Transcranial focused ultrasound remotely modulates extrastriate visual cortex by stimulating frontal eye field with subregion specificity.

Low-intensity transcranial focused ultrasound (tFUS) has emerged as a powerful neuromodulation tool characterized by its deep penetration and precise spatial targeting to influence neural activity. Our study directed low-intensity tFUS stimulation onto a region of prefrontal cortex (the frontal eye field, or FEF) of a rhesus macaque to examine its impact on a remote site, the extrastriate visual cortex (area V4) through this top-down modulatory circuit that has been studied extensively with electrical microstimulation.To measure the impact of tFUS stimulation, we recorded local field potentials and multi-unit spiking activities from a multi-electrode array implanted in the visual cortex.

Low-intensity transcranial focused ultrasound suppresses pain by modulating pain-processing brain circuits.

There is an urgent and unmet clinical need to develop nonpharmacological interventions for chronic pain management because of the critical side effects of opioids. Low-intensity transcranial focused ultrasound (tFUS) is an emerging noninvasive neuromodulation technology with high spatial specificity and deep brain penetration. Here, we developed a tightly focused 128-element ultrasound transducer to specifically target small mouse brains using dynamic focus steering.

Transcranial Focused Ultrasound Remotely Modulates Extrastriate Visual Cortex with Subregion Specificity.

Low-intensity transcranial focused ultrasound (tFUS) has emerged as a powerful neuromodulation tool characterized by its deep penetration and precise spatial targeting to influence neural activity. Our study directed low-intensity tFUS stimulation onto a region of prefrontal cortex (the frontal eye field, or FEF) of a rhesus macaque to examine its impact on a remote site, the extrastriate visual cortex (area V4). This pair of cortical regions form a top-down modulatory circuit that has been studied extensively with electrical microstimulation.

Multimodal deep learning for Alzheimer's disease dementia assessment.

Worldwide, there are nearly 10 million new cases of dementia annually, of which Alzheimer's disease (AD) is the most common. New measures are needed to improve the diagnosis of individuals with cognitive impairment due to various etiologies. Here, we report a deep learning framework that accomplishes multiple diagnostic steps in successive fashion to identify persons with normal cognition (NC), mild cognitive impairment (MCI), AD, and non-AD dementias (nADD).