Abstract

Layer 4 (L4) of mammalian neocortex plays a crucial role in cortical information processing, yet a complete census of its cell types and connectivity remains elusive. Using whole-cell recordings with morphological recovery, we identified one major excitatory and seven inhibitory types of neurons in L4 of adult mouse visual cortex (V1). Nearly all excitatory neurons were pyramidal and all somatostatin-positive (SOM+) non-fast-spiking interneurons were Martinotti cells. In contrast, in somatosensory cortex (S1), excitatory neurons were mostly stellate and SOM+ interneurons were non-Martinotti. These morphologically distinct SOM+ interneurons corresponded to different transcriptomic cell types and were differentially integrated into the local circuit with only S1 neurons receiving local excitatory input. We propose that cell type specific circuit motifs, such as the Martinotti/pyramidal and non-Martinotti/stellate pairs, are used across the cortex as building blocks to assemble cortical circuits.

Details

Title
Layer 4 of mouse neocortex differs in cell types and circuit organization between sensory areas
Author
Scala, Federico 1 ; Kobak, Dmitry 2   VIAFID ORCID Logo  ; Shen, Shan 1   VIAFID ORCID Logo  ; Bernaerts, Yves 2 ; Laturnus, Sophie 2 ; Cadwell, Cathryn Rene 3   VIAFID ORCID Logo  ; Hartmanis, Leonard 4 ; Froudarakis, Emmanouil 1   VIAFID ORCID Logo  ; Jesus Ramon Castro 1 ; Zheng Huan Tan 1 ; Papadopoulos, Stelios 1 ; Patel, Saumil Surendra 1 ; Sandberg, Rickard 4   VIAFID ORCID Logo  ; Berens, Philipp 5   VIAFID ORCID Logo  ; Jiang, Xiaolong 6 ; Andreas Savas Tolias 7   VIAFID ORCID Logo 

 Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA; Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA 
 Institute for Ophthalmic Research, University of Tübingen, Tübingen, Germany 
 Department of Anatomic Pathology, University of California San Francisco, San Francisco, CA, USA 
 Department of Cell and Molecular Biology, Karolinska Institutet, Stockholm, Sweden 
 Institute for Ophthalmic Research, University of Tübingen, Tübingen, Germany; Department of Computer Science, University of Tübingen, Tübingen, Germany 
 Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA; Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA; Jan and Dan Duncan Neurological Research Institute at Texas Children’s Hospital, Houston, TX, USA 
 Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA; Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA; Department of Electrical and Computational Engineering, Rice University, Houston, TX, USA 
Pages
1-12
Publication year
2019
Publication date
Sep 2019
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2290064832
Copyright
© 2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.