Neural Preparation For Step Initiation In Unpredictable Conditions With Age And Parkinson\u27s Disease

Mobility is essential for the independent lifestyle. However, as the US population ages, challenges to mobility start to arise, among them just the aging itself which leads to decreased postural stability, falls and the second most common neurodegenerative disease, that is Parkinson’s disease (PD). We decided to investigate step initiation as it is crucial to mobility: walking is not possible without the first step. Step initiation is impaired in PD. However, the impact of PD on the neural mechanisms of step initiation when some of the step parameters are unpredictable remains unexplored. Cortical preparation for step initiation can be assessed by beta event-related desynchronization (ERD) derived from electroencephalography (EEG) recordings. We hypothesized that subjects with PD would exhibit less cortical modulation between conditions of forward step initiation with and without prior knowledge of limb choice. Further, we hypothesized that decreased cortical modulation in PD would associate with a higher impairment of motor performance. Results identified that the group with PD exhibited decreased beta ERD amplitudes that were similar regardless of condition, whereas control subjects modulated beta ERD amplitudes between conditions, particularly in early stages of pre-movement processing in areas overlying sensory cortex. Subjects with PD presented with delayed and reduced postural preparation with increased step target error across both conditions and exhibited a greater incidence of multiple anticipatory postural adjustments (APAs) in the predictable relative to the unpredictable condition. Delayed postural preparation significantly correlated with lower amplitudes of beta ERD. We concluded that diminished early pre-movement processing over sensory cortex was concomitant with poor pre-selection of the stepping limb in predictable conditions and that a generally diminished amplitude of cortical pre-movement processing relates to delayed step initiation in people with PD. Furthermore, impaired mobility accompanies healthy aging, but there is a need for deeper understanding of how aging changes central control of motor behavior. Using previous study’s method, we compared cortical preparation for step initiation using beta ERD in young and older healthy subjects performing forward steps with and without prior knowledge of limb choice. Our results show that older subjects exhibited increased beta ERD amplitudes before the step regardless of whether they were informed of limb choice or not. Moreover, older subjects exhibited early increases in beta ERD in the “sensory” cluster of electrodes, but only when full limb-choice information was available. Behaviorally, the older subjects also exhibited shortened and increased anticipatory postural adjustments which led to earlier step initiation and similar swing-foot velocities but was also accompanied by greater target step placement errors and decreased postural stability. For the older group, condition-related increases in beta ERD amplitudes and stability correlated with condition-related prolongation of APA durations. We conclude that older subjects exhibited a spectrum across two strategies: (1) a “fast” strategy associated with decreased neural preparation that trades shortened step preparation and higher swing-foot velocity for target step errors and lowered postural stability; and (2) an “accurate” strategy associated with greater neural preparation, longer step-preparation time, and higher stability during step execution. In conclusion, this thesis provides more support for beta ERD as a useful tool for studying cortical preparation non-invasively. We have also established the importance of the signals recorded by “sensory” clusters: in subjects with PD the absence of beta ERD similar to the control group was associated with impaired motor behavior even when conditions were predictable. Similarly, a part of the older group seemed to pre-potentiate its cortex lying beneath the cluster of “sensory” electrodes which was associated with more safe and accurate steps. Further investigations should focus on the importance of sensorimotor integration and its’ changes due to PD or healthy aging and beta ERD may be an excellent tool for this task

Inter-hemispheric EEG coherence analysis in Parkinson's disease : Assessing brain activity during emotion processing

