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心智和大脑中的模块化过程。

Modular processes in mind and brain.

机构信息

University of Pennsylvania, Philadelphia, PA 19104, USA.

出版信息

Cogn Neuropsychol. 2011 May;28(3-4):156-208. doi: 10.1080/02643294.2011.557231.

DOI:10.1080/02643294.2011.557231
PMID:22185235
Abstract

One approach to understanding a complex process starts with an attempt to divide it into modules·, sub-processes that are independent in some sense, and have distinct functions. In this paper, I discuss an approach to the modular decomposition of neural and mental processes. Several examples of process decomposition are presented, together with discussion of inferential requirements. Two examples are of well-established and purely behavioural realizations of the approach (signal detection theory applied to discrimination data; the method of additive factors applied to reaction-time data), and lead to the identification of mental modules. Other examples, leading to the identification of modular neural processes, use brain measures, including the fMRI signal, the latencies of electrophysiological events, and their amplitudes. Some measures are pure (reflecting just one process), while others are composite. Two of the examples reveal mental and neural modules that correspond. Attempts to associate brain regions with behaviourally defined processing modules that use a brain manipulation (transcranial magnetic stimulation, TMS) are promising but incomplete. I show why the process-decomposition approach discussed here, in which the criterion for modularity is separate modifiability, is superior for modular decomposition to the more frequently used task comparison procedure (often used in cognitive neuropsychology) and to its associated subtraction method. To demonstrate the limitations of task comparison, I describe the erroneous conclusion to which it has led about sleep deprivation, and the interpretive difficulties in a TMS study.

摘要

理解复杂过程的一种方法是尝试将其分解为模块,即从某种意义上说是独立的、具有不同功能的子过程。本文讨论了一种对神经和心理过程进行模块化分解的方法。本文呈现了几个过程分解的示例,并讨论了推理要求。其中两个示例是该方法的成熟且纯行为实现(应用于辨别数据的信号检测理论;应用于反应时数据的加因素法),并导致了心理模块的识别。其他示例导致了模块化神经过程的识别,使用了大脑测量,包括 fMRI 信号、电生理事件的潜伏期及其幅度。有些测量是纯的(仅反映一个过程),而有些则是组合的。有两个示例揭示了与行为定义的处理模块相对应的心理和神经模块。使用脑操作(经颅磁刺激,TMS)将大脑区域与行为定义的处理模块相关联的尝试是有希望的,但并不完整。我展示了为什么这里讨论的过程分解方法(其中模块化的标准是可单独修饰性)对于模块化分解优于更常用的任务比较过程(常用于认知神经心理学)及其相关的减法方法。为了演示任务比较的局限性,我描述了它导致的关于睡眠剥夺的错误结论,以及 TMS 研究中的解释困难。

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