- Member of: Barrett, The Honors College Thesis/Creative Project Collection
- Resource Type: Text
The aim of this study was to assess whether exposing individuals who are 6-month post-stroke with an upper extremity motor deficit and some form of speech impairment (aphasia and/or apraxia) to upper extremity training utilizing Startle Adjuvant Rehabilitation Therapy (START) would result in improvement in symptoms of speech impairment. It was hypothesized that while scores on Diadochokinetic Rate (a measure of apraxia) and Repetition (a measure of aphasia) would improve by timepoint with START as compared to the Control group, measures of aphasia including Spontaneous Speech, Auditory Verbal Comprehension, and Naming would not be different in scores by timepoint. Subjects were recruited from two separate ongoing studies consisting of three days of similar upper extremity training on certain functional tasks with and without START and the speech assessments utilized were pulled from the Western Aphasia Battery (Revised) and Apraxia Battery for Adults 2nd Edition. It was found that there were no statistically significant differences by timepoint in either condition for any of the speech assessments. This proof-of-concept study is the first to assess whether the StartReact effect, when applied to the upper extremity domain, will translate into measurable improvements in speech impairment despite the lack of any speech training.
Along with aging, sleep deprivation is correlated with learning deficits. Research has shown that a lack of sleep negatively impacts motor skill learning and consolidation. Since there is a link between sleep and learning, as well as learning and the reticulospinal system, these observations raise the question: does sleep deprivation underlie reticulospinal delays? We hypothesized that sleep deprivation was correlated to a slower startle response, indicating a delayed reticulospinal system. Our objectives were to observe the impact of sleep deprivation on 1) the startle response (characterized by muscle onset latency and percentage of startle responses elicited) and 2) functional performance (to determine whether subjects were sufficiently sleep deprived).
21 young adults participated in two experimental sessions: one control session (8-10 hour time in bed opportunity for at least 3 nights prior) and one sleep deprivation session (0 hour time in bed opportunity for one night prior). The same protocol was conducted during each session. First, subjects were randomly exposed to 15 loud, startling acoustic stimuli of 120 dB. Electromyography (EMG) data measured muscle activity from the left and right sternocleidomastoid (LSCM and RSCM), biceps brachii, and triceps brachii. To assess functional performance, cognitive, balance, and motor tests were also administered. The EMG data were analyzed in MATLAB. A generalized linear mixed model was performed on LSCM and RSCM onset latencies. Paired t-tests were performed on the percentage of startle responses elicited and functional performance metrics. A p-value of less than 0.05 indicated significance.
Thirteen out of 21 participants displayed at least one startle response during their control and sleep deprived sessions and were further analyzed. No differences were found in onset latency (RSCM: control = 75.87 ± 21.94ms, sleep deprived = 82.06 ± 27.47ms; LSCM: control = 79.53 ± 17.85ms, sleep deprived = 78.48 ± 20.75ms) and percentage of startle responses elicited (control = 84.10 ± 15.53%; sleep deprived = 83.59 ± 18.58%) between the two sessions. However, significant differences were observed in reaction time, TUG with Dual time, and average balance time with the right leg up. Our data did not support our hypothesis; no significant differences were seen between subjects’ startle responses during the control and sleep deprived sessions. However, sleep deprivation was indicated with declines were observed in functional performance. Therefore, we concluded that sleep deprivation may not affect the startle response and underlie delays in the reticulospinal system.
movement to become faster, more accurate and efficient, declines with age. Initial skill acquisition is dominated by cortical structures; however as learning proceeds, literature from
rodents and songbirds suggests that there is a transition away from cortical execution. Recent
evidence indicates that the reticulospinal system plays an important role in integration and
retention of learned motor skills. The brainstem has known age-rated deficits including cell
shrinkage & death. Given the role of the reticulospinal system in skill acquisition and older
adult’s poor capacity to learn, it begs the question: are delays in the reticulospinal system
associated with older adult’s poor capacity to learn?
Our objective was to evaluate if delays in the reticulospinal system (measured via the
startle reflex) and corticospinal system (measured via Transcranial Magnetic Stimulation (TMS) are correlated to impairment of motor learning in older adults. We found that individuals with fast startle responses resembling those of younger adults show the most improvement and retention while individuals with delayed startle responses show the least. We also found that there was no relationship between MEP latencies and improvement and retention. Moreover, linear regression analysis indicated that startle onset latency exists within a continuum of learning outcomes suggesting that startle onset latency may be a sensitive measure to predict learning deficits in older adults. As there exists no method to determine an individual’s relative learning capacity, these results open the possibility of startle, which is an easy and inexpensive behavioral measure and can be used to determine learning deficits in older adults to facilitate better dosing during rehabilitation therapy.
Our objective was to evaluate if delays in the reticulospinal system (measured via the startle reflex) are correlated to impairment of motor learning in older adults. We found that individuals with fast startle responses resembling those of younger adults show the most learning and retention of that learning while individuals with delayed startle responses show the least. Moreover, linear regression analysis indicated that startle onset latency exists within a continuum of learning outcomes suggesting that startle onset latency may be a sensitive measure to predict learning deficits in older adults. As there exists no method to determine an individual’s relative learning capacity, these results open the possibility of startle, which is an easy and inexpensive behavioral measure, being used to predict learning deficits in older adults to facilitate better dosing during rehabilitation therapy.