scholarly journals Cell-Type-Specific Outcome Representation in the Primary Motor Cortex

Neuron ◽  
2020 ◽  
Vol 107 (5) ◽  
pp. 954-971.e9 ◽  
Author(s):  
Shahar Levy ◽  
Maria Lavzin ◽  
Hadas Benisty ◽  
Amir Ghanayim ◽  
Uri Dubin ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Primary Motor Cortex ◽  
Cell Type ◽  
Specific Outcome ◽  
Cell Type Specific

scholarly journals Multiscale Co-Expression in the Brain

2020 ◽  
Author(s):  
Benjamin D. Harris ◽  
Megan Crow ◽  
Stephan Fischer ◽  
Jesse Gillis
Keyword(s):  
Motor Cortex ◽  
Single Cell ◽  
Rna Sequencing ◽  
Primary Motor Cortex ◽  
Cell Types ◽  
Cell Type ◽  
Single Cell Rna Sequencing ◽  
Cell Type Specific ◽  
The Brain ◽  
Regulatory Landscape

ABSTRACTSingle-cell RNA-sequencing (scRNAseq) data can reveal co-regulatory relationships between genes that may be hidden in bulk RNAseq due to cell type confounding. Using the primary motor cortex data from the Brain Initiative Cell Census Network (BICCN), we study cell type specific co-expression across 500,000 cells. Surprisingly, we find that the same gene-gene relationships that differentiate cell types are evident at finer and broader scales, suggesting a consistent multiscale regulatory landscape.

scholarly journals Cell-type specific outcome representation in primary motor cortex

2020 ◽  
Author(s):  
Maria Lavzin ◽  
Shahar Levy ◽  
Hadas Benisty ◽  
Uri Dubin ◽  
Zohar Brosh ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Memory Trace ◽  
Primary Motor Cortex ◽  
Initial State ◽  
Task Requirements ◽  
Specific Performance ◽  
Specific Outcome ◽  
Cell Type Specific ◽  
The Brain ◽  
Two Populations

AbstractAdaptive movements are critical to animal survival. To guide future actions, the brain monitors different outcomes, including achievement of movement and appetitive goals. The nature of outcome signals and their neuronal and network realization in motor cortex (M1), which commands the performance of skilled movements, is largely unknown. Using a dexterity task, calcium imaging, optogenetic perturbations, and behavioral manipulations, we studied outcome signals in murine M1. We find two populations of layer 2-3 neurons, “success”- and “failure” related neurons that develop with training and report end-result of trials. In these neurons, prolonged responses were recorded after success or failure trials, independent of reward and kinematics. In contrast, the initial state of layer-5 pyramidal tract neurons contains a memory trace of the previous trial’s outcome. Inter-trial cortical activity was needed to learn new task requirements. These M1 reflective layer-specific performance outcome signals, can support reinforcement motor learning of skilled behavior.

scholarly journals Cell-Type Specific Responses to Associative Learning in the Primary Motor Cortex

2021 ◽  
Author(s):  
Candice Lee ◽  
Emerson Harkin ◽  
Richard Naud ◽  
Simon Chen
Keyword(s):  
Motor Cortex ◽  
Associative Learning ◽  
Primary Motor Cortex ◽  
Neuronal Cell ◽  
Cell Types ◽  
Skill Learning ◽  
Cell Type ◽  
Movement Initiation ◽  
Response Properties ◽  
Cell Type Specific

