Cortical motor network modulation: Common mechanisms parallel efficient motor integration in implicit motor learning in healthy subjects and subthalamic neurostimulation in Parkinson’s disease

On the one hand, the neuronal circuitry and connectivity of the large-scale motor network play an important role in many human cognitive functions, i. e. in implicit motor learning. On the other hand, alterations in connectivity of the motor network are also a hallmark in the pathophysiology of a variety of psychological and neurological diseases, such as Parkinson’s disease. Here, we set out to study the motor network activity (more exactly the cortical and spinal aspects of it) under two different aspects: in healthy controls during implicit motor learning and in Parkinson’s disease patients in the conditions ‘stimulation off’ and ‘stimulation on’. To this end, 12 healthy controls and 20 Parkinson’s disease patients performed externally paced right finger movements with simultaneous recordings of a 64-channel EEG and EMG of the forearm muscles. The healthy controls performed the serial reaction time task. Parkinson’s disease patients conducted the baseline of this task with only random trials in the two conditions ‘stimulation off’ and ‘stimulation on ‘. Cortical and muscular activity was analyzed by time-frequency movement-related spectral perturbations and by power spectral density and corticospinal synchronization was assessed by time-frequency cross-spectra coherence. Clinically, Parkinson’s disease patients improved significantly with deep brain stimulation, assessed by the Unified Parkinson’s Disease Rating Scale III score, the reaction time and the error ratio. Deep brain stimulation lead to an increased cortical beta-band movement-related desynchronization, which was topographically spread over a wider cortical area. Besides, in ‘stimulation off’ after finger tap we found a premature beta-band rebound of the corticomuscular coherence to the extensor digitorum over the primary sensorimotor cortex, which was suppressed with stimulation on. The healthy controls presented with significantly reduced reaction times in the ‘sequence blocks’ compared to ‘random blocks’. In ‘sequence blocks’, power spectral density increased mainly over the right posterior parietal cortex but also over a larger left-hemispheric cortical area in alpha and low beta band. Alpha and beta band movement-related desynchronization presented most pronounced over the bilateral prefrontal, fronto-central and central channels. The movement-related desynchronization was significantly modulated over the course of implicit motor learning. The present findings reveal the impressive modulation of the motor network activity including cortical activations and corticospinal synchronizations introduced by deep brain stimulation therapy of the subthalamic nucleus in Parkinson’s disease

Ruhenetzwerke von Parkinsonpatienten – Effekte der Dopamintherapie

Die Motivation der hier vorliegenden Studie war es, Ruhenetzwerke von Parkinsonpatienten mit der Elektroenzephalographie (EEG) auf einer globalen Hirnnetzwerkebene zu analysieren. Als übergreifendes Ziel der Arbeit galt der vertiefte Einblick in pathophysiologische Mechanismen und Effekte der dopaminergen Therapie. Dabei wurden im Einzelnen folgende Hypothesen untersucht: 1) Die Extraktion von Ruhenetzwerken in einem globalen Analyseansatz ohne a priori Annahmen wurde bislang für magnetenzephalographische (MEG) Daten demonstriert. Es wurde angenommen, dass sich dieser Ansatz auch auf EEG Daten übertragen lässt und robuste Ergebnisse generieren würde. 2) Das Verständnis von Morbus Parkinson geht über eine reine Bewegungsstörung weit hinaus. Als Ausdruck einer solchen globalen Neurodegeneration waren daher pathologische Netzwerkveränderungen im Vergleich von Patienten und Gesunden zu erwarten, die sich nicht nur auf motorische Netzwerke beschränken würden. 3) Die dopaminerge Therapie stellt unverändert den zentralen Baustein der Behandlung der Parkinsonerkrankung dar. Als Ausdruck der resultierenden klinischen Besserung waren auch auf der Netzwerkebene spezifische Therapieeffekte zu erwarten. Inwiefern dies durch Restitution physiologischer Netzwerkmuster oder Etablierung einer alternativen Netzwerkstruktur erfolgen würde, sollte näher untersucht werden. ad 1) In der Literatur mit funktioneller Magnetresonanztomographie (fMRT) gut untersuchte und als etabliert geltende Ruhenetzwerke konnten auch in den EEG Daten identifiziert werden. Dabei wurde die eigentliche Netzwerkextraktion mittels einer Independent Component Analysis (ICA) durch Lösung des inversen Problems im Quellenraum lokalisiert. So konnte neben der im EEG grundsätzlich guten zeitlichen Auflösung auch die räumliche Auflösung optimiert werden. ad 2) Bei den näher untersuchten Ruhenetzwerken ließen sich spezifische räumliche und frequenzbezogene Veränderungen feststellen, welche in die bestehende Forschungsliteratur eingegliedert werden konnten und gleichzeitig das Verständnis dieser Veränderungen erweiterten. Insbesondere für den Bereich von motorischen Arealen zeigte sich ein präzises pathologisches Korrelat im b-Frequenzband, was erneut die Schlüsselrolle von b-Oszillationen betonte. Desweiteren zeigten sich Veränderungen des Default Mode Network (DMN) und des visuellen Netzwerks mit aktuell unklarer klinischer Relevanz. ad 3) Im Bereich der motorischen Kortexareale zeigte das supplementär motorische Areal (SMA) im Sinne einer Restitution auf nahezu physiologische räumliche Netzwerkparameter unmittelbare Effekte der medikamentösen Therapie. Dies war im Einklang mit einer wachsenden Evidenz vor allem aus der fMRT Literatur. Als neuer Aspekt ergab sich nun der offenbar spezifische Effekt im g-Frequenzband

