默认模式网络
任务正网络
心理学
任务(项目管理)
大脑活动与冥想
认知心理学
神经科学
神经活动
背
持续绩效任务
控制(管理)
功能连接
脑电图
计算机科学
认知
人工智能
医学
管理
经济
解剖
作者
Michael Esterman,Sarah Noonan,Monica D. Rosenberg,Joseph DeGutis
出处
期刊:Cerebral Cortex
[Oxford University Press]
日期:2012-08-31
卷期号:23 (11): 2712-2723
被引量:309
标识
DOI:10.1093/cercor/bhs261
摘要
Despite growing recognition that attention fluctuates from moment-to-moment during sustained performance, prevailing analysis strategies involve averaging data across multiple trials or time points, treating these fluctuations as noise. Here, using alternative approaches, we clarify the relationship between ongoing brain activity and performance fluctuations during sustained attention. We introduce a novel task (the gradual onset continuous performance task), along with innovative analysis procedures that probe the relationships between reaction time (RT) variability, attention lapses, and intrinsic brain activity. Our results highlight 2 attentional states-a stable, less error-prone state ("in the zone"), characterized by higher default mode network (DMN) activity but during which subjects are at risk of erring if DMN activity rises beyond intermediate levels, and a more effortful mode of processing ("out of the zone"), that is less optimal for sustained performance and relies on activity in dorsal attention network (DAN) regions. These findings motivate a new view of DMN and DAN functioning capable of integrating seemingly disparate reports of their role in goal-directed behavior. Further, they hold potential to reconcile conflicting theories of sustained attention, and represent an important step forward in linking intrinsic brain activity to behavioral phenomena.
科研通智能强力驱动
Strongly Powered by AbleSci AI