Bayesian decoding of tactile afferents responsible for sensorimotor control

In daily activities, humans manipulate objects and do so with great precision. Empirical studies have demonstrated that signals encoded by mechanoreceptors facilitate the precise object manipulation in humans, however, little is known about the underlying mechanisms. Models used in literature to analyze tactile afferent data range from advanced—for example some models account for skin tissue properties—to simple regression fit. These models, however, do not systematically account for factors that influence tactile afferent activity. For instance, it is not yet clear whether the first derivative of force influences the observed tactile afferent spike train patterns. In this study, I use the technique of microneurography—with the help of Dr. Birznieks—to record tactile afferent data from humans. I then implement spike sorting algorithms to identify spike occurrences that pertain to a single cell. For further analyses of the resulting spike trains, I use a Bayesian decoding framework to investigate tactile afferent mechanisms that are responsible for sensorimotor control in humans. The Bayesian decoding framework I implement is a two stage process where in a first stage (encoding model) the relationships between the administered stimuli and the recorded tactile afferent signals is established, and a second stage uses results based on the first stage to make predictions. The goal of encoding model is to increase our understanding of the mechanisms that underlie dexterous object manipulation and, from an engineering perspective, guide the design of algorithms for inferring stimulus from previously unseen tactile afferent data, a process referred to as decoding. Specifically, the objective of the study was to devise quantitative methods that would provide insight into some mechanisms that underlie touch, as well as provide strategies through which real-time biomedical devices can be realized. Tactile afferent data from eight subjects (18 - 30 years) with no known form of neurological disorders were recorded by inserting a needle electrode in the median nerve at the wrist. I was involved in designing experimental protocols, designing mechanisms that were put in place for safety measures, designing and building electronic components as needed, experimental setup, subject recruitment, and data acquisition. Dr. Ingvars Birznieks (performed the actual microneurography procedure by inserting a needle electrode into the nerve and identifying afferent types) and Dr. Heba Khamis provided assistance with the data acquisition and experimental design. The study took place at Neuroscience Research Australia (NeuRA). Once the data were acquired, I analyzed the data recorded from slowly adapting type I tactile afferents (SA-I). The initial stages of data analysis involved writing software routines to spike sort the data (identify action potential waveforms that pertain to individual cells). I analyzed SA-I tactile afferents because they were more numerous (it was difficult to target other types of afferents during experiments). In addition, SA-I tactile afferents respond during both the dynamic and the static phase of a force stimulus. Since they respond during both the dynamic and static phases of the force stimulus, it seemed reasonable to hypothesize that SA-I’s alone could provide sufficient information for predicting the force profile, given spike data. In the first stage, I used an inhomogeneous Poisson process encoding model through which I assessed the relative importance of aspects of the stimuli to observed spike data. In addition I estimated the likelihood for SA-I data given the inhomogeneous Poisson model, which was used during the second stage. The likelihood is formulated by deriving the joint distribution of the data, as a function of the model parameters with the data fixed. In the second stage, I used a recursive nonlinear Bayesian filter to reconstruct the force profile, given the SA-I spike patterns. Moreover, the decoding method implemented in this thesis is feasible for real-time applications such as interfacing with prostheses because it can be realized with readily available electronic components. I also implemented a renewal point process encoding model—as a generalization of the Poisson process encoding model—which can account for some history dependence properties of neural data. I discovered that under my encoding model, the relative contributions of the force and its derivative are 1.26 and 1.02, respectively. This suggests that the force derivative contributes significantly to the spiking behavior of SA-I tactile afferents. This is a novel contribution because it provides a quantitative result to the long standing question of whether the force derivative contributes towards SA-I tactile afferent spiking behavior. As a result, I incorporated the first derivative of force, along with the force, in the encoding models I implemented in this thesis. The decoding model shows that SA-I fibers provide sufficient information for an approximation of the force profile. Furthermore, including fast adapting tactile afferents would provide better information about the first moment of contact and last moment of contact, and thus improved decoding results. Finally I show that a renewal point process encoding model captures interspike time and stimulus features better than an inhomogeneous Poisson point process encoding model. This is useful because it is now possible to generate synthetic data with statistical structure that is similar to real SA-I data: This would enable further investigations of mechanisms that underlie SA-I tactile afferents

A point process approach to encode tactile afferents

In daily activities, humans manipulate objects and do so with great precision. Empirical studies have demonstrated that signals encoded by mechanoreceptors facilitate the precise object manipulation in humans, however, little is known about the underlying mechanisms. Current models range from complex to simple regression fit. These models do not describe the dynamics of neural data well. Because experimental neural data is limited to spike instances, they can be viewed as point processes. We discuss the point process framework and use it to simulate neural data possessing behaviors similar to experimental neural data. The characteristics of neural data were identified via visualization and descriptive statistics based on the experimental data. Then we fit candidate models to the simulated data and perform goodness-of fit to assess how well the models perform. This type of analysis facilitates the mapping of neural data to stimulus. Given this mapping, we can generate a population of spike trains, and infer from them in order to recover the applied stimulus. The knowledge acquired may provide insight into some fundamental sensory mechanisms that are responsible for coordinating force components during object manipulation.We envisage that the knowledge may guide the design of sensory-controlled bio-medical devices and robotic manipulators

