Click to listen to the podcast!
As Parkinson’s disease progresses, does the brain begin shifting how certain cognitive functions are handled in an attempt to compensate for the effects of the disease? New research suggests the brain’s neural networks may adapt and reorganize over time through a process resembling Dynamic Neural Compensation (when one part is the brain is struggling, other parts step in to help) rather than a simple linear decline, dynamically shifting how certain mental processes are carried out as symptoms worsen over time. The study published in Nature “Temporal Dynamics of Cognitive Functioning in People with Parkinson’s Disease,” examines how thinking and memory changes as Parkinson’s disease progresses over time.
The researchers analyzed cognitive testing data from 355 people with Parkinson’s disease over four years using more than 24,000 cognitive data points and 19 different cognitive test scores with a combination of several advanced research methods that allowed researchers to see which cognitive skills naturally changed together over time. Using a tool called Dynamic Exploratory Graph Analysis (dynEGA), the study also showed how different parts of thinking may become more connected, weaker, or reorganized as Parkinson’s disease progresses, and Panel Graphical Vector Autoregression (GVAR) models, showing how different parts of thinking may become more connected, weaker, or reorganized as Parkinson’s disease progresses. As fantastic as these tools from a science-fiction novel sound, they are still in development and not yet ready for prime time as part of routine clinical care.
Researchers using dynEGA were able to take the test scores and make a web of interconnected points. Each of these points became a point connected to the larger network like, a puzzle in the larger brain network. Researchers looked at which of these skills changed over time as Parkinson’s progression continued. As the patients’ abilities to do tasks strengthened or weakened, the system mapped them into different clusters, exposing how thought patterns interact and reorganize over time, rather than treating memory, attention, language, and problem-solving as separate brain functions.
The results of these tests identified five dynamic cognitive dimensions in the brain that were linked to how the brain processes thinking and memory over time, suggesting an adaptation is taking place as Parkinson’s disease progresses. These dimensions are: Visuoconstruction, which involved tasks like copying figures, recalling shapes, judging distances, and reading maps. Executive/Visual-Spatial Functions that included reasoning, naming objects, reflected planning, updating memory, and attention. Card Sorting/Cognitive Flexibility tasks that measured logical reasoning, set shifting, response inhibition, flexibility, and adapting mentally to changing tasks or rules. Attention/Processing Speed, which measured selective attention and how quickly the brain processes information, and Verbal Functions, which included measured language skills, word recall, and general knowledge stored in memory.
Image by Chris Denny/ChatGPT
The GVAR, using advanced prediction models, then analyzed how earlier changes in one test score relate to later changes in other test scores and how they influenced each other over time, helping to show how abilities in processing thoughts strengthen, weaken, or shift together as Parkinson’s disease progresses. Researchers found that attention and processing speed tended to move together over time. Changes in language and verbal memory abilities were linked to later changes in problem-solving and visual-spatial thinking skills. However, the study found that skills related to adapting, problem-solving, and changing tasks appeared to follow different patterns of decline than abilities involving how the brain understands space, shapes, and visual information.
These shifting patterns, identified by the GVAR, support what is known as the Dual-Syndrome Hypothesis. “The dual-syndrome hypothesis of cognitive impairment in PD… postulates two distinct but overlapping paths of cognitive decline in PD: (1) an early-onset fronto-striatal impairment… and (2) a later-onset cholinergic-modulated posterior and temporal lobe impairments showing as language, memory, and visual-spatial dysfunctions, with more rapid decline to PDD.”
It’s a theory shared among some researchers that the decline in Parkinson’s may follow two different neurological pathways, one involving thinking and attention problems earlier in the disease, and another involving memory, visual-thinking, and dementia-related problems that occur later on. “These patterns suggest temporal ordering in cognitive decline rather than simultaneous deterioration across domains,” meaning that the cognitive decline in Parkinson’s disease may happen in a sequence or in progression instead of someone’s ability to process thoughts declining at the same time. The first of these pathways is thought to be connected to dopamine-related changes that influence attention problems, planning, and multitasking. The second of the two may include memory decline, visual-spatial problems, problems with language, hallucinations, and dementia-related symptoms.
Researchers argue that “Our findings call into question the reliability and validity of widespread guidelines for cognitive diagnostics based on cognitive domains, such as the MDS guidelines for assessment of PD-MCI.” Meaning the current standards may be too rigid and oversimplified in how cognition changes the brain’s landscape over time when it comes to Parkinson’s disease, and may not reflect the brain’s evolving cognitive networks.
Parkinson’s disease research is taking extraordinary leaps and bounds in the kinds of data being generated to help explain more about the disease than ever before, and the ability to be able to map out how thought processes, memory, attention, language, and problem-solving skills interact and reorganize over time may provide researchers with an entirely new way of understanding how cognitive decline develops as the disease progresses. The applications for this type of technology could be adapted for other types of neurodegenerative diseases. “Future studies should investigate the temporal reorganization of cognitive domains in other clinical samples such as AD (Alzheimer’s Disease).”
