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Chockanathan, U.

Publications and source records attributed to Chockanathan, U..

2 recordsLinked to original sources

Divergence in Population Coding for Space between Dorsal and Ventral CA1

Molecular, anatomic, and behavioral studies show that the hippocampus is structurally and functionally heterogeneous, with dorsal hippocampus implicated in mnemonic processes and spatial navigation and ventral hippocampus involved in affective processes. By performing electrophysiological recordings of large neuronal populations in dorsal and ventral CA1 in head-fixed mice navigating a virtual environment, we found that this diversity resulted in different strategies for population coding of space. We found that the populations of neurons in dorsal CA1 had a higher dimensionality and showed more complex patterns of activity, translating to more information being encoded, as compared ensembles in vCA1. Furthermore, a pairwise maximum entropy model was better at predicting the structure of global patterns of activity in ventral CA1 as compared to dorsal CA1. Taken together, we uncovered different coding strategies that likely emerge from anatomical and physiological differences along the longitudinal axis of hippocampus and that may, in turn, underpin the divergent ethological roles of dorsal and ventral CA1. HighlightsO_LINo differences in dCA1 and vCA1 place field size in recordings of neuronal populations in mice navigating a virtual environment C_LIO_LIdCA1 has higher single-neuron and population-level spatial information compared to vCA1 due to differences in the sparsity of firing. C_LIO_LIPopulation activity of dCA1 has higher entropy and is higher dimensional than vCA1 C_LIO_LIPairwise maximum entropy models are better at predicting population activity in vCA1 compared to dCA1 C_LI

neuroscience↗

Altered dorsal CA1 neuronal population coding in the APP/PS1 mouse model of Alzheimer’s disease

While the link between amyloid {beta} (A{beta}) accumulation and synaptic degradation in Alzheimers disease (AD) is known, the consequences of this pathology on coding remain unknown. We found that the entropy across neural ensembles was lower in the CA1 region in the APP/PS1 mouse model of A{beta}, thereby reducing the populations coding capacity. Our results reveal a network level signature of the deficits A{beta} accumulation causes to the computations performed by neural circuits.

neuroscience↗