Parkinson’s disease (PD) is not only characterized by its prominent motor symptoms but also associated with disturbances in cognitive and emotional functioning. The objective of the present study was to investigate the influence of emotion processing on inter-hemispheric electroencephalography (EEG) coherence in PD. Multimodal emotional stimuli (happiness, sadness, fear, anger, surprise, and disgust) were presented to 20 PD patients and 30 age-, education level-, and gender-matched healthy controls (HC) while EEG was recorded. Inter-hemispheric coherence was computed from seven homologous EEG electrode pairs (AF3–AF4, F7–F8, F3–F4, FC5–FC6, T7–T8, P7–P8, and O1–O2) for delta, theta, alpha, beta, and gamma frequency bands. In addition, subjective ratings were obtained for a representative of emotional stimuli. Interhemispherically, PD patients showed significantly lower coherence in theta, alpha, beta, and gamma frequency bands than HC during emotion processing. No significant changes were found in the delta frequency band coherence. We also found that PD patients were more impaired in recognizing negative emotions (sadness, fear, anger, and disgust) than relatively positive emotions (happiness and surprise). Behaviorally, PD patients did not show impairment in emotion recognition as measured by subjective ratings. These findings suggest that PD patients may have an impairment of inter-hemispheric functional connectivity (i.e., a decline in cortical connectivity) during emotion processing. This study may increase the awareness of EEG emotional response studies in clinical practice to uncover potential neurophysiologic abnormalities

On the analysis of EEG power, frequency and asymmetry in Parkinson's disease during emotion processing

Objective: While Parkinson’s disease (PD) has traditionally been described as a movement disorder, there is growing evidence of disruption in emotion information processing associated with the disease. The aim of this study was to investigate whether there are specific electroencephalographic (EEG) characteristics that discriminate PD patients and normal controls during emotion information processing. Method: EEG recordings from 14 scalp sites were collected from 20 PD patients and 30 age-matched normal controls. Multimodal (audio-visual) stimuli were presented to evoke specific targeted emotional states such as happiness, sadness, fear, anger, surprise and disgust. Absolute and relative power, frequency and asymmetry measures derived from spectrally analyzed EEGs were subjected to repeated ANOVA measures for group comparisons as well as to discriminate function analysis to examine their utility as classification indices. In addition, subjective ratings were obtained for the used emotional stimuli. Results: Behaviorally, PD patients showed no impairments in emotion recognition as measured by subjective ratings. Compared with normal controls, PD patients evidenced smaller overall relative delta, theta, alpha and beta power, and at bilateral anterior regions smaller absolute theta, alpha, and beta power and higher mean total spectrum frequency across different emotional states. Inter-hemispheric theta, alpha, and beta power asymmetry index differences were noted, with controls exhibiting greater right than left hemisphere activation. Whereas intra-hemispheric alpha power asymmetry reduction was exhibited in patients bilaterally at all regions. Discriminant analysis correctly classified 95.0% of the patients and controls during emotional stimuli. Conclusion: These distributed spectral powers in different frequency bands might provide meaningful information about emotional processing in PD patients

Sensor Approach for Brain Pathophysiology of Freezing of Gait in Parkinson\u27s Disease Patients

Parkinson\u27s Disease (PD) affects over 1% of the population over 60 years of age and is expected to reach 1 million in the USA by the year 2020, growing by 60 thousand each year. It is well understood that PD is characterized by dopaminergic loss, leading to decreased executive function causing motor symptoms such as tremors, bradykinesia, dyskinesia, and freezing of gait (FoG) as well as non-motor symptoms such as loss of smell, depression, and sleep abnormalities. A PD diagnosis is difficult to make since there is no worldwide approved test and difficult to manage since its manifestations are widely heterogeneous among subjects. Thus, understanding the patient subsets and the neural biomarkers that set them apart will lead to improved personalized care. To explore the physiological alternations caused by PD on neurological pathways and their effect on motor control, it is necessary to detect the neural activity and its dissociation with healthy physiological function. To this effect, this study presents a custom ultra-wearable sensor solution, consisting of electroencephalograph, electromyograph, ground reaction force, and symptom measurement sensors for the exploration of neural biomarkers during active gait paradigms. Additionally, this study employed novel de-noising techniques for dealing with the motion artifacts associated with active gait EEG recordings and compared time-frequency features between a group of PD with FoG and a group of age-matched controls and found significant differences between several EEG frequency bands during start and end of normal walking (with a p\u3c0.05)

