A train of discrete places

Place cells are active when an animal is moving about, when it is learning a route, when it is revisiting the path during sleep, when it is planning a route and when it is taking that route. The place cells are active in a sequence that defines the route.

ScienceDaily has an item (here) on a recent paper (B. E. Pfeiffer, D. J. Foster. Autoassociative dynamics in the generation of sequences of hippocampal place cells. Science, 2015; 349 (6244): 180). The paper describes the events in remembering a route.

Foster says, “My own introspective experience of memory tends to be one of discrete snapshots strung together, as opposed to a continuous video recording. Our data from rats suggest that our memories are actually organized that way, with one network of neurons responsible for the snapshots and another responsible for the string that connects them.

The research showed gaps between the ‘snapshot’ discrete memories of a place. “The trajectories that the rats reconstructed weren’t smooth. We were able to see that neural activity ‘hovers’ in one place for about 20 milliseconds before ‘jumping’ to another place, where it hovers again before moving on to the next point. At first, you get a ‘blurry’ representation of point A because a bunch of place cells all around point A fire, but, as time passes, the activity becomes more focused on A. Then the activity jumps to a “blurry” version of B, which then gets focused. We think that there is a whole network of cells dedicated to this process of fine-tuning and jumping. Without it, memory retrieval would be even messier than it is.

It seems to me that this discrete series of place memories may well be like consciousness – a discrete train of individual conscious moments rather than a continuous ‘movie’.

Here is the abstract:

Neuronal circuits produce self-sustaining sequences of activity patterns, but the precise mechanisms remain unknown. Here we provide evidence for autoassociative dynamics in sequence generation. During sharp-wave ripple (SWR) events, hippocampal neurons express sequenced reactivations, which we show are composed of discrete attractors. Each attractor corresponds to a single location, the representation of which sharpens over the course of several milliseconds, as the reactivation focuses at that location. Subsequently, the reactivation transitions rapidly to a spatially discontiguous location. This alternation between sharpening and transition occurs repeatedly within individual SWRs and is locked to the slow-gamma (25 to 50 hertz) rhythm. These findings support theoretical notions of neural network function and reveal a fundamental discretization in the retrieval of memory in the hippocampus, together with a function for gamma oscillations in the control of attractor dynamics.

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