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Deciphering the impairment of perimenopausal insomnia on visual search from a neurocognitive processing perspective
Liyong Yu1, Yucai Luo1, Wenting Lin2
1School of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Study Objectives:
Perimenopausal insomnia (PMI) is associated with observable performance impairments in visual search tasks. This study examines how various cognitive processing stages contribute to search performance delays in PMI compared to healthy controls (HCs).
Methods:
We recruited 76 participants diagnosed with PMI and 63 HCs. Event-related potentials (ERPs) were recorded as participants engaged in a visual search task, reporting the orientation of a color popout target within an array of ellipses. We analyzed group differences in behavioral performance and ERP components across cognitive processing stages.
Results:
Compared to HCs, PMI patients exhibited behavioral response delays, although accuracy was not different between groups. Electrophysiological analyses revealed group differences across several ERP components. Firstly, the N1 component's amplitude increased bilaterally, suggesting enhanced visual sensory processing. Secondly, a slower and smaller N2pc indicated reduced attentional orienting. Thirdly, a decreased sustained posterior-contralateral negativity amplitude pointed to deficits in target discrimination. Fourthly, an increased amplitude of the stimulus-locked lateralized readiness potential (LRP), with unchanged latency, suggested heightened neural inputs for maintaining motor initiation speed. Fifthly, prolonged response-locked LRP latency indicated slower motor execution. Finally, these changes in ERP components, along with significant correlations between LRP components and insomnia symptoms, suggest potential neural biomarkers for PMI.
Conclusions:
Our findings provide high-temporal-resolution insights into the neurocognitive disruptions associated with PMI, highlighting how sleep disturbances affect cognitive processing in visual tasks. These insights enhance our understanding of PMI and contribute to discussions on neural mechanisms driving behavioral performance in various conditions.
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