Sparse recurrent excitatory connectivity in the microcircuit of the adult mouse and human cortex.

Stephanie C Seeman ,Alex Hoggarth,Tim Jarsky,Charles Cobbs,Christof Koch,Alice Bosma-Moody,Ed Lein,Hongkui Zeng,Pasha A Davoudian,Corinne Teeter,Luke Campagnola,Jung H Lee ,Jeffrey G Ojemann ,Ştefan Mihalaş ,Ryder P Gwinn ,Travis A Hage ,John W Phillips ,Andrew L Ko ,Gabe J Murphy ,Daniel L Silbergeld ,Christopher A Baker

doi:10.7554/elife.37349

Abstract

Generating a comprehensive description of cortical networks requires a large-scale, systematic approach. To that end, we have begun a pipeline project using multipatch electrophysiology, supplemented with two-photon optogenetics, to characterize connectivity and synaptic signaling between classes of neurons in adult mouse primary visual cortex (V1) and human cortex. We focus on producing results detailed enough for the generation of computational models and enabling comparison with future studies. Here, we report our examination of intralaminar connectivity within each of several classes of excitatory neurons. We find that connections are sparse but present among all excitatory cell classes and layers we sampled, and that most mouse synapses exhibited short-term depression with similar dynamics. Synaptic signaling between a subset of layer 2/3 neurons, however, exhibited facilitation. These results contribute to a body of evidence describing recurrent excitatory connectivity as a conserved feature of cortical microcircuits.

Highlights

Generating well-informed, testable hypotheses about how the cortex represents and processes information requires experimental efforts to characterize the connectivity and dynamics of cortical circuit elements as well as efforts to build models that integrate results across studies (Sejnowski et al, 1988)
Using a novel automated method for systematically estimating connectivity across experiments, we further demonstrate that different populations of adult mouse pyramidal neurons exhibit characteristic distance-dependent connectivity profiles and short-term dynamics
Most excitatory recurrent connections in mouse cortex were dominated by short-term synaptic depression

Summary

Introduction

Generating well-informed, testable hypotheses about how the cortex represents and processes information requires experimental efforts to characterize the connectivity and dynamics of cortical circuit elements as well as efforts to build models that integrate results across studies (Sejnowski et al, 1988). This variability limits our ability to generate accurate, integrative computational models Addressing this problem requires standardized experimental methods and large-scale data collection in order to characterize synaptic connections between the large number of potential cell types (Tasic et al, 2016). In the upper layers of mouse cortex, the opposite effect is sometimes seen: more excitatory activity causes the connections to generate stronger responses By feeding these data into a computer model, Seeman, Campagnola et al described and compared the activity of the groups of related excitatory cell types. These results are the first of a new, large-scale project where findings can be integrated across experiments to gain a more detailed picture of cortical circuitry and computation. We quantify and compare differences in short-term dynamics with a mechanistic computational model

Results

Discussion

Materials and methods

Funding Funder National Institutes of Health