Learning Sensory Maps With Real-World Stimuli in Real Time Using A Biophysically Realistic Learning Rule  

Oleh:

Verschure, P. F. M. J. ; Konig, P. ; Sanchez-Montanes, M. A.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 13 no. 3 (2002), page 619-632.
Topik: LEARNING; learning sensory; maps; real - world stimuli; biophysical realistic; learning rule

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.6 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

We present a real - time model of learning in the auditory cortex that is trained using real - world stimuli. The system consists of a peripheral and a central cortical network of spiking neurons. The synapses formed by peripheral neurons on the central ones are subject to synaptic plasticity. We implemented a biophysically realistic learning rule that depends on the precise temporal relation of pre - and post synaptic action potentials. We demonstrate that this biologically realistic real - time neuronal system forms stable receptive fields that accurately reflect the spectral content of the input signals and that the size of these representations can be biased by global signals acting on the local learning mechanism. In addition, we show that this learning mechanism shows fast acquisition and is robust in the presence of large imbalances in the probability of occurrence of individual stimuli and noise.

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