scholarly journals Parkinsonism and vigilance: alteration in neural oscillatory activity and phase-amplitude coupling in the basal ganglia and motor cortex

2017 ◽  
Vol 118 (5) ◽  
pp. 2654-2669 ◽  
Author(s):  
David Escobar Sanabria ◽  
Luke A. Johnson ◽  
Shane D. Nebeck ◽  
Jianyu Zhang ◽  
Matthew D. Johnson ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Basal Ganglia ◽  
Neural Activity ◽  
High Frequency ◽  
Closed Loop ◽  
Oscillatory Activity ◽  
Motor Circuit ◽  
Phase Amplitude ◽  
Frequency Power

Oscillatory neural activity in different frequency bands and phase-amplitude coupling (PAC) are hypothesized to be biomarkers of Parkinson’s disease (PD) that could explain dysfunction in the motor circuit and be used for closed-loop deep brain stimulation (DBS). How these putative biomarkers change from the normal to the parkinsonian state across nodes in the motor circuit and within the same subject, however, remains unknown. In this study, we characterized how parkinsonism and vigilance altered oscillatory activity and PAC within the primary motor cortex (M1), subthalamic nucleus (STN), and globus pallidus (GP) in two nonhuman primates. Static and dynamic analyses of local field potential (LFP) recordings indicate that 1) after induction of parkinsonism using the neurotoxin MPTP, low-frequency power (8–30 Hz) increased in the STN and GP in both subjects, but increased in M1 in only one subject; 2) high-frequency power (~330 Hz) was present in the STN in both normal subjects but absent in the parkinsonian condition; 3) elevated PAC measurements emerged in the parkinsonian condition in both animals, but in different sites in each animal (M1 in one subject and GPe in the other); and 4) the state of vigilance significantly impacted how oscillatory activity and PAC were expressed in the motor circuit. These results support the hypothesis that changes in low- and high-frequency oscillatory activity and PAC are features of parkinsonian pathophysiology and provide evidence that closed-loop DBS systems based on these biomarkers may require subject-specific configurations as well as adaptation to changes in vigilance. NEW & NOTEWORTHY Chronically implanted electrodes were used to record neural activity across multiple nodes in the basal ganglia-thalamocortical circuit simultaneously in a nonhuman primate model of Parkinson’s disease, enabling within-subject comparisons of electrophysiological biomarkers between normal and parkinsonian conditions and different vigilance states. This study improves our understanding of the role of oscillatory activity and phase-amplitude coupling in the pathophysiology of Parkinson’s disease and supports the development of more effective DBS therapies based on pathophysiological biomarkers.

scholarly journals The dynamic of basal ganglia activity with a multiple covariance method: influences of Parkinson’s disease

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Clara Rodriguez-Sabate ◽  
Ingrid Morales ◽  
Ricardo Puertas-Avendaño ◽  
Manuel Rodriguez
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Basal Ganglia ◽  
Closed Loop ◽  
Clinical Manifestations ◽  
Motor Disorders ◽  
Loop Model ◽  
Functional Profile ◽  
Motor Circuit ◽  
Profile Method

Abstract The closed-loop cortico-subcortical pathways of basal ganglia have been extensively used to describe the physiology of these centres and to justify the functional disorders of basal ganglia diseases. This approach justifies some experimental and clinical data but not others, and furthermore, it does not include a number of subcortical circuits that may produce a more complex basal ganglia dynamic than that expected for closed-loop linear networks. This work studied the functional connectivity of the main regions of the basal ganglia motor circuit with magnetic resonance imaging and a new method (functional profile method), which can analyse the multiple covariant activity of human basal ganglia. The functional profile method identified the most frequent covariant functional status (profiles) of the basal ganglia motor circuit, ordering them according to their relative frequency and identifying the most frequent successions between profiles (profile transitions). The functional profile method classified profiles as input profiles that accept the information coming from other networks, output profiles involved in the output of processed information to other networks and highly interconnected internal profiles that accept transitions from input profiles and send transitions to output profiles. Profile transitions showed a previously unobserved functional dynamic of human basal ganglia, suggesting that the basal ganglia motor circuit may work as a dynamic multiple covariance network. The number of internal profiles and internal transitions showed a striking decrease in patients with Parkinson’s disease, a fact not observed for input and output profiles. This suggests that basal ganglia of patients with Parkinson’s disease respond to requirements coming from other neuronal networks, but because the internal processing of information is drastically weakened, its response will be insufficient and perhaps also self-defeating. These marked effects were found in patients with few motor disorders, suggesting that the functional profile method may be an early procedure to detect the first stages of the Parkinson’s disease when the motor disorders are not very evident. The multiple covariance activity found presents a complementary point of view to the cortico-subcortical closed-loop model of basal ganglia. The functional profile method may be easily applied to other brain networks, and it may provide additional explanations for the clinical manifestations of other basal ganglia disorders.

