中文标题#
突觸束理論用於脈衝驅動的感知運動系統：超過八個獨立的突觸束會坍縮獎勵 - STDP 學習
英文标题#
Synaptic bundle theory for spike-driven sensor-motor system: More than eight independent synaptic bundles collapse reward-STDP learning
中文摘要#
神經元尖峰直接驅動肌肉，使動物具有敏捷的運動能力，但將基於尖峰的控制信號應用於人工傳感 - 運動系統中的執行器不可避免地會導致學習崩潰。我們開發了一個系統，可以在感覺 - 運動連接中變化 \emph {獨立突觸束的數量}。本文展示了以下四個發現：(i) 一旦運動神經元的數量或獨立突觸束的數量超過臨界極限，學習就會崩潰。(ii) 運動神經元數量較少會增加學習失敗的概率，而 (iii) 如果學習成功，運動神經元數量較少會導致更快的學習。(iv) 與最優權重方向相反的權重更新次數可以定量解釋這些結果。尖峰的功能仍大多未知。確定使用尖峰的學習系統可以構建的參數範圍，將有可能研究之前由於學習困難而無法研究的尖峰功能。
英文摘要#
Neuronal spikes directly drive muscles and endow animals with agile movements, but applying the spike-based control signals to actuators in artificial sensor-motor systems inevitably causes a collapse of learning. We developed a system that can vary \emph{the number of independent synaptic bundles} in sensor-to-motor connections. This paper demonstrates the following four findings: (i) Learning collapses once the number of motor neurons or the number of independent synaptic bundles exceeds a critical limit. (ii) The probability of learning failure is increased by a smaller number of motor neurons, while (iii) if learning succeeds, a smaller number of motor neurons leads to faster learning. (iv) The number of weight updates that move in the opposite direction of the optimal weight can quantitatively explain these results. The functions of spikes remain largely unknown. Identifying the parameter range in which learning systems using spikes can be constructed will make it possible to study the functions of spikes that were previously inaccessible due to the difficulty of learning.
文章页面#
突觸束理論用於脈衝驅動的感知運動系統：超過八個獨立的突觸束會坍縮獎勵 - STDP 學習
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