Task specific inter-hemispheric coupling in human subthalamic nuclei

Differential contribution of sensorimotor cortex and subthalamic nucleus to unimanual and bimanual hand movements

Why does unilateral deep brain stimulation improve motor function bilaterally? To address this clinical observation, we collected parallel neural recordings from sensorimotor cortex (SMC) and the subthalamic nucleus (STN) during repetitive ipsilateral, contralateral, and bilateral hand movements in patients with Parkinson's disease. We used a cross-validated electrode-wise encoding model to map electromyography data to the neural signals. Electrodes in the STN encoded movement at a comparable level for both hands, whereas SMC electrodes displayed a strong contralateral bias. To examine representational overlap across the two hands, we trained the model with data from one condition (contralateral hand) and used the trained weights to predict neural activity for movements produced with the other hand (ipsilateral hand). Overall, between-hand generalization was poor, and this limitation was evident in both regions. A similar method was used to probe representational overlap across different task contexts (unimanual vs. bimanual). Task context was more important for the STN compared to the SMC indicating that neural activity in the STN showed greater divergence between the unimanual and bimanual conditions. These results indicate that SMC activity is strongly lateralized and relatively context-free, whereas the STN integrates contextual information with the ongoing behavior.

Cortical network formation based on subthalamic beta bursts in Parkinson's disease

Recent evidence suggests that beta bursts in subthalamic nucleus (STN) play an important role in Parkinsonian pathophysiology. We studied the spatio-temporal relationship between STN beta bursts and cortical activity in 26 Parkinson's disease (PD) patients undergoing deep brain stimulation (DBS) surgery. Postoperatively, we simultaneously recorded STN local field potentials (LFP) from externalized DBS leads and cortical activity using whole-brain magnetoencephalography. Event-related magnetic fields (ERF) were averaged time-locked to STN beta bursts and subjected to source localization. Our results demonstrate that ERF exhibiting activity significantly different from baseline activity were localized within areas functionally related to associative, limbic, and motor systems as well as regions pertinent for visual and language processing. Our data suggest that STN beta bursts are involved in network formation between STN and cortex. This interaction is in line with the idea of parallel processing within the basal ganglia-cortex loop, specifically within the functional subsystems of the STN (i.e., associative, limbic, motor, and the related cortical areas). ERFs within visual and language-related cortical areas indicate involvement of beta bursts in STN-cortex networks beyond the associative, limbic, and motor loops. In sum, our results highlight the involvement of STN beta bursts in the formation of multiple STN - cortex loops in patients with PD.

Resting-State Functional Connectivity Predicts STN DBS Clinical Response

BACKGROUND

Deep brain stimulation of the subthalamic nucleus is a widely used adjunctive therapy for motor symptoms of Parkinson's disease, but with variable motor response. Predicting motor response remains difficult, and novel approaches may improve surgical outcomes as well as the understanding of pathophysiological mechanisms. The objective of this study was to determine whether preoperative resting-state functional connectivity MRI predicts motor response from deep brain stimulation of the subthalamic nucleus.

METHODS

We collected preoperative resting-state functional MRI from 70 participants undergoing subthalamic nucleus deep brain stimulation. For this cohort, we analyzed the strength of STN functional connectivity with seeds determined by stimulation-induced (ON/OFF) 15 O H2 O PET regional cerebral blood flow differences in a partially overlapping group (n = 42). We correlated STN-seed functional connectivity strength with postoperative motor outcomes and applied linear regression to predict motor outcomes.

RESULTS

Preoperative functional connectivity between the left subthalamic nucleus and the ipsilateral internal globus pallidus correlated with postsurgical motor outcomes (r = -0.39, P = 0.0007), with stronger preoperative functional connectivity relating to greater improvement. Left pallidal-subthalamic nucleus connectivity also predicted motor response to DBS after controlling for covariates.

DISCUSSION

Preoperative pallidal-subthalamic nucleus resting-state functional connectivity predicts motor benefit from deep brain stimulation, although this should be validated prospectively before clinical application. These observations suggest that integrity of pallidal-subthalamic nucleus circuits may be critical to motor benefits from deep brain stimulation. © 2020 International Parkinson and Movement Disorder Society.

