Neutral coding - A report based on an NRP work session

Neural coding by impulses and trains on single and multiple channels, and representation of information in nonimpulse carrier

Noninvasive Blood Flow and Oxygenation Measurements in Diseased Tissue

The research presented in this dissertation focused on the application of optical imaging techniques to establish blood flow and oxygen saturation as effective biomarkers for two disease cases, Autism Spectrum Disorder (ASD) and Huntington’s Disease (HD). The BTBR mouse model of ASD was utilized to validate measurements of cerebral blood flow and oxygenation as biomarkers for autism. The R6/2 mouse model of juvenile HD was utilized to validate measurements of skeletal muscle blood flow following tetanic muscle contractions induced by electrical nerve stimulation. Next, a noncontact, camera-based system to measure blood flow and oxygen saturation maps was implemented to improve upon the previous HD mouse results by providing spatial heterogeneity in a wild-type mouse model. Finally, translational research was performed to validate a research design conducting concurrent grip strength force and skeletal muscle blood flow and oxygenation measurements in a healthy human population that will be used to establish HD biomarkers in humans in future clinical applications

Modulation of human corticospinal excitability by paired associative stimulation

Paired Associative Stimulation (PAS) has come to prominence as a potential therapeutic intervention for the treatment of brain injury/disease, and as an experimental method with which to investigate Hebbian principles of neural plasticity in humans. Prototypically, a single electrical stimulus is directed to a peripheral nerve in advance of transcranial magnetic stimulation (TMS) delivered to the contralateral primary motor cortex (M1). Repeated pairing of the stimuli (i.e., association) over an extended period may increase or decrease the excitability of corticospinal projections from M1, in manner that depends on the interstimulus interval (ISI). It has been suggested that these effects represent a form of associative long-term potentiation (LTP) and depression (LTD) that bears resemblance to spike-timing dependent plasticity (STDP) as it has been elaborated in animal models. With a large body of empirical evidence having emerged since the cardinal features of PAS were first described, and in light of the variations from the original protocols that have been implemented, it is opportune to consider whether the phenomenology of PAS remains consistent with the characteristic features that were initially disclosed. This assessment necessarily has bearing upon interpretation of the effects of PAS in relation to the specific cellular pathways that are putatively engaged, including those that adhere to the rules of STDP. The balance of evidence suggests that the mechanisms that contribute to the LTP- and LTD-type responses to PAS differ depending on the precise nature of the induction protocol that is used. In addition to emphasizing the requirement for additional explanatory models, in the present analysis we highlight the key features of the PAS phenomenology that require interpretation

Higher Network Activity Induced by Tactile Compared to Electrical Stimulation of Leech Mechanoreceptors

The tiny ensemble of neurons in the leech ganglion can discriminate the locations of touch stimuli on the skin as precisely as a human fingertip. The leech uses this ability to locally bend the body-wall away from the stimulus. It is assumed that a three-layered feedforward network of pressure mechanoreceptors, interneurons, and motor neurons controls this behavior. Most previous studies identified and characterized the local bend network based on electrical stimulation of a single pressure mechanoreceptor, which was sufficient to trigger the local bend response. Recent studies showed, however, that up to six mechanoreceptors of three types innervating the stimulated patch of skin carry information about both touch intensity and location simultaneously. Therefore, we hypothesized that interneurons involved in the local bend network might require the temporally concerted inputs from the population of mechanoreceptors representing tactile stimuli, to decode the tactile information and to provide appropriate synaptic inputs to the motor neurons. We examined the influence of current injection into a single mechanoreceptor on activity of postsynaptic interneurons in the network and compared it to responses of interneurons to skin stimulation with different pressure intensities. We used voltage-sensitive dye imaging to monitor the graded membrane potential changes of all visible cells on the ventral side of the ganglion. Our results showed that stimulation of a single mechanoreceptor activates several local bend interneurons, consistent with previous intracellular studies. Tactile skin stimulation, however, evoked a more pronounced, longer-lasting, stimulus intensity-dependent network dynamics involving more interneurons. We concluded that the underlying local bend network enables a non-linear processing of tactile information provided by population of mechanoreceptors. This task requires a more complex network structure than previously assumed, probably containing polysynaptic interneuron connections and feedback loops. This small, experimentally well-accessible neuronal system highlights the general importance of selecting adequate sensory stimulation to investigate the network dynamics in the context of natural behavior

Physical and electrophysiological motor unit characteristics are revealed with simultaneous high-density electromyography and ultrafast ultrasound imaging