The effects of galvanic vestibular stimulation on motor cortical related potentials in Parkinson's disease

A recent study showed that vestibular stimulation can produce long-lasting alleviation of motor and non-motor symptoms in Parkinson’s disease (PD) sample. The mechanisms of action behind the alleviation of PD symptoms through vestibular stimulation are currently unknown. An electrophysiological marker known to be abnormal in PD is a particular movement-related cortical potential (MRCP) known as the Bereitschaftpotential (BP). The aim of this thesis was to observe the effects of galvanic vestibular stimulation (GVS) on reaction time and MRCPs in PD using electroencephalograph (EEG) to better understand its underlying physiological mechanisms. All Seventeen participants with a diagnosis of Parkinson’s disease completed a voluntary finger and foot tapping task and seven participants also completed a simple reaction time task whilst receiving both active and sham GVS. Analysis revealed that active GVS did not influence any of the mean amplitudes of the MRCPs nor participants reaction time. Exploratory correlation analysis revealed certain clinical characteristics modulated participants responsivity to GVS, however post-hoc manipulation of these correlations did not find them significant. It is unclear whether these null effects were observed due to a lack of sample size and neurologically healthy control group for baseline comparison. It is speculated whether a different GVS technique is needed in order to understand the previous literatures findings, and this is considered through GVS type and frequency

Neuroimaging and serum biomarkers of neurodegeneration and neuroplasticity in Parkinson’s disease patients treated by intermittent theta-burst stimulation over the bilateral primary motor area: a randomized, double-blind, sham-controlled, crossover trial study

Background and objectivesIntermittent theta-burst stimulation (iTBS) is a patterned form of excitatory transcranial magnetic stimulation that has yielded encouraging results as an adjunctive therapeutic option to alleviate the emergence of clinical deficits in Parkinson’s disease (PD) patients. Although it has been demonstrated that iTBS influences dopamine-dependent corticostriatal plasticity, little research has examined the neurobiological mechanisms underlying iTBS-induced clinical enhancement. Here, our primary goal is to verify whether iTBS bilaterally delivered over the primary motor cortex (M1) is effective as an add-on treatment at reducing scores for both motor functional impairment and nonmotor symptoms in PD. We hypothesize that these clinical improvements following bilateral M1-iTBS could be driven by endogenous dopamine release, which may rebalance cortical excitability and restore compensatory striatal volume changes, resulting in increased striato-cortico-cerebellar functional connectivity and positively impacting neuroglia and neuroplasticity.MethodsA total of 24 PD patients will be assessed in a randomized, double-blind, sham-controlled crossover study involving the application of iTBS over the bilateral M1 (M1 iTBS). Patients on medication will be randomly assigned to receive real iTBS or control (sham) stimulation and will undergo 5 consecutive sessions (5 days) of iTBS over the bilateral M1 separated by a 3-month washout period. Motor evaluation will be performed at different follow-up visits along with a comprehensive neurocognitive assessment; evaluation of M1 excitability; combined structural magnetic resonance imaging (MRI), resting-state electroencephalography and functional MRI; and serum biomarker quantification of neuroaxonal damage, astrocytic reactivity, and neural plasticity prior to and after iTBS.DiscussionThe findings of this study will help to clarify the efficiency of M1 iTBS for the treatment of PD and further provide specific neurobiological insights into improvements in motor and nonmotor symptoms in these patients. This novel project aims to yield more detailed structural and functional brain evaluations than previous studies while using a noninvasive approach, with the potential to identify prognostic neuroprotective biomarkers and elucidate the structural and functional mechanisms of M1 iTBS-induced plasticity in the cortico-basal ganglia circuitry. Our approach may significantly optimize neuromodulation paradigms to ensure state-of-the-art and scalable rehabilitative treatment to alleviate motor and nonmotor symptoms of PD

Singing as a Therapeutic Technique to Improve Gait for People with Parkinson Disease

