Abstract
Conventionally, information is represented by spike rates in the neural system. Here, we consider the ability of temporally modulated activities in neuronal networks to carry information extra to spike rates. These temporal modulations, commonly known as population spikes, are due to the presence of synaptic depression in a neuronal network model. We discuss its relevance to an experiment on transparent motions in macaque monkeys by Treue et al. in 2000. They found that if the moving directions of objects are too close, the firing rate profile will be very similar to that with one direction. As the difference in the moving directions of objects is large enough, the neuronal system would respond in such a way that the network enhances the resolution in the moving directions of the objects. In this paper, we propose that this behavior can be reproduced by neural networks with dynamical synapses when there are multiple external inputs. We will demonstrate how resolution enhancement can be achieved, and discuss the conditions under which temporally modulated activities are able to enhance information processing performances in general.
Highlights
An important issue in computational neuroscience is how information is represented in the neural system
We found a rich spectrum of behaviors including population spikes, static bumps, and moving bumps
In this paper, we have demonstrated how short-term depression (STD) plays the role of generating population spikes that can carry information extra to spike rates
Summary
An important issue in computational neuroscience is how information is represented in the neural system. The population spikes are due to the presence of short-term depression (STD) of the synapses, referring to the reduction of synaptic efficacy of a neuron after firing due to the depletion of neurotransmitters (Stevens and Wang, 1993; Markram and Tsodyks, 1996; Dayan and Abbott, 2001) This adds to a recently expanding list of the roles played by STD in neural information processing. As in standard neural field models, there is a local center-surround competition in the space of motion directions This is not sufficient to explain the enhanced resolution, there is the second mechanism, namely, the modulatory feedback signals from higher stages of processing in the area medial superior temporal (MST) area. There is a discussion section concluding our proposed mechanism
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