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Dissociable neural substrates of integration and segregation in exogenous attention

Chen, Y.; Li, A.-S.; Yu, Y.; Hu, S.; He, X.; Zhang, Y.

2026-02-26 neuroscience
10.1101/2025.11.08.687384 bioRxiv
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Impact StatementThis study offers the first direct neuroimaging evidence for the integration-segregation theory of exogenous attention by identifying dissociable neural signatures of the competing integration and segregation processes, strengthening the understanding of attentional orienting mechanisms. The integration-segregation theory proposes that early facilitation and later inhibition (i.e., inhibition of return, IOR) in exogenous attention arise from the competition between cue-target event integration and segregation. Although widely supported behaviorally, the theory lacked direct neural evidence. Here, we used event-related fMRI with an optimized cue-target paradigm to test this account. Cued targets elicited stronger activation in the frontoparietal attention networks, including the bilateral frontal eye field (FEF) and intraparietal sulcus (IPS), right temporoparietal junction (TPJ), and left dorsal anterior cingulate cortex (dACC), consistent with the notion of attentional demand of reactivating the cue-initiated representations for integration. In contrast, uncued targets engaged the medial temporal cortex, particularly the bilateral parahippocampal gyrus (PHG) and superior temporal gyrus (STG), reflecting the segregation processes associated with new object-file creation and novelty encoding. These dissociable activations provide the first direct neuroimaging evidence for the integration-segregation theory. Moreover, we observed neural interactions between IOR and cognitive conflict, suggesting a potential modulation of conflict processing by attentional orienting. Taken together, these findings provide new insights into exogenous attention by clarifying the neural underpinnings of integration and segregation and uncovering the interaction between spatial orienting and conflict processing.

Published in eLife (predicted rank #9) · training set

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