New modeling of brain's circuitry may bring better understanding of Parkinson's disease

Sep 27, 2011

Researchers from the School of Science at Indiana University-Purdue University Indianapolis have developed a mathematical model of the brain's neural circuitry that may provide a better understanding of how and why information is not transmitted correctly in the brains of Parkinson's disease patients. This knowledge may eventually help scientists and clinicians correct these misfires.

Work led by Leonid L. Rubchinsky, Ph.D., associate professor of in the School of Science at IUPUI, examines the exchange of within the Parkinson affected brain, demonstrating that repetitious, overlapped firing of neurons can lead to waves of overly synchronized . A report on the model appears in the September 2011 issue of the journal : An Interdisciplinary Journal of Nonlinear Science, a publication of the American Institute of Physics.

"This of the brain's circuitry provides insight that we could not obtain from animal or in experimental or clinical studies. With this new modeling we, and others, can now better study the mechanisms of information transmission in the Parkinsonian brain – both how the mechanisms work and how they fail. We can also learn about the properties of the cells that are responsible. All this knowledge is critical to the eventual development of therapies to correct defective transmissions found in the brains of those with Parkinson's disease," said Rubchinsky, who is affiliated with the Center for Mathematical Modeling and Computational Sciences in the School of Science at IUPUI.

Parkinson's disease is a progressive disorder causing degeneration of neurons in the substantia nigra, a region of the brain which produces the chemical dopamine. Symptoms of Parkinson's disease include tremor, rigidity or stiffness, slowness of movement and impaired balance and coordination. Approximately 60,000 new cases are diagnosed annually in the United States according to the National Institutes of Health. Currently there is no cure for Parkinson's disease.

"Technically we have the tools needed for deep brain stimulation – stimulators, long lasting batteries and implantable chips – but we don't have the algorithms – the formulas and other mathematical tools necessary to know what we are trying to stimulate and how. Our model, and others that will follow, should make deep brain stimulation a feasible therapy for Parkinson's disease within the next decade," said Rubchinsky, who is also a researcher with the Stark Neurosciences Research Institute at the IU School of Medicine.

Explore further: 'Moral victories' might spare you from losing again

Provided by Indiana University-Purdue University Indianapolis School of Science

not rated yet
add to favorites email to friend print save as pdf

Related Stories

Bursting neurons follow the same beat, sometimes

Sep 12, 2011

A simplified mathematical model of the brain's neural circuitry shows that repetitious, overlapped firing of neurons can lead to the waves of overly synchronized brain activity that may cause the halting movements that are ...

Widely used cholesterol-lowering drug may prevent progression

Oct 29, 2009

Simvastatin, a commonly used, cholesterol-lowering drug, may prevent Parkinson's disease from progressing further. Neurological researchers at Rush University Medical Center conducted a study examining the use of the FDA-approved ...

Recommended for you

Affirmative action elicits bias in pro-equality Caucasians

Jul 25, 2014

New research from Simon Fraser University's Beedie School of Business indicates that bias towards the effects of affirmative action exists in not only people opposed to it, but also in those who strongly endorse equality.

Narcissistic CEOs and financial performance

Jul 24, 2014

Narcissism, considered by some as the "dark side of the executive personality," may actually be a good thing when it comes to certain financial measures, with companies led by narcissistic CEOs outperforming those helmed ...

Election surprises tend to erode trust in government

Jul 24, 2014

When asked who is going to win an election, people tend to predict their own candidate will come out on top. When that doesn't happen, according to a new study from the University of Georgia, these "surprised losers" often ...

User comments : 0