Optimal routing to cerebellum-like structures

The vast expansion from mossy fibers to cerebellar granule cells (GrC) produces a neural representation that supports functions including associative and internal model learning. This motif is shared by other cerebellum-like structures and has inspired numerous theoretical models. Less attention has...

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Bibliographic Details
Published in:Nature neuroscience 2023-09, Vol.26 (9), p.1630-1641
Main Authors: Muscinelli, Samuel P., Wagner, Mark J., Litwin-Kumar, Ashok
Format: Article
Language:English
Subjects:
631/378/116/1925
631/378/2632/1368
631/378/3920
Animal Genetics and Genomics
Antennal lobe
Behavioral Sciences
Biological Techniques
Biomedical and Life Sciences
Biomedicine
Brain
Cerebellum
Compression
Computational neuroscience
Fibers
Granule cells
Insects
Learning
Mossy fibers
Neural coding
Neural networks
Neurobiology
Neurons
Neurosciences
Pons
Representations
Sensorimotor system
Sensory neurons
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Summary:The vast expansion from mossy fibers to cerebellar granule cells (GrC) produces a neural representation that supports functions including associative and internal model learning. This motif is shared by other cerebellum-like structures and has inspired numerous theoretical models. Less attention has been paid to structures immediately presynaptic to GrC layers, whose architecture can be described as a ‘bottleneck’ and whose function is not understood. We therefore develop a theory of cerebellum-like structures in conjunction with their afferent pathways that predicts the role of the pontine relay to cerebellum and the glomerular organization of the insect antennal lobe. We highlight a new computational distinction between clustered and distributed neuronal representations that is reflected in the anatomy of these two brain structures. Our theory also reconciles recent observations of correlated GrC activity with theories of nonlinear mixing. More generally, it shows that structured compression followed by random expansion is an efficient architecture for flexible computation. Sensorimotor inputs are first compressed before being routed to the cerebellum and similar brain structures. The authors develop a theory to understand the computational role of this compression, leading to anatomical and functional predictions.
ISSN:1097-6256
1546-1726
1546-1726
DOI:10.1038/s41593-023-01403-7