EEG Characterization During Motor Tasks That Are Difficult for Movement Disorder Patients

Movement disorders are a group of syndromes that often arise due to neurological abnormalities. Approximately 40 million Americans are affected by some form of movement disorder, significantly impacting patients’ quality of life and their ability to live independently. Deep brain stimulation (DBS) is one treatment that has shown promising results in the past couple decades, however, the currently used open-loop system has several drawbacks. By implementing a closed-loop or adaptive DBS (aDBS) system, the need for expensive parameter reprogramming sessions would be reduced, side-effects may be relieved, and habituation could be avoided. Several biomarkers, for example signals or activity derived from electroencephalogram (EEG), could potentially be used as a feedback source for aDBS. Here, we attempted to characterize cortical EEG potentials in healthy subjects performing six tasks that are difficult for those with movement disorders. Using a 32-channel EEG cap with an amplifier sampling at 500 Hz, we performed our protocol on 11 college-aged volunteers lacking any known movement disorder. For each task, we analyzed task-related power (TRP) changes, spectrograms, and topographical maps. In a finger movement exercise, we found task-related depression (TRD) in the delta band at the F4 electrode, as well as TRD at the C3 electrode in the alpha band during a pencil-pickup task, and TRD at the F3 electrode in the beta band during voluntary swallowing. While delta-ERD in the finger movement exercise was likely due to ocular artifact, the other significant results were in line with what relevant literature would predict. The findings from the work, in conjunction with a future study involving movement disorder patients, can provide insight into the use of EEG as a feedback source for aDBS. Keywords: EEG, electroencephalography, neurostimulation, deep brain stimulation, movement disorders, closed-loop DBS, adaptive DBS, aDB

Optimal set of EEG features for emotional state classification and trajectory visualization in Parkinson's disease

In addition to classic motor signs and symptoms, individuals with Parkinson's disease (PD) are characterized by emotional deficits. Ongoing brain activity can be recorded by electroencephalograph (EEG) to discover the links between emotional states and brain activity. This study utilized machine-learning algorithms to categorize emotional states in PD patients compared with healthy controls (HC) using EEG. Twenty non-demented PD patients and 20 healthy age-, gender-, and education level-matched controls viewed happiness, sadness, fear, anger, surprise, and disgust emotional stimuli while fourteen-channel EEG was being recorded. Multimodal stimulus (combination of audio and visual) was used to evoke the emotions. To classify the EEG-based emotional states and visualize the changes of emotional states over time, this paper compares four kinds of EEG features for emotional state classification and proposes an approach to track the trajectory of emotion changes with manifold learning. From the experimental results using our EEG data set, we found that (a) bispectrum feature is superior to other three kinds of features, namely power spectrum, wavelet packet and nonlinear dynamical analysis; (b) higher frequency bands (alpha, beta and gamma) play a more important role in emotion activities than lower frequency bands (delta and theta) in both groups and; (c) the trajectory of emotion changes can be visualized by reducing subject-independent features with manifold learning. This provides a promising way of implementing visualization of patient's emotional state in real time and leads to a practical system for noninvasive assessment of the emotional impairments associated with neurological disorders

