Self-reported body fat change in HIV-infected men is a marker of decline in physical health-related quality of life with aging, independent of co-morbidity

Objective: Self-perception of changes in body fat among HIV+ persons is associated with decreased health related quality of life in cross-sectional studies. The longitudinal impact of body fat changes on health related quality of life, while accounting for comorbidity and anatomic location or severity of body fat changes, is unknown. Design: This was a longitudinal analysis of HIV+ and HIV- Multicenter AIDS Cohort Study (MACS) participants who completed questionnaires assessing self-perceived body fat changes (baseline visit) and a health related quality of life (Short Form-36) at baseline and then ≥5 years later. Methods: Relationships between body fat changes and change in Short Form-36 Physical and Mental Component Summary scores were investigated using mixedmodel regression. Results: We studied 270 HIV+ and 247 HIV- men. At baseline, ≥50% of HIV+ men reported body fat changes; physical component but not mental component summary scores were lower among HIV+ men who reported moderate/severe leg or abdominal fat changes (p<0.05). At follow-up, physical component summary scores were significantly lower among men with face, leg, or abdominal fat changes compared to men without perceived fat changes (p<0.05). No significant changes were seen in mental component scores by fat change location or severity. In the final model, body fat changes at any site or severity were significant predictors of a decline in physical component summary score (p<0.05), independent of demographics or comorbidities. Mental component summary score was not associated with body fat changes, but higher mental component summary score was associated with increasing age and time. Conclusions: Negative self-perceived body fat changes were associated with decline in physical health related quality of life, independent of comorbidities, and may be a marker of an increased risk for physical function decline with aging

Visual perception in infantile nystagmus

Infantile nystagmus (IN) is often found in conjunction with afferent visual system pathology, but even in isolated cases, visual acuity (VA) is usually reduced. Most individuals with IN do not experience oscillopsia (illusory motion of the world). The presence of visual stability, despite constant eye motion, provides a uniquely dynamic perceptual scenario. Recent advances have demonstrated that VA alone is insufficient to fully explain the subjective perceptual experience of IN. The purpose of this review is to provide a clinical perspective on recent developments in the field, and summarise the novel techniques being used to gain a better understanding of the impact of treatment on visual function in IN

Quick phases of infantile nystagmus show the saccadic inhibition effect

Purpose: Infantile nystagmus (IN) is a pathological, involuntary oscillation of the eyes consisting of slow, drifting eye movements interspersed with rapid reorienting quick phases. The extent to which quick phases of IN are programmed similarly to saccadic eye movements remains unknown. We investigated whether IN quick phases exhibit 'saccadic inhibition', a phenomenon typically related to normal targeting saccades, in which the initiation of the eye movement is systematically delayed by task-irrelevant visual distractors. Methods: We recorded eye position from 10 observers with early-onset idiopathic nystagmus while task-irrelevant distractor stimuli were flashed along the top and bottom of a large screen at ±10° eccentricity. The latency distributions of quick phases were measured with respect to these distractor flashes. Two additional participants, one with possible albinism and one with fusion maldevelopment nystagmus syndrome, were also tested. Results: All observers showed that a distractor flash delayed the execution of quick phases that would otherwise have occurred around 100 ms later, exactly as in the standard saccadic inhibition effect. The delay did not appear to differ between the two main nystagmus types under investigation (idiopathic IN with unidirectional and bidirectional jerk). Conclusions: The presence of the saccadic inhibition effect in IN quick phases is consistent with the idea that quick phases and saccades share a common programming pathway. This could allow quick phases to take on flexible, goal-directed behaviour, at odds with the view that IN quick phases are stereotyped, involuntary eye movements

Analysing nystagmus waveforms: a computational framework

We present a new computational approach to analyse nystagmus waveforms. Our framework is designed to fully characterise the state of the nystagmus, aid clinical diagnosis and to quantify the dynamical changes in the oscillations over time. Both linear and nonlinear analyses of time series were used to determine the regularity and complexity of a specific homogenous phenotype of nystagmus. Two-dimensional binocular eye movement recordings were carried out on 5 adult subjects who exhibited a unilateral, uniplanar, vertical nystagmus secondary to a monocular late-onset severe visual loss in the oscillating eye (the Heimann-Bielschowsky Phenomenon). The non-affected eye held a central gaze in both horizontal and vertical planes (± 10 min. of arc). All affected eyes exhibited vertical oscillations, with mean amplitudes and frequencies ranging from 2.0°–4.0° to 0.25–1.5 Hz, respectively. Unstable periodic orbit analysis revealed only 1 subject exhibited a periodic oscillation. The remaining subjects were found to display quasiperiodic (n = 1) and nonperiodic (n = 3) oscillations. Phase space reconstruction allowed attractor identification and the computation of a time series complexity measure—the permutation entropy. The entropy measure was found to be able to distinguish between a periodic oscillation associated with a limit cycle attractor, a quasiperiodic oscillation associated with a torus attractor and nonperiodic oscillations associated with higher-dimensional attractors. Importantly, the permutation entropy was able to rank the oscillations, thereby providing an objective index of nystagmus complexity (range 0.15–0.21) that could not be obtained via unstable periodic orbit analysis or attractor identification alone. These results suggest that our framework provides a comprehensive methodology for characterising nystagmus, aiding differential diagnosis and also permitting investigation of the waveforms over time, thereby facilitating the quantification of future therapeutic managements. In addition, permutation entropy could provide an additional tool for future oculomotor modelling

Modelling of congenital nystagmus waveforms produced by saccadic system abnormalities

