Multimodal Learning and Intelligent Prediction of Symptom Development in Individual Parkinson\u27s Patients

We still do not know how the brain and its computations are affected by nerve cell deaths and their compensatory learning processes, as these develop in neurodegenerative diseases (ND). Compensatory learning processes are ND symptoms usually observed at a point when the disease has already affected large parts of the brain. We can register symptoms of ND such as motor and/or mental disorders (dementias) and even provide symptomatic relief, though the structural effects of these are in most cases not yet understood. It is very important to obtain early diagnosis, which can provide several years in which we can monitor and partly compensate for the disease\u27s symptoms, with the help of various therapies. In the case of Parkinson\u27s disease (PD), in addition to classical neurological tests, measurements of eye movements are diagnostic. We have performed measurements of latency, amplitude, and duration in reflexive saccades (RS) of PD patients. We have compared the results of our measurement-based diagnoses with standard neurological ones. The purpose of our work was to classify how condition attributes predict the neurologist\u27s diagnosis. For n = 10 patients, the patient age and parameters based on RS gave a global accuracy in predictions of neurological symptoms in individual patients of about 80%. Further, by adding three attributes partly related to patient \u27well-being\u27 scores, our prediction accuracies increased to 90%. Our predictive algorithms use rough set theory, which we have compared with other classifiers such as Naive Bayes, Decision Trees/Tables, and Random Forests (implemented in KNIME/WEKA). We have demonstrated that RS are powerful biomarkers for assessment of symptom progression in PD

Do informal caregivers of people with dementia mirror the cognitive deficits of their demented patients?:A pilot study

Recent research suggests that informal caregivers of people with dementia (ICs) experience more cognitive deficits than noncaregivers. The reason for this is not yet clear. Objective: to test the hypothesis that ICs ‘mirror' the cognitive deficits of the demented people they care for. Participants and methods: 105 adult ICs were asked to complete three neuropsychological tests: letter fluency, category fluency, and the logical memory test from the WMS-III. The ICs were grouped according to the diagnosis of their demented patients. One-sample ttests were conducted to investigate if the standardized mean scores (t-scores) of the ICs were different from normative data. A Bonferroni correction was used to correct for multiple comparisons. Results: 82 ICs cared for people with Alzheimer's dementia and 23 ICs cared for people with vascular dementia. Mean letter fluency score of the ICs of people with Alzheimer's dementia was significantly lower than the normative mean letter fluency score, p = .002. The other tests yielded no significant results. Conclusion: our data shows that ICs of Alzheimer patients have cognitive deficits on the letter fluency test. This test primarily measures executive functioning and it has been found to be sensitive to mild cognitive impairment in recent research. Our data tentatively suggests that ICs who care for Alzheimer patients also show signs of cognitive impairment but that it is too early to tell if this is cause for concern or not

Vision and gait in Parkinson's disease: impact of cognition and response to visual cues

Ph.D. ThesisGait impairment is a core feature of Parkinson’s disease (PD) which is difficult to treat due to its multi-factorial nature. Gait dysfunction in PD has been linked to cognitive and visual deficits through separate strands of research. However cognitive and visual functions likely interact (termed visuo-cognition) and have a combined impact on gait. Attempting to further understand the roles of cognition and vision in gait in PD was the motivation behind this thesis. The primary aim was therefore to investigate visuo-cognition and its role in gait in PD. Saccade frequency during gait represents the amount of visual sampling employed when walking and is a useful online behavioural measure of visuo-cognition. However, previous investigations have been limited by lack of robust methodologies, technology and outcome measures. A key objective was therefore to establish robust saccadic measurement with mobile eye-tracking technology in PD and older adult controls. My original contributions to knowledge were that a mobile eye-tracker can measure saccadic activity during gait in PD and controls, but with variable accuracy and reliability for certain characteristics. Cognitive and visual functions were significantly related in both PD and controls, with stronger association in PD. Saccade frequency during gait was significantly reduced in people with PD compared to controls, particularly under dual task. Impaired saccade frequency can be ameliorated with a visual cue; as such intervention significantly increased saccade frequency in PD and controls which was maintained under dual task. Saccade frequency during gait was independently associated with cognitive and visual functions in PD. A structured model demonstrated that visuo-cognitive dysfunction had an indirect effect on gait in PD, with a central role for attention in all relationships involved. The major conclusion from this thesis was that gait impairment in PD is influenced by visuo-cognitive dysfunction, with implication for poor mobility and falls risk.National Institute for Health Research (NIHR) Biomedical Research Unit (BRU). Newcastle University

Models and Analysis of Vocal Emissions for Biomedical Applications

The International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications (MAVEBA) came into being in 1999 from the particularly felt need of sharing know-how, objectives and results between areas that until then seemed quite distinct such as bioengineering, medicine and singing. MAVEBA deals with all aspects concerning the study of the human voice with applications ranging from the newborn to the adult and elderly. Over the years the initial issues have grown and spread also in other fields of research such as occupational voice disorders, neurology, rehabilitation, image and video analysis. MAVEBA takes place every two years in Firenze, Italy. This edition celebrates twenty-two years of uninterrupted and successful research in the field of voice analysis