The role of somatosensory afferences in Parkinson's disease

Parkinson’s disease (PD) is the second most common neurodegenerative disorder in the world. The primary motor symptom of PD is bradykinesia, a slowing and reduction in amplitude of voluntary movement. Here, I aim to test some neurophysiological aspects of PD. Furthermore, I explored the possibility to develop non-invasive treatment for this group of patients. The first two studies tested the contribution of a specific phenomenon labelled sensory attenuation or sensory gating in the motor symptoms of PD, especially bradykinesia. I found that the sensory attenuation is abnormal in this group of patients. Especially, PD patients OFF medications showed a reduced sensory attenuation measured as the amplitude of the somatosensory evoked potentials. Interestingly, I found that the sensory attenuation was equal to the healthy age matched controls when the patients were tested in ON pharmacological state. Additionally, this research tested a theory of the functional role of sensorimotor beta oscillations that could explain beta power modulations in healthy subjects and the increase in beta power observed in PD patients. My results were in line with the previous data presented in the literature. Indeed, I found the increase beta power in both my two cohorts of PD patients. Finally, I tested a potential correlation between the abnormalities of these two phenomena in PD: reduced sensory attenuation and increased beta oscillations. I did not find any significant correlation between the two phenomena. They might be two different neurophysiological mechanisms 5 underlying this disease. However, further studies are necessary to investigate this hypothesis. Having tested the influence of the somatosensory signal in some motor symptoms, the second part of the thesis was focused on the development of non-invasive treatments of bradykinesia in PD. I tested the impact of vibratory stimuli to improve these motor signs. In particular, several frequencies of vibration have been tested through different devices applied to the wrist. The device was called “Emma watch” and I found that the application of vibration with the modulation of 60 bpm improved the bradykinesia in PD patients Finally, I presented a case study regarding the benefit of vibratory stimulation on the freezing of gait thought shoe insoles generating vibration. The tested patient showed an improvement of the frequency of the freezing episodes after a week wearing the insoles, which generated vibration at 200 Hz

Shaking hands:establishing objective parameters to differentiate between essential tremor and Parkinson's disease

In 1817, James Parkinson was the first physician to publish his observations about the shaking palsy (later: Parkinson’s disease (PD)) and its differences compared to other tremulous disorders [1]. Nowadays, more than 200 years later, a lot more is known about neurodegenerative disorders. However, the exact pathophysiology is yet unknown. Furthermore, differentiation from other tremulous movement disorders, such as essential tremor (ET)], remains difficult due to overlapping symptoms such as tremor or timing deficits during voluntary movement and common diagnostic tools are often either invasive, time consuming, subjective, expensive and/or not widely available.Therefore, in my research I focused on finding objective parameters to differentiate PD from ET that can be measured with commonly available tools. For this purpose we simultaneously measured movement of the hands, using accelerometers, and brain activity using EEG and functional MRI to:1. quantify tremor occurrence and identifying corresponding cortical activity.2. quantify timing deficits during voluntary movement and identifying corresponding neuronal networks.Analyzing cortical activity during tremor revealed cortical involvement in tremor occurrence during rest in PD but not ET. A postural task revealed involvement of the associate and primary visual cortex in ET suggesting that these patients rely on visual guidance for maintaining a posture during tremor. To analyze timing deficits in ET and PD, subjects were asked to perform a bimanual motor task with an without an external cue. In both patient groups areas of motor planning, movement initiation, maintenance and coordination were active. However, activation of additional areas was found in both patient groups.From the results we can conclude that objective differentiation between ET and PD might be possible in the future using only commonly available tools. However, there is still a lot of work that needs to be done

Abnormal reactivity of resting-state EEG alpha rhythms during eyes open in patients with Alzheimer's and Lewy body diseases

