A functional model and simulation of spinal motor pools and intrafascicular recordings of motoneuron activity in peripheral nerve

Decoding motor intent from recorded neural signals is essential for the development of effective neural-controlled prostheses. To facilitate the development of online decoding algorithms we have developed a software platform to simulate neural motor signals recorded with peripheral nerve electrodes, such as longitudinal intrafascicular electrodes (LIFEs). The simulator uses stored motor intent signals to drive a pool of simulated motoneurons with various spike shapes, recruitment characteristics, and firing frequencies. Each electrode records a weighted sum of a subset of simulated motoneuron activity patterns. As designed, the simulator facilitates development of a suite of test scenarios that would not be possible with actual data sets because, unlike with actual recordings, in the simulator the individual contributions to the simulated composite recordings are known and can be methodically varied across a set of simulation runs. In this manner, the simulation tool is suitable for iterative development of real-time decoding algorithms prior to definitive evaluation in amputee subjects with implanted electrodes. The simulation tool was used to produce data sets that demonstrate its ability to capture some features of neural recordings that pose challenges for decoding algorithms

A functional model and simulation of spinal motor pools and intrafascicular recordings of motoneuron activity in peripheral nerve

abstract: Decoding motor intent from recorded neural signals is essential for the development of effective neural-controlled prostheses. To facilitate the development of online decoding algorithms we have developed a software platform to simulate neural motor signals recorded with peripheral nerve electrodes, such as longitudinal intrafascicular electrodes (LIFEs). The simulator uses stored motor intent signals to drive a pool of simulated motoneurons with various spike shapes, recruitment characteristics, and firing frequencies. Each electrode records a weighted sum of a subset of simulated motoneuron activity patterns. As designed, the simulator facilitates development of a suite of test scenarios that would not be possible with actual data sets because, unlike with actual recordings, in the simulator the individual contributions to the simulated composite recordings are known and can be methodically varied across a set of simulation runs. In this manner, the simulation tool is suitable for iterative development of real-time decoding algorithms prior to definitive evaluation in amputee subjects with implanted electrodes. The simulation tool was used to produce data sets that demonstrate its ability to capture some features of neural recordings that pose challenges for decoding algorithms

Limits to temporal synchronization in fundamental hand and finger actions

Coordinated movement is critical not only to sports technique and performance but to daily living and as such represents a fundamental area of research. Coordination requires being able to produce the right actions at the right time and has to incorporate perception, cognition, and forceful neuro-muscular interaction with the environment. Coordinated movements of the hands and fingers are some of the most complex activities undertaken where continuous learning and adaptation take place, but the temporal variability of the most basic movement components is still unknown. This thesis investigates the extent of temporal variability in the execution of four different simple hand and finger coordination tasks, with the purpose to find the various intrinsic temporal variability which limit the ability to coordinate the hands in space and time. Study one showed that in a synchronized bi-lateral two finger tapping test (<<1 cm movement to target) the best participant had a temporaltiming variability of 4.8 ms whereas the largest time variability could be as high as 24.8 ms. No obvious improvement was found after transfer practice, whereas the average time variability for asynchronized tapping decreased from 62.1 ms to 30.3 ms after instructed practice indicating a likely change in task grouping. Study two showed that in a unilateral thumb-index finger pinch and release test, the largest mean timing variability was 12 ms for pinching irrespective of performing the task in a slow alert manner or at a faster speed. However, the mean temporal variability for release was only 6.3 ms when the task was performed in a more alert manner and indicates that release is more accurately controlled temporally than grip. Study three suggested that in a unilateral sagittal plane throwing action of the lower arm and hand, that elbow and wrist coordination for dynamic index finger tip location was better with a radial-ulnar deviation, darts-type, throwing action than a wrist flexor-extensor type action, basketball free throw type action (the mean variability was 37.5 ms and 27.2 ms, respectively). Study four compared the variability in bi-lateral finger tapping between voluntary tapping and involuntary finger contraction tapping. Electrically stimulated neural contractions had significantly lower force onset variability than voluntary or direct magnetic stimulation of muscles (6 ms, 9.5 ms, and 10.3 ms for electrically stimulated, voluntary and Transcranial Magnetic Stimulation stimulated contraction). This work provides a comprehensive analysis of the temporal variability in various fundamental digital movement tasks that can aid with the understanding of basic human coordination in sporting, daily living and clinical areas

