Project in visual hallucinations in Parkinson’s awarded nearly $500K
Researcher using immersive virtual reality to investigate neuronal changes
A researcher at the University of Rhode Island has received nearly $500,000 in federal funding to investigate the neuronal changes underlying visual hallucinations — seeing something that is not real — in people with Parkinson’s disease.
The funding, from the National Science Foundation, was granted to Yalda Shahriari, PhD, for her project “Integrated Framework for Recording and Decoding Multimodal Neural Associations of Visual Hallucinations and Motor Functions in Parkinson’s Disease.”
The three-year, $463,693 grant will help Shahriari and her team study visual hallucinations and how they relate to motor symptoms in Parkinson’s disease using an innovative framework involving immersive virtual reality.
The ultimate goal is to identify reliable biomarkers of visual hallucinations in these patients to allow for early diagnosis and better management strategies. With as many as 75% of Parkinson’s patients developing visual hallucinations over a 20-year period, early detection is critical, a university news story noted.
“Despite extensive research on neural signatures of hallucinations in other neurological conditions like schizophrenia and dementia, the Parkinson’s disease diagnostic field lacks reliable cognitive neural markers for visual hallucinations that can be used for assessment and diagnosis,” Shahriari said. “We’ll take the first steps in addressing this gap.”
National Science Foundation funds Parkinson’s hallucinations project
Visual hallucinations are a common symptom of Parkinson’s disease and various forms of dementia. These hallucinations often stem from the cognitive decline experienced by individuals with Parkinson’s and can precede motor symptoms by up to 10 years, according to researchers.
However, a lack of reliable neuronal markers makes it difficult to detect visual hallucinations in these individuals, which precludes them from accessing effective therapeutic interventions as early as possible.
These hallucinations are believed to stem from disruptions in neural networks, or the interconnected nerve cells that coordinate activities such as cognition and movement, by sending and receiving electrical signals across specific pathways.
In Parkinson’s, changes in these networks in the cerebral cortex, the brain’s outer layer, are thought to lead to hallucinations and also impact movement.
Shahriari’s research aims to pinpoint the underlying causes of visual hallucinations using virtual reality. Patients will be immersed in a controlled, interactive virtual scenario where they are asked to perform face-recognition tasks.
In these tasks, participants will wear a smart glove and complete actions like reaching toward a virtual button when they recognize a face. The smart glove will record finger movements and hand trajectories, allowing researchers to observe electrical and vascular brain activity related to both visual perception and motor function.
The research aims to test several neural networks responsible for visual perception, attention, motor initiation, and executive function, as well as error detection.
The data collected from patients in this study will offer valuable insights, according to the team. The researchers hope their findings will help develop novel diagnostic tools and identify key factors that may be targeted with future therapeutics.
Shahriari and her team will work alongside a team of experts, including Joseph H. Friedman, MD, a neurologist and head of the movement disorders program at Butler Hospital, also in Rhode Island, and Ming Shao, PhD, an associate professor at the University of Massachusetts Dartmouth.
Friedman will lead the enrollment and clinical assessment of patients with and without visual hallucinations, as well as control groups. Shao will oversee the design, development, and evaluation of machine learning algorithms to analyze the data.
According to the award abstract, “visual hallucinations in [Parkinson’s] are believed to result from disrupted brain activities, leading to incorrect visual perceptions.”
The project aims to “develop an engineering framework to integrate brain imaging data of electrical signals and blood flow with human motion data to identify complex connections between vision and movement in the brain.”
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