RT Journal Article
SR Electronic
T1 A distributed neural code in the dentate gyrus and in CA1
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 292953
DO 10.1101/292953
A1 Fabio Stefanini
A1 Mazen A. Kheirbek
A1 Lyudmila Kushnir
A1 Jessica C. Jimenez
A1 Joshua H. Jennings
A1 Garret D. Stuber
A1 René Hen
A1 Stefano Fusi
YR 2019
UL http://biorxiv.org/content/early/2019/02/28/292953.abstract
AB The tuning properties of neurons in a given brain region have been traditionally viewed as the under-pinnings of computation in neural circuits. However, at the higher levels of processing, specialization is often elusive, instead a mix of sensory, cognitive and behavioural quantities drive neural activity. In such networks, ensembles of neurons, rather than single units with easily interpretable tuning properties, encode behaviourally relevant variables. Here we show that this is the case also in the dentate gyrus and CA1 subregions of the hippocampus. Using calcium imaging in freely moving mice, we decoded the instantaneous position, direction of motion and speed from the activity of hundreds of cells in the hippocampus of mice freely exploring an arena. For the vast majority of neurons in both regions, their response properties were not predictive of their importance for encoding position. Furthermore, we could decode position from populations of cells that were important for decoding direction of motion and vice versa, showing that these quantities are encoded by largely overlapping ensembles as in distributed neural code. Finally, we found that correlated activities had an impact on decoding performance in CA1 but not in dentate gyrus, suggesting different enconding strategies for these areas. Our analysis indicates that classical methods of analysis based on single cell response properties might be insufficient to accurately characterize the neural computation in a given area. In contrast, population analysis may help highlight previously overlooked properties of hippocampal circuits.