Non-linear dimensionality reduction on extracellular waveforms reveals cell type diversity in premotor cortex
Abstract
Cortical circuits are thought to contain a large number of cell types that coordinate to produce behavior. Current in vivo methods rely on clustering of specified features of extracellular waveforms to identify putative cell types, but these capture only a small amount of variation. Here, we develop a new method (WaveMAP) that combines non-linear dimensionality reduction with graph clustering to identify putative cell types. We apply WaveMAP to extracellular waveforms recorded from dorsal premotor cortex of macaque monkeys performing a decision-making task. Using WaveMAP, we robustly establish eight waveform clusters and show that these clusters recapitulate previously identified narrow- and broad-spiking types while revealing previously unknown diversity within these subtypes. The eight clusters exhibited distinct laminar distributions, characteristic firing rate patterns, and decision-related dynamics. Such insights were weaker when using featurebased approaches. WaveMAP therefore provides a more nuanced understanding of the dynamics of cell types in cortical circuits.
Data availability
Data generated or analysed during this study are included in the linked Dryad repository (doi:10.5061/dryad.z612jm6cf). Source data for all figures are also in this zip file.
-
WaveMAP analysis of extracellular waveforms from monkey premotor cortex during decision-makinghttps://creativecommons.org/publicdomain/zero/1.0/.
Article and author information
Author details
Funding
National Institute of Neurological Disorders and Stroke (R00NS092972)
- Chandramouli Chandrasekaran
National Institute on Deafness and Other Communication Disorders (DC017844)
- Krishna V Shenoy
National Institute of Neurological Disorders and Stroke (NS095548)
- Krishna V Shenoy
National Institute of Neurological Disorders and Stroke (NS098968)
- Krishna V Shenoy
Defense Advanced Research Projects Agency (N66001-10-C-2010)
- Krishna V Shenoy
Defense Advanced Research Projects Agency (W911NF-14-2-0013)
- Krishna V Shenoy
Simons Foundation (325380)
- Krishna V Shenoy
Simons Foundation (543045)
- Krishna V Shenoy
National Institute of Neurological Disorders and Stroke (122969)
- Chandramouli Chandrasekaran
Office of Naval Research (N000141812158)
- Krishna V Shenoy
Larry and Pamela Garlick
- Krishna V Shenoy
National Institute of Neurological Disorders and Stroke (K99NS092972)
- Chandramouli Chandrasekaran
Wu Tsai Neurosciences Institute, Stanford University
- Krishna V Shenoy
Hong Seh and Vivian H Lim Endowed Professorship
- Krishna V Shenoy
Howard Hughes Medical Institute
- Krishna V Shenoy
National Institute of Mental Health (R00MH101234)
- Maria Medalla
National Institute of Mental Health (R01MH116008)
- Maria Medalla
Whitehall Foundation (2019-12-77)
- Chandramouli Chandrasekaran
Brain and Behavior Research Foundation (27923)
- Chandramouli Chandrasekaran
NIH Office of the Director (DP1HD075623)
- Krishna V Shenoy
National Institute on Deafness and Other Communication Disorders (DC014034)
- Krishna V Shenoy
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. All of the procedures were approved were approved by the Stanford Administrative Panel on Laboratory Animal Care (APLAC, Protocol Number 8856, entitled "Cortical Processing of Arm Movements"). Surgical procedures were performed under anesthesia, and every effort was made to minimize suffering. Appropriate analgesia, pain relief, and antibiotics were administered to the animals when needed after surgical approval.
Copyright
© 2021, Lee et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 6,498
- views
-
- 851
- downloads
-
- 54
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Further reading
-
- Neuroscience
Complex macro-scale patterns of brain activity that emerge during periods of wakeful rest provide insight into the organisation of neural function, how these differentiate individuals based on their traits, and the neural basis of different types of self-generated thoughts. Although brain activity during wakeful rest is valuable for understanding important features of human cognition, its unconstrained nature makes it difficult to disentangle neural features related to personality traits from those related to the thoughts occurring at rest. Our study builds on recent perspectives from work on ongoing conscious thought that highlight the interactions between three brain networks – ventral and dorsal attention networks, as well as the default mode network. We combined measures of personality with state-of-the-art indices of ongoing thoughts at rest and brain imaging analysis and explored whether this ‘tri-partite’ view can provide a framework within which to understand the contribution of states and traits to observed patterns of neural activity at rest. To capture macro-scale relationships between different brain systems, we calculated cortical gradients to describe brain organisation in a low-dimensional space. Our analysis established that for more introverted individuals, regions of the ventral attention network were functionally more aligned to regions of the somatomotor system and the default mode network. At the same time, a pattern of detailed self-generated thought was associated with a decoupling of regions of dorsal attention from regions in the default mode network. Our study, therefore, establishes that interactions between attention systems and the default mode network are important influences on ongoing thought at rest and highlights the value of integrating contemporary perspectives on conscious experience when understanding patterns of brain activity at rest.
-
- Medicine
- Neuroscience
The advent of midazolam holds profound implications for modern clinical practice. The hypnotic and sedative effects of midazolam afford it broad clinical applicability. However, the specific mechanisms underlying the modulation of altered consciousness by midazolam remain elusive. Herein, using pharmacology, optogenetics, chemogenetics, fiber photometry, and gene knockdown, this in vivo research revealed the role of locus coeruleus (LC)-ventrolateral preoptic nucleus noradrenergic neural circuit in regulating midazolam-induced altered consciousness. This effect was mediated by α1 adrenergic receptors. Moreover, gamma-aminobutyric acid receptor type A (GABAA-R) represents a mechanistically crucial binding site in the LC for midazolam. These findings will provide novel insights into the neural circuit mechanisms underlying the recovery of consciousness after midazolam administration and will help guide the timing of clinical dosing and propose effective intervention targets for timely recovery from midazolam-induced loss of consciousness.