Cracking the brain code: could brain-computer interfaces predict disorders before they strike?
In the realm of neuroscience, technology called electroencephalography, also known as EEG, is a way we can monitor brain activity from the surface of the head. It is a powerful tool that observes the brain’s electrical activity and how it changes when nerves fire.
EEG can capture specific patterns of brain activity, common across individuals. However, in certain neurological disorders, evidence suggests these patterns change. Therefore, certain studies suggest that changes in EEG patterns can be used to predict development of neurological disorders before symptoms present by capturing subtle changes in brain activity in the early stages of disease.
A 2018 study demonstrated that changes in EEG patterns could predict the likelihood of spinal cord injury patients developing neuropathic pain[1]. To provide context, neuropathic pain arises from a dysfunction in the communication of pain signals between nerve cells in the brain, resulting in abnormal brain activity. In this study, the researchers took EEG recordings of individuals before they developed neuropathic pain, and they assessed a feature (or signature) of EEG called ‘reactivity’. In this case, reactivity describes the change in rhythmic brain activity seen on EEG when the eyes are closed versus when they are open. In humans, usually there is a significant rhythm change between open and closed eyes due to visual information stimulating certain brain networks when the eyes are open. Interestingly, the researchers found that the patients who went on to develop neuropathic pain showed reduced reactivity on the EEG recordings compared to patients who did not develop neuropathic pain. This change in reactivity was also observed in spinal cord injury patients who already had neuropathic pain. The fact that this feature appeared before the onset of symptoms suggests its potential as a predictor for the development of the condition.
The identification of such disease-related EEG patterns has the potential to be quantified by brain-computer interfaces. The researchers of the 2018 paper suggested that development of a brain-computer interface could allow them to create risk profiles for individuals at high risk of developing neuropathic pain[1]. This may allow clinicians to detect neurological disorders earlier and alter treatment regimens, providing more targeted healthcare and potentially improving the patient’s quality of life. Of course, the feasibility and impact of this approach on healthcare systems is currently unclear, and these considerations must be addressed in future research.
[1] https://pubmed.ncbi.nlm.nih.gov/29751110/
Edited by Hazel Imrie
Copy-edited by Cameron McKeddie
