Individuals with Parkinson's disease (PD) show marked impairments in their ability to generate self-initiated, or "voluntary", saccadic eye movements. Investigations of visually guided, or "reflexive", saccades have, on the other hand, produced inconclusive results with studies showing response times (RTs) in persons with PD that are slower, faster, or indistinguishable from those of controls. We performed a meta-analysis to establish whether there are consistent effects of PD on the metrics of visually guided saccades. Combining results across 47 studies we found that reflexive saccades are overall initiated more slowly in persons with PD than in controls, however, this analysis also revealed considerable heterogeneity across studies. Step-wise meta-regression, using eleven potential predictors, subsequently showed that differences in mean RT between controls and persons with PD may arise due to aspects of experimental design. In particular, mean target eccentricity was shown to impact substantially on RTs such that persons with PD predictably initiate saccades faster than controls at small target eccentricities, while responding more slowly for large target eccentricities. Changes in eye-tracking and display equipment over the period covered by the review were also found to have impacted on the pattern of results obtained. We conclude that a, previously unsuspected, eccentricity effect could explain why the saccadic eye movements of persons with PD are sometimes found to be "hyper-reflexive" compared to controls, and suggest that this effect may arise due to PD-induced changes in both peripheral perceptual processing and in central executive mechanisms involving the basal ganglia.

It is hypothesised that the basal ganglia play a key role in solving the problem of action selection. Here we investigate this hypothesis through computational modelling of the primate saccadic oculomotor system. This system is an excellent target for computational modelling because it is supported by a reasonably well understood functional anatomy, has limited degrees of freedom, and there is a wealth of behavioural and electrophysiological data for model comparison. Here, we describe a computational model of the reflexive saccadic oculomotor system incorporating the basal ganglia, key structures in motor control and competition between possible actions. To restrict the likelihood of overfitting the model it is structured and parameterised by the known anatomy and neurophysiology along with data from a single experimental behavioural paradigm, then validated by testing against several additional behavioural experimental data without modification of the parameters. With this model we reproduce a range of fundamental reflexive saccadic results both qualitatively and quantitatively, comprising: the distribution of saccadic latencies; the effect of eccentricity, luminance and 1/41 fixation-target interactions on saccadic latencies; and the effect of competing targets on saccadic endpoint. By investigating the model dynamics we are able to provide mechanistic explanations for the sources of these behaviours. Further, because of its accesibility, the oculomotor system has also been used to study general principle of sensorimotor control. We interpret the ability of the basal ganglia to successfully control saccade selection in our model as further evidence for the action selection hypothesis.1 Introduction 1 Saccades are ballistic eye movements that direct visual attention to putative targets of 2 interest. Given the primacy of vision as a sensory modality in humans, saccades are 3 clearly essential for our goal-directed behaviour. Reflexive saccades are elicited by the 4 phasic appearance of targets peripheral to the current fixation, and are to be contrasted 5 with voluntary saccades which are under cognitive control via, say, verbal instruction or 6 memory recall [1]. 7The selection of targets for saccade generation in the oculomotor system is a good 8 target for computational modelling for several reasons. First, the behavioural output 9 may be characterised with only three degrees of freedom (dof), of which we are often 10 only interested in two (for horizontal and vertical saccades). This is to be contrasted 11 with upper limb movement, say, which has seven dof (or many more if we work at level 12 of the musculature) [2]. Second, there is a wealth of behavioural data characterising 13 saccades -see for example, [3-6] -which has simple interpretation because of the 2-dof 14 constraint. Often this data takes the form of reaction time and/or saccade location to 15 stimulus onset in simple paradigms with one or two targets. Third, the anatomy of the 16 neural substrate is particularly well understood [7, 8] offerin...

The mammalian brain's decision mechanism may utilise a distributed network of positive feedback loops to integrate, over time, noisy sensory evidence for and against a particular choice. Such loops would mitigate the effects of noise and have the benefit of decoupling response size from the strength of evidence, which could assist animals in acting early at the first signs of opportunity or danger. This hypothesis is explored in the context of the sensorimotor control circuitry underlying eye movements, and in relation to the hypothesis that the basal ganglia serve as a central switch acting to control the competitive accumulation of sensory evidence in positive feedback loops representing alternative actions. Results, in support of these proposals, are presented from a systems-level computational model of the primate oculomotor control. This model is able to reproduce behavioural data relating strength of sensory evidence to response time and accuracy, while also demonstrating how the basal ganglia and related oculomotor circuitry might work together to manage the initiation, control and termination of the decision process over time.

Adaptive energy absorbers (EAs) utilizing magnetorheological fluids (MRFs) are currently being investigated for severe impact or shock mitigation problems because magnetorheological energy absorbers can adjust stroking load to account for severity of impact and payload mass. Utilizing MRFs in such EAs requires a highly stable suspension that maintains a uniform concentration. Suspension stability of MRFs can be studied using a MRF column and an automated vertical axis inductance monitoring system (AVAIMS), where an inductance sensor is translated up and down the vertical MRF column to track the mud-line, defined as the boundary between the clarified fluid at the top of the column and the MRF below. The rate of descent of the mud-line is typically referred to as the sedimentation rate of the MRF. In this paper, a refined inductance sensor is developed that features a low aspect ratio coil to better localize rapid changes in concentration or sedimentation zone boundaries, as well as to improve symmetry of the applied magnetic field in the MRF sample enclosed by the sensor. This low aspect ratio solenoid (LARS) sensor was developed to measure the vertical distribution of the concentration of carbonyl iron particles in the MRF column. Compared with the high aspect ratio solenoid sensor used in our prior work, the results of FEM simulation and sedimentation experiments demonstrate that the LARS sensor was better able to localize rapid changes in concentration or density. Using the AVAIMS with the refined LARS sensor, a method was developed, based on the measured concentration gradient profile, to identify sedimentation zone boundaries in an MRF column, and these results were compared to our prior work using the measured concentration profile only. Sedimentation zone boundaries that are consistent with Kynch's sedimentation theory were obtained using the concentration gradient profile method, such as monotonically descending mud-line, linearly ascending gel-line, and linearly ascending cake-line. Key metrics to characterize the time histories of the sedimentation zone boundaries are measured including mud-line descent rate, gel-line ascent rate, and cake-line ascent rate. Identification of sedimentation zone boundaries using the LARS sensor in conjunction with the concentration gradient profile method exhibited two main advantages including the direct measurement and improved localization of the large concentration change that occurs at a sedimentation zone boundary, and the elimination of sensor bias.

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