Resting oscillatory cortico-subthalamic connectivity in patients with Parkinson's disease.
ABSTRACT Both phenotype and treatment response vary in patients with Parkinson's disease. Anatomical and functional imaging studies suggest that individual symptoms may represent malfunction of different segregated networks running in parallel through the basal ganglia. In this study, we use a newly described, electrophysiological method to describe cortico-subthalamic networks in humans. We performed combined magnetoencephalographic and subthalamic local field potential recordings in thirteen patients with Parkinson's disease at rest. Two spatially and spectrally separated networks were identified. A temporoparietal-brainstem network was coherent with the subthalamic nucleus in the alpha (7-13 Hz) band, whilst a predominantly frontal network was coherent in the beta (15-35 Hz) band. Dopaminergic medication modulated the resting beta network, by increasing beta coherence between the subthalamic region and prefrontal cortex. Subthalamic activity was predominantly led by activity in the cortex in both frequency bands. The cortical topography and frequencies involved in the alpha and beta networks suggest that these networks may be involved in attentional and executive, particularly motor planning, processes, respectively.
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ABSTRACT: Parkinsonism is associated with changes in oscillatory activity patterns and increased synchronization of neurons in the basal ganglia and cortex in patients and animal models of Parkinson's disease, but the relationship between these changes and the severity of parkinsonian signs remains unclear. We examined this relationship by studying changes in local field potentials (LFPs) in the internal pallidal segment (GPi) and the subthalamic nucleus (STN), and in encephalographic signals (EEG) from the primary motor cortex (M1) in Rhesus monkeys which were rendered progressively parkinsonian by repeated systemic injections of small doses of the neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). Observations during wakefulness and sleep (defined by EEG and video records) were analyzed separately. The severity of parkinsonism correlated with increases in spectral power at frequencies below 15.5Hz in M1 and GPi and reductions in spectral power at frequencies above 15.6Hz with little change in STN. The severity of parkinsonism also correlated with increases in the coherence between M1 EEG and basal ganglia LFPs in the low frequency band. Levodopa treatment reduced low-frequency activity and increased high-frequency activity in all three areas, but did not affect coherence. The state of arousal also affected LFP and EEG signals in all three structures, particularly in the STN. These results suggest that parkinsonism-associated changes in alpha and low-beta band oscillatory activity can be detected early in the parkinsonian state in M1 and GPi. Interestingly, oscillations detectable in STN LFP signals (including oscillations in the beta-band) do not appear to correlate strongly with the severity of mild-to-moderate parkinsonism in these animals. Levodopa-induced changes in oscillatory M1 EEG and basal ganglia LFP patterns do not necessarily represent a normalization of abnormalities caused by dopamine depletion.Neurobiology of Disease 04/2014; · 5.62 Impact Factor
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ABSTRACT: Depleted of dopamine, the dynamics of the parkinsonian brain impact on both 'action' and 'resting' motor behaviour. Deep brain stimulation has become an established means of managing these symptoms, although its mechanisms of action remain unclear. Non-invasive characterizations of induced brain responses, and the effective connectivity underlying them, generally appeals to dynamic causal modelling of neuroimaging data. When the brain is at rest, however, this sort of characterization has been limited to correlations (functional connectivity). In this work, we model the 'effective' connectivity underlying low frequency blood oxygen level-dependent fluctuations in the resting Parkinsonian motor network-disclosing the distributed effects of deep brain stimulation on cortico-subcortical connections. Specifically, we show that subthalamic nucleus deep brain stimulation modulates all the major components of the motor cortico-striato-thalamo-cortical loop, including the cortico-striatal, thalamo-cortical, direct and indirect basal ganglia pathways, and the hyperdirect subthalamic nucleus projections. The strength of effective subthalamic nucleus afferents and efferents were reduced by stimulation, whereas cortico-striatal, thalamo-cortical and direct pathways were strengthened. Remarkably, regression analysis revealed that the hyperdirect, direct, and basal ganglia afferents to the subthalamic nucleus predicted clinical status and therapeutic response to deep brain stimulation; however, suppression of the sensitivity of the subthalamic nucleus to its hyperdirect afferents by deep brain stimulation may subvert the clinical efficacy of deep brain stimulation. Our findings highlight the distributed effects of stimulation on the resting motor network and provide a framework for analysing effective connectivity in resting state functional MRI with strong a priori hypotheses.Brain 02/2014; · 9.92 Impact Factor
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ABSTRACT: Positive clinical outcomes are now well established for deep brain stimulation, but little is known about the effects of long-term deep brain stimulation on brain structural and functional connectivity. Here, we used the rare opportunity to acquire pre- and postoperative diffusion tensor imaging in a patient undergoing deep brain stimulation in bilateral subthalamic nuclei for Parkinson's Disease. This allowed us to analyse the differences in structural connectivity before and after deep brain stimulation. Further, a computational model of spontaneous brain activity was used to estimate the changes in functional connectivity arising from the specific changes in structural connectivity. We found significant localised structural changes as a result of long-term deep brain stimulation. These changes were found in sensory-motor, prefrontal/limbic, and olfactory brain regions which are known to be affected in Parkinson's Disease. The nature of these changes was an increase of nodal efficiency in most areas and a decrease of nodal efficiency in the precentral sensory-motor area. Importantly, the computational model clearly shows the impact of deep brain stimulation-induced structural alterations on functional brain changes, which is to shift the neural dynamics back towards a healthy regime. The results demonstrate that deep brain stimulation in Parkinson's Disease leads to a topological reorganisation towards healthy bifurcation of the functional networks measured in controls, which suggests a potential neural mechanism for the alleviation of symptoms. The findings suggest that long-term deep brain stimulation has not only restorative effects on the structural connectivity, but also affects the functional connectivity at a global level. Overall, our results support causal changes in human neural plasticity after long-term deep brain stimulation and may help to identify the underlying mechanisms of deep brain stimulation.PLoS ONE 01/2014; 9(1):e86496. · 3.73 Impact Factor