Visual signs and symptoms of Parkinson's disease

Parkinson's disease (PD) is a common disorder of middle-aged and elderly people, in which there is degeneration of the extra-pyramidal motor system. In some patients, the disease is associated with a range of visual signs and symptoms, including defects in visual acuity, colour vision, the blink reflex, pupil reactivity, saccadic and smooth pursuit movements and visual evoked potentials. In addition, there may be psychophysical changes, disturbances of complex visual functions such as visuospatial orientation and facial recognition, and chronic visual hallucinations. Some of the treatments associated with PD may have adverse ocular reactions. If visual problems are present, they can have an important effect on overall motor function, and quality of life of patients can be improved by accurate diagnosis and correction of such defects. Moreover, visual testing is useful in separating PD from other movement disorders with visual symptoms, such as dementia with Lewy bodies (DLB), multiple system atrophy (MSA) and progressive supranuclear palsy (PSP). Although not central to PD, visual signs and symptoms can be an important though obscure aspect of the disease and should not be overlooked.

Spatial patterns of asynuclein positive glial cytoplasmic inclusions in multiple system atrophy

In cases of multiple system atrophy (MSA), glial cytoplasmic inclusions (GCI) were distributed randomly or present in large diffuse clusters (>1,600 μm in diameter) in most areas studied. These spatial patterns contrast with those reported for filamentous neuronal inclusions in the tauopathies and α-synucleinopathies. © 2003 Movement Disorder Society.

Functional interconnectivity between the globus pallidus and the subthalamic nucleus in the mouse brain slice

In accordance with its central role in basal ganglia circuitry, changes in the rate of action potential firing and pattern of activity in the globus pallidus (GP)-subthalamic nucleus (STN) network are apparent in movement disorders. In this study we have developed a mouse brain slice preparation that maintains the functional connectivity between the GP and STN in order to assess its role in shaping and modulating bursting activity promoted by pharmacological manipulations. Fibre-tract tracing studies indicated that a parasagittal slice cut 20 deg to the midline best preserved connectivity between the GP and the STN. IPSCs and EPSCs elicited by electrical stimulation confirmed connectivity from GP to STN in 44/59 slices and from STN to GP in 22/33 slices, respectively. In control slices, 74/76 (97%) of STN cells fired tonically at a rate of 10.3 ± 1.3 Hz. This rate and pattern of single spiking activity was unaffected by bath application of the GABAA antagonist picrotoxin (50 μM, n = 9) or the glutamate receptor antagonist (6-cyano-7-nitroquinoxaline-2, 3-dione (CNQX) 10 μM, n = 8). Bursting activity in STN neurones could be induced pharmacologically by application of NMDA alone (20 μM, 3/18 cells, 17%) but was more robust if NMDA was applied in conjunction with apamin (20-100 nM, 34/77 cells, 44%). Once again, neither picrotoxin (50 μM, n = 5) nor CNQX (10 μM, n = 5) had any effect on the frequency or pattern of the STN neurone activity while paired STN and GP recordings of tonic and bursting activity show no evidence of coherent activity. Thus, in a mouse brain slice preparation where functional GP-STN connectivity is preserved, no regenerative synaptically mediated activity indicative of a dynamic network is evident, either in the resting state or when neuronal bursting in both the GP and STN is generated by application of NMDA/apamin. This difference from the brain in Parkinson's disease may be attributed either to insufficient preservation of cortico-striato-pallidal or cortico-subthalamic circuitry, and/or an essential requirement for adaptive changes resulting from dopamine depletion for the expression of network activity within this tissue complex. © The Physiological Society 2005.

Visual signs and symptoms of progressive supranuclear palsy

Progressive supranuclear palsy is a rare, degenerative brain disorder and the second most common syndrome in which the patient exhibits 'parkinsonism', that is, a variety of symptoms involving problems with movement. General symptoms include difficulties with gait and balance; the patient walking clumsily and often falling backwards. The syndrome can be difficult to diagnose and visual signs and symptoms can help to separate it from closely related movement disorders such as Parkinson's disease, multiple system atrophy, dementia with Lewy bodies and corticobasal degeneration. A combination of the presence of vertical supranuclear gaze palsy, fixation instability, lid retraction, blepharospasm and apraxia of eyelid opening and closing may be useful visual signs in the identification of progressive supranuclear palsy. As primary eye-care practitioners, optometrists should be able to identify the visual problems of patients with this disorder and be expected to work with patients and their carers to manage their visual welfare.