Previous studies suggest that resting-state electroencephalographic (rsEEG) rhythms recorded in old patients with dementia due to different neurodegenerative diseases have a significant heuristic and clinical potential in identifying peculiar abnormalities of the ascending activating systems and reciprocal thalamocortical circuits in which oscillatory (de)synchronizing signals dynamically underpin cortical arousal in the regulation of quiet vigilance. In the present PhD program, a new methodological approach based on rsEEG cortical source estimation and individually-based frequency bands was used to test the hypothesis of significant abnormalities in the neurophysiological oscillatory mechanisms underlying the regulation of the quiet vigilance during the transition from an eyes-closed to an eyes-open condition in patients with the most prevalent neurodegenerative dementing disorders such as Alzheimer’s disease and Lewy Body and Parkinson’s diseases and initial abnormalities in the prodromal stage of ADD, characterized by mild cognitive impairment. Three rsEEG studies were performed for that purpose. In the first study, we tested if the reactivity of posterior rsEEG alpha rhythms from the eye- closed to the eyes-open condition may differ in patients with dementia due to Lewy Bodies (DLB) and Alzheimer’s disease (ADD) as a functional probe of the dominant neural synchronization mechanisms regulating the vigilance in posterior visual systems. We used clinical, demographical, and rsEEG datasets in 28 healthy elderly (Healthy) seniors, 42 DLB, and 48 ADD participants. The eLORETA freeware estimated rsEEG cortical sources at individual delta, theta, and alpha frequencies. Results showed a substantial (> -10%) reduction in the posterior alpha activities during the eyes-open condition in 24 Healthy, 26 ADD, and 22 DLB subjects. There were lower reductions in the posterior alpha activities in the ADD and DLB groups than in the Healthy group. The reduction in the occipital region was lower in the DLB than in the ADD group. These results suggest that DLB patients may suffer a greater alteration in the neural synchronization mechanisms regulating vigilance in occipital cortical systems compared to ADD patients. In the second study, we hypothesized that the vigilance dysregulation seen in PDD patients might be reflected by altered reactivity of posterior rsEEG alpha rhythms during the vigilance transition from an eyes-closed to an eyes-open condition. We used clinical, demographical, and rsEEG datasets in 28 healthy elderly (Healthy), 73 PDD, and 35 ADD participants. We have applied the same methodology used for the first study. Results showed substantial (> -10%) reduction (reactivity) in the posterior alpha source activities from the eyes-closed to the eyes-open condition in 88% of the Healthy seniors, 57% of the ADD patients, and only 35% of the PDD patients. In these alpha-reactive participants, there was lower reactivity in the parietal alpha source activities in the PDD group than in the Healthy and the ADD groups. These results suggest that PDD is characterized by poor reactivity of mechanisms desynchronizing posterior rsEEG alpha rhythms in response to visual inputs. This finding could be an interesting biomarker of impaired vigilance regulation in quiet wakefulness in PDD patients. Indeed, such biomarkers may provide endpoints for pharmacological intervention and brain electromagnetic stimulations to improve the PDD patients’ general ability to regulate vigilance and primary visual consciousness in the activities of daily living. In the third study, we tested the exploratory hypothesis that rsEEG alpha rhythms may predict and be sensitive to mild cognitive impairment due to AD (ADMCI) progression at a 6-month follow- up (a relevant feature for intervention clinical trials). Clinical, neuroimaging, and rsEEG datasets in 52 ADMCI and 60 Healthy seniors were used. We applied the same methodology used for the first and the second studies. Results showed a substantial (> -10%) reduction in the posterior alpha source activities during the eyes-open condition in about 90% and 70% of the Healthy and ADMCI participants, respectively. In the younger ADMCI patients (mean age of 64.3±1.1) with “reactive” rsEEG alpha source activities, posterior alpha source activities during the eyes closed condition predicted the global cognitive status at the 6-month follow-up. In all ADMCI participants with “reactive” rsEEG alpha source activities, posterior alpha source activities during the eyes-closed condition reduced in magnitude at that follow-up. These effects could not be explained by neuroimaging and neuropsychological biomarkers of AD. These results suggest that in ADMCI patients, the true (“reactive”) posterior rsEEG alpha rhythms, when present, predict (in relation to younger age) and are quite sensitive to the effects of the disease progression on neurophysiological mechanisms underpinning vigilance regulation. The results of the three studies unveiled the significant extent to which the well-known impairments in the cholinergic and dopaminergic neuromodulatory ascending systems could affect the brain neurophysiological oscillatory mechanisms underpinning the reactivity of rsEEG alpha rhythms during eyes open and, then, the regulation of quiet vigilance in ADD, PDD, and DLB patients, thus enriching the neurophysiological model underlying their known difficulties to remain awake in quiet environmental conditions during daytime