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Journal of Cognitive Neuroscience

November 2011, Vol. 23, No. 11, Pages 3318-3330
(doi: 10.1162/jocn_a_00030)
© 2011 Massachusetts Institute of Technology
Orienting Attention in Time Activates Left Intraparietal Sulcus for Both Perceptual and Motor Task Goals
Article PDF (251.99 KB)
Abstract

Attention can be directed not only toward a location in space but also to a moment in time (“temporal orienting”). Temporally informative cues allow subjects to predict when an imminent event will occur, thereby speeding responses to that event. In contrast to spatial orienting, temporal orienting preferentially activates left inferior parietal cortex. Yet, left parietal cortex is also implicated in selective motor attention, suggesting its activation during temporal orienting could merely reflect incidental engagement of preparatory motor processes. Using fMRI, we therefore examined whether temporal orienting would still activate left parietal cortex when the cued target required a difficult perceptual discrimination rather than a speeded motor response. Behaviorally, temporal orienting improved accuracy of target identification as well as speed of target detection, demonstrating the general utility of temporal cues. Crucially, temporal orienting selectively activated left inferior parietal cortex for both motor and perceptual versions of the task. Moreover, conjunction analysis formally revealed a region deep in left intraparietal sulcus (IPS) as common to both tasks, thereby identifying it as a core neural substrate for temporal orienting. Despite the context-independent nature of left IPS activation, complementary psychophysiological interaction analysis revealed how the functional connectivity of left IPS changed as a function of task context. Specifically, left IPS activity covaried with premotor activity during motor temporal orienting but with visual extrastriate activity during perceptual temporal orienting, thereby revealing a cooperative network that comprises both temporal orienting and task-specific processing nodes.