Interhemispheric functional interactions between the subthalamic nuclei of patients with Parkinson's disease.

Parkinson's disease (PD) is characterized by widespread neural interactions in cortico-basal-ganglia networks primarily in beta oscillations (approx. 10-30 Hz), as suggested by previous findings of levodopa-modulated interhemispheric coherence between the bilateral subthalamic nuclei (STN) in local field potential recordings (LFPs). However, due to confounding effects of volume conduction the existence of 'genuine' interhemispheric subcortical coherence remains an open question. To address this issue we utilized the imaginary part of coherency (iCOH) which, in contrast to the standard coherence, is not susceptible to volume conduction. LFPs were recorded from eight patients with PD during wakeful rest before and after levodopa administration. We demonstrated genuine coherence between the bilateral STN in both 10-20 and 21-30 Hz oscillations, as revealed by a non-zero iCOH. Crucially, increased iCOH in 10-20 Hz oscillations positively correlated with the worsening of motor symptoms in the OFF medication condition across patients, which was not the case for standard coherence. Furthermore, across patients iCOH was increased after levodopa administration in 21-30 Hz oscillations. These results suggest a functional distinction between low and high beta oscillations in STN-LFP in line with previous studies. Furthermore, the observed functional coupling between the bilateral STN might contribute to the understanding of bilateral effects of unilateral deep brain stimulation. In conclusion, the present results imply a significant contribution of time-delayed neural interactions to interhemispheric coherence, and the clinical relevance of long-distance neural interactions between bilateral STN for motor symptoms in PD.

Long-range temporal correlations in the subthalamic nucleus of patients with Parkinson's disease.

Neuronal activity in the subthalamic nucleus (STN) of patients with Parkinson's disease (PD) is characterised by excessive neuronal synchronization, particularly in the beta frequency range. However, less is known about the temporal dynamics of neuronal oscillations in PD. In this respect long-range temporal correlations (LRTC) are of special interest as they quantify the neuronal dynamics on different timescales and have been shown to be relevant for optimal information processing in the brain. While the presence of LRTC has been demonstrated in cortical data, their existence in deep brain structures remains an open question. We investigated (i) whether LRTC are present in local field potentials (LFP) recorded bilaterally from the STN at wakeful rest in ten patients with PD after overnight withdrawal of levodopa (OFF) and (ii) whether LRTC can be modulated by levodopa treatment (ON). Detrended fluctuation analysis was utilised in order to quantify the temporal dynamics in the amplitude fluctuations of LFP oscillations. We demonstrated for the first time the presence of LRTC (extending up to 50 s) in the STN. Importantly, the ON state was characterised by significantly stronger LRTC than the OFF state, both in beta (13-35 Hz) and high-frequency (> 200 Hz) oscillations. The existence of LRTC in subcortical structures such as STN provides further evidence for their ubiquitous nature in the brain. The weaker LRTC in the OFF state might indicate limited information processing in the dopamine-depleted basal ganglia. The present results implicate LRTC as a potential biomarker of pathological neuronal processes in PD.

Functional and effective connectivity in subthalamic local field potential recordings of patients with Parkinson's disease.

In Parkinson's disease (PD) levodopa-associated changes in the power and long-range temporal correlations of beta oscillations have been demonstrated, yet the presence and modulation of genuine connectivity in local field potentials (LFP) recorded from the subthalamic nucleus (STN) remains an open question. The present study investigated LFP recorded bilaterally from the STN at wakeful rest in ten patients with PD after overnight withdrawal of levodopa (OFF) and after a single dose levodopa administration (ON). We utilized connectivity measures being insensitive to volume conduction (functional connectivity: non-zero imaginary part of coherency; effective connectivity: phase-slope index). We demonstrated the presence of neuronal interactions in the frequency range of 10-30 Hz in STN-LFP without a preferential directionality of interactions between different contacts along the electrode tracks. While the direction of neuronal interactions per se was preserved after levodopa administration, functional connectivity and the ventral-dorsal information flow were modulated by medication. The OFF-ON differences in functional connectivity were correlated with the levodopa-induced improvement in clinical Unified Parkinson's Disease Rating Scale scores. We hypothesize that regional neuronal interactions, as reflected in STN-LFP connectivity, might represent a basis for the intra-nuclear spatial specificity of deep brain stimulation. Moreover, our results suggest the potential use of volume conduction-insensitive measures of connectivity in STN-LFP as a marker of clinical motor symptoms in PD.

Automated optimization of subcortical cerebral MR imaging-atlas coregistration for improved postoperative electrode localization in deep brain stimulation.

BACKGROUND AND PURPOSE: The efficacy of deep brain stimulation in treating movement disorders depends critically on electrode localization, which is conventionally described by using coordinates relative to the midcommissural point. This approach requires manual measurement and lacks spatial normalization of anatomic variances. Normalization is based on intersubject spatial alignment (coregistration) of corresponding brain structures by using different geometric transformations. Here, we have devised and evaluated a scheme for automated subcortical optimization of coregistration (ASOC), which maximizes patient-to-atlas normalization accuracy of postoperative structural MR imaging into the standard Montreal Neurologic Institute (MNI) space for the basal ganglia. MATERIALS AND METHODS: Postoperative T2-weighted MR imaging data from 39 patients with Parkinson disease and 32 patients with dystonia were globally normalized, representing the standard registration (control). The global transformations were regionally refined by 2 successive linear registration stages (RSs) (ASOC-1 and 2), focusing progressively on the basal ganglia with 2 anatomically selective brain masks, which specify the reference volume (weighted cost function). Accuracy of the RSs was quantified by spatial dispersion of 16 anatomic landmarks and their root-mean-square errors (RMSEs) with respect to predefined MNI-based reference points. The effects of CSF volume, age, and sex on RMSEs were calculated. RESULTS: Mean RMSEs differed significantly (P < .001) between the global control (4.2 +/- 2.0 mm), ASOC-1 (1.92 +/- 1.02 mm), and ASOC-2 (1.29 +/- 0.78 mm). CONCLUSIONS: The present method improves the registration accuracy of postoperative structural MR imaging data into MNI space within the basal ganglia, allowing automated normalization with increased precision at stereotactic targets, and enables lead-contact localization in MNI coordinates for quantitative group analysis.