A computational model being developed at DTU aims to help get to the roots of Parkinson’s disease to allow for future early diagnosis and treatment.
Imagine if—in the future—doctors were able to not just treat the symptoms related to Parkinson’s disease, but also detect and treat it before it becomes debilitating. Associate Professor Silvia Tolu from DTU Electro wants to help make this possible by using an unorthodox approach to creating knowledge that can help identify the roots of the neurodegenerative disease, which affects millions worldwide.
Over time, it leads to walking and movement difficulties, causes shaking and stiffness, and affects the ability to speak.
These problems stem from a communications breakdown in the body’s central nervous system in which neurons experience a loss of dopamine, which is a type of neurotransmitter. This makes the neurons less efficient at conveying messages from different parts of the brain to the body. However, the root cause of the disease remains elusive.
An unorthodox approach to finding the cause
“Because doctors do not understand the cause, they can only treat the symptoms when they appear and not halt the progression of the disease before the debilitating symptoms appear,” explains Silvia Tolu, who has set out to develop a true-to-life model that maps the course of the disease using neurorobotics.
Neurorobotics is a combined study of neuroscience, robotics, and artificial intelligence.
Where previous models have focused on showing what goes on in the parts of the brain that are affected by the disease, the new model aims to track the progression of the disease, allowing researchers to trace it back to its root.
“One advantage of neurorobotics is that you can replicate tests precisely and you can run experiments again and again without harm to the test person and you do not run the risk of them getting tired,” she explains.
In an unorthodox approach, Silvia Tolu and her team will start by creating a computational model of a part of the central nervous system that is located in the spinal cord. Initially, the model will show what it looks like when it is healthy. The focus is on the spinal cord because it plays a pivotal role in a person’s ability to move (locomotion).
By then making adjustments to the model to mimic the changes in dopamine experienced by neurons in patients, Silvia Tolu aims to simulate what changes occur in a Parkinson’s patient’s neural network.
Tool for earlier and better diagnosis
According to Silvia Tolu, identifying the root and gaining a deeper understanding of how the disease progresses would enable early-stage diagnosis of the disease, so the appropriate therapy can be initiated earlier—and ideally before the debilitating symptoms appear.
Currently, the diagnostic tools for Parkinson's disease are based on subjective criteria. Building a model that can serve as a diagnostics tool would—in time—allow medical professionals to not only diagnose the disease in a precise, objective manner but also track its progression in each patient.
In the long term and with additional research and work, such a model could be useful for developing more tailored treatment plans for patients based on their particular disease profile.
Grant for the audacious
To fund their work, Silvia Tolu’s team has received an LF Experiment Grant of almost 2 million Danish Kroner from Lundbeckfonden . These grants are given to audacious and innovative projects to support researchers who are courageous enough to think outside the box.
The selection panel selects recipients using an unusual approach: It reviews applications anonymously, leaving the panel in the dark as to who has submitted them. In addition, each reviewer gets a trump card, which he or she can use to singlehandedly vote through a deserving project.
Other audacious DTU projects to receive funding
Three other researchers at DTU were among the 26 researchers from Danish universities to receive grants of around 2 million Danish Kroner each. The others are:
Associate Professor Andrew Urquhart from DTU Health Tech. His project is devoted to developing novel light-based nano-techniques for precision control of the medical treatment of a range of diseases of the eye.
Associate Professor Tim Dyrby from DTU Compute will be using a special technique for 3D imaging – mapping – of the brain’s entire neural connection landscape. By using the technique on laboratory animals, the project aims to provide a better understanding of the impact of brain disorders on the brain’s nervous system.
Postdoc Ying Gu Ying from DTU Health Tech. Her project is devoted to the design of a portable system able to record with a high degree of precision the incidence of seizures in epilepsy patients. The aim is to improve the precision of both diagnosis and treatment.