Synchrony Detection and Amplification By Silicon Neurons With STDP Synapses  

Oleh:

Bofill-i-Petit, A. ; Murray, A. F.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 15 no. 5 (Sep. 2004), page 1296-1304.
Topik: NEURONS; synchrony detection; amplification; silicon neurons; STDP synapses

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.11 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

Spike - timing dependent synaptic plasticity (STDP) is a form of plasticity driven by precise spike - timing differences between presynaptic and postsynaptic spikes. Thus, the learning rules underlying STDP are suitable for learning neuronal temporal phenomena such as spike - timing synchrony. It is well known that weight - independent STDP creates unstable learning processes resulting in balanced bimodal weight distributions. In this paper, we present a neuromorphic analog very large scale integration (VLSI) circuit that contains a feedforward network of silicon neurons with STDP synapses. The learning rule implemented can be tuned to have a moderate level of weight dependence. This helps stabilise the learning process and still generates binary weight distributions. From on - chip learning experiments we show that the chip can detect and amplify hierarchical spike - timing synchrony structures embedded in noisy spike trains. The weight distributions of the network emerging from learning are bimodal.

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