Collective Behavior of Place and Non-place Neurons in the Hippocampal Network

  title={Collective Behavior of Place and Non-place Neurons in the Hippocampal Network},
  author={Leenoy Meshulam and Jeffrey L Gauthier and Carlos D. Brody and David W. Tank and William Bialek},

Figures from this paper

A Distributed Neural Code in the Dentate Gyrus and in CA1

Object-centered population coding in CA1 of the hippocampus

Objects and landmarks are crucial for guiding navigation and must be integrated into the cognitive map of space and some features of cognitive maps – including object representation – are best understood as emergent properties of neural populations.

The structure of hippocampal CA1 interactions optimizes spatial coding across experience

This work reveals highly structured cell-to-cell interactions whose statistics depend on familiar vs. novel environment and suggests that the efficient coding hypothesis is not applicable only to individual neuron properties in the sensory periphery, but also to neural interactions in the central brain.

Modeling the Correlated Activity of Neural Populations: A Review

A variety of models describing correlations between pairs of neurons, as well as between larger groups, synchronous or delayed in time, with or without the explicit influence of the stimulus, and including or not latent variables are covered.

Persistence of neuronal representations through time and damage in the hippocampus

These findings indicate the presence of attractor-like ensemble dynamics as a mechanism by which the representations of an environment are encoded in the brain by groups of neurons with synchronous activity.

A neuronal code for space in hippocampal coactivity dynamics independent of place fields

It is concluded that ensemble cofiring relationships constitute an advantageous neural code for environmental space, independent of place fields, which is similarly reliable within environments and distinctive between environments.

A distributed neural code in ensembles of dentate gyrus granule cells

The analysis indicates that classical methods of analysis based on single cell response properties might be insufficient to characterize the neural code and that the lack of observation of easily interpretable place cells in one brain area is not necessarily the indication that position is not efficiently encoded in that area.

Choice of method of place cell classification determines the population of cells identified

The Peak method showed high sensitivity and specificity for detecting model place cells and was the most robust to variations in place field width, reliability and field location, and should be used in future studies to identify place cell populations, unless there is an explicit theoretical reason for detecting cells with more narrowly defined properties.



Path Integration and Cognitive Mapping in a Continuous Attractor Neural Network Model

The model provides an explanation for a number of hitherto perplexing observations on hippocampal place fields, including doubling, vanishing, reshaping in distorted environments, acquiring directionality in a two-goal shuttling task, rapid formation in a novel environment, and slow rotation after disorientation.

Place cells and silent cells in the hippocampus of freely-behaving rats

  • L. ThompsonPJ Best
  • Biology, Psychology
    The Journal of neuroscience : the official journal of the Society for Neuroscience
  • 1989
In complex information processing, such as the processing of spatial information by the hippocampus demonstrated here, neural silence may be as important a signal as neural activity.

Dynamical criticality in the collective activity of a population of retinal neurons.

A novel approach to assess criticality that overcomes limitations of arbitrary order parameters, while encompassing and generalizing previous criteria, and takes into account the temporal dynamics of the activity greatly enhances the evidence for criticality.

Attractor neural networks storing multiple space representations: A model for hippocampal place fields

A recurrent neural network model storing multiple spatial maps, or ``charts'', is analyzed, and results suggest a quantitative parallel between theories of hippocampal function in different animal species, such as primates and rodents.

Place cell discharge is extremely variable during individual passes of the rat through the firing field.

  • A. FentonR. Muller
  • Biology
    Proceedings of the National Academy of Sciences of the United States of America
  • 1998
It is demonstrated here that firing is not nearly as reliable in the time domain as in the positional domain.

Development of the Hippocampal Cognitive Map in Preweanling Rats

The results demonstrate the presence of three neuronal representations of space before extensive experience and show how they develop with age, providing experimental support for Kant's 200-year-old concept of space as an a priori faculty of the mind.


A network model for the CA3 area of the hippocampus is presented, which predicts that the place fields should be nonuniformly distributed, clustering in the places where the synaptic interactions between neurons is strongeest.

Hippocampal CA3 region predicts memory sequences: accounting for the phase precession of place cells.

The general success of the model provides support for the idea that the hippocampus stores sequence information and makes predictions of expected positions during gamma-frequency recall.

The Architecture of Functional Interaction Networks in the Retina

This work explored the architecture of maximum entropy models of the functional interaction networks underlying the response of large populations of retinal ganglion cells, in adult tiger salamander retina, responding to natural and artificial stimuli and demonstrated the existence of local network motifs in the interaction map of the retina.