Abstract of the Dissertation Singing as a Therapeutic Technique to Improve Gait for People with Parkinson Disease by Elinor Clare Harrison Doctor of Philosophy in Movement Science Neurosciences Washington University in St. Louis, 2018 Professor Gammon Earhart, Chair Gait impairment is common in older adults and even more prevalent for people with Parkinson disease (PD). Gait dysfunction is often characterized by reductions in speed, step frequency, and step length. In addition, decreased ability to regulate step length and step frequency may contribute to increased gait variability, making walking less stable and increasing risk for falls. As gait deficits are often resistant to drug therapy, there is a need to find alternative therapies that improve mobility. Rhythmic cueing in the form of listening to music is effective at enhancing walking for people with PD, helping people lengthen strides and increase velocity. However, research on rhythmic facilitation of movement has been limited to external cues and it is unknown if self-generated rhythmic cues, such as singing, may provide the same or greater benefit. This projects described in this dissertation are among the first to examine the effects of singing on walking and may reveal a novel, low-cost, non-invasive, accessible and adaptable therapeutic technique to normalize gait in PD. In order to study the effects of internal cues on movement patterns in PD, we conducted four experiments (chapters 2-5). In the first experiment (chapter 2), we tested the feasibility of singing as a cueing technique by comparing it to traditional external cueing and to dual-task walking. We showed that while a dual task slowed and destabilized gait, singing while walking did not have this detrimental effect. In fact, singing did not negatively affect velocity, cadence, or stride length, and it positively impacted measures of gait variability. These results indicated that singing is not only feasible for people with PD but that it may hold potential to improve gait stability. Buoyed by the results of our pilot study, we then set out to examine how best to administer singing as a therapeutic technique to elicit the most benefit for people with PD. In experiment two (chapter 3), we assessed the differential effects of internal and external cueing techniques on basic walking as well as more challenging gait situations. We tested both forward walking, commonly considered an automatic motor pattern, and backward walking, which tends to reveal more pronounced gait impairment and is related to fall risk. We included people with PD and a healthy control group to provide additional insight into how the role of beat impairment in PD may differentially affect task performance. Our results showed that internal cueing was associated with improvements in gait velocity, cadence, and stride length in the backward direction, and reduced variability in both forward and backward walking. In contrast, external cues minimally benefitted gait characteristics and detrimentally affected gait variability. We also confirmed that people with PD may exhibit greater improvement than their healthy counterparts, particularly in more challenging gait situations such as backward walking. In experiment three (chapter 4), we investigated how different cue rates might alter responses in healthy controls and people with PD. In order to test this, we assessed cued walking conditions at tempos above, at, and below preferred gait cadence. We also added a second internal cueing condition of mental singing, in which participants sang in their heads, to determine if it could elicit the same benefits as singing aloud. The results indicated that mental singing was more effective than overt singing at eliciting gait improvement, which renders this technique more practical for everyday use. When done at rates of 10% above preferred cadence, mental singing allowed people to increase velocity while simultaneously reducing variability and gait asymmetry. In our final experiment (chapter 5), we sought to compare the same cued conditions using motion capture technology in order to determine if rhythmic cues can improve movement quality as well as spatiotemporal gait features. In our assessment of lower extremity sagittal plane joint angles, we showed that cues may combat downregulation of movement amplitude by increasing range of motion at all lower limb joints. These increases in movement amplitude may be associated with longer strides and reduced stride-to-stride variability. We were able to distinguish some key features that may predict likelihood of responding positively to internal cueing techniques, such as freezing status, fall history, and prior musical experience. The results indicate that internal cues may benefit a range of people with PD, even those at risk of more debilitating gait impairments such as falling or freezing of gait, and that those with prior musical experience are most likely to respond. Taken together, these results provide compelling evidence that internal cues are a promising therapeutic technique that may transform gait rehabilitation for older adults as well as people with PD. The experiments detailed herein contribute to a burgeoning field of literature concerning rhythm processing and are among the first to examine singing as a cueing technique for people with PD

Quantitative Electroencephalography and genetics as biomarkers of dementia in Parkinson’s disease

