Loading…

Loading grant details…

Active NON-SBIR/STTR RPGS NIH (US)

CRCNS: Computational modeling to predict afferent firing to deep pressure touch

$1.56M USD

Funder NATIONAL CENTER FOR COMPLEMENTARY & INTEGRATIVE HEALTH
Recipient Organization University of Virginia
Country United States
Start Date Sep 06, 2024
End Date Aug 31, 2028
Duration 1,455 days
Number of Grantees 1
Roles Principal Investigator
Data Source NIH (US)
Grant ID 11081830
Grant Description

Deep pressure touch can be pleasant and calming, although sometimes intense. It is often experienced in interpersonal touch, such as a hug, and is commonly used in manual therapy and massage to relieve musculoskeletal pain. Understanding the neuronal mechanisms underlying chronic musculoskeletal pain

is a key health concern. Physical therapists commonly use deep pressure touch in their patients with musculoskeletal pain. Deep pressure touch activates different types of mechanoreceptors in skin, muscles, joints, and fascia. This project will investigate how deep pressure touch is encoded by peripheral

neural afferents - to elucidate how individual subtypes respond to such manipulation, as well as how they work together as a population. The longer-term goal is to uncover correspondences with the encoding of tissue stiffness and tension, giving rise to musculoskeletal discomfort, including myofascial pain. The main

objective of this project is to develop computational stimulus-response models of firing in mechanosensitive afferent subtypes to deep pressure touch in humans. In comparing model predictions to afferent firing, obtained via microneurography before and after soft tissue manipulation, or massage, this

effort will seek to attribute changes to tissue mechanics and/or neuronal mechanisms. The proposed methods combine microneurography recordings from human peripheral nerves, bodily physiological responses, and perceptual judgments, with computational models of time-series relationships between tissue deformation and neural firing, as well as computer vision tracking of tissue deformation.

Microneurography is highly informative about human peripheral nerve activity, but limited by the problem of sparse sampling, thus a computational approach is vital to fill in gaps at individual afferent subtype and population levels. This project focuses on recording from the peroneal nerve, which projects widely

throughout the lower leg, in particular the front and lateral sides of the calf, and the upper foot, which are sites highly relevant to musculoskeletal pain. From a clinical standpoint, the anterior of the lower leg is implicated in shin splits, the lateral posterior of the lower leg is tied to sprained ankles, and the posterior of

the foot and calf are tied to calf strain and Achilles tendinosis. These conditions are frequently addressed via soft tissue manipulation. Overall, the results of this work seek to uncover novel, fundamental insights into human somatosensation, and impact non-pharmaceutical treatment of musculoskeletal pain.

All Grantees

University of Virginia

Advertisement
Apply for grants with GrantFunds
Advertisement
Browse Grants on GrantFunds
Interested in applying for this grant?

Complete our application form to express your interest and we'll guide you through the process.

Apply for This Grant