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Sample Project: Development of a 'Smart' Deep Brain Stimulator

Overview

Deep brain stimulation (DBS) is used to treat Parkinson's Disease. Electrodes are surgically placed in the subthalamic nuclei of each patient, and continuous ~180 Hz electrical stimulation is delivered to this part of the brain. Symptoms of Parkinson's Disease are often dramatically improved (less tremor, stiffness and difficulty initiating movements). But no one knows how the therapy works. We believe that the stimulation releases neurotransmitters, glutamate within the subthalamic nucleus and dopamine at more distant sites in the motor control circuit. A self-sufficient brain machine interface that could sense changes in the neural environment (i.e. neurotransmitter levels) in its vicinity and accordingly direct electrical pulses of the correct amplitude and frequency through microelectrodes to a specific location in the subthalamic nucleus would create closed loop control of the stimulator and improve Parkinson's disease treatment and reduce DBS side effects. However, it is not clear which neurotransmitter is best to use as the feedback signal in a smart DBS system.

We believe that DBS causes glutamate release in the subthalamic nucleus and probably in the substantia nigra (where dopaminergic neurons reside), and that glutamate release, in turn, triggers the production of more dopamine, 'resetting' the motor control structures in the brain. To design DBS control algorithms, an understanding of glutamate and dopamine release as a function of DBS is necessary. We have already used a pseudo-random sequence of stimulation of the subthalamic nucleus (STN) in rats and the tools of system identification to determine a transfer function between the DBS input and the glutamate concentration (the output) and tested its accuracy and ability to predict experimental results. Now we are interested in determining the link between dopamine and glutamate.

Goals

Develop a LabVIEW-based experimental interface to control stimulation and assess neurotransmitter release.
Develop an interface for control of fast cycle voltammetry to measure dopamine levels moment by moment.
Develop adaptive mechanics for dynamic control of glutamate or dopamine release.
Use the tools of system identification to measure the transfer function between electrical stimulation and glutamate and dopamine in a rodent model of Parkinson's Disease.
Determine whether the transfer functions for glutamate and dopamine are correlated, and determine how this correlation is related to the loss of dopaminergic neurons in a rodent model of Parkinson's Disease.

Deliverables

An analysis of the limitations of the current technology available - what needs to happen in order to use smart DBS in humans?
A report comparing the benefits of smart DBS based on dopamine or glutamate - which neurotransmitter is the better target for any commercially viable 'smart' DBS system?
A fully functional algorithm-based experimental control model of a healthy motor control system written in LabVIEW.
A 'smart' DBS system prototype:
1. The prototype will be based on glutamate or dopamine as demonstrated by targeted control of these neurotransmitter levels in the brains of individual rodents.
2. The prototype will be adapted so that when it is used in a rodent with induced Parkinson's, it will maintain the level of the target neurotransmitter within a certain window.

Required Facilities

Must be proficient with MATLAB programming
Must have an interest in neuroscience
LabVIEW experience helpful, but not necessary
System identification knowledge helpful, but not necessary

Knowledge Areas Needed for Project

Control systems
Analog electronics
Digital electronics
Signal processing
Software engineering
Materials science
Biomedical engineering
Product design
Statistical analysis
Modeling and optimization

Proprietary Information and Confidentiality Requirements

Sponsor accepts responsibility to discuss IP ownership directly with the student project team and project advisor