Morphosyntactic and syntactic priming: an investigation of underlying processing mechanisms and the effects of Parkinson’s disease

There is now considerable evidence to suggest that non-demented people with Parkinson's disease (PD) experience difficulties using the morphosyntactic aspects of language. It remains unclear, however, at precisely which point in the processing of morphosyntax, these difficulties emerge. The major objective of the present study was to examine the impact of PD on the processes involved in accessing morphosyntactic information in the lexicon. Nineteen people with PD and 19 matched control subjects participated in the study which employed on-line word recognition tasks to examine morphosyntactic priming for local grammatical dependencies that occur both within (e.g. is going) and across (e.g. she gives) phrasal boundaries (Experiments 1 and 2, respectively). The control group evidenced robust morphosyntactic priming effects that were consistent with the involvement of both pre- (Experiment 1) and post-lexical (Experiment 2) processing routines. Whilst the participants with PD also recorded priming for dependencies within phrasal boundaries (Experiment 1), priming effects were observed over an abnormally brief time course. Further, in contrast to the controls, the PD group failed to record morphosyntactic priming for constructions that crossed phrasal boundaries (Experiment 2). The results demonstrate that attentionally mediated mechanisms operating at both the pre- and post-lexical stages of processing are able to contribute to morphosyntactic priming effects. In addition, the findings support the notion that, whilst people with PD are able to access morphosyntactic information in a normal manner, the time frame in which this information remains available for processing is altered. Deficits may also be experienced at the post-lexical integrational stage of processing.

Discourse priming of homophones in individuals with dominant subcortical lesions, cortical lesions, and Parkinson’s disease

An on-line priming experiment was used to investigate discourse-level processing in four matched groups of subjects: individuals with nonthalamic subcortical lesions (NSL) ( n =10), normal control subjects ( n =10), subjects with Parkinsons disease (PD) ( n =10), and subjects with cortical lesions ( n =10). Subjects listened to paragraphs that ended in lexical ambiguities, and then made speeded lexical decisions on visual letter strings that were: nonwords, matched control words, contextually appropriate associates of the lexical ambiguity, contextually inappropriate associates of the ambiguity, and inferences (representing information which could be drawn from the paragraphs but was not explicitly stated). Targets were presented at an interstimulus interval (ISI) of 0 or 1000ms. NSL and PD subjects demonstrated priming for appropriate and inappropriate associates at the short ISI, similar to control subjects and cortical lesion subjects, but were unable to demonstrate selective priming of the appropriate associate and inference words at the long ISI. These results imply intact automatic lexical processing and a breakdown in discourse-based meaning selection and inference development via attentional/strategic mechanisms.

Test–retest repeatability of self-reported environmental exposures in Parkinson’s disease cases and healthy controls

There is substantial disagreement among published epidemiological studies regarding environmental risk factors for Parkinson’s disease (PD). Differences in the quality of measurement of environmental exposures may contribute to this variation. The current study examined the test–retest repeatability of self-report data on risk factors for PD obtained from a series of 32 PD cases recruited from neurology clinics and 29 healthy sex-, age-and residential suburb-matched controls. Exposure data were collected in face-to-face interviews using a structured questionnaire derived from previous epidemiological studies. High repeatability was demonstrated for ‘lifestyle’ exposures, such as smoking and coffee/tea consumption (kappas 0.70–1.00). Environmental exposures that involved some action by the person, such as pesticide application and use of solvents and metals, also showed high repeatability (kappas>0.78). Lower repeatability was seen for rural residency and bore water consumption (kappa 0.39–0.74). In general, we found that case and control participants provided similar rates of incongruent and missing responses for categorical and continuous occupational, domestic, lifestyle and medical exposures.

Prevalence of Parkinson’s disease in metropolitan and rural Queensland: A general practice survey

The prevalence of idiopathic Parkinson’s disease (IPD) in Australia is unclear. We estimated the prevalence of IPD, and other forms of parkinsonism, through the study of typical caseloads in general practice. A random sample of general practitioners (GPs) throughout Queensland (401 responses from 528 validated practice addresses) was asked to estimate the numbers of patients with IPD and parkinsonism seen in the preceding year. The estimated prevalence of diagnosed IPD in Queensland was 146 per 100 000 (95% CI = 136–155). A further 51 per 100 000 in the population were suspected by doctors to have IPD without formal diagnosis, whereas another 51 per 100 000 people may have non-idiopathic parkinsonism. Idiopathic Parkinson’s disease was more common in rural than metropolitan areas. Although most GPs were confident in making diagnoses of IPD, the majority had little or no confidence in their ability to treat the disease, especially in its later stages. Support from neurologists was perceived by GPs to be very good in cities, but poor in remote areas.

