02675nas a2200325 4500008004100000022001400041245010000055210006900155260001200224300001200236490000800248520178700256653001202043653002602055653001102081653001302092653001302105653001502118653000902133653000902142653002502151653002502176100001302201700001302214700001902227700001302246700002102259700002102280856004802301 2014 eng d a1522-159800aLocomotor impact of beneficial or nonbeneficial H-reflex conditioning after spinal cord injury.0 aLocomotor impact of beneficial or nonbeneficial Hreflex conditio c03/2014 a1249-580 v1113 aWhen new motor learning changes neurons and synapses in the spinal cord, it may affect previously learned behaviors that depend on the same spinal neurons and synapses. To explore these effects, we used operant conditioning to strengthen or weaken the right soleus H-reflex pathway in rats in which a right spinal cord contusion had impaired locomotion. When up-conditioning increased the H-reflex, locomotion improved. Steps became longer, and step-cycle asymmetry (i.e., limping) disappeared. In contrast, when down-conditioning decreased the H-reflex, locomotion did not worsen. Steps did not become shorter, and asymmetry did not increase. Electromyographic and kinematic analyses explained how H-reflex increase improved locomotion and why H-reflex decrease did not further impair it. Although the impact of up-conditioning or down-conditioning on the H-reflex pathway was still present during locomotion, only up-conditioning affected the soleus locomotor burst. Additionally, compensatory plasticity apparently prevented the weaker H-reflex pathway caused by down-conditioning from weakening the locomotor burst and further impairing locomotion. The results support the hypothesis that the state of the spinal cord is a "negotiated equilibrium" that serves all the behaviors that depend on it. When new learning changes the spinal cord, old behaviors undergo concurrent relearning that preserves or improves their key features. Thus, if an old behavior has been impaired by trauma or disease, spinal reflex conditioning, by changing a specific pathway and triggering a new negotiation, may enable recovery beyond that achieved simply by practicing the old behavior. Spinal reflex conditioning protocols might complement other neurorehabilitation methods and enhance recovery.10aAnimals10aConditioning, Operant10aFemale10aH-Reflex10aLearning10aLocomotion10aMale10aRats10aRats, Sprague-Dawley10aSpinal Cord Injuries1 aChen, Yi1 aChen, Lu1 aLiu, Rongliang1 aWang, Yu1 aChen, Xiang Yang1 aWolpaw, Jonathan uhttp://www.ncbi.nlm.nih.gov/pubmed/2437128802577nas a2200301 4500008004100000022001400041245010600055210006900161260001200230300001200242490000800254520171500262653001201977653002601989653002102015653001102036653001502047653000902062653002502071653001202096653001402108653001602122100002402138700002102162700002102183700002302204856004802227 2014 eng d a1522-146600aLong-term recording of external urethral sphincter EMG activity in unanesthetized, unrestrained rats.0 aLongterm recording of external urethral sphincter EMG activity i c08/2014 aF485-970 v3073 a

The external urethral sphincter muscle (EUS) plays an important role in urinary function and often contributes to urinary dysfunction. EUS study would benefit from methodology for longitudinal recording of electromyographic activity (EMG) in unanesthetized animals, but this muscle is a poor substrate for chronic intramuscular electrodes, and thus the required methodology has not been available. We describe a method for long-term recording of EUS EMG by implantation of fine wires adjacent to the EUS that are secured to the pubic bone. Wires pass subcutaneously to a skull-mounted plug and connect to the recording apparatus by a flexible cable attached to a commutator. A force transducer-mounted cup under a metabolic cage collected urine, allowing recording of EUS EMG and voided urine weight without anesthesia or restraint. Implant durability permitted EUS EMG recording during repeated (up to 3 times weekly) 24-h sessions for more than 8 wk. EMG and voiding properties were stable over weeks 2-8. The degree of EUS phasic activity (bursting) during voiding was highly variable, with an average of 25% of voids not exhibiting bursting. Electrode implantation adjacent to the EUS yielded stable EMG recordings over extended periods and eliminated the confounding effects of anesthesia, physical restraint, and the potential for dislodgment of the chronically implanted intramuscular electrodes. These results show that micturition in unanesthetized, unrestrained rats is usually, but not always, associated with EUS bursting. This methodology is applicable to studying EUS behavior during progression of gradually evolving disease and injury models and in response to therapeutic interventions.

