A psychophysical assessment of visual motion processing among high-functioning persons with autism

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

A psychophysical assessment of visual motion processing among high-functioning persons with autism

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

The neuro-muscular and musculo-skeletal characterization of children with joint hypermobility

In children, joint hypermobility (typified by structural instability of joints) manifests clinically as neuro-muscular and musculo-skeletal conditions and conditions associated with development and organization of control of posture and gait (Finkelstein, 1916; Jahss, 1919; Sobel, 1926; Larsson, Mudholkar, Baum and Srivastava, 1995; Murray and Woo, 2001; Hakim and Grahame, 2003; Adib, Davies, Grahame, Woo and Murray, 2005:). The process of control of the relative proportions of joint mobility and stability, whilst maintaining equilibrium in standing posture and gait, is dependent upon the complex interrelationship between skeletal, muscular and neurological function (Massion, 1998; Gurfinkel, Ivanenko, Levik and Babakova, 1995; Shumway-Cook and Woollacott, 1995). The efficiency of this relies upon the integrity of neuro-muscular and musculo-skeletal components (ligaments, muscles, nerves), and the Central Nervous System’s capacity to interpret, process and integrate sensory information from visual, vestibular and proprioceptive sources (Crotts, Thompson, Nahom, Ryan and Newton, 1996; Riemann, Guskiewicz and Shields, 1999; Schmitz and Arnold, 1998) and development and incorporation of this into a representational scheme (postural reference frame) of body orientation with respect to internal and external environments (Gurfinkel et al., 1995; Roll and Roll, 1988). Sensory information from the base of support (feet) makes significant contribution to the development of reference frameworks (Kavounoudias, Roll and Roll, 1998). Problems with the structure and/ or function of any one, or combination of these components or systems, may result in partial loss of equilibrium and, therefore ineffectiveness or significant reduction in the capacity to interact with the environment, which may result in disability and/ or injury (Crotts et al., 1996; Rozzi, Lephart, Sterner and Kuligowski, 1999b). Whilst literature focusing upon clinical associations between joint hypermobility and conditions requiring therapeutic intervention has been abundant (Crego and Ford, 1952; Powell and Cantab, 1983; Dockery, in Jay, 1999; Grahame, 1971; Childs, 1986; Barton, Bird, Lindsay, Newton and Wright, 1995a; Rozzi, et al., 1999b; Kerr, Macmillan, Uttley and Luqmani, 2000; Grahame, 2001), there has been a deficit in controlled studies in which the neuro-muscular and musculo-skeletal characteristics of children with joint hypermobility have been quantified and considered within the context of organization of postural control in standing balance and gait. This was the aim of this project, undertaken as three studies. The major study (Study One) compared the fundamental neuro-muscular and musculo-skeletal characteristics of 15 children with joint hypermobility, and 15 age (8 and 9 years), gender, height and weight matched non-hypermobile controls. Significant differences were identified between previously undiagnosed hypermobile (n=15) and non-hypermobile children (n=15) in passive joint ranges of motion of the lower limbs and lumbar spine, muscle tone of the lower leg and foot, barefoot CoP displacement and in parameters of barefoot gait. Clinically relevant differences were also noted in barefoot single leg balance time. There were no differences between groups in isometric muscle strength in ankle dorsiflexion, knee flexion or extension. The second comparative study investigated foot morphology in non-weight bearing and weight bearing load conditions of the same children with and without joint hypermobility using three dimensional images (plaster casts) of their feet. The preliminary phase of this study evaluated the casting technique against direct measures of foot length, forefoot width, RCSP and forefoot to rearfoot angle. Results indicated accurate representation of elementary foot morphology within the plaster images. The comparative study examined the between and within group differences in measures of foot length and width, and in measures above the support surface (heel inclination angle, forefoot to rearfoot angle, normalized arch height, height of the widest point of the heel) in the two load conditions. Results of measures from plaster images identified that hypermobile children have different barefoot weight bearing foot morphology above the support surface than non-hypermobile children, despite no differences in measures of foot length or width. Based upon the differences in components of control of posture and gait in the hypermobile group, identified in Study One and Study Two, the final study (Study Three), using the same subjects, tested the immediate effect of specifically designed custom-made foot orthoses upon balance and gait of hypermobile children. The design of the orthoses was evaluated against the direct measures and the measures from plaster images of the feet. This ascertained the differences in morphology of the modified casts used to mould the orthoses and the original image of the foot. The orthoses were fitted into standardized running shoes. The effect of the shoe alone was tested upon the non-hypermobile children as the non-therapeutic equivalent condition. Immediate improvement in balance was noted in single leg stance and CoP displacement in the hypermobile group together with significant immediate improvement in the percentage of gait phases and in the percentage of the gait cycle at which maximum plantar flexion of the ankle occurred in gait. The neuro-muscular and musculo-skeletal characteristics of children with joint hypermobility are different from those of non-hypermobile children. The Beighton, Solomon and Soskolne (1973) screening criteria successfully classified joint hypermobility in children. As a result of this study joint hypermobility has been identified as a variable which must be controlled in studies of foot morphology and function in children. The outcomes of this study provide a basis upon which to further explore the association between joint hypermobility and neuro-muscular and musculo-skeletal conditions, and, have relevance for the physical education of children with joint hypermobility, for footwear and orthotic design processes, and, in particular, for clinical identification and treatment of children with joint hypermobility.