scholarly journals Rapid Motor Fluctuations Reveal Short-Timescale Neurophysiological Biomarkers of Parkinson’s Disease

2020 ◽  
Author(s):  
Minkyu Ahn ◽  
Shane Lee ◽  
Peter M. Lauro ◽  
Erin L. Schaeffer ◽  
Umer Akbar ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Neural Activity ◽  
Motor Performance ◽  
Closed Loop ◽  
Oscillatory Activity ◽  
Patient Specific ◽  
Significant Information ◽  
Informative Signal ◽  
Wide Range

ABSTRACTIdentifying neural activity biomarkers of brain disease is essential to provide objective estimates of disease burden, obtain reliable feedback regarding therapeutic efficacy, and potentially to serve as a source of control for closed-loop neuromodulation. In Parkinson’s Disease (PD), microelectrode recordings (MER) are routinely performed in the basal ganglia to guide electrode implantation for deep brain stimulation (DBS). While pathologically-excessive oscillatory activity has been observed and linked to PD motor dysfunction broadly, the extent to which these signals provide quantitative information about disease expression and fluctuations, particularly at short timescales, is unknown. Furthermore, the degree to which informative signal features are similar or different across patients has not been rigorously investigated. Here, we recorded neural activity from the subthalamic nucleus (STN) of patients with PD undergoing awake DBS surgery while they performed an objective, continuous behavioral assessment. This approach leveraged natural motor performance variations as a basis to identify corresponding neurophysiological biomarkers. Using machine learning techniques, we show it was possible to use neural signals from the STN to decode the level of motor impairment at short timescales (as short as one second). Spectral power across a wide range of frequencies, beyond the classic “β” oscillations, contributed to this decoding. While signals providing significant information about the quality of motor performance were found throughout the STN, the most informative signals tended to arise from locations in or near the dorsolateral, sensorimotor portion. Importantly, the informative patterns of neural oscillations were not fully generalizable across subjects, suggesting a patient-specific approach will be critical for optimal disease tracking and closed-loop neuromodulation.

scholarly journals A dynamical model for the basal ganglia-thalamo-cortical oscillatory activity and its implications in Parkinson’s disease

2020 ◽  
Author(s):  
Eva M. Navarro-López ◽  
Utku Çelikok ◽  
Neslihan S. Şengör
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Basal Ganglia ◽  
Activity Patterns ◽  
Dynamical Model ◽  
Substantia Nigra Pars Compacta ◽  
Oscillatory Activity ◽  
Subcortical Structures ◽  
Neuron Models ◽  
Neuronal Patterns

AbstractWe propose to investigate brain electrophysiological alterations associated with Parkinson’s disease through a novel adaptive dynamical model of the network of the basal ganglia, the cortex and the thalamus. The model uniquely unifies the influence of dopamine in the regulation of the activity of all basal ganglia nuclei, the self-organised neuronal interdependent activity of basal ganglia-thalamo-cortical circuits and the generation of subcortical background oscillations. Variations in the amount of dopamine produced in the neurons of the substantia nigra pars compacta are key both in the onset of Parkinson’s disease and in the basal ganglia action selection. We model these dopamine-induced relationships, and Parkinsonian states are interpreted as spontaneous emergent behaviours associated with different rhythms of oscillatory activity patterns of the basal ganglia-thalamo-cortical network. These results are significant because: (1) the neural populations are built upon single-neuron models that have been robustly designed to have eletrophysiologically-realistic responses, and (2) our model distinctively links changes in the oscillatory activity in subcortical structures, dopamine levels in the basal ganglia and pathological synchronisation neuronal patterns compatible with Parkinsonian states, this still remains an open problem and is crucial to better understand the progression of the disease.

