Laszlo Sarah, Armstrong Blair C
Department of Psychology, State University of New York, Binghamton, 4400 Vestal Parkway East, Binghamton, NY 13902, United States.
Basque Center on Cognition, Brain, and Language, Paseo Mikeletegi 69, Piso 2, San Sebastian 20009, Spain.
Brain Lang. 2014 May;132:22-7. doi: 10.1016/j.bandl.2014.03.002. Epub 2014 Mar 29.
The Parallel Distributed Processing (PDP) framework is built on neural-style computation, and is thus well-suited for simulating the neural implementation of cognition. However, relatively little cognitive modeling work has concerned neural measures, instead focusing on behavior. Here, we extend a PDP model of reading-related components in the Event-Related Potential (ERP) to simulation of the N400 repetition effect. We accomplish this by incorporating the dynamics of cortical post-synaptic potentials--the source of the ERP signal--into the model. Simulations demonstrate that application of these dynamics is critical for model elicitation of repetition effects in the time and frequency domains. We conclude that by advancing a neurocomputational understanding of repetition effects, we are able to posit an interpretation of their source that is both explicitly specified and mechanistically different from the well-accepted cognitive one.
平行分布式处理(PDP)框架建立在神经式计算的基础上,因此非常适合模拟认知的神经实现。然而,相对较少的认知建模工作涉及神经测量,而是侧重于行为。在这里,我们将事件相关电位(ERP)中与阅读相关成分的PDP模型扩展到对N400重复效应的模拟。我们通过将皮层突触后电位的动态变化(ERP信号的来源)纳入模型来实现这一点。模拟表明,应用这些动态变化对于模型在时域和频域中引发重复效应至关重要。我们得出结论,通过推进对重复效应的神经计算理解,我们能够提出一种对其来源的解释,这种解释既明确具体,又在机制上与广为接受的认知解释不同。