Algorithm for the Parkinson’s disease behavioural models characterization using a biosensor

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Dissecting gastrointestinal dysfunction and inflammation in a “pre-motor” rodent model of Parkinson’s disease

Research on Parkinson’s disease (PD) has mainly focused on the degeneration of the dopaminergic neurons of nigro-striatal (NS) pathway; also, post-mortem studies have demonstrated that the noradrenergic and the serotonergic transmitter systems are also affected (Jellinger, 1999). Degeneration of these neuronal cell bodies is generally thought to start prior to the loss of dopaminergic neurons in the NS pathway and precedes the appearance of the motor symptoms that are the “hallmark” of PD. Gastrointestinal (GI) motility is often disturbed in PD, manifesting chiefly as impaired gastric emptying and constipation. These GI dysfunction symptoms may be the result of a loss in noradrenergic and serotonergic innervation. GI deficits were evaluated using an organ bath technique. Groups treated with different combinations of neurotoxins (6-OHDA alone, 6-OHDA + pCA or 6-OHDA + DSP-4) presented significant differences in gut contractility compared to control groups. Since a substantial body of literature suggests the presence of an inflammatory process in parkinsonian state (Whitton, 2007), changes in pro-inflammatory cytokines in the gut were assessed using a cytokine microarray. It has been found in this work that groups with a combined dopaminergic and noradrenergic lesion have a significant increase in both expressions of IL-13 and VEGF. IL-6 also shows a decrease in treatment groups; however this decrease did not reach statistical significance. The therapeutic value of Exendin-4 (EX-4) was evaluated. It has been previously demonstrated that EX-4, a glucagon-like peptide-1 receptor (GLP-1R) agonist, is neuroprotective in rodent models of PD (Harkavyi et al., 2008). In this thesis it has been found that EX-4 was able to reverse a decrease in gut contractility obtained through intracerebral bilateral 6-OHDA injection. Although more studies are required, EX-4 could be used as a possible therapy for the GI symptoms prominent in the early stages of PD.

PET and MR imaging in Parkinson’s disease patients with cognitive impairment. A study of dopaminergic dysfunction, amyloid deposition, cortical hypometabolism and brain atrophy

Parkinson’s disease (PD) is the second most common neurodegenerative disorder. It is characterized by a severe loss of substantia nigra dopaminergic neurons leading to dopamine depletion in the striatum. PD affects movement, producing motor symptoms such as rigidity, tremor and bradykinesia. Non-motor symptoms include autonomic dysfunction, neurobehavioral problems and cognitive impairment, which may lead to dementia. The pathophysiological basis of cognitive impairment and dementia in PD is unclear. The aim of this thesis was to study the pathophysiological basis of cognitive impairment and dementia in PD. We evaluated the relation between frontostriatal dopaminergic dysfunction and the cognitive symptoms in PD patients with [18F]Fdopa PET. We also combined [C]PIB and [¹⁸F]FDG PET and magnetic resonance imaging in PD patients with and without dementia. In addition, we analysed subregional striatal [¹⁸F]Fdopa PET data to find out whether a simple ratio approach would reliably separate PD patients from healthy controls. The impaired dopaminergic function of the frontostriatal regions was related to the impairment in cognitive functions, such as memory and cognitive processing in PD patients. PD patients with dementia showed an impaired glucose metabolism but not amyloid deposition in the cortical brain regions, and the hypometabolism was associated with the degree of cognitive impairment. PD patients had atrophy, both in the prefrontal cortex and in the hippocampus, and the hippocampal atrophy was related to impaired memory. A single 15-min scan 75 min after a tracer injection seemed to be sufficient for separating patients with PD from healthy controls in a clinical research environment. In conclusion, the occurrence of cognitive impairment and dementia in PD seems to be multifactorial and relates to changes, such as reduced dopaminergic activity, hypometabolism, brain atrophy and rarely to amyloid accumulation.

