Mechanics Of Ultrasonic Neuromodulation In A Mouse Subject

Abstract

Ultrasound neuromodulation (UNM), where a region in the brain is targeted by focused ultrasound (FUS), which, in turn, causes excitation or inhibition of neural activity, has recently received considerable attention as a promising tool for neuroscience. Despite its great potential, several aspects of UNM are still unknown. An important question pertains to the off-target sensory effects of UNM and their dependence on stimulation frequency. To understand these effects, we have developed a finite-element model of a mouse, including elasticity and viscoelasticity, and used it to interrogate the response of mouse models to focused ultrasound (FUS). We find that, while some degree of focusing and magnification of the signal is achieved within the brain, the induced pressure-wave pattern is complex and delocalized. In addition, we find that the brain is largely insulated, or 'cloaked', from shear waves by the cranium and that the shear waves are largely carried away from the skull by the vertebral column, which acts as a waveguide. We find that, as expected, this waveguide mechanism is strongly frequency dependent, which may contribute to the frequency dependence of UNM effects. Our calculations further suggest that off-target skin locations experience displacements and stresses at levels that, while greatly attenuated from the source, could nevertheless induce sensory responses in the subject.

Application of Data-Driven computing to patient-specific simulation of brain neuromodulation

“…The iteration is repeated until PDzj+1 = PDzj, i.e., until the data association to points in the material data set remains invariant. The convergence properties of the fixed-point solver (13) have been investigated in [16].…”

“…For present purposes, and for the sake of completeness, it only need to characterize the flat-norm distance between harmonic histories. For a precise definition of flat norm and the proof of the following formulas, we refer the reader to [16]. Let us consider two states and as Dirac measures with complex amplitudes and and frequencies ω ’ and ω ″.…”

“…A simple Data-Driven solver consists of the fixed point iteration [16]: for j = 0,1,… and z 0 ∈ Z arbitrary, where and denotes the closest point projection in Z onto and . This solver Eq.…”

“…We demonstrate the range and scope of the model-free Data-Driven brain mechanics framework through an application to transcranial ultrasound stimulation. Transcranial ultrasound has elicited growing interest in both low-intensity mode, suited to neuromodulation applications [2,10,[14][15][16][18][19][20], as well as in high-intensity mode, 3/8 germane to tumor ablation applications [11,23].…”

“…We demonstrate the range and scope of the model-free Data-Driven brain mechanics framework through an application to transcranial harmonic stimulation. Transcranial ultrasound has elicited growing interest in both low-intensity mode, suited to neuromodulation applications [2,10,[14][15][16][18][19][20], as well as in high-intensity mode, germane to tumor ablation applications [11,23]. For purposes of demonstration of the methodology, we use the recently published atlas of viscoelastic properties of brain tissue [9], acquired at a single frequency of 50 Hz from 134 human subjects.…”