apparent clustering of properties along lines in feature space could reflect a continuum of set points, or could result from a small number of discrete set points that are obscured by inter-animal variation (Figure 1B).

Methods

Results

Conclusion