ArticlebioRxiv : the preprint server for biology2026
Bayesian-enhanced closed-loop optimization of ultrasound protocols for targeted and precise neuromodulation.
Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Low-intensity focused ultrasound (LIFU) is a promising neuromodulation modality, but challenges related to high response variability and the poorly understood parameter space undermine progress in clinical applications. To facilitate the development of therapeutic LIFU protocols, we developed an approach for Bayesian-enhanced adaptive control of ultrasound neuromodulation (BEACUN). BEACUN enables efficient, data-driven parameter mapping using a limited number of stimulation-response evaluations. We used functional ultrasound imaging (fUSI) to measure the neural responses to LIFU stimulation in real time, and we carried out
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