Motor Unit Firing Characteristics in Patients with Amyotrophic Lateral Sclerosis

Abstract- In this study, we investigated the behavior of active motor units identified via analysis of electro myographic (EMG) signals recorded from the first dorsal interosseous (FDI) muscle using a quadrifilar needle electrode. Data was collected from control subjects and patients with both upper (UMN) and lower (LMN) motor neuron dominant forms of amyotrophic lateral sclerosis (ALS). EMG recordings were gathered during isometric contractions reaching 20 or 50 % of the force output produced during a maximum voluntary contraction (MVC). Recordings were processed using freely available EMG decomposition software (EMGLAB). Results showed differences in mean motor unit firing rates and variability between ALS patients and control subjects. Differences in mean motor unit firing rates and variability were also observed between ALS patients with LMNand UMN-dominant forms of ALS. Keywords- Amyotrophic lateral sclerosis; motor units; decomposition; firing rate I

Characterization of Motor Unit Behavior in Patients with Amyotrophic Lateral Sclerosis

Abstract — In this study, we investigated the behavior of active motor units identified via analysis of electromyographic (EMG) signals recorded from the first dorsal interosseous (FDI) muscle using a quadrifilar needle electrode. Data was collected from control subjects and patients with both lower (LMN) and upper (UMN) motor neuron dominant forms of amyotrophic lateral sclerosis (ALS). EMG recordings were gathered during isometric contractions reaching 20 or 50 % of the force output produced during a maximum voluntary contraction (MVC). Recordings were analyzed using available EMG decomposition software (EMGLAB). Results showed differences in mean motor unit firing rates between patients with ALS and control subjects. Differences were also observed between patients with LMN- and UMN-dominant forms of ALS. Motor unit substitution was observed in patients despite the contractions lasting just a few seconds. Finally, we observed that motor unit action potential (MUAP) waveforms recorded from patients were more complex than those recorded from control subjects as often observed in motor neuron diseases

“Stable-on-the-Table” Biosensors: Hemoglobin-Poly (Acrylic Acid) Nanogel BioElectrodes with High Thermal Stability and Enhanced Electroactivity

In our efforts toward producing environmentally responsible but highly stable bioelectrodes with high electroactivities, we report here a simple, inexpensive, autoclavable high sensitivity biosensor based on enzyme-polymer nanogels. Met-hemoglobin (Hb) is stabilized by wrapping it in high molecular weight poly(acrylic acid) (PAA, MW 450k), and the resulting nanogels abbreviated as Hb-PAA-450k, withstood exposure to high temperatures for extended periods under steam sterilization conditions (122 °C, 10 min, 17–20 psi) without loss of Hb structure or its peroxidase-like activities. The bioelectrodes prepared by coating Hb-PAA-450k nanogels on glassy carbon showed well-defined quasi-reversible redox peaks at −0.279 and −0.334 V in cyclic voltammetry (CV) and retained >95% electroactivity after storing for 14 days at room temperature. Similarly, the bioelectrode showed ~90% retention in electrochemical properties after autoclaving under steam sterilization conditions. The ultra stable bioelectrode was used to detect hydrogen peroxide and demonstrated an excellent detection limit of 0.5 μM, the best among the Hb-based electrochemical biosensors. This is the first electrochemical demonstration of steam-sterilizable, storable, modular bioelectrode that undergoes reversible-thermal denaturation and retains electroactivity for protein based electrochemical applications

A Preliminary assessment of a novel pneumatic unloading knee brace on the gait mechanics of patients with knee osteoarthritis

Objectives: To determine whether a knee brace incorporating inflatable air bladders can alter the net peak external knee adduction moment in persons with medial compartment knee osteoarthritis. Design: Prospective cohort study. Setting: Motion analysis laboratory. Participants: Subjects (n = 18) diagnosed with knee osteoarthritis as defined by the Diagnostic and Therapeutic Criteria Committee of the American Rheumatism Association. Methods: Instrumented gait analysis was performed while subjects walked with and without the knee brace. When subjects wore the knee brace, the air bladders were either uninflated or inflated to 7 psi. The net external knee adduction moment was obtained by subtracting the abduction moment produced by the knee brace (estimated using a finite element analysis model) from the external knee adduction moment (estimated using a camera-based motion analysis system). Main Outcome Measurements: The net external knee adduction moment was compared across all testing conditions. Results: A 7.6% decrease in net peak external knee adduction moment was observed when subjects wore the knee brace uninflated compared with when they did not wear the brace. Inflation of the bladders to 7 psi led to a 26.0% decrease in net peak external knee adduction moment. Conclusions: The results of the study suggest that the effects of an unloading knee brace may be enhanced by incorporating inflatable air bladders into the design of the brace, thus leading to an improved correction of the excessive peak external knee adduction moment observed in patients with medial compartment knee osteoarthritis.</br

Decoding tactile afferent responses relevant for sensorimotor control during dexterous object manipulation

This study investigates how friction is encoded by mechanoreceptors in the human finger pad and how the resulting neural code is interpreted by the brain. It is hoped that an understanding of mechanisms that underlie tactile coding may provide the benchmark needed to design robotics that can perform well in unstructured environments, inform the design of sensory feedback devices, and possibly guide the development of new methods to improve upon therapies for individuals with neurological disorders