Neuromodulation in Alzheimer's Disease: A Review With Illustrative Pilot Data Using Focused Ultrasound.

Alzheimer's disease (AD) is increasingly characterized as a disorder of large-scale brain networks driven by synaptic dysfunction, excitation-inhibition imbalance, and progressive breakdown of hippocampal-cortical communication. Although recently developed disease-modifying therapies target molecular pathology, their clinical benefits remain modest, underscoring the need for interventions that target dysfunctional circuits. Neuromodulatory techniques such as transcranial magnetic stimulation, transcranial electrical stimulation, and deep brain stimulation demonstrate safety and act at network/system levels to engage target sites, yet these techniques are limited by their ability to modulate deep anatomic structures and/or their invasiveness. Focused ultrasound (FUS) offers the distinct capability of modulating cortical and deep subcortical networks noninvasively and with anatomic precision. Preclinical studies demonstrate that FUS neuromodulation can influence mechanosensitive ion channels, synaptic plasticity, neurotrophic signaling, and oscillatory dynamics, with downstream effects on distributed memory networks. Early human investigations similarly suggest that FUS neuromodulation can alter functional connectivity within default mode, frontoparietal, and limbic networks. Together, these findings support a framework in which FUS may help reshape pathological network states that emerge prior to irreversible neurodegeneration. Here, we present a narrative review of evidence across neuromodulation approaches to define principles of circuit engagement in AD and discuss a network-based rationale for ultrasound interventions. As an illustration of this framework, we also report preliminary findings from a phase I pilot study of FUS neuromodulation in amyloid-positive mild cognitive impairment demonstrating safety, tolerability, and measurable modulation of hippocampal connectivity. We conclude that mechanistic biomarkers of network response may accelerate translational development and guide controlled trials in the future.