ArticleAnnual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference2024
Optogenetic Locus Coeruleus Stimulation Improves Pupil Size Tracking of Cortical State.
Article in Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Long-term Locus Coeruleus Stimulation Exacerbates Tau Pathology in PS19 Mice.bioRxiv : the preprint server for biology · 2025Article
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Authors and funding
3 authors.
Funding
Abstract
Brain state heavily influences our perception, cognition, and behavior. Multiple neuromodulatory systems, including the locus coeruleus - norepinephrine (LC-NE) system, contribute to the regulation of brain state. This research harnesses machine learning and optogenetics technologies to probe the impact of the LC on cortical state and pupillary responses in awake mice. Our integrative approach combines EEG recordings with pupillometry to capture the LC's optogenetic activation, evoking notable EEG spectral power shifts synchronized with pupil dilation. These changes provide a noninvasive glimpse into the cortical states, modulated by the LC's activity. Central to our methodology is the application of Support Vector Regression (SVR) modeling, which robustly correlates LC-induced pupillary changes with EEG power fluctuations. These insights help reinforce the LC's crucial role in modulating prefrontal activity and its regulatory influence over arousal states. Beyond advancing our comprehension of the LC's function, our work also highlights the potential for developing closed-loop stimulation systems. These systems, integrated with machine-learning techniques and multimodal data, could offer precise therapeutic interventions for neurological disorders characterized by abnormal arousal states.
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Registered trials
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