标题:
自传体记忆系统及其神经机制Autobiographical Memory System and Its
Neural Correlates
作者:
尹璐, 毛利华, 冯胜闯, 叶香, 史煜才
关键字:
自传体记忆, 记忆系统, 操作成分, 相互作用, 多体素分析, 时间序列分析Autobiographical Memory; Memory System; Operating Component; Interaction; Multi-Voxel Analysis; Time Series Analysis
期刊名称:
《Advances in Psychology》, Vol.3 No.4, 2013-07-05
摘要:
自传体记忆作为一个复杂的，涉及众多因素的长时记忆成分，具有独特的记忆结构；相应地，自传体记忆的神经机制也包括了众多脑区。基于自传体记忆的复杂性，本文总结了先前对于自传体记忆及其神经机制的研究，从记忆系统的角度对自传体记忆包含的认知加工成分及相应的神经机制进行了归纳总结，并就各认知加工成分间的相互联系和相互作用进行了详尽的分析；同时分析了目前自传体记忆神经机制研究存在的一些局限性，包括偏重强调实验条件间差异性而对不同认知加工成分脑机制间的相互联系分析不足，只关注脑区激活的空间定位而忽视时间维度的差异信息等。最后本文提出在将来的研究中需要更多地从系统的观点出发，重视认知加工成分间的相互联系，引入多体素分析和时间序列分析以便能为自传体记忆神经机制研究提供更深入的证据。
Autobiographical memory, with special inherent structure, is a complex component of long-term memory. It has a close relationship with semantic memory and episodic memory and is also connected with many other psychological cognitive processes, such as the emotional process, self-referential process etc. Accordingly, the neural correlates of autobiographical memory consist of many brain areas, including the frontal lobe, temporal lobe, superior parietal lobe and the adjacent occipital area etc. All of the brain areas mentioned above are mainly on the left hemisphere. This article summarizes the previous researches on autobiographical memory and its neural correlates. Given the complexity of autobiographical memory, we divide different cognitive processes of autobiographical memory into 5 operating components from the perspective of memory-system. These operating components include semantic component, episodic component, self-referential component, emotional component and general cognitive processing component (cognitive process related to general memory retrieval), and each component has its underlying neural correlates. What is more important, these operating components interact with each other coherently within the autobiographical memory system and this article discusses these interactions and connections in depth. These interactions analyzed in this article includes the semantic & episodic interaction, the self-referential processing & general cognitive processing interaction, the emotional & episodic interaction, the general cognitive processing & episodic interaction and the general cognitive processing & emotional interaction. By taking the interactions among the operating components into consideration, different ideas and opinions to integrate the experiment findings are offered, and new ways and solutions to settle some heating debates in the field of autobiographical memory are proposed. Furthermore, this article points out that even though the operating components of autobiographical memory system are closely connected with one another, the previous researches didn’t pay enough attention to it. This article analyzes two problems existing in the previous studies. First, most of the previous researches spent much effort in analyzing the different activated brain areas among different experiment tasks, while leaving the common brain activation alone, which might reflect the interaction and connection among the operating components. Second, those studies investigating neural correlates of autobiographical memory using brain imaging techniques tended to overlook the different brain activations at different time points, and these temporal differences may carry important information about the neural mechanism of autobiographical memory. Finally, the article proposes two analytical methods in order to solve the problems mentioned above to some extent. First is using multi-voxel analysis instead of the conventional analysis method to reveal the useful information held by the common activated brain areas, second is employing time series analysis to analyze the changes of brain activation pattern in the temporal dimension. In sum, if researchers are going to investigate the neural mechanism of autobiographical memory thoroughly and offered more convincing evidence, they should treat the various cognitive processes of autobiographical memory as a whole, take the interactions among different components into consideration and pay more attention to the neural correlates underlying these interactions.