Electromyography and ultrasonography provide complementary information about electrophysiological and physical (i.e. anatomical and mechanical) muscle properties. In this study, we propose a method to assess the electrical and physical properties of single motor units (MUs) by combining High-Density surface Electromyography (HDsEMG) and ultrafast ultrasonography (US). Individual MU firings extracted from HDsEMG were used to identify the corresponding region of muscle tissue displacement in US videos. The time evolution of the tissue velocity in the identified region was regarded as the MU tissue displacement velocity. The method was tested in simulated conditions and applied to experimental signals to study the local association between the amplitude distribution of single MU action potentials and the identified displacement area. We were able to identify the location of simulated MUs in the muscle cross-section within a 2 mm error and to reconstruct the simulated MU displacement velocity (cc > 0.85). Multiple regression analysis of 180 experimental MUs detected during isometric contractions of the biceps brachii revealed a significant association between the identified location of MU displacement areas and the centroid of the EMG amplitude distribution. The proposed approach has the potential to enable non-invasive assessment of the electrical, anatomical, and mechanical properties of single MUs in voluntary contractions

Point Process Analysis Techniques: Theory and Applications to Complex Neurophysiological Systems

The main objective of this thesis is the development of analytical techniques and computational procedures for the analysis of complex neuronal networks. The techniques are applied to data obtained from elements of neurophysiological systems and simulated models to illustrate different aspects of these analysis tools. The nerve signals that occur within neuromuscular control systems are widely accepted to be stochastic in nature and are characterised by the times of occurrence of events, typically 1 msec, in duration of fixed amplitude, within the process. This provides the basis for considering these processes as stochastic point processes. The analytical approach adopted is similar to that used in ordinary time series and requires an inter-disciplinary approach involving linear and non-linear system analysis, estimation theory, probability theory and statistical inference. In this thesis a considerable amount of work is devoted to the discussion of these various areas related to the point process analysis techniques. In addition, neurophysiological concepts are discussed to provide a basis for the application of these techniques. These techniques are applied to the analysis of real data obtained from physiological experiments and simulated data generated by model neuronal networks of different complexities. Finally, some possibilities for future work opened up by the present investigation are considered. An introduction together with some historical notes are given in Chapter 1. The objectives of this thesis are set down and some general ideas of a point process and neurophysiology are introduced. The historical notes at the end of Chapter 1 are intended to give a picture of the trend of developments concerning point processes. Chapter 2 presents a simplified account of the relevant neurophysiological background. Some features of the neuromuscular system which lead to the use of point process analysis techniques are discussed. This is followed by a brief description of the organisation of neuromuscular system and some of its elements. The idea that the generation of an action potential occurs when the membrane potential at the trigger zone of a neurone exceeds the threshold forms the basis for the neurone model used in this thesis . The multiple input and output nature of neuromuscular systems in addition to the short duration of an action potential justify the realisation of a spike train as stochastic point process. Chapter 2 is concluded by considering some findings from the application of point process analysis techniques to data recorded from neuromuscular elements. The details of the techniques are then explained in Chapter 3-5. Chapter 3 gives a development of the theory of linear point process system analysis. The formal definitions of the assumptions involved, namely stationarity, mixing, and orderliness are explained. These assumptions are important in simplifying the theories involved and are seen to be valid in our applications. Theories for univariate, bivariate and multi-variate point processes are considered. The asymptotic value of the auto- spectrum of a point process is shown to be a non-zero constant, which marks the distinction from the auto-spectrum of an ordinary time series. Various quantities in both time and frequency domains are introduced and, among them, the coherence function and its partial and multiple forms are explained in particular details. The application of coherence is emphasised in Chapter 6. Since the processes involved are stochastic in nature, appropriate estimation procedures for the time and frequency domain quantities should be used. Chapter 4 is devoted to explaining the estimation procedure used and the statistical properties of these estimates. Also the Poisson point process - which possesses similar properties to Gaussian white noise in the case of ordinary time series - is introduced. The importance of the Poisson point process lies on the fact that it may be used as a 'reference process' to indicate departure of independence within a point process. At the end of Chapter 4, the confidence intervals of the time and frequency domain estimates under the hypothesis of independence are developed. The confidence interval approach forms the basis of inferring whether there is any significant association between processes or within a process. Chapter 5 describes briefly the implementation of the neurophysiological and simulation experiments. The digital algorithm for generating the exponential and Gaussian variables to provide the required stimuli in the experiment are explained. The neurone model, which is the building block of more complicated neuronal networks, is also described. Chapter 6 presents results and discussion. First some simulated spike trains of different structures are analysed using histogram, auto-intensity and auto-spectrum. The histogram is found to be least sensitive in revealing significant information concerning the processes. (Abstract shortened by ProQuest.)

