Freezing of gait is a disabling symptom of Parkinson’s disease that causes a paroxysmal inability to generate effective stepping. The underlying pathophysiology has recently migrated towards a dysfunctional supraspinal locomotor network, but the actual network derangements during ongoing gait freezing are unknown. We investigated the communication between the cortex and the subthalamic nucleus, two main nodes of the locomotor network, in seven freely-moving subjects with Parkinson’s disease with a novel deep brain stimulation device, which allows on-demand recording of subthalamic neural activity from the chronically-implanted electrodes months after the surgical procedure. Multisite neurophysiological recordings during (effective) walking and ongoing gait freezing were combined with kinematic measurements and individual molecular brain imaging studies. Patients walked in a supervised environment closely resembling everyday life challenges. We found that during (effective) walking, the cortex and subthalamic nucleus were synchronized in a low frequency band (4–13 Hz). In contrast, gait freezing was characterized in every patient by low frequency cortical-subthalamic decoupling in the hemisphere with less striatal dopaminergic innervation. Of relevance, this decoupling was already evident at the transition from normal (effective) walking into gait freezing, was maintained during the freezing episode, and resolved with recovery of the effective walking pattern. This is the first evidence for a decoding of the networked processing of locomotion in Parkinson’s disease and suggests that freezing of gait is a ‘circuitopathy’ related to a dysfunctional cortical-subcortical communication. A successful therapeutic approach for gait freezing in Parkinson’s disease should aim at directly targeting derangements of neural network dynamics.

BackgroundIn the evaluation of Stereo-Electroencephalography (SEEG) signals, the physicist’s workflow involves several operations, including determining the position of individual electrode contacts in terms of both relationship to grey or white matter and location in specific brain regions. These operations are (i) generally carried out manually by experts with limited computer support, (ii) hugely time consuming, and (iii) often inaccurate, incomplete, and prone to errors.ResultsIn this paper we present SEEG Assistant, a set of tools integrated in a single 3DSlicer extension, which aims to assist neurosurgeons in the analysis of post-implant structural data and hence aid the neurophysiologist in the interpretation of SEEG data. SEEG Assistant consists of (i) a module to localize the electrode contact positions using imaging data from a thresholded post-implant CT, (ii) a module to determine the most probable cerebral location of the recorded activity, and (iii) a module to compute the Grey Matter Proximity Index, i.e. the distance of each contact from the cerebral cortex, in order to discriminate between white and grey matter location of contacts. Finally, exploiting 3DSlicer capabilities, SEEG Assistant offers a Graphical User Interface that simplifies the interaction between the user and the tools. SEEG Assistant has been tested on 40 patients segmenting 555 electrodes, and it has been used to identify the neuroanatomical loci and to compute the distance to the nearest cerebral cortex for 9626 contacts. We also performed manual segmentation and compared the results between the proposed tool and gold-standard clinical practice. As a result, the use of SEEG Assistant decreases the post implant processing time by more than 2 orders of magnitude, improves the quality of results and decreases, if not eliminates, errors in post implant processing.ConclusionsThe SEEG Assistant Framework for the first time supports physicists by providing a set of open-source tools for post-implant processing of SEEG data. Furthermore, SEEG Assistant has been integrated into 3D Slicer, a software platform for the analysis and visualization of medical images, overcoming limitations of command-line tools.

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Objective. Technical advances in deep brain stimulation (DBS) are crucial to improve therapeutic efficacy and battery life. We report the potentialities and pitfalls of one of the first commercially available devices capable of recording brain local field potentials (LFPs) from the implanted DBS leads, chronically and during stimulation. The aim was to provide clinicians with well-grounded tips on how to maximize the capabilities of this novel device, both in everyday practice and for research purposes. Approach. We collected clinical and neurophysiological data of the first 20 patients (14 with Parkinson’s disease (PD), five with dystonia, one with chronic pain) that received the Percept™ PC in our centres. We also performed tests in a saline bath to validate the recordings quality. Main results. The Percept PC reliably recorded the LFP of the implanted site, wirelessly and in real time. We recorded the most promising clinically useful biomarkers for PD and dystonia (beta and theta oscillations) with and without stimulation. Furthermore, we provide an open-source code to facilitate export and analysis of data. Critical aspects of the system are presently related to contact selection, artefact detection, data loss, and synchronization with other devices. Significance. New technologies will soon allow closed-loop neuromodulation therapies, capable of adapting stimulation based on real-time symptom-specific and task-dependent input signals. However, technical aspects need to be considered to ensure reliable recordings. The critical use by a growing number of DBS experts will alert new users about the currently observed shortcomings and inform on how to overcome them.

Background: Abnormal beta band activity in the subthalamic nucleus (STN) is known to be exaggerated in patients with Parkinson's disease, and the amplitude of such activity has been associated with akinetic rigid symptoms. New devices for deep brain stimulation (DBS) that operate by adapting the stimulation parameters generally rely on the detection of beta activity amplitude modulations in these patients. Movement-related frequency modulation of beta oscillatory activity has been poorly investigated, despite being an attractive variable for extracting information about basal ganglia activity. Objective: We studied the STN oscillatory activity associated with locomotion and proposed a new approach to extract movement related information from beta band activity. Methods: We recorded bilateral local field potential of the STN in eight parkinsonian patients implanted with DBS electrodes during upright quiet standing and unperturbed walking. Neurophysiological recordings were combined with kinematic measurements and individual molecular brain imaging studies. We then determined the information carried by the STN oscillatory activity about locomotion and we identified task-specific biomarkers. Results: We found a gait-related peak frequency modulation of the beta band of STN recordings of parkinsonian patients. This novel biomarker and the associated power modulations were highly informative to detect the walking state (with respect to standing) in each single patient. Conclusion: Frequency modulation in the human STN represents a fundamental aspect of information processing of locomotion. Our information-driven approach could significantly enrich the spectrum of Parkinson's neural markers, with input signals encoding ongoing tasks execution for an appropriate online tuning of DBS delivery.

Recently we found that modulation depth of beta power during movement increases with practice over sensory-motor areas in normal subjects but not in patients with Parkinson's disease (PD). As such changes might reflect use-dependent modifications, we concluded that reduction of beta enhancement in PD represents saturation of cortical plasticity. A few questions remained open: What is the relation between these EEG changes and retention of motor skills? Would a second task exposure restore beta modulation enhancement in PD? Do practice-induced increases of beta modulation occur within each block? We thus recorded EEG in patients with PD and age-matched controls in two consecutive days during a 40-min reaching task divided in fifteen blocks of 56 movements each. The results confirmed that, with practice, beta modulation depth over the contralateral sensory-motor area significantly increased across blocks in controls but not in PD, while performance improved in both groups without significant correlations between behavioral and EEG data. The same changes were seen the following day in both groups. Also, beta modulation increased within each block with similar values in both groups and such increases were partially transferred to the successive block in controls, but not in PD. Retention of performance improvement was present in the controls but not in the patients and correlated with the increase in day 1 modulation depth. Therefore, the lack of practice-related increase beta modulation in PD is likely due to deficient potentiation mechanisms that permit between-block saving of beta power enhancement and trigger mechanisms of memory formation.

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.