The primary motor cortex (M1) is known to be a critical site for movement initiation and motor learning. Surprisingly, it has also been shown to possess reward-related activity, presumably to facilitate reward-based learning of new movements. However, whether reward-related signals are represented among different cell types in M1, and whether their response properties change after cue-reward conditioning remains unclear. Here, we performed longitudinal in vivo two-photon Ca2+ imaging to monitor the activity of different neuronal cell types in M1 while mice engaged in a classical conditioning task. Our results demonstrate that most of the major neuronal cell types in M1 showed robust but differential responses to both cue and reward stimuli, and their response properties undergo cell-type specific modifications after associative learning. PV-INs' responses became more reliable to the cue stimulus, while VIP-INs' responses became more reliable to the reward stimulus. PNs only showed robust response to the novel reward stimulus, and they habituated to it after associative learning. Lastly, SOM-IN responses emerged and became more reliable to both conditioned cue and reward stimuli after conditioning. These observations suggest that cue- and reward-related signals are represented among different neuronal cell types in M1, and the distinct modifications they undergo during associative learning could be essential in triggering different aspects of local circuit reorganization in M1 during reward-based motor skill learning.

scholarly journals Comparative cellular analysis of motor cortex in human, marmoset and mouse

Nature ◽  
2021 ◽  
Vol 598 (7879) ◽  
pp. 111-119 ◽  
Author(s):  
Trygve E. Bakken ◽  
Nikolas L. Jorstad ◽  
Qiwen Hu ◽  
Blue B. Lake ◽  
Wei Tian ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Primary Motor Cortex ◽  
Neuronal Cell ◽  
Cell Types ◽  
Morphological Characterization ◽  
Fine Motor ◽  
Marker Genes ◽  
Cell Type ◽  
Regulatory Pathways ◽  
Cellular Analysis

AbstractThe primary motor cortex (M1) is essential for voluntary fine-motor control and is functionally conserved across mammals1. Here, using high-throughput transcriptomic and epigenomic profiling of more than 450,000 single nuclei in humans, marmoset monkeys and mice, we demonstrate a broadly conserved cellular makeup of this region, with similarities that mirror evolutionary distance and are consistent between the transcriptome and epigenome. The core conserved molecular identities of neuronal and non-neuronal cell types allow us to generate a cross-species consensus classification of cell types, and to infer conserved properties of cell types across species. Despite the overall conservation, however, many species-dependent specializations are apparent, including differences in cell-type proportions, gene expression, DNA methylation and chromatin state. Few cell-type marker genes are conserved across species, revealing a short list of candidate genes and regulatory mechanisms that are responsible for conserved features of homologous cell types, such as the GABAergic chandelier cells. This consensus transcriptomic classification allows us to use patch–seq (a combination of whole-cell patch-clamp recordings, RNA sequencing and morphological characterization) to identify corticospinal Betz cells from layer 5 in non-human primates and humans, and to characterize their highly specialized physiology and anatomy. These findings highlight the robust molecular underpinnings of cell-type diversity in M1 across mammals, and point to the genes and regulatory pathways responsible for the functional identity of cell types and their species-specific adaptations.

scholarly journals Target-specific M1 inputs to infragranular S1 pyramidal neurons

2016 ◽  
Vol 116 (3) ◽  
pp. 1261-1274 ◽  
Author(s):  
Amanda K. Kinnischtzke ◽  
Erika E. Fanselow ◽  
Daniel J. Simons
Keyword(s):  
Primary Motor Cortex ◽  
Pyramidal Neurons ◽  
Projection Neurons ◽  
Cell Type ◽  
Intrinsic Properties ◽  
Subcortical Structures ◽  
Medial Nucleus ◽  
Cell Type Specific ◽  
Posterior Medial Nucleus

The functional role of input from the primary motor cortex (M1) to primary somatosensory cortex (S1) is unclear; one key to understanding this pathway may lie in elucidating the cell-type specific microcircuits that connect S1 and M1. Recently, we discovered that a subset of pyramidal neurons in the infragranular layers of S1 receive especially strong input from M1 (Kinnischtzke AK, Simons DJ, Fanselow EE. Cereb Cortex 24: 2237–2248, 2014), suggesting that M1 may affect specific classes of pyramidal neurons differently. Here, using combined optogenetic and retrograde labeling approaches in the mouse, we examined the strengths of M1 inputs to five classes of infragranular S1 neurons categorized by their projections to particular cortical and subcortical targets. We found that the magnitude of M1 synaptic input to S1 pyramidal neurons varies greatly depending on the projection target of the postsynaptic neuron. Of the populations examined, M1-projecting corticocortical neurons in L6 received the strongest M1 inputs, whereas ventral posterior medial nucleus-projecting corticothalamic neurons, also located in L6, received the weakest. Each population also possessed distinct intrinsic properties. The results suggest that M1 differentially engages specific classes of S1 projection neurons, thereby regulating the motor-related influence S1 exerts over subcortical structures.

