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Journal of Alzheimers Disease & Parkinsonism | ISSN: 2161-0460 | Volume: 8

October 19-20, 2018 | New York, USA

International Conference on

Parkinson’s disease and Movement Disorders

Optogenetics, functional imaging, and computational modeling to develop a diagnostic tool for Parkinson’s

disease

David Bernal Casas

University College of London, UK

he diagnosis of Parkinson’s disease (PD) is based on the observation of clinical symptoms and neurological examinations

and significantly relies on the identification of classical motor symptoms. However, the severity of the symptoms varies from

person to person, and misdiagnoses and confusion with other illnesses are frequent. To date, no laboratory biomarkers exist for this

neurological condition, and findings on functional imaging are not remarkable. Thus, there is a critical need to develop diagnostic

tools to assist medical doctors. Our long-term goal is to develop a reliable diagnostic tool for hospitals, a method that may assist

physicians to determine the illness. In response to this need, we have designed and developed an interdisciplinary approach to

achieve this ambitious goal. Our approach combines two experimental tools with a computational method and uses both animals

and humans. The first experimental tool is optogenetics. Optogenetics modifies specific types of neurons so they can be switched on

in response to light. Optogenetics now allows for precise spatial and temporal control of the experimental input enabling a broad

array of applications to study the responses of neuronal systems. The second experimental tool is functional magnetic resonance

imaging (fMRI), which measures blood flow in the brain. We associate increased blood flow with increased neuronal activity.

Using optogenetics to switch on a specific type of neuron, and fMRI to map how other regions of the brain respond, we can use

computational modeling to generate quantitative descriptions of specific brain networks with cell-type specificity, and also determine

its function. Then, we can estimate the contribution of each specific brain network to the same networks estimated in the healthy

and diseased human brain and develop a diagnostic tool. Testing our approach to rodents, we have targeted two different types of

neurons known to be involved in PD. We found that upon stimulation of a specific type of neurons that has D1-dopamine receptors,

we activated a pathway – the direct pathway - that called for greater motion while when stimulating the other type of neurons that has

D2-dopamine receptors, we activated another pathway – the indirect pathway – that called for less motion. We then imaged animals

while stimulating either type of neuron and showed how the different neuron types generate distinct whole-brain activation maps,

maps with different behavioral outcomes. Finally, we designed a computational approach to draw circuit diagrams that underlie these

neuron-specific brain circuit functions. For the first time, we published quantitative neural circuits with cell-type specificity. These

findings may already help to improve treatments for PD. For instance, medical doctors are already using a technique called deep

brain stimulation (DBS) to ameliorate Parkinson’s tremors in their patients. In short, DBS delivers tiny electric jolts at high frequency

to neurons that are thought to be responsible for the tremors. A better understanding of the how those neurons work to control

movement could help guide more effective stimulation therapies. However, more broadly speaking, our approach – optogenetics

and fMRI combined with computational modeling – may give scientists a novel way to reverse-engineer the functions of the many

different types of neurons in the brain and the humongous diverse array of neural circuits formed to carry out various commands

which are responsible for behavior

J Alzheimers Dis Parkinsonism 2018, Volume 8

DOI: 10.4172/2161-0460-C6-052