Facial hacking: the twisted logic of electro-facial choreography

This research addresses the development of a computational facial language that enables systematic exploration of the external controlled human face with the aim to identify fundamental electro-facial choreographic patterns. Rewiring the human face to an external digital control system, has sparked a radical new way of thinking about the human facial display. Radical, as facial movement is now rooted in digital instead of neural computation. The human face has become an extension of a digital control system inheriting its characteristics: i.e. temporal accuracy, consistency of execution and high programmability. How do we conceptualize the thinking about the human face as a digital computational display device? What are the implications of the “regime change” from neural to digital? The research addresses these issues within the contextual framework where it also originated, in the practice of hacking. It uses the results oriented methods and strategies of hacking to analyze, explore and contextualize the human facial display as a site for digital computational expression. The contributions of this work include the following. 1) External facial control transgresses the neural performance limitations and enables us to think about facial movement from a digital computational choreographic paradigm. 2) A facial language, the Language of Facial E-motion, that allows systematic computational exploration of possible facial movement patterns. Choreologic probing of dynamic face space has brought about unseen facial movement patterns and has uncovered a latent expressive potential of the facial hardware

Computational Intelligence in Electromyography Analysis

Electromyography (EMG) is a technique for evaluating and recording the electrical activity produced by skeletal muscles. EMG may be used clinically for the diagnosis of neuromuscular problems and for assessing biomechanical and motor control deficits and other functional disorders. Furthermore, it can be used as a control signal for interfacing with orthotic and/or prosthetic devices or other rehabilitation assists. This book presents an updated overview of signal processing applications and recent developments in EMG from a number of diverse aspects and various applications in clinical and experimental research. It will provide readers with a detailed introduction to EMG signal processing techniques and applications, while presenting several new results and explanation of existing algorithms. This book is organized into 18 chapters, covering the current theoretical and practical approaches of EMG research

Critical analysis of techniques for normalising electromyographic data : from laboratory to clinical research

Includes abstract.Includes bibliographical references (p. 185-201).Measurements of muscle activity derived from surface EMG electrodes are variable due to both intrinsic and extrinsic factors. The intrinsic factors are endogenous in nature (features within the body) and include muscle fiber type, muscle fiber diameter and length, the amount of tissue between muscle and electrode, and depth and location of muscle with respect to the placement of electrodes (24). These biological factors vary between subjects and cannot be controlled. The extrinsic factors are experimental variables which are influenced by the researcher and can be controlled to some extent. Examples of extrinsic factors include the location, area, orientation, shape of electrodes and the distance between electrodes (interelectrode distance). In order to measure biological variation in the EMG signal, which is important in studies where surface EMG is used to gain understanding of physiological regulation, it is important to minimise the variation caused by these factors. This is in part achieved through the appropriate method of normalisation. The isometric maximal voluntary contraction (MVC) has been used as a standardmethod of normalisation for both static and dynamic exercises. However, researchers have recently improved the methods of normalisation by developing alternative techniques for the measurement of EMG during dynamic activities. By using the same type of movement for normalisation as during the trial, experimental errors can be reduced. The appropriate method of normalisation is defined as a method that is capable of showing repeatability, reliability (low intra-subject variation) and sensitivity to changes in EMG amplitude that is due to biological change and not the contribution of experimental factors. The aim of this thesis was to critically analyse alternative methods of EMG normalisation during dynamic exercise. The data should provide possible guidelines to researchers who are planning studies involving measurement of EMG activity during cycling, running and in clinical populations. Furthermore, the thesis aimed to illustrate that decisions regarding the most appropriate method of normalisation should be based on the study design, research question (absolute muscle activity or changes in muscle pattern) and the muscles being investigated

Applications of EMG in Clinical and Sports Medicine

This second of two volumes on EMG (Electromyography) covers a wide range of clinical applications, as a complement to the methods discussed in volume 1. Topics range from gait and vibration analysis, through posture and falls prevention, to biofeedback in the treatment of neurologic swallowing impairment. The volume includes sections on back care, sports and performance medicine, gynecology/urology and orofacial function. Authors describe the procedures for their experimental studies with detailed and clear illustrations and references to the literature. The limitations of SEMG measures and methods for careful analysis are discussed. This broad compilation of articles discussing the use of EMG in both clinical and research applications demonstrates the utility of the method as a tool in a wide variety of disciplines and clinical fields