Multi-step ahead direct prediction for the machine condition prognosis using regression trees and neuro-fuzzy systems

This paper presents an approach to predict the operating conditions of machine based on classification and regression trees (CART) and adaptive neuro-fuzzy inference system (ANFIS) in association with direct prediction strategy for multi-step ahead prediction of time series techniques. In this study, the number of available observations and the number of predicted steps are initially determined by using false nearest neighbor method and auto mutual information technique, respectively. These values are subsequently utilized as inputs for prediction models to forecast the future values of the machines’ operating conditions. The performance of the proposed approach is then evaluated by using real trending data of low methane compressor. A comparative study of the predicted results obtained from CART and ANFIS models is also carried out to appraise the prediction capability of these models. The results show that the ANFIS prediction model can track the change in machine conditions and has the potential for using as a tool to machine fault prognosis.

Fault diagnosis of induction motor based on decision trees and adaptive neuro-fuzzy inference

This paper presents a fault diagnosis method based on adaptive neuro-fuzzy inference system (ANFIS) in combination with decision trees. Classification and regression tree (CART) which is one of the decision tree methods is used as a feature selection procedure to select pertinent features from data set. The crisp rules obtained from the decision tree are then converted to fuzzy if-then rules that are employed to identify the structure of ANFIS classifier. The hybrid of back-propagation and least squares algorithm are utilized to tune the parameters of the membership functions. In order to evaluate the proposed algorithm, the data sets obtained from vibration signals and current signals of the induction motors are used. The results indicate that the CART–ANFIS model has potential for fault diagnosis of induction motors.

Developing an evidence-based clinical pathway for the assessment, diagnosis and management of acute Charcot Neuro-Arthropathy : a systematic review

Background: Charcot Neuro-Arthropathy (CN) is one of the more devastating complications of diabetes. To the best of the authors' knowledge, it appears that no clinical tools based on a systematic review of existing literature have been developed to manage acute CN. Thus, the aim of this paper was to systematically review existing literature and develop an evidence-based clinical pathway for the assessment, diagnosis and management of acute CN in patients with diabetes. Methods: Electronic databases (Medline, PubMed, CINAHL, Embase and Cochrane Library), reference lists, and relevant key websites were systematically searched for literature discussing the assessment, diagnosis and/or management of acute CN published between 2002-2012. At least two independent investigators then quality rated and graded the evidence of each included paper. Consistent recommendations emanating from the included papers were then fashioned in a clinical pathway. Results: The systematic search identified 267 manuscripts, of which 117 (44%) met the inclusion criteria for this study. Most manuscripts discussing the assessment, diagnosis and/or management of acute CN constituted level IV (case series) or EO (expert opinion) evidence. The included literature was used to develop an evidence-based clinical pathway for the assessment, investigations, diagnosis and management of acute CN. Conclusions: This research has assisted in developing a comprehensive, evidence-based clinical pathway to promote consistent and optimal practice in the assessment, diagnosis and management of acute CN. The pathway aims to support health professionals in making early diagnosis and providing appropriate immediate management of acute CN, ultimately reducing its associated complications such as amputations and hospitalisations.

