The brain uses the somatosensory system to interact with the environment and control movements. Additionally, many movement disorders are associated with deficits in the somatosensory sensory system. Thus, understanding the somatosensory system is essential for developing treatments for movement disorders. Previous studies have extensively examined the role of the somatosensory…
The brain uses the somatosensory system to interact with the environment and control movements. Additionally, many movement disorders are associated with deficits in the somatosensory sensory system. Thus, understanding the somatosensory system is essential for developing treatments for movement disorders. Previous studies have extensively examined the role of the somatosensory system in controlling the lower and upper extremities; however, little is known about the contributions of the orofacial somatosensory system. The overall goal of this study was to determine factors that influence the sensitivity of the orofacial somatosensory system. To measure the somatosensory system's sensitivity, transcutaneous electrical current stimulation was applied to the skin overlaying the trigeminal nerve on the lower portion of the face. After applying stimulation, participants' sensitivity was determined through the detection of the electrical stimuli (i.e., perceptual threshold). The data analysis focused on the impact of (1) stimulation parameters, (2) electrode placement, and (3) motor tasks on the perceptual threshold. The results showed that, as expected, stimulation parameters (such as stimulation frequency and duration) influenced perceptual thresholds. However, electrode placement (left vs. right side of the face) and motor tasks (lip contraction vs. rest) did not influence perceptual thresholds. Overall, these findings have important implications for designing and developing therapeutic neuromodulation techniques based on trigeminal nerve stimulation.
A current thrust in neurorehabilitation research involves exogenous neuromodulation of peripheral nerves to enhance neuroplasticity and maximize recovery of function. This dissertation presents the results of four experiments aimed at assessing the effects of trigeminal nerve stimulation (TNS) and occipital nerve stimulation (ONS) on motor learning, which was behaviorally characterized…
A current thrust in neurorehabilitation research involves exogenous neuromodulation of peripheral nerves to enhance neuroplasticity and maximize recovery of function. This dissertation presents the results of four experiments aimed at assessing the effects of trigeminal nerve stimulation (TNS) and occipital nerve stimulation (ONS) on motor learning, which was behaviorally characterized using an upper extremity visuomotor adaptation paradigm. In Aim 1a, the effects of offline TNS using clinically tested frequencies (120 and 60 Hz) were characterized. Sixty-three participants (22.75±4.6 y/o), performed a visuomotor rotation task and received TNS before encountering rotation of hand visual feedback. In Aim 1b, TNS at 3 kHz, which has been shown to be more tolerable at higher current intensities, was evaluated in 42 additional subjects (23.4±4.6 y/o). Results indicated that 3 kHz stimulation accelerated learning while 60 Hz stimulation slowed learning, suggesting a frequency-dependent effect on learning. In Aim 2, the effect of online TNS using 120 and 60 Hz were characterized to determine if this protocol would deliver better outcomes. Sixty-three participants (23.2±3.9 y/o) received either TNS or sham concurrently with perturbed visual feedback. Results showed no significant differences among groups. However, a cross-study comparison of results obtained with 60 Hz offline TNS showed a statistically significant improvement in learning rates with online stimulation relative to offline, suggesting a timing-dependent effect on learning. In Aim 3, TNS and ONS were compared using the best protocol from previous aims (offline 3 kHz). Additionally, concurrent stimulation of both nerves was explored to look for potential synergistic effects. Eighty-four participants (22.9±3.2 y/o) were assigned to one of four groups: TNS, ONS, TNS+ONS, and sham. Visual inspection of learning curves revealed that the ONS group demonstrated the fastest learning among groups. However, statistical analyses did not confirm this observation. In addition, the TNS+ONS group appeared to learn faster than the sham and TNS groups but slower than the ONS only group, suggesting no synergistic effects using this protocol, as initially hypothesized.
The results provide new information on the potential use of TNS and ONS in neurorehabilitation and performance enhancement in the motor domain.
Sensorimotor adaptation is a type of learning that allows sustaining accurate movements by adjusting motor output. This allows the brain to adapt to temporary changes when engaged in a certain task. Within sensorimotor adaptation, visuomotor adaptation (VMA) is one’s ability to correct a visual perturbation. In this study, we present…
Sensorimotor adaptation is a type of learning that allows sustaining accurate movements by adjusting motor output. This allows the brain to adapt to temporary changes when engaged in a certain task. Within sensorimotor adaptation, visuomotor adaptation (VMA) is one’s ability to correct a visual perturbation. In this study, we present preliminary results on the effects of VMA with the control group, compared to groups undergoing trigeminal nerve stimulation (TNS) or SHAM (placebo) effects. Twenty-two healthy subjects with no past medical history participated in this study. Subjects performed a visuomotor rotation task, which required gradually adapting to a perturbation between hand motion and corresponding visual feedback. Five total blocks were completed: two familiarization blocks, one baseline block, one rotation block with a 30◦ counterclockwise rotation, and one washout block with no rotation. The control group performed better than the 120 Hz (TNS) and SHAM groups due to less directional error (DE) on the respective learning curves. Additionally, the control group adapted faster (less DE) than the SHAM groups that either felt stimulation, or did not feel the stimulation. The results yield new information regarding VMA which can be used in the future when comparing sensorimotor adaptation and its many applications.