Models of the mechanisms of normal eye movements are typically described in terms of the block diagrams which are used in control theory. An alternative approach to understanding the mechanisms of normal eye movements involves describing the eye movement behaviour in terms of smooth changes in state variables. The latter approach captures the burst cell firing against motor error (difference between target gaze angle and current gaze angle) phase plane behaviour which is found experimentally and facilitates the modelling of variations in burst cell behaviour. A novel explanation of several types of congenital nystagmus waveforms is given in terms of a saccadic termination abnormality

The Fourier analysis of saccadic eye movements

This thesis examines saccadic eye movements in the frequency domain and develops sensitive tools for characterising their dynamics. It tests a variety of saccade models and provides the first strong empirical evidence that saccades are time-optimal. By enabling inferences on the neural command, it also allows for better clinical differentiation of abnormalities and the evaluation of putative mechanisms for the development of congenital nystagmus. Chapters 3 and 4 show how Fourier transforms reveal sharp minima in saccade frequency spectra, which are robust to instrument noise. The minima allow models based purely on the output trajectory, purely on the neural input, or both, to be directly compared and distinguished. The standard, most commonly accepted model based on bang-bang control theory is discounted. Chapter 5 provides the first empirical evidence that saccades are time-optimal by demonstrating that saccade bandwidths overlap across amplitude onto a single slope at high frequencies. In Chapter 6, the overlap also allows optimal (Wiener) filtering in the frequency domain without a priori assumptions. Deconvolution of the aggregate neural driving signal is then possible for current models of the oculomotor plant. The final two chapters apply these Fourier techniques to the quick phases of physiological (optokinetic) nystagmus and of pathological (congenital) nystagmus. These quick phases are commonly assumed to be saccadic in origin. This assumption is thoroughly tested and found to hold, but with subtle differences implying that the smooth pursuit system interacts with the saccade system during the movement. This interaction is taken into account in Chapter 8 in the assessment of congenital nystagmus quick phases, which are found to be essentially normal. Congenital nystagmus models based on saccadic abnormalities are appraised

Optimisation and Computational Methods to Model the Oculomotor System with Focus on Nystagmus

Open access. Use it freely but cite it.Infantile nystagmus is a condition that causes involuntary, bilateral and conjugate oscillations of the eyes, which are predominately restricted to the horizontal plane. In order to investigate the cause of nystagmus, computational models and nonlinear dynamics techniques have been used to model and analyse the oculomotor system. Computational models are important in making predictions and creating a quantitative framework for the analysis of the oculomotor system. Parameter estimation is a critical step in the construction and analysis of these models. A preliminary parameter estimation of a nonlinear dynamics model proposed by Broomhead et al. [1] has been shown to be able to simulate both normal rapid eye movements (i.e. saccades) and nystagmus oscillations. The application of nonlinear analysis to experimental jerk nystagmus recordings, has shown that the local dimensions number of the oscillation varies across the phase angle of the nystagmus cycle. It has been hypothesised that this is due to the impact of signal dependent noise (SDN) on the neural commands in the oculomotor system. The main aims of this study were: (i) to develop parameter estimation methods for the Broomhead et al. [1] model in order to explore its predictive capacity by fitting it to experimental recordings of nystagmus waveforms and saccades; (ii) to develop a stochastic oculomotor model and examine the hypothesis that noise on the neural commands could be the cause of the behavioural characteristics measured from experimental nystagmus time series using nonlinear analysis techniques. In this work, two parameter estimation methods were developed, one for fitting the model to the experimental nystagmus waveforms and one to saccades. By using the former method, we successfully fitted the model to experimental nystagmus waveforms. This fit allowed to find the specific parameter values that set the model to generate these waveforms. The types of the waveforms that we successfully fitted were asymmetric pseudo-cycloid, jerk and jerk with extended foveation. The fit of other types of nystagmus waveforms were not examined in this work. Moreover, the results showed which waveforms the model can generate almost perfectly and the waveform characteristics of a number of jerk waveforms which it cannot exactly generate. These characteristics were on a specific type of jerk nystagmus waveforms with a very extreme fast phase. The latter parameter estimation method allowed us to explore whether the model can generate horizontal saccades of different amplitudes with the same behaviour as observed experimentally. The results suggest that the model can generate the experimental saccadic velocity profiles of different saccadic amplitudes. However, the results show that best fittings of the model to the experimental data are when different model parameter values were used for different saccadic amplitude. Our parameter estimation methods are based on multi-objective genetic algorithms (MOGA), which have the advantage of optimising biological models with a multi-objective, high-dimensional and complex search space. However, the integration of these models, for a wide range of parameter combinations, is very computationally intensive for a single central processing unit (CPU). To overcome this obstacle, we accelerated the parameter estimation method by utilising the parallel capabilities of a graphics processing unit (GPU). Depending of the GPU model, this could provide a speedup of 30 compared to a midrange CPU. The stochastic model that we developed is based on the Broomhead et al. [1] model, with signal dependent noise (SDN) and constant noise (CN) added to the neural commands. We fitted the stochastic model to saccades and jerk nystagmus waveforms. It was found that SDN and CN can cause similar variability to the local dimensions number of the oscillation as found in the experimental jerk nystagmus waveforms and in the case of saccade generation the saccadic variability recorded experimentally. However, there are small differences in the simulated behaviour compared to the nystagmus experimental data. We hypothesise that these could be caused by the inability of the model to simulate exactly key jerk waveform characteristics. Moreover, the differences between the simulations and the experimental nystagmus waveforms indicate that the proposed model requires further expansion, and this could include other oculomotor subsystem(s).Engineering and Physical Sciences Research Council (EPSRC