THESIS
2013
xi, 53 pages : illustrations (some color) ; 30 cm
Abstract
In this thesis, the continuous attractor neural network (CANN) model is applied to investigate
neural field dynamics in the presence of short-term synaptic depression (STD). There are three
parts related to neural field dynamics. They are: 1) intrinsic dynamics, 2) response to a single
static input, and 3) response to two overlapping inputs. In the first part, intrinsic dynamics in
both strong global inhibition and weak inhibition scenarios are explored. Different dynamics
of these two scenarios are related to the ratio of the neuronal time constant to the STD time
constant. In the second part, response to one single static input is investigated. Four basic
kinds of response patterns and more complex mixtures of them are discovered. By monitoring
the period of the response dynam...[
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In this thesis, the continuous attractor neural network (CANN) model is applied to investigate
neural field dynamics in the presence of short-term synaptic depression (STD). There are three
parts related to neural field dynamics. They are: 1) intrinsic dynamics, 2) response to a single
static input, and 3) response to two overlapping inputs. In the first part, intrinsic dynamics in
both strong global inhibition and weak inhibition scenarios are explored. Different dynamics
of these two scenarios are related to the ratio of the neuronal time constant to the STD time
constant. In the second part, response to one single static input is investigated. Four basic
kinds of response patterns and more complex mixtures of them are discovered. By monitoring
the period of the response dynamics, relations among them in the phase diagram are presented.
The effects of STD and the input of different strengths on the response are discussed. In the last
part, the ability of these networks to better resolve two overlapping inputs are presented. Resolution
enhancement is enabled by population spikes, one of the four basic response patterns
to one single static input. When two overlapping inputs are imposed, population spikes will
switch back and forth between the two inputs, thus facilitating temporal coding, which preserves
more information than traditional time-averaged rate coding. Several conditions for the
resolution enhancement in our model are discussed and we argue that resolution enhancement
can be achieved in other models as long as those conditions are met.
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