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Cross-species neuroscience: closing the explanatory gap

Abstract:
Neuroscience has seen substantial development in non-invasive methods available for investigating the living human brain. However, these tools are limited to coarse macroscopic measures of neural activity that aggregate the diverse responses of thousands of cells. To access neural activity at the cellular and circuit level, researchers instead rely on invasive recordings in animals. Recent advances in invasive methods now permit large-scale recording and circuit-level manipulations with exquisite spatio-temporal precision. Yet, there has been limited progress in relating these microcircuit measures to complex cognition and behaviour observed in humans. Contemporary neuroscience thus faces an explanatory gap between macroscopic descriptions of the human brain and microscopic descriptions in animal models. To close the explanatory gap, we propose adopting a cross-species approach. Despite dramatic differences in the size of mammalian brains, this approach is broadly justified by preserved homology. Here, we outline a three-armed approach for effective cross-species investigation that highlights the need to translate different measures of neural activity into a common space. We discuss how a cross-species approach has the potential to transform basic neuroscience while also benefiting neuropsychiatric drug development where clinical translation has, to date, seen minimal success.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1098/rstb.2019.0633

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Division:
MSD
Department:
Clinical Neurosciences
Oxford college:
Trinity College
Role:
Author
ORCID:
0000-0002-0040-1766


Publisher:
Royal Society
Journal:
Philosophical Transactions B: Biological Sciences More from this journal
Volume:
376
Issue:
1815
Article number:
20190633
Publication date:
2020-11-16
Acceptance date:
2020-05-20
DOI:
EISSN:
1471-2970
ISSN:
0962-8436


Language:
English
Keywords:
Pubs id:
1105615
Local pid:
pubs:1105615
Deposit date:
2020-05-20
ARK identifier:

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