How many neurons are sufficient for perception of cortical activity?
- University College London, United Kingdom
- University of Oxford, United Kingdom
Abstract
Many theories of brain function assume that information is encoded and behaviour is controlled through sparse, distributed patterns of activity. It is therefore crucial to place a lower bound on the amount of neural activity that can drive behaviour and to understand how neuronal networks operate within these constraints. We use an all-optical approach to test this lower limit by driving behaviour with targeted two-photon optogenetic activation of small ensembles of L2/3 pyramidal neurons in mouse barrel cortex while using two-photon calcium imaging to record the impact on the local network. By precisely titrating the number of neurons in activated ensembles we demonstrate that the lower bound for detection of cortical activity is ~14 pyramidal neurons. We show that there is a very steep sigmoidal relationship between the number of activated neurons and behavioural output, saturating at only ~37 neurons, and that this relationship can shift with learning. By simultaneously measuring activity in the local network, we show that the activation of stimulated ensembles is balanced by the suppression of neighbouring neurons. This surprising behavioural sensitivity in the face of potent network suppression supports the sparse coding hypothesis and suggests that perception of cortical activity balances a trade-off between minimizing the impact of noise while efficiently detecting relevant signals.
Data availability
Import, processing, analysis and figure code is available on Github (Dalgleish, 2020; https://github.com/alloptical/Dalgleish-eLife-2020) for use with analysed data (https://doi.org/10.6084/m9.figshare.13135505) and/or unprocessed behavioural session data (https://doi.org/10.6084/m9.figshare.13128950). Raw calcium imaging movies are ~1TB in size and are thus available upon reasonable request.
-
How many neurons are sufficient for perception of cortical activity?Figshare, https://doi.org/10.6084/m9.figshare.13128950; https://doi.org/10.6084/m9.figshare.13135505.
Article and author information
Author details
Funding
ERC (695709)
- Michael Häusser
Wellcome Trust (201225)
- Michael Häusser
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Brice Bathellier, CNRS, France
Ethics
Animal experimentation: All experimental procedures were carried out under Project Licence 70/14018 (PCC4A4ECE) issued by the UK Home Office in accordance with the UK Animals (Scientific Procedures) Act (1986) and were also subject to local ethical review. All surgical procedures were carried out under isoflurane anaesthesia (5% for induction, 1.5% for maintenance), and every effort was made to minimize suffering.
Version history
- Received: May 13, 2020
- Accepted: October 17, 2020
- Accepted Manuscript published: October 26, 2020 (version 1)
- Version of Record published: November 27, 2020 (version 2)
Copyright
© 2020, Dalgleish 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
-
- 12,574
- views
-
- 1,700
- downloads
-
- 87
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
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)
How many neurons are sufficient for perception of cortical activity?
eLife 9:e58889.
https://doi.org/10.7554/eLife.58889
Further reading
-
- Neuroscience
Natural behaviors have redundancy, which implies that humans and animals can achieve their goals with different strategies. Given only observations of behavior, is it possible to infer the control objective that the subject is employing? This challenge is particularly acute in animal behavior because we cannot ask or instruct the subject to use a particular strategy. This study presents a three-pronged approach to infer an animal’s control objective from behavior. First, both humans and monkeys performed a virtual balancing task for which different control strategies could be utilized. Under matched experimental conditions, corresponding behaviors were observed in humans and monkeys. Second, a generative model was developed that represented two main control objectives to achieve the task goal. Model simulations were used to identify aspects of behavior that could distinguish which control objective was being used. Third, these behavioral signatures allowed us to infer the control objective used by human subjects who had been instructed to use one control objective or the other. Based on this validation, we could then infer objectives from animal subjects. Being able to positively identify a subject’s control objective from observed behavior can provide a powerful tool to neurophysiologists as they seek the neural mechanisms of sensorimotor coordination.
-
- Neuroscience
The retina consumes massive amounts of energy, yet its metabolism and substrate exploitation remain poorly understood. Here, we used a murine explant model to manipulate retinal energy metabolism under entirely controlled conditions and utilised 1H-NMR spectroscopy-based metabolomics, in situ enzyme detection, and cell viability readouts to uncover the pathways of retinal energy production. Our experimental manipulations resulted in varying degrees of photoreceptor degeneration, while the inner retina and retinal pigment epithelium were essentially unaffected. This selective vulnerability of photoreceptors suggested very specific adaptations in their energy metabolism. Rod photoreceptors were found to rely strongly on oxidative phosphorylation, but only mildly on glycolysis. Conversely, cone photoreceptors were dependent on glycolysis but insensitive to electron transport chain decoupling. Importantly, photoreceptors appeared to uncouple glycolytic and Krebs-cycle metabolism via three different pathways: (1) the mini-Krebs-cycle, fuelled by glutamine and branched chain amino acids, generating N-acetylaspartate; (2) the alanine-generating Cahill-cycle; (3) the lactate-releasing Cori-cycle. Moreover, the metabolomics data indicated a shuttling of taurine and hypotaurine between the retinal pigment epithelium and photoreceptors, likely resulting in an additional net transfer of reducing power to photoreceptors. These findings expand our understanding of retinal physiology and pathology and shed new light on neuronal energy homeostasis and the pathogenesis of neurodegenerative diseases.
