Pair-associate learning with modulated spike-time dependent plasticity

• المؤلفون الرئيسيون: Yusoff, Nooraini, Grüning, André, Notley, Scott
• مؤلفون آخرون: Villa, Alessandro E. P.
• التنسيق: Book Section
• منشور في: Springer 2012
• الموضوعات: QA76 Computer software
• الوصول للمادة أونلاين: http://repo.uum.edu.my/12489/; http://dx.doi.org/10.1007/978-3-642-33269-2_18

We propose an associative learning model using reward modulated spike-time dependent plasticity in reinforcement learning paradigm. The task of learning is to associate a stimulus pair, known as the predictor−choice pair, to a target response.In our model, a generic architecture of neural network has been used, with minimal assumption about the network dynamics.We demonstrate that stimulus-stimulus-response association can be implemented in a stochastic way within a noisy setting.The network has rich dynamics resulting from its recurrent connectivity and background activity. The algorithm can learn temporal sequence detection and solve temporal XOR problem.