Development of Markerless Systems for Automatic Analysis of Movements and Facial Expressions: Applications in Neurophysiology

This project is focused on the development of markerless methods for studying facial expressions and movements in neurology, focusing on Parkinson’s disease (PD) and disorders of consciousness (DOC). PD is a neurodegenerative illness that affects around 2% of the population over 65 years old. Impairments of voice/speech are among the main signs of PD. This set of impairments is called hypokinetic dysarthria, because of the reduced range of movements involved in speech. This reduction can be visible also in other facial muscles, leading to a hypomimia. Despite the high percentage of patients that suffer from dysarthria and hypomimia, only a few of them undergo speech therapy with the aim to improve the dynamic of articulatory/facial movements. The main reason is the lack of low cost methodologies that could be implemented at home. DOC after coma are Vegetative State (VS), characterized by the absence of self-awareness and awareness of the environment, and Minimally Conscious State (MCS), in which certain behaviors are sufficiently reproducible to be distinguished from reflex responses. The differential diagnosis between VS and MCS can be hard and prone to a high rate of misdiagnosis (~40%). This differential diagnosis is mainly based on neuro-behavioral scales. A key role to plan the rehabilitation in DOC patients is played by the first diagnosis after coma. In fact, MCS patients are more prone to a consciousness recovery than VS patients. Concerning PD the aim is the development of contactless systems that could be used to study symptoms related to speech and facial movements/expressions. The methods proposed here, based on acoustical analysis and video processing techniques could support patients during speech therapy also at home. Concerning DOC patients the project is focused on the assessment of reflex and cognitive responses to standardized stimuli. This would allow objectifying the perceptual analysis performed by clinicians

Application of MRI Connectivity in Stereotactic Functional Neurosurgery

This thesis examines potential applications of advanced MRI-connectivity studies in stereotactic functional neurosurgery. Several new analysis methodologies are employed to: (1) build predictive models of DBS surgery outcome; (2) refine the surgical target and (3) help build a better understanding of the pathogenesis of the treated conditions and the mechanism of action of DBS therapy. The experimental component is divided into three main parts focusing on the following pathologies: (1) Parkinson’s disease (PD), (2) tremor and (3) trigeminal autonomic cephalalgias (TAC). Section I: In the first experiment (chapter 3), resting state fMRI was used to find radiological biomarkers predictive of response to L-DOPA in 19 patients undergoing subthalamic nucleus (STN) DBS for PD. A greater improvement in UPDRS-III scores following L-DOPA administration was characterized by higher resting state functional connectivity (fcMRI) between the prefrontal cortex and the striatum (p=0.001) and lower fcMRI between the pallidum (p=0.001), subthalamic nucleus (p=0.003) and the paracentral lobule. In the second experiment (chapter 4), structural (diffusion) connectivity was used to map out the influence of the hyperdirect pathways on outcome and identify the therapeutic ‘sweet spots’ in twenty PD patients undergoing STN-DBS. Clusters corresponding to maximum improvement in symptoms were in the posterior, superior and lateral portion of the STN. Greater connectivity to the primary motor area, supplementary motor area and prefrontal cortex was predictive of higher improvement in tremor, bradykinesia and rigidity, and rigidity respectively. The third experiment (chapter 5) examined pyramidal tract (PT) activation in 20 PD patients with STN-DBS. Volume of tissue activation (VTA) around DBS contacts were modelled in relation to the PT. VTA/ PT overlap predicted EMG activation thresholds. Sections II: Pilot data suggest that probabilistic tractography techniques can be used to segment the ventrolateral (VL) and ventroposterior (VP) thalamus based on cortical and cerebellar connectivity in nine patients who underwent thalamic DBS for tremor (chapter 6). The thalamic area, best representing the ventrointermedialis nucleus (VIM), was connected to the contralateral dentate cerebellar nucleus. Streamlines corresponding to the dentato-rubro-thalamic tract (DRT) connected M1 to the contralateral dentate nucleus via the dentato-thalamic area. Good response was seen when the active contact’s VTA was in the thalamic area with the highest connectivity to the contralateral dentate nucleus. Section III: The efficacy and safety of DBS in the ventral tegmental area (VTa) in the treatment of chronic cluster headache (CH) and short lasting unilateral neuralgiform headache attacks (SUNA) were examined (chapters 7 and 8). The optimum stimulation site within the VTa that best controls symptoms was explored (chapter 9). The average responders’ deep brain stimulation activation volume lay on the trigemino-hypothalamic tract, connecting the trigeminal system and other nociceptive brainstem nuclei, with the hypothalamus, and the prefrontal and mesial temporal areas