Constructing Brain Connectivity Model Using Causal Network Reconstruction Approach

Studying brain function is a challenging task. In the past, we could only study brain anatomical structures post-mortem, or infer brain functions from clinical data of patients with a brain injury. Nowadays technology, such as functional magnetic resonance imaging (fMRI), enable non-invasive brain activity observation. Several approaches have been proposed to interpret brain activity data. The brain connectivity model is a graphical tool that represents the interaction between brain regions, during certain states. It depicts how a brain region cause changes to other parts of the brain, which can be implied as information flow. This model can be used to help interpret how the brain works. There are several mathematical frameworks that can be used to infer the connectivity model from brain activity signals. Granger causality is one such approach and is one of the first that has been applied to brain activity data. However, due to the concept of the framework, such as the use of pairwise correlation, combined with the limitation of brain activity data such as low temporal resolution in case of fMRI signal, makes the interpretation of the connectivity difficult. We therefore propose the application of the Tigramite causal discovery framework on fMRI data. The Tigramite framework uses measures such as causal effect to analyze causal relations in the system. This enables the framework to identify both direct and indirect pathways or connectivities. In this paper, we applied the framework to the Human Connectome Project motor task-fMRI dataset. We then present the results and discuss how the framework improves interpretability of the connectivity model. We hope that this framework will help us understand more complex brain functions such as memory, consciousness, or the resting-state of the brain, in the future.

Movement-Modulation of Local Power and Phase Amplitude Coupling in Bilateral Globus Pallidus Interna in Parkinson Disease

There is converging evidence that bilateral basal ganglia motor networks jointly support normal movement behaviors including unilateral movements. The extent and manner in which these networks interact during lateralized movement remains unclear. In this study, simultaneously recorded bilateral Globus Pallidus interna (GPi) local field potentials (LFP) were examined from 19 subjects with idiopathic Parkinson disease (PD), while undergoing awake deep brain stimulation (DBS) implantation. Recordings were carried out during two behavioral states; rest and cued left hand movement (finger tapping). The state-dependent effects on α- β oscillatory power and β phase-encoded phase amplitude coupling (PAC), including symmetrical and assymetrical changes between hemispheres, were identified. Unilateral hand movement resulted in symmetrical oscillatory power suppression within bilateral GPi at α (8-12 Hz) and high β (21-35 Hz) and increase in power of high frequency oscillations (HFO, 200-300 Hz) frequency bands. Asymmetrical attenuation was also observed at both low β (13-20 Hz) and low γ (40-80 Hz) bands within the contralateral GPi (P = 0.009). In addition, unilateral movement effects on PAC were confined to the contralateral GPi with attenuation of both low β-low γ and β-HFO PAC (P < 0.05). Further analysis showed that the lateralized attenuation of low β and low γ power did not correlate with low β-low γ PAC changes. The overall coherence between bilateral GPi was not significantly altered with unilateral movement, however the preferred phase difference in the high β range increased from 0.23 (±1.31) radians during rest to 1.99 (±0.78) radians during movement execution. Together, the present results suggest that unilateral motor control involves bilateral basal ganglia networks with movement features differentially encoded by distinct frequency bands. The lateralization of low β and low γ attenuation with movement suggests that these frequency bands are specific to the motor act whereas symmetrical expression of α, high β, and HFO oscillations best correspond to motor state. The restriction of movement-related PAC modulation to the contralateral GPi indicates that cross-frequency interactions appear to be associated with lateralized movements. Despite no significant movement-related changes in the interhemispheric coherence, the increase in phase difference suggests that the communication between bilateral GPi is altered with unilateral movement.

Phase matters: A role for the subthalamic network during gait

The role of the subthalamic nucleus in human locomotion is unclear although relevant, given the troublesome management of gait disturbances with subthalamic deep brain stimulation in patients with Parkinson’s disease. We investigated the subthalamic activity and inter-hemispheric connectivity during walking in eight freely-moving subjects with Parkinson’s disease and bilateral deep brain stimulation. In particular, we compared the subthalamic power spectral densities and coherence, amplitude cross-correlation and phase locking value between resting state, upright standing, and steady forward walking. We observed a phase locking value drop in the β-frequency band (≈13-35Hz) during walking with respect to resting and standing. This modulation was not accompanied by specific changes in subthalamic power spectral densities, which was not related to gait phases or to striatal dopamine loss measured with [¹²³I]N-ω-fluoropropyl-2β-carbomethoxy-3β-(4-iodophenyl)nortropane and single-photon computed tomography. We speculate that the subthalamic inter-hemispheric desynchronization in the β-frequency band reflects the information processing of each body side separately, which may support linear walking. This study also suggests that in some cases (i.e. gait) the brain signal, which could allow feedback-controlled stimulation, might derive from network activity.

