Current perspectives on galvanic vestibular stimulation in the treatment of Parkinson’s disease

ABSTRACT

Introduction: Galvanic vestibular stimulation (GVS) is a noninvasive technique that activates vestibular afferents, influencing activity and oscillations in a broad network of brain regions. Several studies have suggested beneficial effects of GVS on motor symptoms in Parkinson’s Disease (PD).

Areas covered: A comprehensive overview of the stimulation techniques, potential mechanisms of action, challenges, and future research directions.

Expert opinion: This emerging technology is not currently a viable therapy. However, a complementary therapy that is inexpensive, easily disseminated, customizable, and portable is sufficiently enticing that continued research and development is warranted. Future work utilizing biomedical engineering approaches, including concomitant functional neuroimaging, have the potential to significantly increase efficacy. GVS could be explored for other PD symptoms including orthostatic hypotension, dyskinesia, and sleep disorders.

KEYWORDS:

• Galvanic vestibular stimulation
• parkinson’s disease
• neuromodulation
• eeg
• fMRI
• motor function
• the vestibular system

Article highlights

• Galvanic Vestibular Stimulation (GVS) is a safe, non-invasive brain stimulation technique that can influence neural activity in various cortical and subcortical areas related to vestibular and multisensory processing.

• Several studies have suggested that noisy GVS, applied at imperceptible current intensity, can alleviate some of the motor symptoms in PD. More recently, it has been shown that GVS can modulate cortical oscillations and induce neurochemical changes in the substantia nigra and parvocellular medial vestibular nucleus.

• Symptomatic improvements produced by GVS are typically mild and often involve substantial inter- and intra-subject variability in the results. The effects of GVS are significantly stimulus-dependent, yet to date, how to optimize stimulation parameters to maximize behavioral changes in PD is unknown.

• Utilizing biomedical engineering approaches to optimize the choice of stimulation parameters based on individual-specific characteristics and dynamic brain states could enhance stimulation effects.

• Concurrent GVS and neuroimaging analysis will enable non-invasive assessment of the modulatory effects of stimulation and resultant behavior changes, significantly enhancing the understanding of GVS mechanisms.

Over the next 5 years, employing deep learning could promote GVS development by assisting in extracting features that reflect stimulation effects and designing precision stimuli.

Declaration of interest

The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or conflict with the subject matter or materials discussed in this manuscript apart from those disclosed.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Additional information

Funding

S Lee has received funding from Rina M. Bidin Foundation Fellowship in Research of Brain Treatments. A Liu has received a grant from the National Natural Science Foundation of China (61701158) and USTC research funds of the Double First-class Initiative (YD2100002004).