BME PhD Dissertation Defense - Joshua Christian Kline

Starts:
1:00 pm on Friday, November 22, 2013
Location:
8 St. Mary’s Street, Photonic Center, Room 339
Title: SYNCHRONIZATION OF MOTONEURON FIRINGS: AN EPIPHENOMENON OF HIERARCHICAL CONTROL REVEALED BY STATISTICALLY ROBUST METHODS

Committee:
Dr. Carlo J. De Luca (*Advisor, BU, NMRC, BME, ECE, Physical Therapy, Neurology)
Dr. Kamal Sen (*Chair, BU, BME)
Dr. S Hamid Nawab (BU, ECE, BME, NMRC)
Dr. Serge H. Roy (BU, NMRC, Physical Therapy)

Abstract:
For more than four decades, observations of synchronized motoneuron firings detected during human muscle contractions have been used to determine the strength of common inputs shared by motoneurons. This notion is referred to as the “common input”. It relies on the supposition that synchronization is caused by branches of presynaptic inputs shared by motoneurons. However, direct empirical observations that physical common inputs elicit synchronized firings have never been reported. The disquiet over the lack of physical evidence has been compounded by the lack of statistical rigor of the methods used to detect synchronized firings. In spite of its seemingly wide acceptance, the validity of the common input notion remains unproven.
I set out to evaluate the methods used to detect synchronization and derive an improved statistical approach to test rigorously the notion that common inputs cause synchronization. More than, 1,000,000 firings from over 2,100 motoneurons were decomposed from EMG signals collected during voluntary contractions ranging from 5% to 50% of the maximal force in two human muscles – a data set an order of magnitude greater than any reported in previous synchronization studies. Any errors that occurred during EMG decomposition were classified and mitigated using a newly derived error reduction algorithm. With improved estimates of the firing times, I developed a statistically-based method (SigMax) for detecting synchronized firings and compared it to three other commonly used techniques. SigMax revealed three types of errors produced by the previous methods that ignore proper statistical considerations necessary to detect synchronization.
Using the error reduction and SigMax method, I designed two experiments to examine the possible physiological cause of motoneuron synchronization. The first experiment implemented a dual force-level contraction paradigm to test the common input notion. My analysis demonstrated that anatomically hard-wired common inputs were not responsible for the changes in synchronization that occurred with changes in contraction force. Therefore, I implemented a second experimental protocol to ascertain factors other than common inputs that may cause synchronization. Results from a three-dimensional regression analysis of these data indicated that synchronization likely occurs as an epiphenomenon of the sensitivities of motoneuron firing rates to voluntary excitation.