Impaired auditory-to-motor entrainment in Parkinson’s disease

Several electrophysiological studies suggest that Parkinson's disease (PD) patients have a reduced tendency to entrain to regular environmental patterns. Here we investigate whether this reduced entrainment concerns a generalized deficit or is confined to movement-related activity, leaving sensory entrainment intact. Magnetoencephalography was recorded during a rhythmic auditory target detection task in 14 PD patients and 14 control subjects. Participants were instructed to press a button when hearing a target tone amid an isochronous sequence of standard tones. The variable pitch of standard tones indicated the probability of the next tone to be a target. In addition, targets were occasionally omitted to evaluate entrainment uncontaminated by stimulus effects. Response times were not significantly different between groups and both groups benefited equally from the predictive value of standard tones. Analyses of oscillatory beta power over auditory cortices showed equal entrainment to the tones in both groups. By contrast, oscillatory beta power and event-related fields demonstrated a reduced engagement of motor cortical areas in PD patients, expressed in the modulation depth of beta power, in the response to omitted stimuli, and in an absent motor area P300 effect. Together, these results show equally strong entrainment of neural activity over sensory areas in controls and patients, but, in patients, a deficient translation of the adjustment to the task rhythm to motor circuits. We suggest that the reduced activation reflects not merely altered resonance to rhythmic external events, but a compromised recruitment of an endogenous response reflecting internal rhythm generation. NEW & NOTEWORTHY Previous studies suggest that motor cortical activity in PD patients has a reduced tendency to entrain to regular environmental patterns. This study demonstrates that the deficient entrainment in PD concerns the motor system only, by showing equally strong entrainment of neural activity over sensory areas in controls and patients but, in patients, a deficient translation of this adjustment to the task rhythm to motor circuits.

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Disruption of cortical dopaminergic modulation impairs preparatory activity and delays licking initiation

10.1101/337014 ◽

2018 ◽

Author(s):

Ke Chen ◽

Roberto Vincis ◽

Alfredo Fontanini

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Motor Cortex ◽

Neural Activity ◽

Cortical Activity ◽

Motor Deficits ◽

Receptor Modulation ◽

Dopaminergic Modulation ◽

Preparatory Activity ◽

Motor Cortical

ABSTRACTDysfunction of motor cortices is thought to contribute to motor disorders such as Parkinson’s disease (PD). However, little is known on the link between cortical dopaminergic loss, abnormalities in motor cortex neural activity and motor deficits. We address the role of dopamine in modulating motor cortical activity by focusing on the anterior lateral motor cortex (ALM) of mice performing a cued-licking task. We first demonstrate licking deficits and concurrent alterations of spiking activity in ALM of mice with unilateral depletion of dopaminergic neurons (i.e., mice injected with 6-OHDA into the medial forebrain bundle). Hemi-lesioned mice displayed delayed licking initiation, shorter duration of licking bouts, and lateral deviation of tongue protrusions. In parallel with these motor deficits, we observed a reduction in the prevalence of cue responsive neurons and altered preparatory activity. Acute and local blockade of D1 receptors in ALM recapitulated some of the key behavioral and neural deficits observed in hemi-lesioned mice. Altogether, our data show a direct relationship between cortical D1 receptor modulation, cue-evoked and preparatory activity in ALM, and licking initiation.SIGNIFICANCE STATEMENTThe link between dopaminergic signaling, motor cortical activity and motor deficits is not fully understood. This manuscript describes alterations in neural activity of the anterior lateral motor cortex (ALM) that correlate with licking deficits in mice with unilateral dopamine depletion or with intra-ALM infusion of dopamine antagonist. The findings emphasize the importance of cortical dopaminergic modulation in motor initiation. These results will appeal not only to researchers interested in cortical control of licking, but also to a broader audience interested in motor control and dopaminergic modulation in physiological and pathological conditions. Specifically, our data suggest that dopamine deficiency in motor cortex could play a role in the pathogenesis of the motor symptoms of Parkinson’s disease.

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Pathological Beta Burst Dynamics are Conserved Across Different Movements in Parkinson’s Disease

10.1101/2020.04.12.20063032 ◽

2020 ◽

Cited By ~ 1

Author(s):

Raumin S. Neuville ◽

Ross. W. Anderson ◽

Matthew N. Petrucci ◽

Jordan E. Parker ◽

Kevin B. Wilkins ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Deep Brain Stimulation ◽

Neural Activity ◽

Resting State ◽

Closed Loop ◽

Peak Frequency ◽

Beta Band ◽

Beta Power ◽

Deep Brain

AbstractBackgroundResting state beta band (13 – 30 Hz) oscillations represent pathological neural activity in Parkinson’s disease (PD). It is unknown whether the peak frequency or dynamics of beta oscillations change among rest, fine, limb and axial movements. This will be critical for the development and feasibility of closed loop deep brain stimulation (DBS) algorithms during resting and movement states.MethodsSubthalamic (STN) local field potentials (LFPs) were recorded from a sensing neurostimulator (Activa® PC+S, Medtronic Inc.,) and synchronized to kinematic recordings in twelve PD participants off medication/off STN DBS during thirty seconds of repetitive alternating finger tapping, wrist-flexion extension, stepping in place, and free walking. Beta power peaks and beta burst dynamics were identified by custom algorithms; beta burst dynamics were compared among rest and movement tasks.ResultsResting state burst durations were longer in a PD beta band, which was elevated above the 1/f physiological spectrum compared to an overlapping band (p < 0.001). Beta power peaks were evident during fine, limb, and axial movements in 98% of movement trials; the peak frequencies were similar during movements and at rest. Burst duration, average and peak power were also similar among the four movement tasks across the group but varied within individuals.ConclusionsProlonged burst durations were a feature of PD bands elevated above and not of PD bands overlapping the 1/f spectrum. The conservation of rest/movement band peak frequency and burst dynamics during different activity states supports the feasibility of successful closed loop DBS algorithms driven by beta burst dynamics during different activities and at rest.HighlightsProlonged beta burst durations represent pathological neural activity in Parkinson’s diseaseBeta band peak frequencies are similar across rest, fine, limb and axial movementsBeta burst dynamics are similar among rest and different movement statesConservation of Parkinsonian neural characteristics across different activity states supports the feasibility of closed loop deep brain stimulation systems in daily life

