New article published in Cerebral Cortex: Motor control and pain processing in midcingulate cortex

Misra and Coombes

Human neuroimaging and virus-tracing studies in monkey predict that motor control and pain processes should overlap in anterior midcingulate cortex (aMCC), but there is currently no direct evidence that this is the case. We used a novel functional magnetic resonance imaging paradigm to examine brain activity while subjects performed a motor control task, experienced a pain-eliciting stimulus on their hand, and performed the motor control task while also experiencing the pain-eliciting stimulus. Our experiment produced 3 novel results. First, group-level analyses showed that when separate trials of motor control and pain processing were performed, overlapping functional activity was found in the same regions of aMCC, supplementary motor area (SMA), anterior insula, and putamen. Secondly, increased activity was found in the aMCC and SMA when motor control and pain processing occurred simultaneously. Thirdly, individual-level analyses showed that 93% of subjects engaged the same region of aMCC during separate trials of motor control and pain processing irrespective of differences in the sulcal/gyral morphology of the cingulate cortex across individuals. These observations provide direct evidence in humans that the same region of aMCC is engaged for motor control and pain processing.

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Dana Foundation Highlights Biomarkers for Parkinson’s Disease

Work from our laboratory was highlighted by the Dana Foundation

Read more about the article by Carl Sherman:

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Review describes evidence for dopamine overdose hypothesis

Movement Disorders
Dopamine overdose hypothesis: Evidence and clinical implications.
Vaillancourt DE, Schonfeld D, Kwak Y, Bohnen NI, Seidler R.

About a half a century has passed since dopamine was identified as a neurotransmitter, and it has been several decades since it was established that people with Parkinson’s disease receive motor symptom relief from oral levodopa. Despite the evidence that levodopa can reduce motor symptoms, there has been a developing body of literature that dopaminergic therapy can improve cognitive functions in some patients but make them worse in others. Over the past two decades, several laboratories have shown that dopaminergic medications can impair the action of intact neural structures and impair the behaviors associated with these structures. In this review, we consider the evidence that has accumulated in the areas of reversal learning, motor sequence learning, and other cognitive tasks. The purported inverted-U shaped relationship between dopamine levels and performance is complex and includes many contributory factors. The regional striatal topography of nigrostriatal denervation is a critical factor, as supported by multimodal neuroimaging studies. A patient’s individual genotype will determine the relative baseline position on this inverted-U curve. Dopaminergic pharmacotherapy and individual gene polymorphisms can affect the mesolimbic and prefrontal cortical dopaminergic functions in a comparable, inverted-U dose-response relationship. Depending on these factors, a patient can respond positively or negatively to levodopa when performing reversal learning and motor sequence learning tasks. These tasks may continue to be relevant as our society moves to increased technological demands of a digital world that requires newly learned motor sequences and adaptive behaviors to manage daily life activities.

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New article shows that acute exercise reduces pain perception

Effects of a Force Production Task and a Working Memory Task on Pain Perception

Tiffany A. Paris, Gaurav Misra, Derek B. Archer, Stephen A. Coombes

The goal in the current study was to examine the analgesic effects of a pinch grip-force production task and a working memory task when pain-eliciting thermal stimulation was delivered simultaneously to the left or right hand during task performance. Control conditions for visual distraction and thermal stimulation were included, and force performance measures and working memory performance measures were collected and analyzed. Our experiments revealed 3 novel findings. First, we showed that accurate isometric force contractions elicit an analgesic effect when pain-eliciting thermal stimulation was delivered during task performance. Second, the magnitude of the analgesic effect was not different when the pain-eliciting stimulus was delivered to the left or right hand during the force task or the working memory task. Third, we found no correlation between analgesia scores during the force task and the working memory task. Our findings have clinical implications for rehabilitation settings because they suggest that acute force production by one limb influences pain perception that is simultaneously experienced in another limb. From a theoretical perspective, we interpret our findings on force and memory driven analgesia in the context of a centralized pain inhibitory response.

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Review: Diffusion MRI, DTI, and Movement Disorders

Curr Neurol Neurosci Rep. 2013 Nov;13(11):400. doi: 10.1007/s11910-013-0400-1.

The evolving role of diffusion magnetic resonance imaging in movement disorders.
Hess CW, Ofori E, Akbar U, Okun MS, Vaillancourt DE.

