,
Self-organizing continuous attractor networks and path integration: Two-dimensional models of place cells
Network: Computation in Neural Systems, (2002)
Аннотация
Single-neuron recording studies have demonstrated the existence of
neurons in
the hippocampus which appear to encode information about the place
where a
rat is located, and about the place at which a macaque is looking.
We describe
continuous attractor neural network models of place cells with Gaussian
spatial fields in which the recurrent collateral synaptic connections
between
the neurons reflect the distance between two places. The networks
maintain a
localized packet of neuronal activity that represents the place where
the animal
is located. We show for two related models how the representation
of the
two-dimensional space in the continuous attractor network of place
cells could
self-organize by modifying the synaptic connections between the neurons,
and
also howthe place being represented can be updated by idiothetic (self-motion)
signals in a neural implementation of path integration.
