神经网络模型中的神经波和短期记忆

IF 1.8 4区 生物学 Q3 BIOPHYSICS
Stephen Selesnick
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引用次数: 0

摘要

我们表明,可识别的神经波形在先前工作中描述的模型中重现。在这样做的过程中,我们以封闭的数学形式再现了与某些观察到的密切匹配,尽管经过过滤,类似脑电图的测量结果,达到了很好的近似。这些神经波代表了单个网络对外部和内部输入的反应,并且可能是实际大脑中用于执行计算的信息的载体,而实际大脑是相互连接的网络的复合体。然后,我们将这些发现应用于人类短期记忆处理中出现的问题。也就是说,我们展示了在斯滕伯格任务的某些试验中,从短期记忆中发现的异常少量的可靠检索是如何与所涉及的神经波的相对频率相关的。这一发现证明了相位编码的假设是正确的,这一假设被认为是对这种效应的解释。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Neural waves and short-term memory in a neural net model

Neural waves and short-term memory in a neural net model

We show that recognizable neural waveforms are reproduced in the model described in previous work. In so doing, we reproduce close matches to certain observed, though filtered, EEG-like measurements in closed mathematical form, to good approximations. Such neural waves represent the responses of individual networks to external and endogenous inputs and are presumably the carriers of the information used to perform computations in actual brains, which are complexes of interconnected networks. Then, we apply these findings to a question arising in short-term memory processing in humans. Namely, we show how the anomalously small number of reliable retrievals from short-term memory found in certain trials of the Sternberg task is related to the relative frequencies of the neural waves involved. This finding justifies the hypothesis of phase-coding, which has been posited as an explanation of this effect.

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来源期刊
Journal of Biological Physics
Journal of Biological Physics 生物-生物物理
CiteScore
3.00
自引率
5.60%
发文量
20
审稿时长
>12 weeks
期刊介绍: Many physicists are turning their attention to domains that were not traditionally part of physics and are applying the sophisticated tools of theoretical, computational and experimental physics to investigate biological processes, systems and materials. The Journal of Biological Physics provides a medium where this growing community of scientists can publish its results and discuss its aims and methods. It welcomes papers which use the tools of physics in an innovative way to study biological problems, as well as research aimed at providing a better understanding of the physical principles underlying biological processes.
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