Noise correlations in neural ensemble activity limit the accuracy of hippocampal spatial representations

Omer Hazon, Victor H. Minces, David P. Tomàs, Surya Ganguli, Mark J. Schnitzer and Pablo E. Jercog ()
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Omer Hazon: Stanford University
Victor H. Minces: University California San Diego
David P. Tomàs: Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS)
Surya Ganguli: Stanford University
Mark J. Schnitzer: Stanford University
Pablo E. Jercog: Stanford University

Nature Communications, 2022, vol. 13, issue 1, 1-13

Abstract: Abstract Neurons in the CA1 area of the mouse hippocampus encode the position of the animal in an environment. However, given the variability in individual neurons responses, the accuracy of this code is still poorly understood. It was proposed that downstream areas could achieve high spatial accuracy by integrating the activity of thousands of neurons, but theoretical studies point to shared fluctuations in the firing rate as a potential limitation. Using high-throughput calcium imaging in freely moving mice, we demonstrated the limiting factors in the accuracy of the CA1 spatial code. We found that noise correlations in the hippocampus bound the estimation error of spatial coding to ~10 cm (the size of a mouse). Maximal accuracy was obtained using approximately [300–1400] neurons, depending on the animal. These findings reveal intrinsic limits in the brain’s representations of space and suggest that single neurons downstream of the hippocampus can extract maximal spatial information from several hundred inputs.

Date: 2022
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DOI: 10.1038/s41467-022-31254-y

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