May 23, 2023, 15.00:

Christopoulos, Vasileios (University of California, Riverside):

Functional ultrasound imaging in neuroscience

Functional ultrasound imaging in neuroscienceRecent advances in neuroimaging technology have significantly contributed to a better understanding of human brain organization, and the development and application of more efficient clinical programs. However, the limitations and tradeoffs inherent to the existing techniques, prevent them from providing large-scale imaging of neural activity with high spatiotemporal resolution, deep penetration, and specificity in awake and behaving participants. Recently, functional ultrasound imaging (fUSI) was introduced as a revolutionary technology that provides a unique combination of spatial coverage, unprecedented spatiotemporal resolution (~100 μm, up to ~10 ms), high sensitivity (~ 1 mm/s velocity) to detect relative hemodynamic changes of only 2% without averaging over multiple trials, and compatibility with freely moving animals. While fUSI is a hemodynamic technique, its superior spatiotemporal performance and single-trial sensitivity offer a substantially closer connection to the underlying neuronal signals than achievable with other hemodynamic methods such as fMRI. In addition, the relative simplicity and portability of ultrasound have allowed fUSI to be performed in awake and behaving participants, providing minimally invasive neural imaging in species ranging from mice to humans. In vivo fUSI was first reported in 2011 by imaging cerebral blood volume (CBV) changes in the micro-vascularization of the rat brain during whisker stimulation. Since then, this technique has been applied to brain activity imaging during olfactory stimuli, resting state connectivity and behavioral tasks on freely moving rodents. Our team took the next major leap in fUSI and demonstrated for the first time that functional ultrasound images encode the motor intention of non-human primates (i.e., monkeys) before they perform an actual movement - a prerequisite to brain-machine interfaces (BMIs). Current BMI technologies that can give movement back to those who have lost it due to neurological injury or disease, require invasive brain surgery to read out neural activity. Our results showed that fUSI can decode detailed brain activity without damaging brain tissues. This is a critical step in the development of neuro-recording and brain interface tools that are less invasive, with high resolution, and scalable across species. Recently, we combined fUSI technology with machine learning to study the pathophysiology of neurological (e.g., chronic pain, epilepsy, urinary incontinence) and psychiatric (e.g., schizophrenia) diseases in pre-clinical and clinical studies, and to guide therapeutic neuromodulation treatments – a technology that currently does not exist. We performed the first in-human fUSI of spinal cord response to epidural electrical stimulation in patients who underwent surgery for chronic back pain treatment. We demonstrated that fUSI can successfully evaluate the effectiveness of a stimulation protocol in a single trial, which is of fundamental importance for developing real-time closed-loop neuromodulation systems. Additionally, we showed that fUSI can detect region-specific changes in spinal cord hemodynamics associated with micturition, opening a new avenue to develop spinal cord machine interface for patients with urinary incontinence diseases. Overall, our work establishes fUSI as a promising platform for neuroscientific investigation with potential for profound clinical impact.

June 8, 2023, 15.00:

Tung, Jenny (Max Planck Institute for Evolutionary Anthropology, Leipzig)

Topic and abstract to be announced soon.