Neuropathology of Basal Ganglia and its role in the Parkinsonian syndromes with special reference to the Globus pallidus

The globus pallidus, together with the striatum (caudate nucleus and putamen), substantia nigra, nucleus accumbens, and subthalamic nucleus constitute the basal ganglia, a group of nuclei which act as a single functional unit. The basal ganglia have extensive connections to the cerebral cortex and thalamus and exert control over a variety of functions including voluntary motor control, procedural learning, and motivation. The action of the globus pallidus is primarily inhibitory and balances the excitatory influence of other areas of the brain such as the cerebral cortex and cerebellum. Neuropathological changes affecting the basal ganglia play a significant role in the clinical signs and symptoms observed in the ‘parkinsonian syndromes’ viz., Parkinson’s disease (PD), progressive supranuclear palsy (PSP), dementia with Lewy bodies (DLB), multiple system atrophy (MSA), and corticobasal degeneration (CBD). There is increasing evidence that different regions of the basal ganglia are differentially affected in these disorders. Hence, in all parkinsonian disorders and especially PD, there is significant pathology affecting the substantia nigra and its dopamine projection to the striatum. However, in PSP and MSA, the globus pallidus is also frequently affected while in DLB and CBD, whereas the caudate nucleus and/or putamen are affected, the globus pallidus is often spared. This chapter reviews the functional pathways of the basal ganglia, with special reference to the globus pallidus, and the role that differential pathology in these regions may play in the movement disorders characteristic of the parkinsonian syndromes.

Clinical utility of implantable neurostimulation devices as adjunctive treatment of uncontrolled seizures

About one third of patients with epilepsy are refractory to medical treatment. For these patients, alternative treatment options include implantable neurostimulation devices such as vagus nerve stimulation (VNS), deep brain stimulation (DBS), and responsive neurostimulation systems (RNS). We conducted a systematic literature review to assess the available evidence on the clinical efficacy of these devices in patients with refractory epilepsy across their lifespan. VNS has the largest evidence base, and numerous randomized controlled trials and open-label studies support its use in the treatment of refractory epilepsy. It was approved by the US Food and Drug Administration in 1997 for treatment of partial seizures, but has also shown significant benefit in the treatment of generalized seizures. Results in adult populations have been more encouraging than in pediatric populations, where more studies are required. VNS is considered a safe and well-tolerated treatment, and serious side effects are rare. DBS is a well-established treatment for several movement disorders, and has a small evidence base for treatment of refractory epilepsy. Stimulation of the anterior nucleus of the thalamus has shown the most encouraging results, where significant decreases in seizure frequency were reported. Other potential targets include the centromedian thalamic nucleus, hippocampus, cerebellum, and basal ganglia structures. Preliminary results on RNS, new-generation implantable neurostimulation devices which stimulate brain structures only when epileptic activity is detected, are encouraging. Overall, implantable neurostimulation devices appear to be a safe and beneficial treatment option for patients in whom medical treatment has failed to adequately control their epilepsy. Further large-scale randomized controlled trials are required to provide a sufficient evidence base for the inclusion of DBS and RNS in clinical guidelines.

High-accuracy discrimination of Parkinson’s Disease participants from healthy controls using smartphones

Objective: To test the practicality and effectiveness of cheap, ubiquitous, consumer-grade smartphones to discriminate Parkinson’s disease (PD) subjects from healthy controls, using self-administered tests of gait and postural sway. Background: Existing tests for the diagnosis of PD are based on subjective neurological examinations, performed in-clinic. Objective movement symptom severity data, collected using widely-accessible technologies such as smartphones, would enable the remote characterization of PD symptoms based on self-administered, behavioral tests. Smartphones, when backed up by interviews using web-based videoconferencing, could make it feasible for expert neurologists to perform diagnostic testing on large numbers of individuals at low cost. However, to date, the compliance rate of testing using smart-phones has not been assessed. Methods: We conducted a one-month controlled study with twenty participants, comprising 10 PD subjects and 10 controls. All participants were provided identical LG Optimus S smartphones, capable of recording tri-axial acceleration. Using these smartphones, patients conducted self-administered, short (less than 5 minute) controlled gait and postural sway tests. We analyzed a wide range of summary measures of gait and postural sway from the accelerometry data. Using statistical machine learning techniques, we identified discriminating patterns in the summary measures in order to distinguish PD subjects from controls. Results: Compliance was high all 20 participants performed an average of 3.1 tests per day for the duration of the study. Using this test data, we demonstrated cross-validated sensitivity of 98% and specificity of 98% in discriminating PD subjects from healthy controls. Conclusions: Using consumer-grade smartphone accelerometers, it is possible to distinguish PD from healthy controls with high accuracy. Since these smartphones are inexpensive (around $30 each) and easily available, and the tests are highly non-invasive and objective, we envisage that this kind of smartphone-based testing could radically increase the reach and effectiveness of experts in diagnosing PD.