Significant advances have allowed diffusion magnetic resonance imaging (MRI) to evolve into a powerful tool in the field of movement disorders that can be used to study disease states and connectivity between brain regions. Diffusion MRI is a promising potential biomarker for Parkinson’s disease and other forms of parkinsonism, and may allow the distinction of different forms of parkinsonism. Techniques such as tractography have contributed to our current thinking regarding the pathophysiology of dystonia and possible mechanisms of penetrance. Diffusion MRI measures could potentially assist in monitoring disease progression in Huntington’s disease, and in uncovering the nature of the processes and structures involved the development of essential tremor. The ability to represent structural connectivity in vivo also makes diffusion MRI an ideal adjunctive tool for the surgical treatment of movement disorders. We review recent studies using diffusion MRI in movement disorders research and present the current state of the science as well as future directions.

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REM sleep problems linked with freezing of gait in Parkinson’s disease

Neurology. 2013 Aug 14. [Epub ahead of print]
Increased REM sleep without atonia in Parkinson disease with freezing of gait.
Videnovic A, Marlin C, Alibiglou L, Planetta PJ, Vaillancourt DE, Mackinnon CD.

The objective of this cross-sectional study was to test the hypothesis that patients with Parkinson disease (PD) and freezing of gait (PD+FOG) would demonstrate sleep disturbances comparable to those seen in patients with REM sleep behavior disorder (RBD) and these changes would be significantly different from those in PD patients without FOG (PD-FOG) and age-matched controls.
We conducted overnight polysomnography studies in 4 groups of subjects: RBD, PD-FOG, PD+FOG, and controls. Tonic and phasic muscle activity during REM sleep were quantified using EMG recordings from the chin, compared among study groups, and correlated with disease metrics.
There were no significant differences in measures of disease severity, duration, or dopaminergic medications between the PD+FOG and PD-FOG groups. Tonic muscle activity was increased significantly (p < 0.007) in the RBD and PD+FOG groups compared to the PD-FOG and control groups. There was no significant difference in tonic EMG between the PD+FOG and RBD group (p = 0.364), or in tonic or phasic EMG between the PD-FOG and control group (p = 0.107). Phasic muscle activity was significantly increased in the RBD group compared to all other groups (p = 0.029) and between the PD+FOG and control group (p = 0.001), but not between the PD+FOG and PD-FOG groups (p = 0.059). CONCLUSIONS: These findings provide evidence that increased muscle activity during REM sleep is a comorbid feature of patients with PD who exhibit FOG as a motor manifestation of their disease.

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New article published on Parkinson’s disease, atypical parkinsonism, and essential tremor

Mov Disord. 2013 May 14. doi: 10.1002/mds.25491. [Epub ahead of print]
Diffusion tensor imaging of Parkinson’s disease, atypical parkinsonism, and essential tremor.
Prodoehl J, Li H, Planetta PJ, Goetz CG, Shannon KM, Tangonan R, Comella CL, Simuni T, Zhou XJ, Leurgans S, Corcos DM, Vaillancourt DE.

Diffusion tensor imaging could be useful in characterizing movement disorders because it noninvasively examines multiple brain regions simultaneously. We report a multitarget imaging approach focused on the basal ganglia and cerebellum in Parkinson’s disease, parkinsonian variant of multiple system atrophy, progressive supranuclear palsy, and essential tremor and in healthy controls. Seventy-two subjects were studied with a diffusion tensor imaging protocol at 3 Tesla. Receiver operating characteristic analysis was performed to directly compare groups. Sensitivity and specificity values were quantified for control versus movement disorder (92% sensitivity, 88% specificity), control versus parkinsonism (93% sensitivity, 91% specificity), Parkinson’s disease versus atypical parkinsonism (90% sensitivity, 100% specificity), Parkinson’s disease versus multiple system atrophy (94% sensitivity, 100% specificity), Parkinson’s disease versus progressive supranuclear palsy (87% sensitivity, 100% specificity), multiple system atrophy versus progressive supranuclear palsy (90% sensitivity, 100% specificity), and Parkinson’s disease versus essential tremor (92% sensitivity, 87% specificity). The brain targets varied for each comparison, but the substantia nigra, putamen, caudate, and middle cerebellar peduncle were the most frequently selected brain regions across classifications. These results indicate that using diffusion tensor imaging of the basal ganglia and cerebellum accurately classifies subjects diagnosed with Parkinson’s disease, atypical parkinsonism, and essential tremor and clearly distinguishes them from control subjects. © 2013 Movement Disorder Society.

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UF study finds brain-imaging technique can help diagnose movement disorders

GAINESVILLE, Fla. — A new University of Florida study suggests a promising brain-imaging technique has the potential to improve diagnoses for the millions of people with movement disorders such as Parkinson’s disease.

Utilizing the diffusion tensor imaging technique, as it is known, could allow clinicians to assess people earlier, leading to improved treatment interventions and therapies for patients.

The three-year study looked at 72 patients, each with a clinically defined movement disorder diagnosis. Using a technique called diffusion tensor imaging, the researchers successfully separated the patients into disorder groups with a high degree of accuracy.

