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Strong and weak principles of neural dimension reduction

Humphries, Mark D

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Authors

MARK HUMPHRIES Mark.Humphries@nottingham.ac.uk
Professor of Computational Neuroscience



Abstract

If spikes are the medium, what is the message? Answering that question is driving the development of large-scale, single neuron resolution recordings from behaving animals, on the scale of thousands of neurons. But these data are inherently high-dimensional, with as many dimensions as neurons - so how do we make sense of them? For many the answer is to reduce the number of dimensions. Here I argue we can distinguish weak and strong principles of neural dimension reduction. The weak principle is that dimension reduction is a convenient tool for making sense of complex neural data. The strong principle is that dimension reduction shows us how neural circuits actually operate and compute. Elucidating these principles is crucial, for which we subscribe to provides radically different interpretations of the same neural activity data. I show how we could make either the weak or strong principles appear to be true based on innocuous looking decisions about how we use dimension reduction on our data. To counteract these confounds, I outline the experimental evidence for the strong principle that do not come from dimension reduction; but also show there are a number of neural phenomena that the strong principle fails to address. To reconcile these conflicting data, I suggest that the brain has both principles at play.

Citation

Humphries, M. D. (2021). Strong and weak principles of neural dimension reduction. Neurons, Behavior, Data Analysis, and Theory, 5(2), https://doi.org/10.51628/001c.24619

Journal Article Type Article
Acceptance Date May 21, 2021
Online Publication Date Jun 17, 2021
Publication Date 2021
Deposit Date Jul 1, 2021
Publicly Available Date Jul 1, 2021
Journal Neurons, Behavior, Data analysis, and Theory
Print ISSN 2690-2664
Publisher Neurons, Behavior, Data Analysis and Theory Collective
Peer Reviewed Peer Reviewed
Volume 5
Issue 2
DOI https://doi.org/10.51628/001c.24619
Public URL https://nottingham-repository.worktribe.com/output/5693526
Publisher URL https://nbdt.scholasticahq.com/article/24619-strong-and-weak-principles-of-neural-dimension-reduction

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