Machine learning for large-scale wearable sensor data in Parkinson disease:concepts, promises, pitfalls, and futures

For the treatment and monitoring of Parkinson's disease (PD) to be scientific, a key requirement is that measurement of disease stages and severity is quantitative, reliable, and repeatable. The last 50 years in PD research have been dominated by qualitative, subjective ratings obtained by human interpretation of the presentation of disease signs and symptoms at clinical visits. More recently, “wearable,” sensor-based, quantitative, objective, and easy-to-use systems for quantifying PD signs for large numbers of participants over extended durations have been developed. This technology has the potential to significantly improve both clinical diagnosis and management in PD and the conduct of clinical studies. However, the large-scale, high-dimensional character of the data captured by these wearable sensors requires sophisticated signal processing and machine-learning algorithms to transform it into scientifically and clinically meaningful information. Such algorithms that “learn” from data have shown remarkable success in making accurate predictions for complex problems in which human skill has been required to date, but they are challenging to evaluate and apply without a basic understanding of the underlying logic on which they are based. This article contains a nontechnical tutorial review of relevant machine-learning algorithms, also describing their limitations and how these can be overcome. It discusses implications of this technology and a practical road map for realizing the full potential of this technology in PD research and practice. © 2016 International Parkinson and Movement Disorder Society.

Technology in Parkinson's disease:challenges and opportunities

The miniaturization, sophistication, proliferation, and accessibility of technologies are enabling the capture of more and previously inaccessible phenomena in Parkinson's disease (PD). However, more information has not translated into a greater understanding of disease complexity to satisfy diagnostic and therapeutic needs. Challenges include noncompatible technology platforms, the need for wide-scale and long-term deployment of sensor technology (among vulnerable elderly patients in particular), and the gap between the "big data" acquired with sensitive measurement technologies and their limited clinical application. Major opportunities could be realized if new technologies are developed as part of open-source and/or open-hardware platforms that enable multichannel data capture sensitive to the broad range of motor and nonmotor problems that characterize PD and are adaptable into self-adjusting, individualized treatment delivery systems. The International Parkinson and Movement Disorders Society Task Force on Technology is entrusted to convene engineers, clinicians, researchers, and patients to promote the development of integrated measurement and closed-loop therapeutic systems with high patient adherence that also serve to (1) encourage the adoption of clinico-pathophysiologic phenotyping and early detection of critical disease milestones, (2) enhance the tailoring of symptomatic therapy, (3) improve subgroup targeting of patients for future testing of disease-modifying treatments, and (4) identify objective biomarkers to improve the longitudinal tracking of impairments in clinical care and research. This article summarizes the work carried out by the task force toward identifying challenges and opportunities in the development of technologies with potential for improving the clinical management and the quality of life of individuals with PD. © 2016 International Parkinson and Movement Disorder Society.

A smart sensing platform for the discrimination of human movement

This thesis documents the design, implementation and testing of a smart sensing platform that is able to discriminate between differences or small changes in a persons walking. The distributive tactile sensing method is used to monitor the deflection of the platform surface using just a small number of sensors and, through the use of neural networks, infer the characteristics of the object in contact with the surface. The thesis first describes the development of a mathematical model which uses a novel method to track the position of a moving load as it passes over the smart sensing surface. Experimental methods are then described for using the platform to track the position of swinging pendulum in three dimensions. It is demonstrated that the method can be extended to that of real-time measurement of balance and sway of a person during quiet standing. Current classification methods are then investigated for use in the classification of different gait patterns, in particular to identify individuals by their unique gait pattern. Based on these observations, a novel algorithm is developed that is able to discriminate between abnormal and affected gait. This algorithm, using the distributive tactile sensing method, was found to have greater accuracy than other methods investigated and was designed to be able to cope with any type of gait variation. The system developed in this thesis has applications in the area of medical diagnostics, either as an initial screening tool for detecting walking disorders or to be able to automatically detect changes in gait over time. The system could also be used as a discrete biometric identification method, for example identifying office workers as they pass over the surface.

Eye movement problems and differential diagnosis of the parkinsonian syndromes

Differential clinical diagnosis of the parkinsonian syndromes, viz., Parkinson’s disease (PD), progressive supranuclear palsy (PSP), dementia with Lewy bodies (DLB), and multiple system atrophy (MSA) can be difficult. Eye movement problems, however, are a chronic complication of many of these disorders and may be a useful aid to diagnosis. Hence, the presence in PSP of vertical supranuclear gaze palsy, fixation instability, lid retraction, blepharospasm, and apraxia of eyelid opening and closing is useful in separating PD from PSP. Moreover, atypical features of PSP include slowing of upward saccades, moderate slowing of downward saccades, the presence of a full range of voluntary vertical eye movements, a curved trajectory of oblique saccades, and absence of square-wave jerks. Downgaze palsy is probably the most useful diagnostic clinical symptom of PSP. By contrast, DLB patients are specifically impaired in both reflexive and saccadic execution and in the performance of more complex saccadic eye movement tasks. Problems in convergence in DLB are also followed by akinesia and rigidity. Abnormal ocular fixation may occur in a significant proportion of MSA patients along with excessive square-wave jerks, a mild supranuclear gaze palsy, a gaze-evoked nystagmus, a positioning down-beat nystagmus, mild-moderate saccadic hypometria, impaired smooth pursuit movements, and reduced vestibulo-ocular reflex (VOR) suppression. There may be considerable overlap between the eye movement problems characteristic of the various parkinsonian disorders, but taken together with other signs and symptoms, can be a useful aid in differential diagnosis, especially in the separation of PD and PSP.