When thinking of neuropsychological testing, most people imagine that it has to be lengthy, rigid, and in person. 

These assumptions are not surprising, since this is what neuropsychological testing has looked like until recently. For decades, assessments were strictly done in person. Often, lengthier tests have been justified by clinicians because they believed this was the only way to ensure thorough and accurate results. 

Yet, research has shown that by leveraging the Internet, neuropsychological assessments can be administered online, in consolidated formats, and from the comfort of people’s homes, while still maintaining accuracy and reliability. 

While people might be deterred from signing up for neuropsychological testing because they live far from a medical center, have limited access to information on the impact of such testing, or simply find the whole process to be too burdensome, online methods might bridge these gaps for many patients. More specifically, for people with Cerebellar Ataxia, having the option to avoid travel offers a great advantage.  Testing people in a more accessible and scalable format ensures more diversity in our research results and clinical knowledge. 

During our data collection phase, I met with participants online, administered tests, and learned more about the rare condition that would slowly captivate my attention. I was amazed by the range of people I was able to meet from geographic areas that I never would have encountered without the use of digital methods. Additionally, I met with individuals with Cerebellar Ataxia, a condition so rare (less than 1% of the population) that I probably would have had to wait years to encounter even one, let alone two individuals with this condition in an in person clinical setting. From this, I realized the incredible diagnostic potential for remote health methods. 

My first impression when learning about Cerebellar Ataxia was that it must be a condition that exclusively affects motor movements, balance, and coordination. After all, this is how neuroscientists and physicians have understood Cerebellar Ataxia and the cerebellum overall for quite some time. 

Only recently have there been research-backed indicators that Cerebellar Ataxia has links to certain neuropsychological characteristics. These insights sparked our interest in researching the non-motor symptoms experienced by people with Cerebellar Ataxia. 

In our bi-center study, we assessed people with Cerebellar Ataxia, Parkinson’s disease, and age matched neurotypically healthy controls. Using accessible online tools, we were able to assess domains, such as cognition, anxiety, depression, social support, and personality. We used machine-learning classifiers in order to evaluate whether non-motor measures could support accurate identification of Cerebellar Ataxia. The machine learning models were fed data relating to the collected non-motor measures and from this they were trained to identify non-motor symptoms as either consistent with or inconsistent with a diagnosis of Cerebellar Ataxia. By processing this information using machine-learning models, we were able to examine which features had the most predictive power in Cerebellar Ataxia classification. 

We found that people with Cerebellar Ataxia displayed a specific pattern of non-motor symptoms. Specifically, their scores on the cognitive tests and personality measures seemed to follow a trend that differed significantly from neurotypically healthy controls and people with Parkinson’s disease. Overall, participants reported that they felt the testing was quick, enjoyable, and user-friendly. These results will have a significant impact for patients as they suggest that online assessments could improve access to care and research for people with Cerebellar Ataxia. Further, by using remote assessments alongside machine learning models, we can build a better understanding of the non-motor symptoms relating to Cerebellar Ataxia, which can serve as potential digital-markers.