Abstract

Neocortical feedback is critical for attention, prediction, and learning. To mechanically understand its function requires deciphering its cell-type wiring. Recent studies revealed that feedback between primary motor to primary somatosensory areas in mice is disinhibitory, targeting vasoactive intestinal peptide-expressing interneurons, in addition to pyramidal cells. It is unknown whether this circuit motif represents a general cortico-cortical feedback organizing principle. Here we show that in contrast to this wiring rule, feedback between higher-order lateromedial visual area to primary visual cortex preferentially activates somatostatin-expressing interneurons. Functionally, both feedback circuits temporally sharpen feed-forward excitation eliciting a transient increase–followed by a prolonged decrease–in pyramidal cell activity under sustained feed-forward input. However, under feed-forward transient input, the primary motor to primary somatosensory cortex feedback facilitates bursting while lateromedial area to primary visual cortex feedback increases time precision. Our findings argue for multiple cortico-cortical feedback motifs implementing different dynamic non-linear operations.

Cortical activity is modulated by an intricate network of feedforward and feedback connectivity. Here the authors demonstrate distinct organizational rules govern feedback projections from lateral medial area to V1 versus projections from vibrissal M1 to vibrissal S1.

Details

Title
Distinct organization of two cortico-cortical feedback pathways
Author
Shen, Shan 1 ; Jiang, Xiaolong 2   VIAFID ORCID Logo  ; Scala, Federico 1 ; Fu, Jiakun 1 ; Fahey, Paul 1   VIAFID ORCID Logo  ; Kobak, Dmitry 3   VIAFID ORCID Logo  ; Tan, Zhenghuan 1 ; Zhou, Na 1 ; Reimer, Jacob 1 ; Sinz, Fabian 4 ; Tolias, Andreas S. 5   VIAFID ORCID Logo 

 Baylor College of Medicine, Center for Neuroscience and Artificial Intelligence, Houston, USA (GRID:grid.39382.33) (ISNI:0000 0001 2160 926X); Baylor College of Medicine, Department of Neuroscience, Houston, USA (GRID:grid.39382.33) (ISNI:0000 0001 2160 926X) 
 Baylor College of Medicine, Center for Neuroscience and Artificial Intelligence, Houston, USA (GRID:grid.39382.33) (ISNI:0000 0001 2160 926X); Baylor College of Medicine, Department of Neuroscience, Houston, USA (GRID:grid.39382.33) (ISNI:0000 0001 2160 926X); Jan and Dan Duncan Neurological Research Institute at Texas Children’s Hospital, Houston, USA (GRID:grid.416975.8) (ISNI:0000 0001 2200 2638) 
 University of Tübingen, Institute for Ophthalmic Research, Tübingen, Germany (GRID:grid.10392.39) (ISNI:0000 0001 2190 1447) 
 Baylor College of Medicine, Center for Neuroscience and Artificial Intelligence, Houston, USA (GRID:grid.39382.33) (ISNI:0000 0001 2160 926X); Baylor College of Medicine, Department of Neuroscience, Houston, USA (GRID:grid.39382.33) (ISNI:0000 0001 2160 926X); University of Tübingen, Bernstein Center for Computational Neuroscience, Tübingen, Germany (GRID:grid.10392.39) (ISNI:0000 0001 2190 1447); University of Tübingen, Institute for Bioinformatics and Medical Informatics, Tübingen, Germany (GRID:grid.10392.39) (ISNI:0000 0001 2190 1447) 
 Baylor College of Medicine, Center for Neuroscience and Artificial Intelligence, Houston, USA (GRID:grid.39382.33) (ISNI:0000 0001 2160 926X); Baylor College of Medicine, Department of Neuroscience, Houston, USA (GRID:grid.39382.33) (ISNI:0000 0001 2160 926X); Rice University, Department of Electrical and Computational Engineering, Houston, USA (GRID:grid.21940.3e) (ISNI:0000 0004 1936 8278) 
Publication year
2022
Publication date
2022
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2729316527
Copyright
© The Author(s) 2022. 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.