scholarly journals A multimodal cell census and atlas of the mammalian primary motor cortex

2020 ◽  
Author(s):  
◽  
Ricky S. Adkins ◽  
Andrew I. Aldridge ◽  
Shona Allen ◽  
Seth A. Ament ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Single Cell ◽  
Primary Motor Cortex ◽  
Spatial Information ◽  
Molecular Genetic ◽  
Cell Types ◽  
Developmental Trajectory ◽  
Open Chromatin ◽  
Cell Type ◽  
Spatially Resolved

ABSTRACTWe report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex (MOp or M1) as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties, and cellular resolution input-output mapping, integrated through cross-modal computational analysis. Together, our results advance the collective knowledge and understanding of brain cell type organization: First, our study reveals a unified molecular genetic landscape of cortical cell types that congruently integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a unified taxonomy of transcriptomic types and their hierarchical organization that are conserved from mouse to marmoset and human. Third, cross-modal analysis provides compelling evidence for the epigenomic, transcriptomic, and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types and subtypes. Fourth, in situ single-cell transcriptomics provides a spatially-resolved cell type atlas of the motor cortex. Fifth, integrated transcriptomic, epigenomic and anatomical analyses reveal the correspondence between neural circuits and transcriptomic cell types. We further present an extensive genetic toolset for targeting and fate mapping glutamatergic projection neuron types toward linking their developmental trajectory to their circuit function. Together, our results establish a unified and mechanistic framework of neuronal cell type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties.

scholarly journals A multimodal cell census and atlas of the mammalian primary motor cortex

Nature ◽  
2021 ◽  
Vol 598 (7879) ◽  
pp. 86-102 ◽  
Author(s):  
◽  
Edward M. Callaway ◽  
Hong-Wei Dong ◽  
Joseph R. Ecker ◽  
Michael J. Hawrylycz ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Single Cell ◽  
Primary Motor Cortex ◽  
Spatial Information ◽  
Molecular Genetic ◽  
Cortical Cell ◽  
Neuronal Cell ◽  
Open Chromatin ◽  
Cell Type ◽  
Spatially Resolved

AbstractHere we report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties and cellular resolution input–output mapping, integrated through cross-modal computational analysis. Our results advance the collective knowledge and understanding of brain cell-type organization1–5. First, our study reveals a unified molecular genetic landscape of cortical cell types that integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a consensus taxonomy of transcriptomic types and their hierarchical organization that is conserved from mouse to marmoset and human. Third, in situ single-cell transcriptomics provides a spatially resolved cell-type atlas of the motor cortex. Fourth, cross-modal analysis provides compelling evidence for the transcriptomic, epigenomic and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types. We further present an extensive genetic toolset for targeting glutamatergic neuron types towards linking their molecular and developmental identity to their circuit function. Together, our results establish a unifying and mechanistic framework of neuronal cell-type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties.

scholarly journals Brain Data Standards Ontology: A data-driven ontology of transcriptomically defined cell types in the primary motor cortex

2021 ◽  
Author(s):  
Shawn Zheng Kai Tan ◽  
Huseyin Kir ◽  
Brian Aevermann ◽  
Tom Gillespie ◽  
Michael Hawrylycz ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Single Cell ◽  
Primary Motor Cortex ◽  
Cell Types ◽  
Use Cases ◽  
Data Driven ◽  
Cell Type ◽  
Data Standards ◽  
Brain Data ◽  
The Brain

