911±¬ÁÏÍø

911±¬ÁÏÍø researchers Shrikanth Kulashekhar and Hanna Renvall have received funding from the Finnish Research Impact Foundation to develop diagnostics for early detection of dementia risk. The need is great, as there are at least 50 million people with memory problems worldwide, a number that is expected to double in the following 20 years.

Currently, there are no methods for screening for dementia risk. Classical neuropsychological testing and cerebrospinal fluid (CSF) based screening methods are not sensitive enough in identifying people at increased dementia risk at an early stage. Methods based on functional brain imaging, such as electroencephalography (EEG) and magnetoencephalography (MEG) are still in the exploratory phase.

Th new project is an offshoot of the European Union's AI Mind project, which aims to find early on patients with increased risk for clinical dementia, and whose dementia onset could be delayed or even prevented. Kulashekhar's contribution in AI Mind has included software development and data analysis. In the AI Mind project, experiments have been conducted in a laboratory environment. However, in the current project the measurements will be conducted while patients move and interact in natural environments, such as parks, using a method known as mobile brain imaging.

‘We now want to combine signals from the body, such as, muscle, head and limb velocity data, and, eye movements, with brain imaging data (EEG). We are interested in a naturalistic environment where complex behaviour relevant to dementia happens.’

Noise in the park

In a laboratory study there is very little movement. It can be, for example, pressing a button or moving your eyes. It is also possible to control what the patient feels or sees during the study.

‘Now is a good time to move from the laboratory to naturalistic environments. For example, in a park, all sorts of noise and stimulation are mixed in with the data. There is existing research evidence that as dementia progresses there are also changes in movements, such as walking manners, so we are interested in what kind of data we can extract. Artificial intelligence will help process complex data and find indicators of these changes’, says Kulashekhar.

The project is a collaboration with the health technology company Bittium Biosignals. For a good reason: a typical EEG cap used in research has 64-128 sensors, it would take a lot of time and money to prepare one patient for the measurement. Bittium has developed a 16-sensor cap that the patient can carry with them.

‘The goal is to first conduct the study in Aalto with 64 sensors, and then replicate it using Bittium's much simpler and easier technology,’ says Kulashekhar.

Many people experience mild cognitive impairment (MCI) as they get older, with some progressing to dementia, such as Alzheimer's disease. In light of existing research, Kulashekhar recommends that as people age, they continue to do complex things.

‘The brain stays alert when we learn languages or do tasks that require balance, for example. But if you don't use your brain, it tends to cut down resources. If we know early enough who is at risk of developing dementia, we may be able to halt the progression by addressing lifestyle factors such as blood pressure, cholesterol and an inactive lifestyle.’

Contact information:

Shrikanth Kulashekhar
Postdoctoral researcher
911±¬ÁÏÍø
shrikanth.kulashekhar@aalto.fi

Hanna Renvall
Assistant professor
911±¬ÁÏÍø and HUS
hanna.renvall@aalto.fi
Tel +358 50 501 0326