Indian Scientists' Experiment May Solve Treatment Puzzles of Neurological Disorders Like Alzheimer's

Using and analysing electroencephalogram (EEG) signals to understand the human brain's response to various stimuli has intrigued scientists for a while – a team of Indian scientists recently conducted an experiment to understand the link between the human brain and behaviour.

They found with the help of deep learning that EEG signals can be used to predict various stages of how a human brain responds to visual stimuli. According to the scientists, this understanding will help treat patients suffering from neurological disorders as well as the application of the brain-computer interface (BCI).

BCI is a computer-based system that acquires signals from a human brain, analyses them, and translates them into command signals to carry out the desired action.

"Our brain analyses the incoming sensations and codes the information about an object in different areas of the brain. It identifies any object with the help of its features, say, shape, color, size, location, orientation etc. This process of object identification is facilitated via the discrimination of individual features as well as the binding/integration of the visual features into one object," Anubha Gupta, a professor from the Department of Electronics and Communications Engineering at the Indraprastha Institute of Information Technology Delhi (IIIT-Delhi) in New Delhi – and co-author of the study – told Sputnik.

The scientists conducted an experiment comparing two stages of visual processing with the help of shape-colour binding for object recognition. First, they displayed a study screen with different shapes and colours to a person. Later, with a gap of 100 milliseconds or 1500 milliseconds, they showed a test screen where either the shape-colour binding of two objects was swapped or kept the same. The subject was then asked whether the test screen had the same objects or whether the test screen had different objects.

"This task is called the change-detection task. These two-time intervals- 100ms and 1500 ms between the two screens (first study screen and then test screen) denote the two stages of visual processing in the human brain. During the time, when the person is doing this task, we captured his EEG signals by pasting sensors on his skull," Dr. Gupta said. "EEG is a test that detects abnormalities in human brain waves, or in the electrical activity of the brain."

"Our major aim in this study is to explore whether the study-test intervals in a change detection task denoting the two stages of visual processing could be accurately predicted by the analysis of EEG signals recorded during the experiment. We utilised artificial intelligence (deep learning) and hence, demonstrated its utility on the visual processing and working memory-related EEG data," she added.

'A Crucial Step In Biomedical Research'

Since patients with neurological disorders like dementia, Alzheimer's, and schizophrenia often show a cognitive decline, where the alterations in feature binding can be used as a biomarker for early detection of these disorders, it becomes very important to understand brain information processing in visual tasks.

"In the near future, BCI systems can be used in behavioural therapy to assist people with psychological disorders. Our study is a step in this direction and can be later used to design rehabilitation tools and programs for such patients using BCI tools," Dr. Gupta explained.

Currently, the team is working on EEG analysis of patients suffering from depression.

"In the near future, we will try to come up with some assisted technology-based solution using EEG signals that can support subjects suffering from neuro disorders," Snehlata Jaiswal, professor and head of the Department of Psychology at Chaudhary Charan Singh University – and study co-author – told Sputnik.

The study was published in Biomedical Signal Processing and Control, a publication of the Elsevier, and came out in its September issue.