Better Electric Signals At Lower Energy Provide Relief from Parkinsonís Disease

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Highlights
  • A new deep brain stimulator that sends electric signals in patterns was designed by a research team from Duke University.
  • The new device aided in lowering energy requirement by 75% and proved effective in treating symptoms of Parkinson's disease as standard devices in trials.
  • If found effective, the device might not require battery replacement for the entire life of a patient with Parkinson's disease.
A method of using supercomputers that 'evolve' better patterns of electric shock which, when delivered deep into the brain, can be used to treat symptoms of Parkinson's. Disease, finds a study from the Duke University.
Better Electric Signals At Lower Energy Provide Relief from Parkinsonís Disease

The newly designed electric patterns can be customized for particular diseases and may also do away with battery replacement procedure that are currently required by many patients.

The technique of deep brain stimulation was initially introduced during the year 1987 and was designed to send electrical signals into the brain of people suffering from neurological symptoms. It is used to treat symptoms such as stiffness, walking problems, tremor as well as slow movement. Deep brain stimulation does not affect the healthy tissue of the brain by destroying neurons but it aids in blocking electrical signals from certain targeted areas of the brain.

Currently, this procedure is used for patients for whom medications do not adequately control the symptoms. In deep brain simulation, a neurostimulator, which is a device similar to that of a pacemaker, is used to deliver specific signals to areas that are associated with controlling movement and block signals that lead to tremor or other Parkinson's disease symptoms.

The exact region of the brain from which the electric nerve signals that trigger symptoms of Parkinson's disease is identified using magnetic resonance imaging (MRI) or by using computer tomography(CT). The neurostimulator is generally implanted into the basal ganglia and many patients have improved motor function.

The research team from Duke University discovered that there were no specific time lapse between electrical signals and that random pattern produced better results. This showed that random passage of electric signals was more significant than non-stop passage of signals. The researchers discovered many different patterns that were effective.

Computer Algorithm

The researchers have developed specific algorithms that can purposefully send electric signals in specific patterns. This aided in reducing the energy of the stimulator by 75% while there was no loss of treatment benefits. The algorithms can also be tailored for individual needs. The study was published in the Journal Translational Medicine.

According to Dr. Warren Grill who is an Edmund T. Pratt Jr. School Professor of Biomedical Engineering, reducing the energy use meant that the primary cells used in the device will last longer. Earlier the batteries had to be replaced with a risk of infection every time they were replaced. The batteries generally lasted only 3 to 5 years and for a patient who received an implant at 50, it would mean several battery replacement procedures over the period of his life.

Evolving Timing Patterns

Dr. Grill and his colleagues devised patterns in timing in which each second was split into 5 segments, which were further divided into 200 segments. One repetition pattern constituted every segment with a millisecond long slice receiving a pulse or a blank. These patterns resulted in one hundred quindecillion possible patterns. The research team utilized computational evolution that was used to identify promising patterns.

The method that was used by Dr. Grill and colleagues were very similar to evolution but it was conducted within the computer. The patterns that were used became better as time passed to cater to the needs of the patient, rather than a fixed set of signals.

Initially the evolutionary algorithm creates 10 patterns of deep brain stimulation and tests these patterns in a computer model of Parkinson's disease. When a pattern performs well it will lead to other patterns. Small variations are included into the patterns to create a highly efficient pattern. The patterns were measured by the algorithm on two counts, effectiveness and efficiency. The computer selected for patterns that utilized minimum energy but produced results just like standard and constant signals.

The number of pulses that each pattern consisted of was 45 pulses per second, which is a drastic reduction from 130-180 that are currently in use. This would save energy by 60 to 75%, doubling or tripling the lifetime of the implanted battery. The results were encouraging when tested on mice and the research team is looking forward to testing on humans.

The current deep brain stimulators cannot deliver the patterns that Dr. Grill and his team designed. Therefore, there were other measures that were included. The team designed their own test devices and in collaboration with neurosurgeons from Duke Health as well as Emory Healthcare in Atlanta, Parkinson's disease patients who visited the hospital for battery replacement were studied. The battery replacement procedure required only local anesthesia, therefore the nerve impulses were still active. When the neurotransmitter device was removed to replace the battery, the devise that was designed by the researchers were tested temporarily.

The device that was designed by the researchers performed as well as the standard device that has been in use for many years. However, the new device required substantially less amount of energy when compared to the currently used device.

The exact mechanism of action of wrong neurological signals triggering symptoms of Parkinson's disease is unknown but the design of this new device would aid in improving the quality of life of patients. Repeated trips to the doctor to change batteries may not be required and further studies about patterns that are effective may provide a better insight into how these signals work.

Reference:
  1. Facts on Deep Brain Stimulation - (http://www.parkinson.org/understanding-parkinsons/treatment/surgery-treatment-options/Deep-Brain-Stimulation)
Source: Medindia

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