Unilateral deep brain stimulation suppresses alpha and beta oscillations in sensorimotor cortices

Deep brain stimulation (DBS) is an established therapy to treat motor symptoms in movement disorders such as Parkinson's disease (PD). The mechanisms leading to the high therapeutic effectiveness of DBS are poorly understood so far, but modulation of oscillatory activity is likely to play an important role. Thus, investigating the effect of DBS on cortical oscillatory activity can help clarifying the neurophysiological mechanisms of DBS. Here, we aimed at scrutinizing changes of cortical oscillatory activity by DBS at different frequencies using magnetoencephalography (MEG). MEG data from 17 PD patients were acquired during DBS of the subthalamic nucleus (STN) the day after electrode implantation and before implanting the pulse generator. We stimulated the STN unilaterally at two different stimulation frequencies, 130 Hz and 340 Hz using an external stimulator. Data from six patients had to be discarded due to strong artefacts and two other datasets were excluded since these patients were not able to finalize the paradigm. After DBS artefact removal, power spectral density (PSD) values of MEG were calculated for each individual patient and averaged over the group. DBS at both 130 Hz and 340 Hz led to a widespread suppression of cortical alpha/beta band activity (8-22 Hz) specifically over bilateral sensorimotor cortices. No significant differences were observed between the two stimulation frequencies. Our finding of a widespread suppression of cortical alpha/beta band activity is particularly interesting as PD is associated with pathologically increased levels of beta band activity in the basal ganglia-thalamo-cortical circuit. Therefore, suppression of such oscillatory activity might be an essential effect of DBS for relieving motor symptoms in PD and can be achieved at different stimulation frequencies above 100 Hz.

Asymmetric neuromodulation of motor circuits in Parkinson's disease: The role of subthalamic deep brain stimulation

Whereas hemispheric dominance is well-established for appendicular motor control in humans, the evidence for dominance in axial motor control is still scarce. In Parkinson's disease (PD), unilateral (UL) onset of appendicular motor symptoms corresponds with asymmetric neurodegeneration predominantly affecting contralateral nigrostriatal circuits. Disease progression yields bilateral and axial motor symptoms but the initial appendicular asymmetry usually persists. Furthermore, there is evidence for hemispheric dominance for axial motor dysfunction in some of these patients. Dopaminergic medications improve appendicular symptoms but can also produce motor complications over time. Once these complications develop, bilateral (BL) deep brain stimulation (DBS) of the subthalamic nuclei (STN) can significantly improve appendicular symptoms while reducing medication doses and motor complications. Conversely, axial motor symptoms remain a significant source of disability, morbidity, and mortality for patients with PD. These axial symptoms do not necessarily improve with dopaminergic therapy, might not respond, and could even worsen after BL-DBS. In contrast to medications, DBS provides the opportunity to modify stimulation parameters for each cerebral hemisphere. Identical, BL-DBS of motor circuits with hemispheric dominance in PD might produce overstimulation on one side and/or understimulation on the other side, which could contribute to motor dysfunction. Several studies based on asymmetry of appendicular motor symptoms already support an initial UL rather than BL approach to DBS in some patients. The response of axial motor symptoms to UL versus BL-DBS remains unclear. Nonetheless, UL-DBS, staged BL-DBS, or asymmetric programming of BL-DBS could also be considered in patients with PD.

Motor Task Detection From Human STN Using Interhemispheric Connectivity

Deep brain stimulation (DBS) provides significant therapeutic benefit for movement disorders, such as Parkinson's disease (PD). Current DBS devices lack real-time feedback (thus are open loop) and stimulation parameters are adjusted during scheduled visits with a clinician. A closed-loop DBS system may reduce power consumption and side effects by adjusting stimulation parameters based on patient's behavior. Subthalamic nucleus (STN) local field potential (LFP) is a great candidate signal for the neural feedback, because it can be recorded from the stimulation lead and does not require additional sensors. In this paper, we introduce a behavior detection method capable of asynchronously detecting the finger movements of PD patients. Our study indicates that there is a motor-modulated inter-hemispheric connectivity between LFP signals recorded bilaterally from the STN. We utilize a non-linear regression method to measure this inter-hemispheric connectivity for detecting finger movement. Our experimental results, using the recordings from 11 patients with PD, demonstrate that this approach is applicable for behavior detection in the majority of subjects (average area under curve of 70±12%).