The study is being published in the journal Movement Disorders.

“The purpose of this study is to identify markers in the brain that differentiate movement disorders which have clinical symptoms that overlap, making [the disorders] difficult to distinguish,” said David Vaillancourt, associate professor in the department of applied physiology and kinesiology and the study’s principal investigator.

“No other imaging, cerebrospinal fluid or blood marker has been this successful at differentiating these disorders,” he said. “The results are very promising.”

Movement disorders such as Parkinson’s disease, essential tremor, multiple system atrophy and progressive supranuclear palsy exhibit similar symptoms in the early stages, which can make it challenging to assign a specific diagnosis. Often, the original diagnosis changes as the disease progresses, Vaillancourt said.

Diffusion tensor imaging, known as DTI, is a non-invasive method that examines the diffusion of water molecules within the brain and can identify key areas that have been affected as a result of damage to gray matter and white matter in the brain. Vaillancourt and his team measured areas of the basal ganglia and cerebellum in individuals, and used a statistical approach to predict group classification. By asking different questions within the data and comparing different groups to one another, they were able to show distinct separation among disorders.

“Our goal was to use these measures to accurately predict the original disease classification,” Vaillancourt said. “The idea being that if a new patient came in with an unknown diagnosis, you might be able to apply this algorithm to that individual.

He compared the process to a cholesterol test.

“If you have high cholesterol, it raises your chances of developing heart disease in the future,” he said. “There are tests like those that give a probability or likelihood scenario of a particular disease group. We’re going a step further and trying to utilize information to predict the classification of specific tremor and Parkinsonian diseases.”

Vaillancourt and his team are part of the National Institute of Neurological Disorders and Stroke Parkinson’s Disease Biomarkers Program, an effort that was launched in 2012 and awarded nine grants to scientists across the U.S., totaling more than $5 million in the first year. The program gives researchers access to a much broader community of individuals and patients as part of a biomarker initiative for Parkinson’s disease.

Vaillancourt’s team is engaged in a longitudinal study at UF that will assess between 150 and 180 people over the next few years. His team will be using DTI as well as other MRI-based techniques to classify subjects and track their progression, he said.

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People with Parkinson’s with Tremors Show Different Brain Activity Than Those Without Tremors

Science News:
People with Parkinson’s with Tremors Show Different Brain Activity Than Those Without Tremors

People with Parkinson’s disease (PD) who experience tremor of the hand or leg show different brain activity than people without tremors, according to a report in the January 2013 issue of the Journal of the American Medical Association Neurology. These differences, revealed by brain scans with functional magnetic resonance imaging (fMRI), point to pathologically distinct forms of Parkinson’s disease.

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Exercise & Parkinson’s disease paper accepted in Movement Disorders

Mov Disord. 2013 Mar 27. doi: 10.1002/mds.25380. [Epub ahead of print]

A two-year randomized controlled trial of progressive resistance exercise for Parkinson’s disease.

Corcos DM, Robichaud JA, David FJ, Leurgans SE, Vaillancourt DE, Poon C, Rafferty MR, Kohrt WM, Comella CL.

The effects of progressive resistance exercise (PRE) on the motor signs of Parkinson’s disease have not been studied in controlled trials. The objective of the current trial was to compare 6-, 12-, 18-, and 24-month outcomes of patients with Parkinson’s disease who received PRE with a stretching, balance, and strengthening exercise program. The authors conducted a randomized controlled trial between September 2007 and July 2011. Pairs of patients matched by sex and off-medication scores on the Unified Parkinson’s Disease Rating Scale, motor subscale (UPDRS-III), were randomly assigned to the interventions with a 1:1 allocation ratio. The PRE group performed a weight-lifting program. The modified fitness counts (mFC) group performed a stretching, balance, and strengthening exercise program. Patients exercised 2 days per week for 24 months at a gym. A personal trainer directed both weekly sessions for the first 6 months and 1 weekly session after 6 months. The primary outcome was the off-medication UPDRS-III score. Patients were followed for 24 months at 6-month intervals. Of 51 patients, 20 in the PRE group and 18 in the mFC group completed the trial. At 24 months, the mean off-medication UPDRS-III score decreased more with PRE than with mFC (mean difference, -7.3 points; 95% confidence interval, -11.3 to -3.6; P<0.001). The PRE group had 10 adverse events, and the mFC group had 7 adverse events. PRE demonstrated a statistically and clinically significant reduction in UPDRS-III scores compared with mFC and is recommended as a useful adjunct therapy to improve Parkinsonian motor signs. © 2013 Movement Disorder Society. Link :

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