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Tanni, S.

Publications and source records attributed to Tanni, S..

2 recordsLinked to original sources

State transitions in the statistically stable place cell population are determined by visual change

The hippocampus plays a central role in mammalian navigation and memory, yet an implementational understanding of the rules that govern the granularity of location encoding and the spatial-statistics of the population as a whole are lacking. We analysed large numbers of CA1 place fields recorded while rats foraged in environments up to 8.75 m2. We found that place cell propensities to form fields were proportional to open-field area, gamma-distributed, and conserved across environments. The properties of place fields varied positionally with a denser distribution of smaller fields near boundaries. Remarkably, field size and density were in a dynamic equilibrium, such that population-level activity statistics remained constant. We showed that the rate of transition through the statistically stable place cell population matched the rate of change in the animals visual scenes - demonstrating that the resolution of the spatial-memory system is bounded by perceptual information afforded by the environment.

neuroscience↗

DeepInsight: A general framework for interpreting wide-band neural activity

AO_SCPLOWBSTRACTC_SCPLOWRapid progress in technologies such as calcium imaging and electrophysiology has seen a dramatic increase in the size and extent of neural recordings. Even so, interpretation of this data often depends on manual operations and requires considerable knowledge about the nature of the representation. Decoding provides a means to infer the information content of such recordings but typically requires highly processed data and prior knowledge of the encoding scheme. Here, we developed a deep-learning-framework able to decode sensory and behavioural variables directly from wide-band neural data. The network requires little user input and generalizes across stimuli, behaviours, brain regions, and recording techniques. Once trained, it can be analysed to determine elements of the neural code that are informative about a given variable. We validated this approach using data from rodent auditory cortex and hippocampus, identifying a novel representation of head direction encoded by putative CA1 interneurons.

neuroscience↗