The importance of cognitive decline in Parkinson’s disease (PD), which eventually progresses to dementia (PD-D) in the majority of surviving patients, has been widely recognised during the last decade. PD-D is associated with a twofold increase in mortality, increased caregiver strain and increased healthcare costs. Thus, early and correct identification of the PD patients with a risk of dementia is a challenging problem of neurology, which has led to the suggestion of various markers of cognitive decline in PD. If validated, these markers would offer the opportunity for disease modification and therapeutic intervention at a critical early stage of the illness, when the viable neuronal population is greater. The focus of this thesis was to assess how various factors - quantitative electroencephalography (qEEG) changes, genetics, deep brain stimulation (DBS), olfactory function, etc. – may be related with the risk of cognitive decline in PD patients. We performed four clinical studies with various design. These studies included PD patients who were dementia-free on inclusion, and control participants. Principal findings are the following: (1) increase of global median relative power theta (4–8 Hz), executive and working memory dysfunction are independent prognostic markers of severe cognitive decline in PD patients over a period of 3 years. (2) DBS of the subthalamic nuclei in a group of PD patients with mean age 63.2 years, in comparison with a group of younger patients (52.9 years), causes higher incidence of psychiatric events over 2 years of observation. However, these events were transient and did not outweigh the benefits of surgery. (3) Worsening of verbal fluency performance is an early cognitive outcome of DBS of the subthalamic nuclei in PD patients. (4) Among early appearing non-motor signs of Parkinson’s disease, alteration of olfaction but not EEG spectrum correlates with motor function. (5) A composite score approach seems to be a realistic goal in the search for biomarkers of severe cognitive decline

Biological motion perception in Parkinson's disease

Parkinson’s disease (PD) disrupts many aspects of visual perception, which has negative functional consequences. How PD affects perception of moving human bodies, or biological motion, is unknown. The ability to accurately perceive others’ motion is related to one’s own motor ability and depends on the integrity of brain areas affected in PD, including superior temporal sulcus and premotor cortex. Biological motion perception may therefore be compromised in PD but also provide a target for intervention, with perceptual training potentially improving motor function. Experiment 1 investigated whether perception of biological motion was impaired in PD (N=26) relative to neurologically-healthy control (NC; N=24) individuals. Participants viewed videos of point-light human figures and judged whether or not they depicted walking. As predicted, PD were less sensitive to biological motion than NC. This deficit was not associated with participants’ own walking difficulties or with other perceptual deficits (contrast sensitivity, coherent motion perception). Experiment 2 evaluated the hypothesis that PD deficits would extend to more socially-complex biological motion. PD (N=23) and NC (N=24) viewed point-light figures depicting communicative and non-communicative (object-oriented) gestures. The PD group was less accurate than NC in describing non-communicative gestures, an effect driven by PD men, who also had difficulty perceiving communicative gestures. Experiment 3 tested the efficacy of perceptual training for PD. Because biological motion perception is associated with motor function, it was hypothesized that perceptual training would improve walking. Individuals with PD were randomized to Gait Observation (N=13; viewing videos of healthy and unhealthy gait) or Landscape Observation (N=10; viewing videos of moving water) and trained daily for one week while gait data were collected with accelerometers. Post-training, only the Gait Observation group self-reported increased mobility, though improvements were not seen in objective gait data (daily activity, walking speed, stride length, stride frequency, leg swing time, gait asymmetry). These studies demonstrate that individuals with PD have difficulty perceiving biological motion (walking and socially-complex gestures). Improving biological motion perception led to enhancement in self-perceived walking ability. Perceptual training that incorporates more explicit learning over a longer time period may be required to effect objective improvements in walking.2018-12-06T00:00:00

Classification of Resting-State fMRI using Evolutionary Algorithms: Towards a Brain Imaging Biomarker for Parkinson’s Disease

It is commonly accepted that accurate early diagnosis and monitoring of neurodegenerative conditions is essential for effective disease management and delivery of medication and treatment. This research develops automatic methods for detecting brain imaging preclinical biomarkers for Parkinson’s disease (PD) by considering the novel application of evolutionary algorithms. An additional novel element of this work is the use of evolutionary algorithms to both map and predict the functional connectivity in patients using rs-fMRI data. Specifically, Cartesian Genetic Programming was used to classify dynamic causal modelling data as well as timeseries data. The findings were validated using two other commonly used classification methods (Artificial Neural Networks and Support Vector Machines) and by employing k-fold cross-validation. Across dynamic causal modelling and timeseries analyses, findings revealed maximum accuracies of 75.21% for early stage (prodromal) PD patients in which patients reveal no motor symptoms versus healthy controls, 85.87% for PD patients versus prodromal PD patients, and 92.09% for PD patients versus healthy controls. Prodromal PD patients were classified from healthy controls with high accuracy – this is notable and represents the key finding since current methods of diagnosing prodromal PD have low reliability and low accuracy. Furthermore, Cartesian Genetic Programming provided comparable performance accuracy relative to Artificial Neural Networks and Support Vector Machines. Nevertheless, evolutionary algorithms enable us to decode the classifier in terms of understanding the data inputs that are used, more easily than in Artificial Neural Networks and Support Vector Machines. Hence, these findings underscore the relevance of both dynamic causal modelling analyses for classification and Cartesian Genetic Programming as a novel classification tool for brain imaging data with medical implications for disease diagnosis, particularly in early stages 5-20 years prior to motor symptoms