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. © 2013 Fung, Wang, Lam, Wong and Wu.
| Original language | English |
|---|---|
| Journal | Frontiers in Computational Neuroscience |
| Issue number | MAY |
| DOIs | |
| Publication status | Published - 15 May 2013 |
| Externally published | Yes |
Bibliographical note
Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].Research Keywords
- Continuous attractor neural network
- Neural field model
- Short-term synaptic depression
- Short-term synaptic plasticity
- Transparent motion
Publisher's Copyright Statement
- This full text is made available under CC-BY 3.0. https://creativecommons.org/licenses/by/3.0/