A Multiple Kernel Learning approach for human behavioral task classification using STN-LFP signal

Deep Brain Stimulation (DBS) has gained increasing attention as an effective method to mitigate Parkinson's disease (PD) disorders. Existing DBS systems are open-loop such that the system parameters are not adjusted automatically based on patient's behavior. Classification of human behavior is an important step in the design of the next generation of DBS systems that are closed-loop. This paper presents a classification approach to recognize such behavioral tasks using the subthalamic nucleus (STN) Local Field Potential (LFP) signals. In our approach, we use the time-frequency representation (spectrogram) of the raw LFP signals recorded from left and right STNs as the feature vectors. Then these features are combined together via Support Vector Machines (SVM) with Multiple Kernel Learning (MKL) formulation. The MKL-based classification method is utilized to classify different tasks: button press, mouth movement, speech, and arm movement. Our experiments show that the lp-norm MKL significantly outperforms single kernel SVM-based classifiers in classifying behavioral tasks of five subjects even using signals acquired with a low sampling rate of 10 Hz. This leads to a lower computational cost.

Striatal Dopaminergic Innervation Regulates Subthalamic Beta-Oscillations and Cortical-Subcortical Coupling during Movements: Preliminary Evidence in Subjects with Parkinson's Disease

Activation of the basal ganglia has been shown during the preparation and execution of movement. However, the functional interaction of cortical and subcortical brain areas during movement and the relative contribution of dopaminergic striatal innervation remains unclear. We recorded local field potential (LFP) activity from the subthalamic nucleus (STN) and high-density electroencephalography (EEG) signals in four patients with Parkinson’s disease (PD) off dopaminergic medication during a multi-joint motor task performed with their dominant and non-dominant hand. Recordings were performed by means of a fully-implantable deep brain stimulation (DBS) device at 4 months after surgery. Three patients also performed a single-photon computed tomography (SPECT) with [¹²³I]N-ω-fluoropropyl-2β-carbomethoxy-3β-(4-iodophenyl)nortropane (FP-CIT) to assess striatal dopaminergic innervation. Unilateral movement execution led to event-related desynchronization (ERD) followed by a rebound after movement termination event-related synchronization (ERS) of oscillatory beta activity in the STN and primary sensorimotor cortex of both hemispheres. Dopamine deficiency directly influenced movement-related beta-modulation, with greater beta-suppression in the most dopamine-depleted hemisphere for both ipsi- and contralateral hand movements. Cortical-subcortical, but not interhemispheric subcortical coherencies were modulated by movement and influenced by striatal dopaminergic innervation, being stronger in the most dopamine-depleted hemisphere. The data are consistent with a role of dopamine in shielding subcortical structures from an excessive cortical entrapment and cross-hemispheric coupling, thus allowing fine-tuning of movement.

Time evolution of interhemispheric coupling in a model of focal neocortical epilepsy in mice

Epilepsy is characterized by substantial network rearrangements leading to spontaneous seizures and little is known on how an epileptogenic focus impacts on neural activity in the contralateral hemisphere. Here, we used a model of unilateral epilepsy induced by injection of the synaptic blocker tetanus neurotoxin (TeNT) in the mouse primary visual cortex (V1). Local field potential (LFP) signals were simultaneously recorded from both hemispheres of each mouse in acute phase (peak of toxin action) and chronic condition (completion of TeNT effects). To characterize the neural electrical activities the corresponding LFP signals were analyzed with several methods of time series analysis. For the epileptic mice, the spectral analysis showed that TeNT determines a power redistribution among the different neurophysiological bands in both acute and chronic phases. Using linear and nonlinear interdependence measures in both time and frequency domains, it was found in the acute phase that TeNT injection promotes a reduction of the interhemispheric coupling for high frequencies (12-30 Hz) and small time lag (<20 ms), whereas an increase of the coupling is present for low frequencies (0.5-4 Hz) and long time lag (>40 ms). On the other hand, the chronic period is characterized by a partial or complete recovery of the interhemispheric interdependence level. Granger causality test and symbolic transfer entropy indicate a greater driving influence of the TeNT-injected side on activity in the contralateral hemisphere in the chronic phase. Lastly, based on experimental observations, we built a computational model of LFPs to investigate the role of the ipsilateral inhibition and exicitatory interhemispheric connections in the dampening of the interhemispheric coupling. The time evolution of the interhemispheric coupling in such a relevant model of epilepsy has been addressed here.

