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Evolving processing speed asymmetries and hemispheric interactions in a neural network model

机译:神经网络模型中不断发展的处理速度不对称性和半球相互作用

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摘要

Substantial experimental data suggests that the cerebral hemispheres have different processing speeds, and that this may contribute to hemispheric specialization. Here, we use evolutionary computation models to examine whether asymmetric hemispheric processing speeds and lateralization can emerge in neural networks from the need to respond quickly to stimuli and/or to minimize energy consumption. Simulated neuroevolution produced networks with left-right asymmetric processing speeds whenever fitness depended on energy minimization, but not on quickness of response. The results also provide support for a recent hypothesis that subcortical cross-midline interactions are inhibitory/competitive.
机译:大量的实验数据表明,大脑半球的处理速度不同,这可能有助于大脑半球的专业化。在这里,我们使用进化计算模型来检查神经网络是否会因需要快速响应刺激和/或使能量消耗最小化而出现不对称半球处理速度和偏侧化的问题。只要适合度取决于能量最小化,而不取决于响应速度,模拟的神经进化产生的网络就具有左右不对称的处理速度。这些结果也为最近的假设提供了支持,即皮层下跨中线相互作用具有抑制性/竞争性。

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