Biomedical subjects

Joel W Burdick

Publications and source records attributed to Joel W Burdick.

6 recordsLinked to original sources

PubMed2006

Implications of assist-as-needed robotic step training after a complete spinal cord injury on intrinsic strategies of motor learning.

Robotic training paradigms that enforce a fixed kinematic control might be suboptimal for rehabilitative training because they abolish variability, an intrinsic property of neuromuscular control (Jezernik et al., 2003). In the present study we introduce "assist-as-needed" (AAN) robotic training paradigms for rehabilitation of spinal cord injury subjects. To test the efficacy of these robotic control strategies to teach spinal mice to step, we divided 27 adult female Swiss-Webster mice randomly into three groups. Each group was trained robotically by using one of three control strategies: a fixed training trajectory (Fixed group), an AAN training paradigm without interlimb coordination (Band group), and an AAN training paradigm with bilateral hindlimb coordination (Window group). Beginning at 14 d after a complete midthoracic spinal cord transection, the mice were trained daily (10 min/d, 5 d/week) to step on a treadmill 10 min after the administration of quipazine (0.5 mg/kg), a serotonin agonist, for a period of 6 weeks. During weekly performance evaluations, the mice trained with the AAN window paradigm generally showed the highest level of recovery as measured by the number, consistency, and periodicity of steps during the testing sessions. In all three measurements there were no significant differences between the Band and the Fixed training groups. These results indicate that the window training approach, which includes loose alternating interlimb coordination, is more effective than a fixed trajectory paradigm with rigid alternating interlimb coordination or an AAN paradigm without any interlimb constraints in promoting robust postinjury stepping behavior.

Animals↗

PubMed2006

A control algorithm for autonomous optimization of extracellular recordings.

This paper develops a control algorithm that can autonomously position an electrode so as to find and then maintain an optimal extracellular recording position. The algorithm was developed and tested in a two-neuron computational model representative of the cells found in cerebral cortex. The algorithm is based on a stochastic optimization of a suitably defined signal quality metric and is shown capable of finding the optimal recording position along representative sampling directions, as well as maintaining the optimal signal quality in the face of modeled tissue movements. The application of the algorithm to acute neurophysiological recording experiments and its potential implications to chronic recording electrode arrays are discussed.

Action Potentials↗

PubMed2005

Spinal cord-transected mice learn to step in response to quipazine treatment and robotic training.

In the present study, concurrent treatment with robotic step training and a serotonin agonist, quipazine, generated significant recovery of locomotor function in complete spinal cord-transected mice (T7-T9) that otherwise could not step. The extent of recovery achieved when these treatments were combined exceeded that obtained when either treatment was applied independently. We quantitatively analyzed the stepping characteristics of spinal mice after alternatively administering no training, manual training, robotic training, quipazine treatment, or a combination of robotic training with quipazine treatment, to examine the mechanisms by which training and quipazine treatment promote functional recovery. Using fast Fourier transform and principal components analysis, significant improvements in the step rhythm, step shape consistency, and number of weight-bearing steps were observed in robotically trained compared with manually trained or nontrained mice. In contrast, manual training had no effect on stepping performance, yielding no improvement compared with nontrained mice. Daily bolus quipazine treatment acutely improved the step shape consistency and number of steps executed by both robotically trained and nontrained mice, but these improvements did not persist after quipazine was withdrawn. At the dosage used (0.5 mg/kg body weight), quipazine appeared to facilitate, rather than directly generate, stepping, by enabling the spinal cord neural circuitry to process specific patterns of sensory information associated with weight-bearing stepping. Via this mechanism, quipazine treatment enhanced kinematically appropriate robotic training. When administered intermittently during an extended period of robotic training, quipazine revealed training-induced stepping improvements that were masked in the absence of the pharmacological treatment.

Animals↗

PubMed2005

Spike detection using the continuous wavelet transform.

This paper combines wavelet transforms with basic detection theory to develop a new unsupervised method for robustly detecting and localizing spikes in noisy neural recordings. The method does not require the construction of templates, or the supervised setting of thresholds. We present extensive Monte Carlo simulations, based on actual extracellular recordings, to show that this technique surpasses other commonly used methods in a wide variety of recording conditions. We further demonstrate that falsely detected spikes corresponding to our method resemble actual spikes more than the false positives of other techniques such as amplitude thresholding. Moreover, the simplicity of the method allows for nearly real-time execution.

Action Potentials↗

PubMed2004

Semi-chronic motorized microdrive and control algorithm for autonomously isolating and maintaining optimal extracellular action potentials.

A system was developed that can autonomously position recording electrodes to isolate and maintain optimal quality extracellular signals. The system consists of a novel motorized miniature recording microdrive and a control algorithm. The microdrive was designed for chronic operation and can independently position four glass-coated Pt-Ir electrodes with micrometer precision over a 5-mm range using small (3 mm diam) piezoelectric linear actuators. The autonomous positioning algorithm is designed to detect, align, and cluster action potentials and then command the microdrive to optimize and maintain the neural signal. This system is shown to be capable of autonomous operation in monkey cortical tissue.

Action Potentials↗

PubMed2003

Neural prosthetic control signals from plan activity.

The prospect of assisting disabled patients by translating neural activity from the brain into control signals for prosthetic devices, has flourished in recent years. Current systems rely on neural activity present during natural arm movements. We propose here that neural activity present before or even without natural arm movements can provide an important, and potentially advantageous, source of control signals. To demonstrate how control signals can be derived from such plan activity we performed a computational study with neural activity previously recorded from the posterior parietal cortex of rhesus monkeys planning arm movements. We employed maximum likelihood decoders to estimate movement direction and to drive finite state machines governing when to move. Performance exceeded 90% with as few as 40 neurons.

Action Potentials↗