Compensatory Arm Reactions in Individuals with Parkinson’s Disease

This study examined how perturbation-evoked compensatory arm reactions in individuals with Parkinson’s disease (PD) are influenced by explicit verbal instruction. Ten individuals with PD and 15 older adults without PD responded to surface translations with or without specific instruction to reach for and grasp the handrail. Electromyographic (EMG) and kinematic recordings were taken from the reaching arm. Results showed that individuals with and without PD benefitted similarly from explicit instruction. Explicit instruction resulted in earlier (p=0.005) and larger (p<0.001) medial deltoid EMG responses in comparison to no specific instructions. Compensatory arm reactions also occurred with a higher peak medio-lateral wrist velocity (p<0.001) and higher peak shoulder abduction angular velocity (p<0.001) with explicit instruction. Explicit instruction positively influenced compensatory arm reactions in individuals with and without PD. Future research is needed to determine whether the benefits of instruction persist over time and translate to a loss of balance in real life.

Longitudinal assessment of neural activity in Parkinson’s disease with mild cognitive impairment using task based fMRI

La maladie de Parkinson (PD) a été uniquement considérée pour ses endommagements sur les circuits moteurs dans le cerveau. Il est maintenant considéré comme un trouble multisystèmique, avec aspects multiples non moteurs y compris les dommages intérêts pour les circuits cognitifs. La présence d’un trouble léger de la cognition (TCL) de PD a été liée avec des changements structurels de la matière grise, matière blanche ainsi que des changements fonctionnels du cerveau. En particulier, une activité significativement réduite a été observée dans la boucle corticostriatale ‘cognitive’ chez des patients atteints de PD-TCL vs. PD non-TCL en utilisant IRMf. On sait peu de cours de ces modèles fonctionnels au fil du temps. Dans cette étude, nous présentons un suivi longitudinal de 24 patients de PD non démente qui a subi une enquête neuropsychologique, et ont été séparés en deux groupes - avec et sans TCL (TCL n = 11, non-TCL n = 13) en fonction du niveau 2 des recommandations de la Movement Disrders Society pour le diagnostic de PD-TCL. Ensuite, chaque participant a subi une IRMf en effectuant la tâche de Wisconsin pendant deux sessions, 19 mois d'intervalle. Nos résultats longitudinaux montrent qu'au cours de la planification de période de la tâche, les patients PD non-TCL engageant les ressources normales du cortex mais ils ont activé en plus les zones corticales qui sont liés à la prise de décision tel que cortex médial préfrontal (PFC), lobe pariétal et le PFC supérieure, tandis que les PD-TCL ont échoué pour engager ces zones en temps 2. Le striatum n'était pas engagé pour les deux groupes en temps 1 et pour le groupe TCL en temps 2. En outre, les structures médiales du lobe temporal étaient au fil du temps sous recrutés pour TCL et Non-TCL et étaient positivement corrélés avec les scores de MoCA. Le cortex pariétal, PFC antérieur, PFC supérieure et putamen postérieur étaient négativement corrélés avec les scores de MoCA en fil du temps. Ces résultats révèlent une altération fonctionnelle pour l’axe ganglial-thalamo-corticale au début de PD, ainsi que des niveaux différents de participation corticale pendant une déficience cognitive. Cette différence de recrutement corticale des ressources pourrait refléter longitudinalement des circuits déficients distincts de trouble cognitive légère dans PD.

Detection of Parkinson’s disease tremor-onset with a frequency analysing artificial neural network

Deep Brain Stimulator devices are becoming widely used for therapeutic benefits in movement disorders such as Parkinson's disease. Prolonging the battery life span of such devices could dramatically reduce the risks and accumulative costs associated with surgical replacement. This paper demonstrates how an artificial neural network can be trained using pre-processing frequency analysis of deep brain electrode recordings to detect the onset of tremor in Parkinsonian patients. Implementing this solution into an 'intelligent' neurostimulator device will remove the need for continuous stimulation currently used, and open up the possibility of demand-driven stimulation. Such a methodology could potentially decrease the power consumption of a deep brain pulse generator.

