Mean-field analysis of basal ganglia and thalamocortical dynamics

When modeling a system as complex as the brain, considerable simplifications are inevitable. The nature of these simplifications depends on the available experimental evidence, and the desired form of model predictions. A focus on the former often inspires models of networks of individual neurons, since properties of single cells are more easily measured than those of entire populations. However, if the goal is to describe the processes responsible for the electroencephalogram (EEG), such models can become unmanageable due to the large numbers of neurons involved. Mean-field models in which assemblies of neurons are represented by their average properties allow activity underlying the EEG to be captured in a tractable manner. The starting point of the results presented here is a recent physiologically-based mean-field model of the corticothalamic system, which includes populations of excitatory and inhibitory cortical neurons, and an excitatory population representing the thalamic relay nuclei, reciprocally connected with the cortex and the inhibitory thalamic reticular nucleus. The average firing rates of these populations depend nonlinearly on their membrane potentials, which are determined by afferent inputs after axonal propagation and dendritic and synaptic delays. It has been found that neuronal activity spreads in an approximately wavelike fashion across the cortex, which is modeled as a two-dimensional surface. On the basis of the literature, the EEG signal is assumed to be roughly proportional to the activity of cortical excitatory neurons, allowing physiological parameters to be extracted by inverse modeling of empirical EEG spectra. One objective of the present work is to characterize the statistical distributions of fitted model parameters in the healthy population. Variability of model parameters within and between individuals is assessed over time scales of minutes to more than a year, and compared with the variability of classical quantitative EEG (qEEG) parameters. These parameters are generally not normally distributed, and transformations toward the normal distribution are often used to facilitate statistical analysis. However, no single optimal transformation exists to render data distributions approximately normal. A uniformly applicable solution that not only yields data following the normal distribution as closely as possible, but also increases test-retest reliability, is described in Chapter 2. Specialized versions of this transformation have been known for some time in the statistical literature, but it has not previously found its way to the empirical sciences. Chapter 3 contains the study of intra-individual and inter-individual variability in model parameters, also providing a comparison of test-retest reliability with that of commonly used EEG spectral measures such as band powers and the frequency of the alpha peak. It is found that the combined model parameters provide a reliable characterization of an individual's EEG spectrum, where some parameters are more informative than others. Classical quantitative EEG measures are found to be somewhat more reproducible than model parameters. However, the latter have the advantage of providing direct connections with the underlying physiology. In addition, model parameters are complementary to classical measures in that they capture more information about spectral structure. Another conclusion from this work was that a few minutes of alert eyes-closed EEG already contain most of the individual variability likely to occur in this state on the scale of years. In Chapter 4, age trends in model parameters are investigated for a large sample of healthy subjects aged 6-86 years. Sex differences in parameter distributions and trends are considered in three age ranges, and related to the relevant literature. We also look at changes in inter-individual variance across age, and find that subjects are in many respects maximally different around adolescence. This study forms the basis for prospective comparisons with age trends in evoked response potentials (ERPs) and alpha peak morphology, besides providing a standard for the assessment of clinical data. It is the first study to report physiologically-based parameters for such a large sample of EEG data. The second main thrust of this work is toward incorporating the thalamocortical system and the basal ganglia in a unified framework. The basal ganglia are a group of gray matter structures reciprocally connected with the thalamus and cortex, both significantly influencing, and influenced by, their activity. Abnormalities in the basal ganglia are associated with various disorders, including schizophrenia, Huntington's disease, and Parkinson's disease. A model of the basal ganglia-thalamocortical system is presented in Chapter 5, and used to investigate changes in average firing rates often measured in parkinsonian patients and animal models of Parkinson's disease. Modeling results support the hypothesis that two pathways through the basal ganglia (the so-called direct and indirect pathways) are differentially affected by the dopamine depletion that is the hallmark of Parkinson's disease. However, alterations in other components of the system are also suggested by matching model predictions to experimental data. The dynamics of the model are explored in detail in Chapter 6. Electrophysiological aspects of Parkinson's disease include frequency reduction of the alpha peak, increased relative power at lower frequencies, and abnormal synchronized fluctuations in firing rates. It is shown that the same parameter variations that reproduce realistic changes in mean firing rates can also account for EEG frequency reduction by increasing the strength of the indirect pathway, which exerts an inhibitory effect on the cortex. Furthermore, even more strongly connected subcircuits in the indirect pathway can sustain limit cycle oscillations around 5 Hz, in accord with oscillations at this frequency often observed in tremulous patients. Additionally, oscillations around 20 Hz that are normally present in corticothalamic circuits can spread to the basal ganglia when both corticothalamic and indirect circuits have large gains. The model also accounts for changes in the responsiveness of the components of the basal ganglia-thalamocortical system, and increased synchronization upon dopamine depletion, which plausibly reflect the loss of specificity of neuronal signaling pathways in the parkinsonian basal ganglia. Thus, a parsimonious explanation is provided for many electrophysiological correlates of Parkinson's disease using a single set of parameter changes with respect to the healthy state. Overall, we conclude that mean-field models of brain electrophysiology possess a versatility that allows them to be usefully applied in a variety of scenarios. Such models allow information about underlying physiology to be extracted from the experimental EEG, complementing traditional measures that may be more statistically robust but do not provide a direct link with physiology. Furthermore, there is ample opportunity for future developments, extending the basic model to encompass different neuronal systems, connections, and mechanisms. The basal ganglia are an important addition, not only leading to unified explanations for many hitherto disparate phenomena, but also contributing to the validation of this form of modeling

