A midbrain-thalamus-cortex circuit reorganizes cortical dynamics to initiate movement

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Summary

Motor behaviors are often planned long before execution, but only released after specific sensory events. Planning and execution are each associated with distinct patterns of motor cortex activity. Key questions are how these dynamic activity patterns are generated and how they relate to behavior. Here we investigate the multi-regional neural circuits that link an auditory ‘go cue’ and the transition from planning to execution of directional licking. Ascending glutamatergic neurons in the midbrain reticular and pedunculopontine nuclei show short-latency and phasic changes in spike rate that are selective for the go cue. This signal is transmitted via the thalamus to the motor cortex, where it triggers a rapid reorganization of motor cortex state from planning-related activity to a motor command, which in turn drives appropriate movement. Our studies show how midbrain can control cortical dynamics via the thalamus for rapid and precise motor behavior.

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Ascending midbrain neurons trigger rapid reorganization of motor cortex activity via thalamus to switch from planning-related activity to a motor command that initiates movement in mice

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DeepLabCut: markerless pose estimation of user-defined body parts with deep learning

Pranav Mamidanna, Venkatesh N. Murthy, Mackenzie Weygandt Mathis … (2018)

Quantifying behavior is crucial for many applications in neuroscience. Videography provides easy methods for the observation and recording of animal behavior in diverse settings, yet extracting particular aspects of a behavior for further analysis can be highly time consuming. In motor control studies, humans or other animals are often marked with reflective markers to assist with computer-based tracking, but markers are intrusive, and the number and location of the markers must be determined a priori. Here we present an efficient method for markerless pose estimation based on transfer learning with deep neural networks that achieves excellent results with minimal training data. We demonstrate the versatility of this framework by tracking various body parts in multiple species across a broad collection of behaviors. Remarkably, even when only a small number of frames are labeled (~200), the algorithm achieves excellent tracking performance on test frames that is comparable to human accuracy.

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A mesoscale connectome of the mouse brain.

Seung Wook Oh, Julie Harris, Lydia Ng … (2014)

Comprehensive knowledge of the brain's wiring diagram is fundamental for understanding how the nervous system processes information at both local and global scales. However, with the singular exception of the C. elegans microscale connectome, there are no complete connectivity data sets in other species. Here we report a brain-wide, cellular-level, mesoscale connectome for the mouse. The Allen Mouse Brain Connectivity Atlas uses enhanced green fluorescent protein (EGFP)-expressing adeno-associated viral vectors to trace axonal projections from defined regions and cell types, and high-throughput serial two-photon tomography to image the EGFP-labelled axons throughout the brain. This systematic and standardized approach allows spatial registration of individual experiments into a common three dimensional (3D) reference space, resulting in a whole-brain connectivity matrix. A computational model yields insights into connectional strength distribution, symmetry and other network properties. Virtual tractography illustrates 3D topography among interconnected regions. Cortico-thalamic pathway analysis demonstrates segregation and integration of parallel pathways. The Allen Mouse Brain Connectivity Atlas is a freely available, foundational resource for structural and functional investigations into the neural circuits that support behavioural and cognitive processes in health and disease.

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A resource of Cre driver lines for genetic targeting of GABAergic neurons in cerebral cortex.

Hiroki Taniguchi, Miao He, Priscilla Wu … (2011)

A key obstacle to understanding neural circuits in the cerebral cortex is that of unraveling the diversity of GABAergic interneurons. This diversity poses general questions for neural circuit analysis: how are these interneuron cell types generated and assembled into stereotyped local circuits and how do they differentially contribute to circuit operations that underlie cortical functions ranging from perception to cognition? Using genetic engineering in mice, we have generated and characterized approximately 20 Cre and inducible CreER knockin driver lines that reliably target major classes and lineages of GABAergic neurons. More select populations are captured by intersection of Cre and Flp drivers. Genetic targeting allows reliable identification, monitoring, and manipulation of cortical GABAergic neurons, thereby enabling a systematic and comprehensive analysis from cell fate specification, migration, and connectivity, to their functions in network dynamics and behavior. As such, this approach will accelerate the study of GABAergic circuits throughout the mammalian brain. Copyright © 2011 Elsevier Inc. All rights reserved.

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Author and article information

Journal

Journal ID (nlm-journal-id): 0413066

Journal ID (pubmed-jr-id): 2830

Journal ID (nlm-ta): Cell

Journal ID (iso-abbrev): Cell

Title: Cell

ISSN (Print): 0092-8674

ISSN (Electronic): 1097-4172

Publication date Nihms-submitted: 16 March 2022

Publication date (Print): 17 March 2022

Publication date (Electronic): 03 March 2022

Publication date PMC-release: 17 March 2023

Volume: 185

Issue: 6

Pages: 1065-1081.e23

Affiliations

[1 ] Janelia Research Campus, HHMI, Ashburn, VA, 20147, USA.

[2 ] Max Planck Florida Institute for Neuroscience, Jupiter, FL, 33458, USA.

[3 ] Department of Neuroscience, Physiology, and Pharmacology, University College London, London WC1E 6BT, UK.

[4 ] Queensland Brain Institute, The University of Queensland, Brisbane, QLD, 4072, Australia.

[5 ] Joint Center for Neuroscience and Neural Engineering, and Department of Biology, Southern University of Science and Technology, Shenzhen, Guangdong Province, 518055, P. R. China.

[6 ] Department of Neuroscience, Baylor College of Medicine, Houston, TX, 77030, USA.

[7 ] Department of Neuroscience, Erasmus MC, Rotterdam, 3015GE, The Netherlands.

[8 ] National Institute of Mental Health, Bethesda, MD, 20892, USA.

[9 ] Allen Institute for Neural Dynamics, Seattle, WA, 98109, USA.

[10 ] These authors contributed equally.

[11 ] Lead contact.

Author notes

Author contributions

H.K.I. and K.S. planned the study. H.K.I. and S.C. performed experiments. H.K.I. analyzed data with S.C., K.S. and Z.Y. M.R. and P.S. performed slice recordings. C.G., H.H., and Z.G. performed histology. N.L. provided DCN data. H.K.I. and K.S. wrote the paper, with input from all the authors.

[* ]Correspondence: hidehiko.inagaki@ 123456mpfi.org or karel.svoboda@ 123456alleninstitute.org

Article

Manuscript ID: NIHMS1784450

DOI: 10.1016/j.cell.2022.02.006

PMC ID: 8990337

PubMed ID: 35245431

SO-VID: 2585dcd6-7318-423c-8489-53229ceba2e2

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This work is licensed under a Creative Commons Attribution 4.0 International License, which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.

A midbrain-thalamus-cortex circuit reorganizes cortical dynamics to initiate movement

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Evolutionary Cell Biology

Most cited references 122

DeepLabCut: markerless pose estimation of user-defined body parts with deep learning

A mesoscale connectome of the mouse brain.

A resource of Cre driver lines for genetic targeting of GABAergic neurons in cerebral cortex.

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