Prediction of driving safety in individuals with homonymous hemianopia and quadrantanopia from clinical neuro-imaging

BACKGROUND: The objective of this study was to determine whether it is possible to predict driving safety in individuals with homonymous hemianopia or quadrantanopia based upon a clinical review of neuro-images that are routinely available in clinical practice. METHODS: Two experienced neuro-ophthalmologists viewed a summary report of the CT/MRI scans of 16 participants with homonymous hemianopic or quadrantanopic field defects which provided information regarding the site and extent of the lesion and made predictions regarding whether they would be safe/unsafe to drive. Driving safety was defined using two independent measures: (1) The potential for safe driving was defined based upon whether the participant was rated as having the potential for safe driving, determined through a standardized on-road driving assessment by a certified driving rehabilitation specialist conducted just prior and (2) state recorded motor vehicle crashes (all crashes and at-fault). Driving safety was independently defined at the time of the study by state recorded motor vehicle crashes (all crashes and at-fault) recorded over the previous 5 years, as well as whether the participant was rated as having the potential for safe driving, determined through a standardized on-road driving assessment by a certified driving rehabilitation specialist. RESULTS: The ability to predict driving safety was highly variable regardless of the driving outcome measure, ranging from 31% to 63% (kappa levels ranged from -0.29 to 0.04). The level of agreement between the neuro-ophthalmologists was also only fair (kappa =0.28). CONCLUSIONS: The findings suggest that clinical evaluation of summary reports currently available neuro-images by neuro-ophthalmologists is not predictive of driving safety. Future research should be directed at identifying and/or developing alternative tests or strategies to better enable clinicians to make these predictions.

Neuro- and immunotoxic effects of fumonisin B1 in cells

Fumonisin B1 (FB1) is a mycotoxin produced by the fungus Fusarium verticillioides, which commonly infects corn and other agricultural products. Fusarium species can also be found in moisture-damaged buildings, and therefore there may also be human exposure to Fusarium mycotoxins, including FB1. FB1 affects the metabolism of sphingolipids by inhibiting the enzyme ceramide synthase. It is neuro-, hepato- and nephrotoxic, and it is classified as possibly carcinogenic to humans. This study aimed to clarify the mechanisms behind FB1-induced neuro- and immunotoxicity. Four neural and glial cell lines of human, rat and mouse origin were exposed to graded doses of FB1 and the effects on the production of reactive oxygen species, lipid peroxidation, intracellular glutathione levels, cell viability and apoptosis were investigated. Furthermore, the effects of FB1, alone or together with lipopolysaccharide (LPS), on the mRNA and protein expression levels of different cytokines and chemokines were studied in human dendritic cells (DC). FB1 induced oxidative stress and cell death in all cell lines studied. Generally, the effects were only seen after prolonged exposure at 10 and 100 µM of FB1. Signs of apoptosis were also seen in all four cell lines. The sensitivities of the cell lines used in this study towards FB1 may be classified as human U-118MG glioblastoma > mouse GT1-7 hypothalamic > rat C6 glioblastoma > human SH-SY5Y neuroblastoma cells. When comparing cell lines of human origin, it can be concluded that glial cells seem to be more sensitive towards FB1 toxicity than those of neural origin. After exposure to FB1, significantly increased levels of the cytokine interferon-γ (IFNγ) were detected in human DC. This observation was further confirmed by FB1-induced levels of the chemokine CXCL9, which is known to be regulated by IFNγ. During co-exposure of DC to both LPS and FB1, significant inhibitions of the LPS-induced levels of the pro-inflammatory cytokines interleukin-6 (IL-6) and IL-1β, and their regulatory chemokines CCL3 and CCL5 were observed. FB1 can thus affect immune responses in DC, and therefore, it is rather likely that it also affects other types of cells participating in the immune defence system. When evaluating the toxicity potential of FB1, it is important to consider the effects on different cell types and cell-cell interactions. The results of this study represent new information, especially about the mechanisms behind FB1-induced oxidative stress, apoptosis and immunotoxicity, as well as the varying sensitivities of different cell types towards FB1.