Optimising programming to reduce side effects of subthalamic nucleus deep brain stimulation in Parkinson’s Disease

Subthalamic nucleus deep brain stimulation (STN DBS) is a widely used treatment for Parkinson’s disease patients with motor complications refractory to medical management. However, a significant proportion of treated patients suffer from stimulation induced side effects. Conventional options to address these by modulation of stimulation parameters and programming configurations have been limited. In recent years, technological advances have resulted in the emergence of novel programming features, including the use of short pulse width (PW) and directional steering, that represent further avenues to explore in this regard. In this thesis, I will present data on the utility of these programming techniques in alleviating stimulation induced side effects, and explore mechanisms that may mediate any observed effects. The data presented here is derived from four studies. Study 1 quantified the therapeutic window using short PW stimulation at 30μs relative to conventional 60μs settings. Study 2 represents a randomised controlled trial on short PW in chronic STN DBS patients with dysarthria. Study 3 evaluated the utility of directional steering, short PW, and the combination of these features in reversing stimulation induced dysarthria, dyskinesia, and pyramidal side effects. The findings of these studies suggest that short PW significantly increases the therapeutic window in terms of amplitude and charge, and that while it may not benefit chronic dysarthric patients collectively, directional steering and short PW can each significantly improve reversible stimulation induced side effects early in the course of STN DBS therapy. These novel techniques represent effective additional tools to conventional methods for optimising stimulation. In study 4, imaging and visualisation software are used to model and explore shifts in volume of tissue activated based on clinical data from study 3, and quantitatively compare charge per pulse, in order to explore potential mechanisms underlying the changes seen with these techniques

Pathophysiological mechanisms in Parkinson`s Disease and Dystonia – converging aetiologies

