Functional fractionation of the stimulus-driven attention network
Han, Suk Won
It has long been recognized that people demonstrate orienting responses to novel, salient stimuli in the environment. The presentation of such an oddball stimulus does not only induce physiological, reflexive responses, but also allocation of cognitive processing resource to the stimulus. Specifically, once the oddball is detected, and attention is switched to the oddball (attentional orienting). This stimulus-driven attentional capture is followed by an evaluative process to determine how to react to the attended oddball; if the oddball is evaluated to be behaviorally significant, it will be acted upon. Otherwise, attention will be redirected to other behaviorally relevant stimuli (reorienting of attention). While a network of brain regions, consisting of anterior insula (AI), inferior frontal junction (IFJ), and temporo-parietal junction (TPJ) have been associated with stimulus-driven attention, how distinct processes evoked by the oddball presentation are implemented in the brain remains unknown. This is primarily due to methodological limitations of previous approaches in dissociating neural substrates underlying each component of oddball processing. In the first chapter of this dissertation, I introduce a novel experimental approach to distinguish neural substrates associated with the distinct cognitive processes evoked by an oddball presentation. The second chapter reports findings that each individual node in the stimulus-driven network plays a different role in stimulus-driven attention, such that the AI, along with the anterior cingulate cortex (ACC), is primarily involved in attentional orienting/reorienting, while the TPJ is involved in stimulus evaluation. The IFJ is implicated in both processes. Having established the functional dissociation of the network, the third and fourth chapters further elucidate the specific function subserved by each individual region in the network. Specifically, the third chapter presents findings that the AI is not only involved in detecting and switching attention to a salient stimulus, but also plays a role in emotional, affective processes. The fourth chapter reports findings that the ACC is specialized in switching of attentional sets, whereas the AI is primarily involved in detecting the occurrence of behaviorally significant events. Having specified specific roles of each individual node in the stimulus-driven attention network, the dissertation concludes by envisioning how external sensory inputs are registered, interpreted, and responded in the human information processing system.