Structured model-following neuro-adaptive design for attitude maneuver of rigid bodies

A new structured model-following adaptive approach is presented in this paper to achieve large attitude maneuvers of rigid bodies. First, a nominal controller is designed using the dynamic inversion philosophy. Next, a neuro- adaptive design is proposed to augment the nominal design in order to assure robust performance in the presence of parameter inaccuracies as well as unknown constant external disturbances. The structured approach proposed in this paper (where kinematic and dynamic equations are handled separately), reduces the complexity of the controller structure. From simulation studies, this adaptive controller is found to be very effective in assuring robust performance.

Neuro-angiostrongylosis in wild Black and Grey-headed flying foxes (Pteropus spp)

Objective: To identify nematodes seen in histological sections of brains of flying foxes (fruit bats) and describe the associated clinical disease and pathology. Proceedures: Gross and histological examination of brains from 86 free-living flying foxes with neurological disease was done as part of an ongoing surveillance program for Australian bat lyssavirus. Worms were recovered, or if seen in histological sections, extracted by maceration of half the brain and identified by microscopic examination. Histological archives were also reviewed. Results: There was histological evidence of angiostrongylosis in 16 of 86 recently submitted flying foxes with neurological disease and in one archival case from 1992. In 10 flying foxes, worms were definitively identified as Angiostrongylus cantonensis fifth-stage larvae. A worm fragment and third stage larvae were identified as Angiostrongylus sp, presumably A cantonensis, in a further three cases. The clinical picture was dominated by paresis, particularly of the hindlimbs, and depression, with flying foxes surviving up to 22 days in the care of wildlife volunteers. Brains containing fifthstage larvae showed a moderate to severe eosinophilic and granulomatous meningoencephalitis (n = 14), whereas there was virtually no inflammation of the brains of bats which died when infected with only smaller, third-stage larvae (n = 3). There was no histological evidence of pulmonary involvement. Conclusion: This is the first report of the recovery and identification of A cantonensis from free-living Australian wildlife. While angiostrongylosis is a common cause of paresis in flying foxes, the initial clinical course cannot be differentiated from Australian bat lyssavirus infection, and wildlife carers should be urged not to attempt to rehabilitate flying foxes with neurological disease.

An optimal dynamic inversion-based neuro-adaptive approach for treatment of chronic myelogenous leukemia

Combining the advanced techniques of optimal dynamic inversion and model-following neuro-adaptive control design, an innovative technique is presented to design an automatic drug administration strategy for effective treatment of chronic myelogenous leukemia (CML). A recently developed nonlinear mathematical model for cell dynamics is used to design the controller (medication dosage). First, a nominal controller is designed based on the principle of optimal dynamic inversion. This controller can treat the nominal model patients (patients who can be described by the mathematical model used here with the nominal parameter values) effectively. However, since the system parameters for a realistic model patient can be different from that of the nominal model patients, simulation studies for such patients indicate that the nominal controller is either inefficient or, worse, ineffective; i.e. the trajectory of the number of cancer cells either shows non-satisfactory transient behavior or it grows in an unstable manner. Hence, to make the drug dosage history more realistic and patient-specific, a model-following neuro-adaptive controller is augmented to the nominal controller. In this adaptive approach, a neural network trained online facilitates a new adaptive controller. The training process of the neural network is based on Lyapunov stability theory, which guarantees both stability of the cancer cell dynamics as well as boundedness of the network weights. From simulation studies, this adaptive control design approach is found to be very effective to treat the CML disease for realistic patients. Sufficient generality is retained in the mathematical developments so that the technique can be applied to other similar nonlinear control design problems as well.

