- Poster presentation
- Open Access
A spiking neuron network model for the delayed motion direction discrimination task
© Yu et al. 2015
- Published: 4 December 2015
- Neural Mechanism
- Test Direction
- Longe Reaction Time
- Reference Direction
- Rotational Invariance
To test this hypothesis, we build a spiking neuron network model and investigate whether it can solve the DMD task. The network consists of three parts (Figure 1.B): 1) a working memory circuit (WMC) 2) two information extraction circuits, referred to as clockwise-preferred circuit (CPC) and anticlockwise-preferred circuit (APC) respectively, and 3) a decision-making circuit. At the core of the network is the assumption of an asymmetric offset and rotational invariance of the connectivity profile. The former ensures that CPC (or APC) has stronger response when the test direction is CW (or ACW) rotated with respect to the reference direction and the latter guarantees the feasibility of the network under variable references. The simulations demonstrate that the proposed network is indeed capable of solving the DMD task (Figure 1.C) showing a similar detection threshold (2°) as previous behavioral data . Furthermore, the model correctly predicts that with higher similarity of reference and test direction or lower coherence level of the RDK, the performance gets worse (lower accuracy and longer reaction time). Our results suggest a possible neural mechanism for memory-guided decision making.
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