An entropy-based investigation of underpinnings and impact of
oscillations in a model of PD.
Doctoral thesis, UCL (University College London).
The involvement of the basal ganglia in motor control has been highlighted in studies of Parkinson’s disease (PD) and other movement disorders. The loss of dopaminergic neurons in the substantia nigra pars compacta and subsequent decrease of the dopamine level in the basal ganglia is recognized as the hallmark of PD. The classical view of the architecture of the dopamine depleted basal ganglia-thalamo-cortical circuit identifies changes in firing rates as the probable cause for the motor impairments in PD. Yet, more recent findings have shown that disturbances in other intrinsic dynamical properties of these networks may also contribute to motor deficits. Electrophysiological recordings in the basal ganglia of deep brain stimulation (DBS) patients (when OFF stimulation) have found pathological oscillations at beta frequency (13-30 Hz). This abnormal oscillatory activity has also been found in basal ganglia nuclei of animal models of PD. Additionally, the beta frequency oscillations were found to decrease when the patients are on dopamine replacement therapies and as they initiate movement. Beta frequency oscillations have been identified in the firing of single neurons and in the coupling of discharges between neurons. Within the framework of information theory, we proposed a time series model to analyse and relate the effects of changes in the dynamics of individual factors – such as alterations in firing rates, oscillations and synchrony (or auto and cross-correlations) caused by dopamine depletion – on the coding capacity (i.e., entropy) of a network. We estimated the entropy of a neural network based on the probabilities of current spiking conditioned on the observation of firing rate and spiking history of the current neuron and of neighbouring neurons. Moreover, we could estimate entropies for each of these factors separately, in healthy and dopamine depleted conditions, and assess their relative contribution to the decrease of coding capacity in disease. Furthermore, the causal characteristics of the model made it possible to compare the synaptic connectivity of neuronal populations in health with that in disease, by measuring the amount of directed information transferred between populations. We employed the model to study the external globus pallidus (GPe) network in control and 6-hydroxydopamine (6-OHDA) lesioned rats – a model for PD. We found a significant decrease in the coding capacity in lesioned animals, compared to controls, and that this decrease was predominantly on account of a reduction in the GPe firing rates. Although to a lesser extent, the amplification of the oscillatory activity (mainly in the beta frequency range) observed in the lesioned animals had also a significant impact on the reduction of their coding capacity. The higher synchrony found in the 6-OHDA rats had the least effect. We also found that the levels of coding capacity in the GPe were restored to levels close to control when the lesioned animals were treated with the dopamine agonist apomorphine. In addition, we detected a stronger coupling between the subthalamic nucleus (STN) and the GPe in the dopamine depleted rats, pointing to an abnormally exaggerated transfer of information within this network. We have shown that the GPe and the STN-GPe networks in the dopamine depleted rat exhibit information processing irregularities. We believe these deficits in processing and relaying information may also be present in other structures of the basal ganglia-thalamo-cortical circuit and that they may underlie the motor impairment in PD.
|Title:||An entropy-based investigation of underpinnings and impact of oscillations in a model of PD|
|Open access status:||An open access version is available from UCL Discovery|
|UCL classification:||UCL > School of Life and Medical Sciences > Faculty of Brain Sciences > Institute of Neurology > Motor Neuroscience and Movement Disorders|
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