标题： 使用标准和振荡邻域SOM神经网络的神经发育障碍的认知建模方面 显示英文标题

标题： Cognitive Modelling Aspects of Neurodevelopmental Disorders Using Standard and Oscillating Neighbourhood SOM Neural Networks

摘要： 背景/引言：在本文中，研究了自组织映射（SOMs）这一神经网络类别在认知建模中的理论和应用有效性，特别是对神经发育障碍的建模。 方法：引入了一种改进的SOM网络类型，具有更高的生物学合理性，结合了一种皮层柱状振荡的形式，即振荡拓扑邻域（TN），并将其与标准SOM一起应用。 基于现有的神经计算理论，使用SOM网络对两种神经发育障碍——自闭症和精神分裂症的方面进行了建模。 标准SOM和振荡TN-SOM的训练都被采用，并对TN宽度函数进行了有针对性的修改。 使用基于新建模假设的先前介绍的模型（IPSOM）的修订版本进行计算机模拟。 结果/结论：结果表明，在地图形成行为、输出和结构方面，标准SOM和振荡TN-SOM建模之间存在很强的相似性，而振荡版本提供了更真实的脑功能计算模拟。 提出了神经科学和计算论点，以在认知建模框架内验证所提出的SOM修改。 显示英文摘要

摘要： Background/Introduction: In this paper, the neural network class of Self-Organising Maps (SOMs) is investigated in terms of its theoretical and applied validity for cognitive modelling, particularly of neurodevelopmental disorders. Methods: A modified SOM network type, with increased biological plausibility, incorporating a type of cortical columnar oscillation in the form of an oscillating Topological Neighbourhood (TN), is introduced and applied alongside the standard SOM. Aspects of two neurodevelopmental disorders, autism and schizophrenia, are modelled using SOM networks, based on existing neurocomputational theories. Both standard and oscillating-TN SOM training is employed with targeted modifications in the TN width function. Computer simulations are conducted using revised versions of a previously introduced model (IPSOM) based on a new modelling hypothesis. Results/Conclusions: The results demonstrate that there is strong similarity between standard and oscillating-TN SOM modelling in terms of map formation behaviour, output and structure, while the oscillating version offers a more realistic computational analogue of brain function. Neuroscientific and computational arguments are presented to validate the proposed SOM modification within a cognitive modelling framework.