Doctor of Philosophy

dissertationMedical intervention to restore motor function lost due to injury, stroke, or disease is increasingly common. Recent research in this field, known as functional electrical stimulation (FES), has produced a new generation of electrode devices that greatly enhance selectivity of access to neural populations, enabling-for the first time-restoration of motor function approaching what healthy humans enjoy. Research with these devices, however, has been severely hampered by the lack of a stimulation platform and control algorithms capable of exploring their full potential. The following dissertation presents the results of research aimed at addressing this problem. A major theme of this work is the use of software algorithms and analysis principles to facilitate both investigation and control of the motor system. Though many of the algorithms are well known in computer science, their application to the field of motor restoration is novel. Associated with use of these algorithms are important methodological considerations such as speed of execution, convergence, and optimality. The first phase of the research involved development of a hardware and software platform designed to support a wide range of closed-loop response mapping and control routines. Software routines to automate three time-consuming tasks-mapping stimulus thresholds, mapping stimulus-response recruitment curves, and mapping electrode pair excitation overlap- were implemented and validated in a cat model. Computer control, combined with the use of an efficient binary search algorithm, reduced the time need to complete required implant mapping tasks by a factor of 4 or more (compared to manual mapping), making feasible-for the first time-acute experiments investigating multi-array, multijoint experimental limb control. The second phase of the research involved investigating the influence of stimulus timing, within multielectrode trains, on the smoothness of evoked muscle responses. A model for predicting responses was developed and used, in conjunction with function optimization techniques, to identify stimulus timings that minimize response variation (ripple). In-vivo validation demonstrated that low-ripple timings can be identified, and that the influence of timing on ripple depends largely on the response kinetics of the motor unit pools recruited by constituent electrodes. The final phase of the research involved using the response prediction model to simulate the behavior of a feedback-based, stimulus-timing adjustment algorithm. Multiple simulations were executed to assess the influence of three algorithm parameters-filter bandwidth, error sampling delay, and timing adjustment gain-on two performance metrics- convergence time and percent reduction in ripple. Results show that all parameters have an influence on algorithm performance. Convergence speed is the metric most a↵ected by parameter adjustment, improving by a factor of more than 3 (13 cycles to approximately 4 cycles). Ripple reduction is also a↵ected-exhibiting a 17% reduction with appropriate selection of error sampling delay. These results demonstrate the value of using this simulation approach for parameter tuning

Feedback control of cycling in spinal cord injury using functional electrical stimulation

This thesis is concerned with the realisation of leg cycling by means of FES in SCI individuals with complete paraplegia. FES lower-limb cycling can be safely performed by paraplegics on static ergometers or recumbent tricycles. In this work, different FES cycling systems were developed for clinical and home use. Two design approaches have been followed. The first is based on the adaptation of commercially available recumbent tricycles. This results in devices which can be used as static trainers or for mobile cycling. The second design approach utilises a commercially available motorised ergometer which can be operated while sitting in a wheelchair. The developed FES cycling systems can be operated in isotonic (constant cycling resistance) or isokinetic mode (constant cadence) when used as static trainers. This represents a novelty compared to existing FES cycling systems. In order to realise isokinetic cycling, an electric motor is needed to assist or resist the cycling movement to maintain a constant cadence. Repetitive control technology is applied to the motor in this context to virtually eliminate disturbance caused by the FES activated musculature which are periodic with respect to the cadence. Furthermore, new methods for feedback control of the patient’s work rate have been introduced. A one year pilot study on FES cycling with paraplegic subjects has been carried out. Effective indoor cycling on a trainer setup could be achieved for long periods up to an hour, and mobile outdoor cycling was performed over useful distances. Power output of FES cycling was in the range of 15 to 20 W for two of the three subjects at the end of the pilot study. A muscle strengthening programme was carried out prior and concurrent to the FES cycling. Feedback control of FES assisted weight lifting exercises by quadriceps stimulation has been studied in this context

Noninvasive brain stimulation techniques can modulate cognitive processing

Recent methods that allow a noninvasive modulation of brain activity are able to modulate human cognitive behavior. Among these methods are transcranial electric stimulation and transcranial magnetic stimulation that both come in multiple variants. A property of both types of brain stimulation is that they modulate brain activity and in turn modulate cognitive behavior. Here, we describe the methods with their assumed neural mechanisms for readers from the economic and social sciences and little prior knowledge of these techniques. Our emphasis is on available protocols and experimental parameters to choose from when designing a study. We also review a selection of recent studies that have successfully applied them in the respective field. We provide short pointers to limitations that need to be considered and refer to the relevant papers where appropriate