Brain Star Award Winner Niklas Brake

Better understanding the non-rhythmic components of Electroencephalography (EEG) can lead to better interpretation of brain activity

Electroencephalography (EEG) has been in use for almost a century to study brain activity, during which time its rhythmic oscillations in signal, seen as waves of activity, have shaped a unique lens through which many researchers view the nervous system. Recently, interest has shifted toward seemingly non-rhythmic (i.e., aperiodic) EEG signals, which have been linked to various neurological conditions and states of consciousness. However, these findings have been primarily descriptive, leaving interpretations of these aperiodic signals elusive.
In this study, Niklas Brake, in the research group of Professor Anmar Khadra at McGill University and collaborating with anesthesiologist Dr. Gilles Plourde at the Montreal Neurological Institute, used biophysical modeling to show that large aperiodic fluctuations in the brain’s electric field arise from cortical circuits synchronizing with aperiodic dynamics. These fluctuations, in turn, can significantly bias traditional EEG interpretations. Additionally, the model predicted that both periodic and aperiodic EEG signals are shaped by the molecular timescales of the brain’s inhibitory pathways. To test this, they collected EEG data from individuals undergoing general anesthesia with propofol, a drug that alters the molecules underlying neural inhibition. The observed signal changes matched their model predictions. Using insights from the modeling, they developed an analysis method for identifying and removing aperiodic EEG signals, both to extract aperiodic features and to improve brain rhythm characterization. Applying this method to EEG data revealed that loss of consciousness from propofol was uniquely associated with an increase in delta rhythms, an observation that had previously been masked by propofol’s molecular effects.
Overall, this study extends EEG theory beyond neural oscillations, illustrating how EEG signals are shaped by neural mechanisms other than brain rhythms and revealing how these signals can undermine traditional analysis methods.

This publication has a broad impact because it presents a fundamentally new way of looking at EEG. This work is the first to propose a unified theory of EEG that includes a non-rhythmic component, demonstrating that EEG can be generated from a mixture of periodic and aperiodic neural signals. The researchers therefore expect this study to form a core theoretical framework for many future EEG studies, particularly those that seek to characterize the dynamics of specific brain states.
Following publication, these results have been used by others to interpret EEG signatures of a broad range of experimental variables, including stroke recovery, Down syndrome, autism, depression, epilepsy, sleep, and visual perception. Importantly, by tying aperiodic EEG signatures to specific physiological mechanisms, this study opens the door to investigating new neural mechanisms underlying these various conditions, cognitive abilities, and states of consciousness. In the same way that EEG has tied neural oscillations to various cognitive functions – such as gamma oscillations and attention – this publication holds promise for inspiring studies of the aperiodic neural dynamics underlying brain function and dysfunction.

About Niklas Brake

Niklas Brake completed this work as a doctoral student in the research group of Professor Anmar Khadra at McGill’s Center for Applied Mathematics in Biosciences and Medicine. Dr. Brake is currently a postdoctoral researcher in the Department of Physiology where he continues to study neural dynamics, now using in vivo calcium and voltage imaging in behaving mice.

Source of funding

This project was funded through an NSERC discovery grant to Professor Khadra and graduate research scholarships from FRQNT and NSERC-Create in Complex Dynamics to Dr. Brake.