Analyzing and shaping human attentional networks

被引:158
作者
Posner, Michael I. [1 ]
Sheese, Brad E.
Odludas, Yalcin
Tang, YiYuan
机构
[1] Univ Oregon, Dept Psychol, Eugene, OR 97403 USA
[2] Dalian Univ Technol, Inst Neuroinformat, Dalian, Peoples R China
关键词
alerting; DCM (Dynamic causal model for connectivity analysis); DTI (Diffusion tensor imaging); EEG frequency (electroencephalographic); fMRI (functional magnetic resonance imaging); executive attention; orienting; self-regulation;
D O I
10.1016/j.neunet.2006.08.004
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper we outline a conception of attentional networks arising from imaging studies as connections between activated brain areas carrying out localized mental operations. We consider both the areas of functional activation (nodes) and the structural (DTI) and functional connections (I)CM) between them in real time (EEG, frequency analysis) as important tools in analyzing the network. The efficiency of network function involves the time course of activation of nodes and their connectivity to other areas of the network. We outline landmarks in the development of brain networks underlying executive attention from infancy and childhood. We use individual differences in network efficiency to examine genetic alleles that are related to performance. We consider how animal studies might be used to determine the genes that influence network development. Finally we indicate how training may aid in enhancing attentional networks. Our goal is to show the wide range of methods that can be used to suggest and analyze models of network function in the study of attention. (c) 2006 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1422 / 1429
页数:8
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