The Basal Ganglia and Disorders of Movement: Pathophysiological Mechanisms

Physiology ◽  
2002 ◽  
Vol 17 (2) ◽  
pp. 51-55 ◽  
Author(s):  
José A. Obeso ◽  
María C. Rodríguez-Oroz ◽  
Manuel Rodríguez ◽  
Javier Arbizu ◽  
José M. Giménez-Amaya
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Basal Ganglia ◽  
Neuronal Network ◽  
Motor Circuit ◽  
Pathophysiological Mechanisms ◽  
Parallel Circuits

The basal ganglia are part of a neuronal network organized in parallel circuits. The “motor circuit” is most relevant to the pathophysiology of movement. Abnormal increment or reduction in the inhibitory output activity of basal ganglia give rise, respectively, to poverty and slowness of movement (i.e., Parkinson's disease) or dyskinesias.

scholarly journals Oscillatory activity in basal ganglia and motor cortex in an awake behaving rodent model of Parkinson's disease

Basal Ganglia ◽  
2014 ◽  
Vol 3 (4) ◽  
pp. 221-227 ◽  
Author(s):  
Claire Delaville ◽  
Ana V. Cruz ◽  
Alex J. McCoy ◽  
Elena Brazhnik ◽  
Irene Avila ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Basal Ganglia ◽  
Motor Cortex ◽  
Rodent Model ◽  
Oscillatory Activity

14 Pathological oscillatory activity in Parkinson’s disease; what does it mean and how should we treat it?

2020 ◽  
Vol 91 (8) ◽  
pp. e6.1-e6
Author(s):  
Peter Brown
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Deep Brain Stimulation ◽  
Basal Ganglia ◽  
Side Effects ◽  
Brain Stimulation ◽  
Neural Circuit ◽  
Symptom Control ◽  
Oscillatory Activity ◽  
Deep Brain

Professor Peter Brown is Professor of Experimental Neurology and Director of the Medical Research Council Brain Network Dynamics Unit at the University of Oxford. Prior to 2010 he was a Professor of Neurology at University College London.For decades we have had cardiac pacemakers that adjust their pacing according to demand and yet therapeutic adaptive stimulation approaches for the central nervous system are still not clinically available. Instead, to treat patients with advanced Parkinson’s disease we stimulate the basal ganglia with fixed regimes, unvarying in frequency or intensity. Although effective, this comes with side-effects and in terms of sophistication this treatment approach could be compared to having central heating system on all the time, regardless of temperature. This talk will describe recent steps being taken to define the underlying circuit dysfunction in Parkinson’s and to improve deep brain stimulation by controlling its delivery according to the state of pathological activity.Evidence is growing that motor symptoms in Parkinson’s disease are due, at least in part, to excessive synchronisation between oscillating neurons. Recordings confirm bursts of oscillatory synchronisation in the basal ganglia centred around 20 Hz. The bursts of 20 Hz activity are prolonged in patients withdrawn from their usual medication and the dominance of these long duration bursts negatively correlates with motor impairment. Longer bursts attain higher amplitudes, indicative of more pervasive oscillatory synchronisation within the neural circuit. In contrast, in heathy primates and in treated Parkinson’s disease bursts tend to be short. Accordingly, it might be best to use closed-loop controlled deep brain stimulation to selectively terminate longer, bigger, pathological beta bursts to both save power and to spare the ability of underlying neural circuits to engage in more physiological processing between long bursts. It is now possible to record and characterise bursts on-line during stimulation of the same site and trial adaptive stimulation. Thus far, this has demonstrated improvements in efficiency and side-effects over conventional continuous stimulation, with at least as good symptom control in Parkinsonian patients.

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