Network Modeling of Motor Pathways from Neural Recordings

During cued motor tasks, for both speech and limb movement, information propagates from primary sensory areas, to association areas, to primary and supplementary motor and language areas. Through the recent advent of high density recordings at multiple scales, it has become possible to simultaneously observe activity occurring from these disparate regions at varying resolution. Models of brain activity generally used in brain-computer interface (BCI) control do not take into account the global differences in recording site function, or the interactions between them. Through the use of connectivity measures, however, it has been made possible to determine the contribution of individual recording sites to the global activity, as they vary with task progression. This dissertation extends those connectivity models to provide summary information about the importance of individual sites. This is achieved through the application of network measures on the adjacency structure determined by connectivity measures. Similarly, by analyzing the coordinated activity of all of the electrode sites simultaneously during task performance, it is possible to elucidate discrete functional units through clustering analysis of the electrode recordings. In this dissertation, I first describe a BCI system using simple motor movement imagination at single recording sites. I then incorporate connectivity through the use of TV-DBN modeling on higher resolution electrode recordings, specifically electrocorticography (ECoG). I show that PageRank centrality reveals information about task progression and regional specificity which was obscured by direct application of the connectivity measures, due to the combinatorial increase in feature dimensionality. I then show that clustering of ECoG recordings using a method to determine the inherent cluster count algorithmically provides insight into how network involvement in task execution evolves, though in a manner dependent on grid coverage. Finally, I extend clustering analysis to show how individual neurons in motor cortex form distinct functional communities. These communities are shown to be task-specific, suggesting that neurons can form functional units with distinct neural populations across multiple recording sites in a context dependent impermanent manner. This work demonstrates that network measures of connectivity models of neurophysiological recordings are a rich source of information relevant to the field of neuroscience, as well as offering the promise of improved degree-of-freedom and naturalness possible through direct BCI control. These models are shown to be useful at multiple recording scales, from cortical-area level ECoG, to highly localized single unit microelectrode recordings

Internal representation in nurse education: Imagery and identity

The main aim of this thesis was to examine internal representation in the context of nurse education using two main output variables - namely imagery and identity. The initial basic argument for the thesis was that procedures to facilitate the acquisition of psychomotor skills that have been developed in sports science could fruitfully be applied to the development of skills in other areas, such as nurse education. Study one approached this through the use of an imagery training programme - PETTIER (Holmes & Collins, 2001) on an undergraduate nursing curriculum. PETTIER served as the independent variable with the dependent variable - performance - being measured through Obje&tive Structured Clinical Examinations (OSCEs). Unexpected results revealed no significant differences between the control and experimental groups, with the control group actually performing better overall. Given this, the explicit choice was made to pursue investigation into the other plausible factors affecting behaviour, in order to explicate and underpin the results obtained. Study two investigated students' perceptions of and preparation for the OSCEs using a skills training questionnaire. Results revealed common concerns, specifically related to skills practice. Furthermore these concerned the amount of practice time provided; the practice environment; and the amount of support and training during teaching. In light of these findings, study three pursued a contrasting and comparative investigation from the professionals' perspective on the curriculum. This specifically examined perceptions of the assessment structure and expectations within the curriculum; the content of the curriculum; levels of support and provision for training; and the application of theory and practice. This aimed to identify any coherent or conflicting views between the students' receiving the curriculum and the staff delivering the curriculum. Results revealed coherency in the professional view that theory and practice were equally as important for nurse education. However, students commonly perceived practice as the most important aspect. Also, some students often struggled to apply theory to practice and vice versa. In light of this it became apparent that students may in fact identify differently with the content of the curriculum. Therefore, appraisal of the content may have different significance for students and affect behaviour differently both internally and/or externally. Study four investigated this using Identity Structure Analysis (ISA)/lpseus (Weinreich & Saunderson, 2003).This explored how students applied themselves to the various aspects of nursing in the contexts of healthcare and broader affiliations, and how these fitted into students' broader sense of identity. It also looked at typologies within nursing and whether identity fitted into three distinct categories depending on construals. Study five followed this up using two individual case studies. The purpose of this was to encapsulate meaning behind individual construals and typologies and explicate the findings of ISA/lpseus and the implications for nurse education. Results found that construals are grounded in experiences which can affect development, behaviour and identity towards nursing and the broader affiliations in individuals' lives. In conclusion identity in nursing should be investigated further in order to provide stronger evidence in regards to typologies and how these may be influencing students' behaviour and development in nurse education. Such research could have important implications for the future of nurse education and be a positive step towards future curriculum revisions