10aAnimals10aElectrodes, Implanted10aElectromyography10aFemale10aPubic Bone10aRats10aRats, Sprague-Dawley10aUrethra10aUrination10aUrodynamics1 aLaPallo, Brandon, K1 aWolpaw, Jonathan1 aChen, Xiang Yang1 aCarp, Jonathan, S. uhttp://www.ncbi.nlm.nih.gov/pubmed/2499089501203nas a2200277 4500008004100000022001400041245009000055210006900145260001200214300001000226490000700236520041500243653001200658653002600670653001300696653001100709653001700720653002100737653002400758653001100782653001600793653002500809100002200834700002100856856004800877 2014 eng d a1538-300800aThe simplest motor skill: mechanisms and applications of reflex operant conditioning.0 asimplest motor skill mechanisms and applications of reflex opera c04/2014 a82-900 v423 aOperant 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.10aAnimals10aConditioning, Operant10aH-Reflex10aHumans10aMotor Skills10aMuscle, Skeletal10aNeuronal Plasticity10aReflex10aSpinal Cord10aSpinal Cord Injuries1 aThompson, Aiko, K1 aWolpaw, Jonathan uhttp://www.ncbi.nlm.nih.gov/pubmed/2450873802977nas a2200361 4500008004100000022001400041245007400055210006800129260001200197300001100209490000700220520195300227653001202180653001002192653002702202653002202229653001102251653002702262653001302289653001302302653001602315653003102331653001702362653002802379100002402407700002602431700001902457700002502476700002402501700002102525700002102546856004802567 2006 eng d a1534-432000aThe Wadsworth BCI Research and Development Program: At Home with BCI.0 aWadsworth BCI Research and Development Program At Home with BCI c06/2006 a229-330 v143 a

The ultimate goal of brain-computer interface (BCI) technology is to provide communication and control capacities to people with severe motor disabilities. BCI research at the Wadsworth Center focuses primarily on noninvasive, electroencephalography (EEG)-based BCI methods. We have shown that people, including those with severe motor disabilities, can learn to use sensorimotor rhythms (SMRs) to move a cursor rapidly and accurately in one or two dimensions. We have also improved P300-based BCI operation. We are now translating this laboratory-proven BCI technology into a system that can be used by severely disabled people in their homes with minimal ongoing technical oversight. To accomplish this, we have: improved our general-purpose BCI software (BCI2000); improved online adaptation and feature translation for SMR-based BCI operation; improved the accuracy and bandwidth of P300-based BCI operation; reduced the complexity of system hardware and software and begun to evaluate home system use in appropriate users. These developments have resulted in prototype systems for every day use in people's homes.

10aAnimals10aBrain10aElectroencephalography10aEvoked Potentials10aHumans10aNeuromuscular Diseases10aNew York10aResearch10aSwitzerland10aTherapy, Computer-Assisted10aUniversities10aUser-Computer Interface1 aVaughan, Theresa, M1 aMcFarland, Dennis, J.1 aSchalk, Gerwin1 aSarnacki, William, A1 aKrusienski, Dean, J1 aSellers, Eric, W1 aWolpaw, Jonathan uhttp://www.ncbi.nlm.nih.gov/pubmed/1679230102917nas a2200265 4500008004100000022001400041245009700055210006900152260001200221300001000233490000800243520213200251653002202383653001202405653002102417653001302438653001802451653002102469653000902490653004102499100001902540700002302559700002102582856004802603 2002 eng d a0165-027000aTemporal transformation of multiunit activity improves identification of single motor units.0 aTemporal transformation of multiunit activity improves identific c02/2002 a87-980 v1143 a

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.

10aAction Potentials10aAnimals10aElectromyography10aH-Reflex10aMotor Neurons10aMuscle, Skeletal10aRats10aSignal Processing, Computer-Assisted1 aSchalk, Gerwin1 aCarp, Jonathan, S.1 aWolpaw, Jonathan uhttp://www.ncbi.nlm.nih.gov/pubmed/11850043