TY - JOUR T1 - The simplest motor skill: mechanisms and applications of reflex operant conditioning. JF - Exerc Sport Sci Rev Y1 - 2014 A1 - Thompson, Aiko K A1 - Jonathan Wolpaw KW - Animals KW - Conditioning, Operant KW - H-Reflex KW - Humans KW - Motor Skills KW - Muscle, Skeletal KW - Neuronal Plasticity KW - Reflex KW - Spinal Cord KW - Spinal Cord Injuries AB - Operant conditioning protocols can change spinal reflexes gradually, which are the simplest behaviors. This article summarizes the evidence supporting two propositions: that these protocols provide excellent models for defining the substrates of learning and that they can induce and guide plasticity to help restore skills, such as locomotion, that have been impaired by spinal cord injury or other disorders. VL - 42 UR - http://www.ncbi.nlm.nih.gov/pubmed/24508738 IS - 2 ER - TY - JOUR T1 - Temporal transformation of multiunit activity improves identification of single motor units. JF - J Neurosci Methods Y1 - 2002 A1 - Gerwin Schalk A1 - Jonathan S. Carp A1 - Jonathan Wolpaw KW - Action Potentials KW - Animals KW - Electromyography KW - H-Reflex KW - Motor Neurons KW - Muscle, Skeletal KW - Rats KW - Signal Processing, Computer-Assisted AB -

This report describes a temporally based method for identifying repetitive firing of motor units. This approach is ideally suited to spike trains with negative serially correlated inter-spike intervals (ISIs). It can also be applied to spike trains in which ISIs exhibit little serial correlation if their coefficient of variation (COV) is sufficiently low. Using a novel application of the Hough transform, this method (i.e. the modified Hough transform (MHT)) maps motor unit action potential (MUAP) firing times into a feature space with ISI and offset (defined as the latency from an arbitrary starting time to the first MUAP in the train) as dimensions. Each MUAP firing time corresponds to a pattern in the feature space that represents all possible MUAP trains with a firing at that time. Trains with stable ISIs produce clusters in the feature space, whereas randomly firing trains do not. The MHT provides a direct estimate of mean firing rate and its variability for the entire data segment, even if several individual MUAPs are obscured by firings from other motor units. Addition of this method to a shape-based classification approach markedly improved rejection of false positives using simulated data and identified spike trains in whole muscle electromyographic recordings from rats. The relative independence of the MHT from the need to correctly classify individual firings permits a global description of stable repetitive firing behavior that is complementary to shape-based approaches to MUAP classification.

VL - 114 UR - http://www.ncbi.nlm.nih.gov/pubmed/11850043 IS - 1 ER -