In this thesis I used a range of experimental approaches including genetics, enzyme activity measurements, histology and imaging to explore converging pathophysiological mechanisms of Parkinson`s disease and dystonia, two conditions with frequent clinical overlap. First, based on a combined retro- and prospective cohort of patients, using a combination of lysosomal enzyme activity measurements in peripheral blood and brain samples, as well as a target gene approach, I provide first evidence of reduced levels of enzyme activity in Glucocerebrosidase and the presence of GBA mutations, indicating lysosomal abnormality, in a relevant proportion of patients with dystonia of previously unknown origin. Second, based on a retrospective cohort of patients, I detail that a relevant proportion of genetically confirmed mitochondrial disease patients present with a movement disorder phenotype - predominantly dystonia and parkinsonism. Analysing volumetric MRI data, I describe a patterned cerebellar atrophy in these particular patients. This also includes the first cases of isolated dystonia due to mitochondrial disease, adding the latter as a potential aetiology for dystonia of unknown origin. Third, I used a combination of post-GWAS population genetic approaches and tissue-based experiments to explore in how far the strong association between advancing age and Parkinson ́s disease is mediated via telomere length. Although the initial finding of an association between genetically determined telomere length and PD risk did not replicate in independent cohorts, I provide evidence that telomere length in human putamen physiologically shortens with advancing age and 3 is regulated differently than in other brain regions. This is unique in the human brain, implying a particular age-related vulnerability of the striatum, part of the nigro-striatal network, crucially involved in PD pathophysiology. I conclude by discussing the above findings in light of the current literature, expand on their relevance and possible direction of future experiments

The use of current steering during subthalamic deep brain stimulation to alleviate upper limb symptoms of Parkinson\u27s disease

Subthalamic (STN) deep brain stimulation (DBS) is an established treatment to alleviate the appendicular motor symptoms of Parkinson\u27s Disease (PD). Current steering during DBS allows the unequal fractionation of current between two electrodes on the lead, resulting in a non-spherical electrical field. It is hypothesized that the way the electrical field is shaped will affect a patient’s upper limb symptom alleviation. Seven PD patients who underwent bilateral STN-DBS were tested over four weeks post-operation. 16 current fractionation settings were tested each week at an amplitude that increased weekly. Optimal setting was defined as the setting that provided the best symptom improvement based on kinematic data detected by a motion capture system and the Unified Parkinson\u27s Disease Rating Scale. Results assessing right and left upper limb symptoms gave 14 optimal settings in seven patients, of which eight settings employed current steering either unilaterally or bilaterally, and six settings employed bilateral monopolar stimulation. Thus, the use of current steering was patient-dependent and limb-dependent; factors contributing to this finding include differences in lead placement, symptom heterogeneity, and possible differences in STN functionality

Diagnosis and Treatment of Parkinson's Disease

Parkinson's disease is diagnosed by history and physical examination and there are no laboratory investigations available to aid the diagnosis of Parkinson's disease. Confirmation of diagnosis of Parkinson's disease thus remains a difficulty. This book brings forth an update of most recent developments made in terms of biomarkers and various imaging techniques with potential use for diagnosing Parkinson's disease. A detailed discussion about the differential diagnosis of Parkinson's disease also follows as Parkinson's disease may be difficult to differentiate from other mimicking conditions at times. As Parkinson's disease affects many systems of human body, a multimodality treatment of this condition is necessary to improve the quality of life of patients. This book provides detailed information on the currently available variety of treatments for Parkinson's disease including pharmacotherapy, physical therapy and surgical treatments of Parkinson's disease. Postoperative care of patients of Parkinson's disease has also been discussed in an organized manner in this text. Clinicians dealing with day to day problems caused by Parkinson's disease as well as other healthcare workers can use beneficial treatment outlines provided in this book

Neuromagnetic investigations of mechanisms and effects of STN-DBS and medication in Parkinson's disease

