Cognitive experience alters cortical involvement in goal-directed navigation
- Harvard Medical School, United States
Abstract
Neural activity in the mammalian cortex has been studied extensively during decision tasks, and recent work aims to identify under what conditions cortex is actually necessary for these tasks. We discovered that mice with distinct cognitive experiences, beyond sensory and motor learning, use different cortical areas and neural activity patterns to solve the same navigation decision task, revealing past learning as a critical determinant of whether cortex is necessary for goal-directed navigation. We used optogenetics and calcium imaging to study the necessity and neural activity of multiple cortical areas in mice with different training histories. Posterior parietal cortex and retrosplenial cortex were mostly dispensable for accurate performance of a simple navigation task. In contrast, these areas were essential for the same simple task when mice were previously trained on complex tasks with delay periods or association switches. Multi-area calcium imaging showed that, in mice with complex-task experience, single-neuron activity had higher selectivity and neuron-neuron correlations were weaker, leading to codes with higher task information. Therefore, past experience is a key factor in determining whether cortical areas have a causal role in goal-directed navigation.
Data availability
Data have been deposited in Dryad with the DOI: https://doi.org/10.5061/dryad.34tmpg4nr.
-
Cognitive experience alters cortical involvement in goal-directed navigationDryad Digital Repository, doi:10.5061/dryad.34tmpg4nr.
Article and author information
Author details
Christopher D Harvey
Funding
National Institutes of Health (R01 MH107620)
- Christopher D Harvey
JSPS Overseas Research Fellowship
- Shinichiro Kira
EMBO Postdoctoral Fellowship
- Sofia Soares
Stuart H.Q. & Victoria Quan Fellowship
- Noah L Pettit
National Institutes of Health (R01 NS089521)
- Christopher D Harvey
National Institutes of Health (R01 NS108410)
- Christopher D Harvey
National Institutes of Health (DP1 MH125776)
- Christopher D Harvey
Louis Perry Jones Postdoctoral Fellowship
- Charlotte Arlt
Alice and Joseph Brooks Postdoctoral Fellowship
- Charlotte Arlt
Uehara Foundation Research Fellowship
- Shinichiro Kira
Leonard and Isabelle Goldenson Postdoctoral Fellowship
- Shinichiro Kira
NARSAD Young Investigator Grant
- Shinichiro Kira
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: All experimental procedures were approved by the Harvard Medical School Institutional Animal Care and Use Committee (protocol # 00000073-6) and were performed in compliance with the Guide for the Care and Use of Laboratory Animals.
Reviewing Editor
- Mathieu Wolff, CNRS, University of Bordeaux, France
Version history
- Received: December 2, 2021
- Preprint posted: December 10, 2021 (view preprint)
- Accepted: June 22, 2022
- Accepted Manuscript published: June 23, 2022 (version 1)
- Version of Record published: July 6, 2022 (version 2)
Copyright
© 2022, Arlt 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
-
- 1,927
- Page views
-
- 493
- Downloads
-
- 5
- Citations
Article citation count generated by polling the highest count across the following sources: PubMed Central, Crossref, Scopus.
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)
Cognitive experience alters cortical involvement in goal-directed navigation
eLife 11:e76051.
https://doi.org/10.7554/eLife.76051
Further reading
-
- Cell Biology
- Neuroscience
The amyloid beta (Aβ) plaques found in Alzheimer’s disease (AD) patients’ brains contain collagens and are embedded extracellularly. Several collagens have been proposed to influence Aβ aggregate formation, yet their role in clearance is unknown. To investigate the potential role of collagens in forming and clearance of extracellular aggregates in vivo, we created a transgenic Caenorhabditis elegans strain that expresses and secretes human Aβ1-42. This secreted Aβ forms aggregates in two distinct places within the extracellular matrix. In a screen for extracellular human Aβ aggregation regulators, we identified different collagens to ameliorate or potentiate Aβ aggregation. We show that a disintegrin and metalloprotease a disintegrin and metalloprotease 2 (ADM-2), an ortholog of ADAM9, reduces the load of extracellular Aβ aggregates. ADM-2 is required and sufficient to remove the extracellular Aβ aggregates. Thus, we provide in vivo evidence of collagens essential for aggregate formation and metalloprotease participating in extracellular Aβ aggregate removal.
-
- Computational and Systems Biology
- Neuroscience
The cerebellar granule cell layer has inspired numerous theoretical models of neural representations that support learned behaviors, beginning with the work of Marr and Albus. In these models, granule cells form a sparse, combinatorial encoding of diverse sensorimotor inputs. Such sparse representations are optimal for learning to discriminate random stimuli. However, recent observations of dense, low-dimensional activity across granule cells have called into question the role of sparse coding in these neurons. Here, we generalize theories of cerebellar learning to determine the optimal granule cell representation for tasks beyond random stimulus discrimination, including continuous input-output transformations as required for smooth motor control. We show that for such tasks, the optimal granule cell representation is substantially denser than predicted by classical theories. Our results provide a general theory of learning in cerebellum-like systems and suggest that optimal cerebellar representations are task-dependent.