Toward Deep Brain Monitoring with Superficial EEG Sensors Plus Neuromodulatory Focused Ultrasound

Noninvasive recordings of electrophysiological activity have limited anatomic specificity and depth. We hypothesized that spatially tagging a small volume of brain with a unique electroencephalography (EEG) signal induced by pulsed focused ultrasound could overcome those limitations. As a first step toward testing this hypothesis, we applied transcranial ultrasound (2 MHz, 200-ms pulses applied at 1050 Hz for 1 s at a spatial peak temporal average intensity of 1.4 W/cm(2)) to the brains of anesthetized rats while simultaneously recording EEG signals. We observed a significant 1050-Hz electrophysiological signal only when ultrasound was applied to a living brain. Moreover, amplitude demodulation of the EEG signal at 1050 Hz yielded measurement of gamma band (>30 Hz) brain activity consistent with direct measurements of that activity. These results represent preliminary support for use of pulsed focused ultrasound as a spatial tagging mechanism for non-invasive EEG-based mapping of deep brain activity with high spatial resolution.

Frequency-Specific Synchronization in the Bilateral Subthalamic Nuclei Depending on Voluntary Muscle Contraction and Relaxation in Patients with Parkinson's Disease

The volitional control of muscle contraction and relaxation is a fundamental component of human motor activity, but how the processing of the subcortical networks, including the subthalamic nucleus (STN), is involved in voluntary muscle contraction (VMC) and voluntary muscle relaxation (VMR) remains unclear. In this study, local field potentials (LFPs) of bilateral STNs were recorded in patients with Parkinson’s disease (PD) while performing externally paced VMC and VMR tasks of the unilateral wrist extensor muscle. The VMC- or VMR-related oscillatory activities and their functional couplings were investigated over the theta (4–7 Hz), alpha (8–13 Hz), beta (14–35 Hz), and gamma (40–100 Hz) frequency bands. Alpha and beta desynchronizations were observed in bilateral STNs at the onset of both VMC and VMR tasks. On the other hand, theta and gamma synchronizations were prominent in bilateral STNs specifically at the onset of the VMC task. In particular, just after VMC, theta functional coupling between the bilateral STNs increased, and the theta phase became coupled to the gamma amplitude within the contralateral STN in a phase-amplitude cross-frequency coupled manner. On the other hand, the prominent beta-gamma cross-frequency couplings observed in the bilateral STNs at rest were reduced by the VMC and VMR tasks. These results suggest that STNs are bilaterally involved in the different performances of muscle contraction and relaxation through the theta-gamma and beta-gamma networks between bilateral STNs in patients with PD.

Motor task event detection using Subthalamic Nucleus Local Field Potentials

Deep Brain Stimulation (DBS) provides significant therapeutic benefit for movement disorders such as Parkinson's disease. Current DBS devices lack real-time feedback (thus are open loop) and stimulation parameters are adjusted during scheduled visits with a clinician. A closed-loop DBS system may reduce power consumption and DBS side effects. In such systems, DBS parameters are adjusted based on patient's behavior, which means that behavior detection is a major step in designing such systems. Various physiological signals can be used to recognize the behaviors. Subthalamic Nucleus (STN) Local Field Potential (LFP) is a great candidate signal for the neural feedback, because it can be recorded from the stimulation lead and does not require additional sensors. A practical behavior detection method should be able to detect behaviors asynchronously meaning that it should not use any prior knowledge of behavior onsets. In this paper, we introduce a behavior detection method that is able to asynchronously detect the finger movements of Parkinson patients. As a result of this study, we learned that there is a motor-modulated inter-hemispheric connectivity between LFP signals recorded bilaterally from STN. We used non-linear regression method to measure this connectivity and use it to detect the finger movements. Performance of this method is evaluated using Receiver Operating Characteristic (ROC).

Functional Connectivity Differences of the Subthalamic Nucleus Related to Parkinson's Disease

A typical feature of Parkinson's disease (PD) is pathological activity in the subthalamic nucleus (STN). Here, we tested whether in patients with PD under dopaminergic treatment functional connectivity of the STN differs from healthy controls (HC) and whether some brain regions show (anti-) correlations between functional connectivity with STN and motor symptoms. We used functional magnetic resonance imaging to investigate whole-brain resting-state functional connectivity with STN in 54 patients with PD and 55 HC matched for age, gender, and within-scanner motion. Compared to HC, we found attenuated negative STN-coupling with Crus I of the right cerebellum and with right ventromedial prefrontal regions in patients with PD. Furthermore, we observed enhanced negative STN-coupling with bilateral intraparietal sulcus/superior parietal cortex, right sensorimotor, right premotor, and left visual cortex compared to HC. Finally, we found a decline in positive STN-coupling with the left insula related to severity of motor symptoms and a decline of inter-hemispheric functional connectivity between left and right STN with progression of PD-related motor symptoms. Motor symptom related uncoupling of the insula, a key region in the saliency network and for executive function, from the STN might be associated with well-known executive dysfunction in PD. Moreover, uncoupling between insula and STN might also induce an insufficient setting of thresholds for the discrimination between relevant and irrelevant salient environmental stimuli, explaining observations of disturbed response control in PD. In sum, motor symptoms in PD are associated with a reduced coupling between STN and a key region for executive function.