A neuro-adaptive augmented optimal dynamic inversion approach for effective and efficient treatment of chronic myelogenous leukemia

Combining the advanced techniques of optimal dynamic inversion and model-following neuro-adaptive control design, an efficient technique is presented for effective treatment of chronic myelogenous leukemia (CML). A recently developed nonlinear mathematical model for cell dynamics is used for the control (medication) synthesis. First, taking a set of nominal parameters, a nominal controller is designed based on the principle of optimal dynamic inversion. This controller can treat nominal patients (patients having same nominal parameters as used for the control design) effectively. However, since the parameters of an actual patient can be different from that of the ideal patient, to make the treatment strategy more effective and efficient, a model-following neuro-adaptive controller is augmented to the nominal controller. In this approach, a neural network trained online (based on Lyapunov stability theory) facilitates a new adaptive controller, computed online. From the simulation studies, this adaptive control design approach (treatment strategy) is found to be very effective to treat the CML disease for actual patients. Sufficient generality is retained in the theoretical developments in this paper, so that the techniques presented can be applied to other similar problem as well. Note that the technique presented is computationally non-intensive and all computations can be carried out online.

A Neuro-Adaptive Approach for Robust Control of High Performance Aircrafts with Parameter Inaccuracies

For high performance aircrafts, the flight control system needs to be quite effective in both assuring accurate tracking of pilot commands, while simultaneously assuring overall stability of the aircraft. In addition, the control system must also be sufficiently robust to cater to possible parameter variations. The primary aim of this paper is to enhance the robustness of the controller for a HPA using neuro-adaptive control design. Here the architecture employs a network of Gaussian Radial basis functions to adaptively compensate for the ignored system dynamics. A stable weight mechanism is determined using Lyapunov theory. The network construction and performance of the resulting controller are illustrated through simulations with a low-fidelity six –DOF model of F16 that is available in open literature.

Model-following Neuro-adaptive approach for robust control of high performance aircrafts

Based on dynamic inversion, a relatively straightforward approach is presented in this paper for nonlinear flight control design of high performance aircrafts, which does not require the normal and lateral acceleration commands to be first transferred to body rates before computing the required control inputs. This leads to substantial improvement of the tracking response. Promising results are obtained from six degree-offreedom simulation studies of F-16 aircraft, which are found to be superior as compared to an existing approach (which is also based on dynamic inversion). The new approach has two potential benefits, namely reduced oscillatory response (including elimination of non-minimum phase behavior) and reduced control magnitude. Next, a model-following neuron-adaptive design is augmented the nominal design in order to assure robust performance in the presence of parameter inaccuracies in the model. Note that in the approach the model update takes place adaptively online and hence it is philosophically similar to indirect adaptive control. However, unlike a typical indirect adaptive control approach, there is no need to update the individual parameters explicitly. Instead the inaccuracy in the system output dynamics is captured directly and then used in modifying the control. This leads to faster adaptation, which helps in stabilizing the unstable plant quicker. The robustness study from a large number of simulations shows that the adaptive design has good amount of robustness with respect to the expected parameter inaccuracies in the model.

Fast Robust Pattern Classification Algorithms for Real Time Neuro-Motor Prosthetic Applications

In this paper, we give a brief review of pattern classification algorithms based on discriminant analysis. We then apply these algorithms to classify movement direction based on multivariate local field potentials recorded from a microelectrode array in the primary motor cortex of a monkey performing a reaching task. We obtain prediction accuracies between 55% and 90% using different methods which are significantly above the chance level of 12.5%.