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Different features of the cortical sensorimotor rhythms are uniquely linked to the severity of specific symptoms in Parkinson's disease

10.1101/2021.06.27.21259592 ◽

2021 ◽

Author(s):

Mikkel C. Vinding ◽

Allison Eriksson ◽

Cassia Low Man Ting ◽

Josefine Waldthaler ◽

Daniel Ferreira ◽

...

Keyword(s):

Parkinson’S Disease ◽

Time Series ◽

Parkinson's Disease ◽

Neural Activity ◽

Full Range ◽

Alpha Power ◽

Motor Symptoms ◽

Healthy Controls ◽

Functional Changes ◽

Beta Power

Parkinson's disease (PD) is associated with functional changes in the neural activity within the brain's sensorimotor network, which in turn are related to the characteristic motor symptoms in PD. The functional changes in PD are particularly prominent in terms of oscillatory neuronal activity in the characteristic sensorimotor alpha and beta rhythms. However, summaries in terms of alpha or beta power do not capture the full range of the complex dynamic nature of the signals from the somatosensory cortex. This raises the question of how to quantify and summarise the functional changes in such oscillatory features in a manner that captures the relevant disease- and symptom-related neural activity. We investigated the role of spontaneous cortical somatosensory activity in the electrophysiological alpha and beta bands among a cohort of early- to mid-stage PD patients (N=78) and age- and gender-matched healthy controls (N=60) using source reconstructed resting-state magnetoencephalography (MEG) recordings. We quantified the oscillatory features of the neural time series by its oscillatory alpha power, beta power, and 1/f broadband characteristics using power spectral density, and additionally by characterising "burst" properties in the signals. We examined the relationship between the signal features and disease state, age, sex, and cortical thickness. Using multiple regression, we examined the relative contribution of the oscillatory features on the clinical manifestation of motor symptoms in the PD group. Our results show that PD patients differ from healthy controls on several of the oscillatory features, showing higher beta-band power, higher burst amplitude, and steeper 1/f broadband characteristics compared to healthy controls, as well as a steeper age-related decrease in the bursts rate. While there was a high degree of correlation between some of the oscillatory features, several features also appeared functionally separated, showing independent feature-to-symptom relationships. For instance, oscillatory beta power increased with the severity of midline function symptoms, while burst rate decreased with the severity of bradykinesia. Our study shows that quantification of distinct features within the oscillatory sensorimotor neural time series in PD captures different underlying mechanisms related to disease progression and symptom severity, which in turn has a potential for a more individualised and precision-based approach to assessing functional neural changes in PD.

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Faculty Opinions recommendation of Motor-cortical oscillations in early stages of Parkinson's disease.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.717971066.793469425 ◽

2013 ◽

Author(s):

Peter Brown

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Early Stages ◽

Cortical Oscillations ◽

Motor Cortical

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S13-1 The motor cortical plasticity and neurorehabilitation in Parkinson’s disease

Clinical Neurophysiology ◽

10.1016/j.clinph.2020.04.087 ◽

2020 ◽

Vol 131 (10) ◽

pp. e250-e251

Author(s):

Yoshino Ueki

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Cortical Plasticity ◽

Motor Cortical

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Individual Magnetoencephalography Response Profiles to Short-Duration L-Dopa in Parkinson’s Disease

Frontiers in Human Neuroscience ◽

10.3389/fnhum.2021.640591 ◽

2021 ◽

Vol 15 ◽

Author(s):

Edgar Peña ◽

Tareq M. Mohammad ◽

Fedaa Almohammed ◽

Tahani AlOtaibi ◽

Shahpar Nahrir ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Short Duration ◽

Spectral Power ◽

Clinical State ◽

Support Vector ◽

Learning Approaches ◽

Factor Scores ◽

Subject Specific ◽

Motor Cortical

Clinical responses to dopamine replacement therapy for individuals with Parkinson’s disease (PD) are often difficult to predict. We characterized changes in MDS-UPDRS motor factor scores resulting from a short-duration L-Dopa response (SDR), and investigated how the inter-subject clinical differences could be predicted from motor cortical magnetoencephalography (MEG). MDS-UPDRS motor factor scores and resting-state MEG recordings were collected during SDR from twenty individuals with a PD diagnosis. We used a novel subject-specific strategy based on linear support vector machines to quantify motor cortical oscillatory frequency profiles that best predicted medication state. Motor cortical profiles differed substantially across individuals and showed consistency across multiple data folds. There was a linear relationship between classification accuracy and SDR of lower limb bradykinesia, although this relationship did not persist after multiple comparison correction, suggesting that combinations of spectral power features alone are insufficient to predict clinical state. Factor score analysis of therapeutic response and novel subject-specific machine learning approaches based on subject-specific neuroimaging provide tools to predict outcomes of therapies for PD.

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