Metabolic, synaptic and behavioral impact of 5-week chronic deep brain stimulation in hemiparkinsonian rats

The long-term effects and action mechanisms of subthalamic nucleus (STN) high-frequency stimulation (HFS) for Parkinson's disease still remain poorly characterized, mainly due to the lack of experimental models relevant to clinical application. To address this issue, we performed a multilevel study in freely moving hemiparkinsonian rats undergoing 5-week chronic STN HFS, using a portable constant-current microstimulator. In vivo metabolic neuroimaging by (1) H-magnetic resonance spectroscopy (11.7 T) showed that STN HFS normalized the tissue levels of the neurotransmission-related metabolites glutamate, glutamine and GABA in both the striatum and substantia nigra reticulata (SNr), which were significantly increased in hemiparkinsonian rats, but further decreased nigral GABA levels below control values; taurine levels, which were not affected in hemiparkinsonian rats, were significantly reduced. Slice electrophysiological recordings revealed that STN HFS was, uniquely among antiparkinsonian treatments, able to restore both forms of corticostriatal synaptic plasticity, i.e. long-term depression and potentiation, which were impaired in hemiparkinsonian rats. Behavior analysis (staircase test) showed a progressive recovery of motor skill during the stimulation period. Altogether, these data show that chronic STN HFS efficiently counteracts metabolic and synaptic defects due to dopaminergic lesion in both the striatum and SNr. Comparison of chronic STN HFS with acute and subchronic treatment further suggests that the long-term benefits of this treatment rely both on the maintenance of acute effects and on delayed actions on the basal ganglia network. We studied the effects of chronic (5 weeks) continuous subthalamic nucleus (STN) high-frequency stimulation (HFS) in hemiparkinsonian rats. The levels of glutamate and GABA in the striatum () and substantia nigra reticulata (SNr) (), measured by in vivo proton magnetic resonance spectroscopy ((1) H-MRS), were increased by 6-hydroxydopamine (6-OHDA) lesion, which also disrupted corticostriatal synaptic plasticity () and impaired forepaw skill () in the staircase test. Five-week STN HFS normalized glutamate and GABA levels and restored both synaptic plasticity and motor function. A partial behavioral recovery was observed at 2-week STN HFS.

Correlation between cortical and subcortical neural dynamics on multiple time scales in Parkinson's disease

Complex amplitude dynamics of dominant alpha oscillations (8-13 Hz) in the cortex can be captured with long-range temporal correlations (LRTC) in healthy subjects and in various diseases. In patients with Parkinson's disease (PD), intra-nuclear coherence was demonstrated in dominant beta rhythms (10-30 Hz) in the basal ganglia. However, so far the relation between cortical LRTC (across tens of seconds) and subcortical coherence (millisecond scale) is unknown. We addressed these "multiscale interactions" by simultaneous recordings of surface electroencephalography (EEG) and deep local field potentials (LFP) from the bilateral subthalamic nucleus (STN) in eight patients with severe PD eligible for deep brain stimulation, who performed a lexical decision task on medication. In the continuous data set LRTC up to 20s were calculated in the amplitude envelope of 8-13-Hz EEG oscillations (across whole scalp), and subcortical coherence was assessed with measures being insensitive to volume conduction artifacts (imaginary part of coherency; iCOH) in 10-20 and 21-30-Hz oscillations in STN-LFP. We showed a significant positive correlation across patients between cortical LRTC (8-13Hz) and subcortical iCOH selectively in 10-20-Hz oscillations in the left STN. Our results suggest a relation between neural dynamics in the most dominant rhythms in the cortex and basal ganglia in PD, extending across multiple time scales (milliseconds vs. tens of seconds). Furthermore, the investigation of multiscale interactions might contribute to our understanding of cortical-subcortical neural coupling in PD.