Tracking a trajectory of a moving stimulus by spike timing dependent plasticity
© Fujita; licensee BioMed Central Ltd. 2012
Published: 16 July 2012
The present study, we propose the recurrent network with spike timing dependent plasticity (STDP) that can track a trajectory of a moving stimulus. In STDP, synaptic efficiency is changed depending on the difference of firing time between pre- and postsynaptic neurons. There are many researches about temporal information processing. In the previous study, we have shown that the recurrent network with STDP can provide spatial filtering stimulating a static input . Here we demonstrate the recurrent network with STDP can store spatiotemporal information of a stimulus.
The structure of the proposed network is 2-dimension array. A neuron in the network connects with the neighbor neurons through synapses whose changes are subjected to STDP. The learning window of STDP is applied to that found in hippocampus. We used STDP model proposed by Song and Abbott .
In the summary, the present study showed that the recurrent network with STDP could store a trajectory of a moving stimulus. STDP is also found in the midbrain of an electric fish. The electric fish can detect features of a moving object using electrosensory system. The object features present on the fish body surface as an electric image . The function of the network shown in the present study helps explain how the electric fish can extract information from the features of an electric image generated by a moving object.
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