Identification of Parkinson’s disease tremor onset using artificial neural networks

In this paper we consider the possibility of using an artificial neural network to accurately identify the onset of Parkinson’s Disease tremors in human subjects. Data for the network is obtained by means of deep brain implantation in the human brain. Results presented have been obtained from a practical study (i.e. real not simulated data) but should be regarded as initial trials to be discussed further. It can be seen that a tuned artificial neural network can act as an extremely effective predictor in these circumstances.

Prediction of Parkinson’s disease tremor onset using radial basis function neural networks

The possibility of using a radial basis function neural network (RBFNN) to accurately recognise and predict the onset of Parkinson’s disease tremors in human subjects is discussed in this paper. The data for training the RBFNN are obtained by means of deep brain electrodes implanted in a Parkinson disease patient’s brain. The effectiveness of a RBFNN is initially demonstrated by a real case study.

Prediction of Parkinson’s Disease tremor onset using a radial basis function neural network based on particle swarm optimization

Deep Brain Stimulation (DBS) has been successfully used throughout the world for the treatment of Parkinson's disease symptoms. To control abnormal spontaneous electrical activity in target brain areas DBS utilizes a continuous stimulation signal. This continuous power draw means that its implanted battery power source needs to be replaced every 18–24 months. To prolong the life span of the battery, a technique to accurately recognize and predict the onset of the Parkinson's disease tremors in human subjects and thus implement an on-demand stimulator is discussed here. The approach is to use a radial basis function neural network (RBFNN) based on particle swarm optimization (PSO) and principal component analysis (PCA) with Local Field Potential (LFP) data recorded via the stimulation electrodes to predict activity related to tremor onset. To test this approach, LFPs from the subthalamic nucleus (STN) obtained through deep brain electrodes implanted in a Parkinson patient are used to train the network. To validate the network's performance, electromyographic (EMG) signals from the patient's forearm are recorded in parallel with the LFPs to accurately determine occurrences of tremor, and these are compared to the performance of the network. It has been found that detection accuracies of up to 89% are possible. Performance comparisons have also been made between a conventional RBFNN and an RBFNN based on PSO which show a marginal decrease in performance but with notable reduction in computational overhead.

Riluzole neuroprotection in a parkinson’s disease model involves suppression of reactive astrocytosis but not GLT-1 regulation

Background Riluzole is a neuroprotective drug used in the treatment of motor neurone disease. Recent evidence suggests that riluzole can up-regulate the expression and activity of the astrocyte glutamate transporter, GLT-1. Given that regulation of glutamate transport is predicted to be neuroprotective in Parkinson's disease, we tested the effect of riluzole in parkinsonian rats which had received a unilateral 6-hydroxydopamine injection into the median forebrain bundle. Results Rats were treated with intraperitoneal riluzole (4 mg/kg or 8 mg/kg), 1 hour before the lesion then once daily for seven days. Riluzole produced a modest but significant attenuation of dopamine neurone degeneration, assessed by suppression of amphetamine-induced rotations, preservation of tyrosine hydroxylase positive neuronal cell bodies in the substantia nigra pars compacta and attenuation of striatal tyrosine hydroxylase protein loss. Seven days after 6-hydroxydopamine lesion, reactive astrocytosis was observed in the striatum, as determined by increases in expression of glial fibrillary acidic protein, however the glutamate transporter, GLT-1, which is also expressed in astrocytes was not regulated by the lesion. Conclusions The results confirm that riluzole is a neuroprotective agent in a rodent model of parkinson’s disease. Riluzole administration did not regulate GLT-1 levels but significantly reduced GFAP levels, in the lesioned striatum. Riluzole suppression of reactive astrocytosis is an intriguing finding which might contribute to the neuroprotective effects of this drug.

Parkinson’s Disease tremor classification – a comparison between Support Vector Machines and neural networks

Deep Brain Stimulation has been used in the study of and for treating Parkinson’s Disease (PD) tremor symptoms since the 1980s. In the research reported here we have carried out a comparative analysis to classify tremor onset based on intraoperative microelectrode recordings of a PD patient’s brain Local Field Potential (LFP) signals. In particular, we compared the performance of a Support Vector Machine (SVM) with two well known artificial neural network classifiers, namely a Multiple Layer Perceptron (MLP) and a Radial Basis Function Network (RBN). The results show that in this study, using specifically PD data, the SVM provided an overall better classification rate achieving an accuracy of 81% recognition.