Parkinson’s disease (PD) is a neurodegenerative disorder cardinally marked by motor symptoms, but also sensory symptoms and several other non-motor symptoms. PD patients are typically treated with dopaminergic medication for several years. Many patients eventually experience bouts of periods where medication might not be able to effectively control symptoms as well as experience side-effects of long-term dopaminergic treatments. Deep brain stimulation (DBS) is an option as the next therapeutic recourse for such patients. DBS treatment essentially involves placement of stimulating electrodes in the subthalamic nucleus (STN) or the globus pallidus internum (GPi) along with an implanted pulse generator (IPG) in the sub-clavicular space. STN-DBS alleviates motor symptoms and leads to substantial improvements in quality of life for PD patients. Although DBS is known to improve several classes of symptoms, the effect mechanism of DBS is still not clear. While there is a lack of electrophysiological investigation of sensory processing and the effects of treatments in PD altogether, the electrophysiological studies of the cortical dynamics during motor tasks and at rest lack consensus.We recorded magnetoencephalography (MEG) and electromyography (EMG) from PD patients in three studies: (i) at rest, (ii) during median nerve stimulation, and (iii) while performing phasic contractions (hand gripping). The three studies focused on cortical oscillatory dynamics at rest, during somatosensory processing and during movement, respectively. The measurements were conducted in DBS-treated, untreated (DBS washout) and dopaminergic-medicated states. While both treatments (DBS and dopaminergic medication) ameliorated motor symptoms similarly in all studies, they showed differentiated effects on: (i) increased sensorimotor cortical low-gamma spectral power (31-45 Hz) (but no changes in beta power (13-30 Hz)) at rest only during DBS, (ii) somatosensory processing with higher gamma augmentation (31-45 Hz, 20-60 ms) in the dopaminergic-medicated state compared to DBS-treated and untreated states, and (iii) hand gripping with increased motor-related beta corticomuscular coherence (CMC, 13-30 Hz) during dopaminergic medication in contrast to increased gamma power (31-45 Hz) during DBS.Firstly, we infer from the three studies that DBS and dopaminergic medication employ partially different anatomo-functional pathways and functional strategies when improving PD symptoms. Secondly, we suggest that treatments act on pathological oscillatory dynamics differently at cortical and sub-cortical levels and may do so through more sophisticated mechanisms than mere suppression of the pathological spectral power in a particular band. And thirdly, we urge exploring effect mechanisms of PD treatments beyond the motor system. The effects of dopaminergic medication on early somatosensory processing has opened the door for exploring the effects of treatments and studying their mechanisms using electrophysiology, especially in higher order sensory deficits. Integration of such research findings into a holistic view on mechanisms of treatments could pave way for better disease management paradigms. 

The role of oscillation population activity in cortico-basal ganglia circuits.

The basal ganglia (BG) are a group of subcortical brain nuclei that are anatomically situated between the cortex and thalamus. Hitherto, models of basal ganglia function have been based solely on the anatomical connectivity and changes in the rate of neurons mediated by inhibitory and excitatory neurotransmitter interactions and modulated by dopamine. Depletion of striatal dopamine as occurs in Parkinson's Disease (PD) however, leads primarily to changes in the rhythmicity of basal ganglia neurons. The general aim of this thesis is to use frontal electrocorticogram (ECoG) and basal ganglia local field potential (LFP) recordings in the rat to further investigate the putative role for oscillations and synchronisation in these structures in the healthy and dopamine depleted brain. In the awake animal, lesion of the SNc lead to a dramatic increase in the power and synchronisation of P-frequency band oscillations in the cortex and subthalamic nucleus (STN) compared to the sham lesioned animal. These results are highly similar to those in human patients and provide further evidence for a direct pathophysological role for p-frequency band oscillations in PD. In the healthy, anaesthetised animal, LFPs recorded in the STN, globus pallidus (GP) and substantia nigra pars reticulata (SNr) were all found to be coherent with the ECoG. A detailed analysis of the interdependence and direction of these activities during two different brain states, prominent slow wave activity (SWA) and global activation, lead to the hypothesis that there were state dependant changes in the dominance of the cortico-subthalamic and cortico-striatal pathways. Multiple LFP recordings in the striatum and GP provided further evidence for this hypothesis, as coherence between the ECoG and GP was found to be dependent on the striatum. Together these results suggest that oscillations and synchronisation may mediate information flow in cortico-basal ganglia networks in both health and disease