Brainwaves to Breakthroughs: Navigating EEG's Data Analysis in Cognitive and Medical Fields

Dr Conor Houghton is an associate professor in Computer Science and reader in mathematical neuroscience at the University of Bristol. He is principally focused on mathematical and computational approaches to neuroscience, particularly on models of mood and movement and on computational approaches to neurolinguistics.

Electroencephalography (EEG) is a convenient approach to measuring neural activity; it is relatively cheap, temporally precise, and completely non-invasive. However, the data it produces is very noisy, both because the signal is very weak and because the measurement mixes together lots of different neural activities, from daydreaming to low-level activity serving the brain's more mundane tasks. This means that although it is an important diagnostic tool for epilepsy, it is less often used for more cognitive tasks.

Dr. Houghton will discuss how this may be changing as new approaches to data analysis become available. He will explore how advancements in EEG data analysis are transforming its application in cognitive and medical fields, potentially making it a more viable tool for a broader range of neurological studies and applications.