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The Dynamics of Bimodular Continuous Attractor Neural Networks with Static and Moving Stimuli
| Content Provider | Semantic Scholar |
|---|---|
| Author | Zhang, Wenhao Wang, He Wong, K. Y. Michael |
| Copyright Year | 2019 |
| Abstract | The brain achieves multisensory integration by combining the information received from different sensory inputs to yield inferences with higher speed or more accuracy. We consider a bimodular neural network each processing a modality of sensory input and interacting with each other. The dynamics of excitatory and inhibitory couplings between the two modules are studied with static and moving stimuli. The modules exhibit non-trivial interactive behaviors depending on the input strengths, their disparity and speed (for moving inputs), and the inter-modular couplings. They give rise to a family of models applicable to causal inference problems in neuroscience. They also provide a model for the experiment of motion-bounce illusion, yielding consistent results and predicting their robustness. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://arxiv.org/pdf/1910.07263v1.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