Large scale single cell omics profiling is revolutionising our understanding of cell types, especially in complex organs like the brain. This presents both an opportunity and a challenge for cell ontologies. Annotation of cell types in single cell 'omics data typically uses unstructured free text, making comparison and mapping of annotation between datasets challenging. Annotation with cell ontologies is key to overcoming this challenge, but this will require meeting the challenge of extending cell ontologies representing classically defined cell types by defining and classifying cell types directly from data. Here we present the Brain Data Standards Ontology (BDSO), a data driven ontology that is built as an extension to the Cell Ontology (CL). It supports two major use cases: cell type annotation, and navigation, search, and organisation of a web application integrating single cell omics datasets for the mammalian primary motor cortex. The ontology is built using a semi-automated pipeline that interlinks cell type taxonomies and necessary and sufficient marker genes, and imports relevant ontology modules derived from external ontologies. Overall, the BDS ontology provides an underlying structure that supports these use cases, while remaining sustainable and extensible through automation as our knowledge of brain cell type expands.

scholarly journals Cell-Type-Specific Decrease of the Intrinsic Excitability of Motor Cortical Pyramidal Neurons in Parkinsonian Mice

2020 ◽  
Author(s):  
Liqiang Chen ◽  
Yerim Kim ◽  
Hong-Yuan Chu
Keyword(s):  
Basal Ganglia ◽  
Motor Cortex ◽  
Dopaminergic Neurons ◽  
Action Potentials ◽  
Pyramidal Neurons ◽  
Intrinsic Excitability ◽  
Cell Type ◽  
Midbrain Dopaminergic Neurons ◽  
Cell Type Specific ◽  
Motor Cortical

AbstractThe hypokinetic motor symptoms of Parkinson’s disease (PD) are closely linked with a decreased motor cortical output as a consequence of elevated basal ganglia inhibition. However, whether and how the loss of dopamine alters the cellular properties of motor cortical neurons in PD remains undefined. We induced experimental parkinsonism in adult C57BL6 mice of both sexes by injecting neurotoxin, 6-hydroxydopamine, into the medial forebrain bundle. By using ex vivo patch-clamp recording and retrograde tracing approach, we found that the intrinsic excitability of pyramidal tract neurons (PTNs) in the motor cortical layer 5b was greatly decreased following the degeneration of midbrain dopaminergic neurons; but the intratelencephalic neurons (ITNs) were not affected. The cell-type-specific intrinsic adaptations were associated with a significant broadening of the action potentials in PTNs but not in ITNs. Moreover, the loss of midbrain dopaminergic neurons impaired the capability of M1 PTNs to sustain high-frequency firing, which could underlie their abnormal pattern of activity in the parkinsonian state. We also showed that the decreased excitability and broadened action potentials were largely caused by a disrupted function of the large conductance, Ca2+-activated K+ channels. The restoration of dopaminergic neuromodulation failed to rescue the impaired intrinsic excitability of M1 PTNs in parkinsonian mice. Altogether, our data show cell-type-specific decreases of the excitability of M1 pyramidal neurons following the loss of midbrain dopaminergic neurons. Thus, intrinsic adaptations in the motor cortex, together with pathological basal ganglia inhibition, underlie the decreased motor cortical output in parkinsonian state and exacerbate parkinsonian motor deficits.Significance statementThe degeneration of midbrain dopaminergic neurons in Parkinson’s disease remodels the connectivity and function of cortico–basal ganglia–thalamocortical network. However, whether and how the loss of dopamine and aberrant basal ganglia activity alter motor cortical circuitry remain undefined. We found that pyramidal neurons in the layer 5b of the primary motor cortex (M1) exhibit distinct adaptations in response to the loss of midbrain dopaminergic neurons, depending on their long-range projections. Besides the decreased thalamocortical synaptic excitation as proposed by the classical model of Parkinson’s pathophysiology, these results, for the first time, show novel cellular and molecular mechanisms underlying the abnormal motor cortical output in parkinsonian state.

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