Machines Like Us

Among nature's most impressive feats of engineering is the remarkably flexible and self-optimizing quality of human cognition. People seem to dynamically determine whether speed or accuracy is of utmost importance in a certain task, or whether they should continue with a current approach or begin anew with another, or whether they should rely on logic or intuition to solve a certain problem. A topic of intense research in cognitive neuroscience is how cognition can be made so flexible.

One possibility proposed by by Brown, Reynolds & Braver is that cognitive control is multi-faceted, in that different forms of control are engaged in response to different scenarios. For example, if tasks or responses shift unpredictably, then behavior may be generally slowed in order to reduce the chances for responding before stimuli have been adequately processed. Alternatively, even if the responses and task remain the same, new stimuli may appear that disrupt ongoing processing. A different form of control may then engage increased or "tightened" attentional focus, so as to reduce interference from the irrelevant or incongruent stimuli.

Brown et al. argue that these two functions each fill distinct computational roles: general slowing is not helpful if the cause of conflict is from incongruent stimuli, and tightened focus on the current task is not helpful if that task has unpredictably switched to something entirely different.

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