首页> 美国卫生研究院文献>Proceedings of the National Academy of Sciences of the United States of America >Non-Hebbian properties of long-term potentiation enable high-capacity encoding of temporal sequences.
【2h】

Non-Hebbian properties of long-term potentiation enable high-capacity encoding of temporal sequences.

机译:长期增强的非赫比特性可对时间序列进行高容量编码。

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

A hypothesis commonly found in biological and computational studies of synaptic plasticity embodies a version of the 1949 postulate of Hebb that coactivity of pre- and postsynaptic elements results in increased efficacy of their synaptic contacts. This general proposal presaged the identification of the first and still only known long-lasting synaptic plasticity mechanism, long-term potentiation (LTP). Yet the detailed physiology of LTP induction and expression differs in many specifics from Hebb's rule. Incorporation of these physiological LTP constraints into a simple non-Hebbian network model enabled development of "sequence detectors" that respond preferentially to the sequences on which they were trained. The network was found to have unexpected capacity (e.g., 50 x 10(6) random sequences in a network of 10(5) cells), which scales linearly with network size, thereby addressing the question of memory capacity in brain circuitry of realistic size.
机译:突触可塑性的生物学和计算研究中普遍发现的这一假设体现了1949年赫布(Hebb)假设的一种说法,即突触前和突触后元素的协同​​作用导致突触接触的功效增强。这项一般性建议预示了第一个(也是唯一已知的)持久突触可塑性机制-长期增强(LTP)的鉴定。然而,LTP诱导和表达的详细生理学在许多细节上与赫布定律不同。将这些生理LTP约束条件合并到简单的非Hebbian网络模型中,可以开发“序列检测器”,该序列检测器优先响应对其进行训练的序列。发现该网络具有意外的容量(例如,一个10(5)个单元的网络中有50 x 10(6)个随机序列),该容量随网络大小线性缩放,从而解决了实际大小的大脑电路中的存储容量问题。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号