MEG/EEG Part 2: Analysis, Application and Interpretation

Date & Time

About Biotech

Biotech lectures are open to the public and are held at the Gerald D. Fischbach Auditorium at the Simons Foundation headquarters in New York City. Tea is served prior to each lecture.

View all Lectures in This Series

Jonathan Simon, University of Maryland
Timothy Roberts, Children’s Hospital of Philadelphia
Jonathan Winawer, New York University


Signal Analysis Primer and Applications
Jonathan Z. Simon, University of Maryland

Modern cognitive neuroscientists using electrocorticography (ECoG), MEG and electroencephalography (EEG) are under substantial pressure to use advanced signal processing and analysis techniques, but typically receive little formal training in their usage.

Jonathan Simon, whose departmental affiliations are with both electrical engineering and biology, will provide a signal analysis tutorial aimed at cognitive neuroscientists who wish to better understand their own signal analysis methods. The tutorial will be a mix of an elementary primer with a collection of useful tips and tricks, all aimed at cognitive neuroscientists who routinely analyze ECoG, MEG or EEG signals.

The goal will be to expand signal-processing intuition by bridging the gap between mathematical abstractions (e.g., complex numbers, Fourier transforms and functional analysis) and their applications (e.g., phase relationships, frequency bands, and desirable and undesirable filter properties), using a mix of mathematical and illustrative examples.


Applications of Timing and Spectro-temporal Analysis
Timothy Roberts, Children’s Hospital of Philadelphia

Magnetoencephalography (MEG) offers intrinsic capabilities afforded by high temporal resolution. Not only can subtle shifts in response timing be resolved, but higher frequency oscillatory brain activity can also be precisely defined. Combined with advanced spatial localization algorithms, this offers a powerful five-dimensional modality capable of interrogating the ‘where?’, ‘when?’ and, indeed, ‘what?’ of brain function.

Because spatially resolved signals can be obtained, each rich with spectro-temporal features, analysis of both spatial (regional) functional connectivity, and cross-spectral coupling, this technique presents insight into the dynamics and regional interplay of brain networks.

Timothy Roberts will discuss these technical capabilities and examine the clinical research opportunities they afford, especially in the field of neuropsychiatric disorders, in which disruptions of neural systems, circuitry and connectivity may be implicated. The talk will focus on the field of autism, but will also illustrate the relevance of the spatio-spectro-temporal approach to other disorders, such as attention deficit hyperactivity disorder, schizophrenia and mild traumatic brain injury.

Additionally, integration of MEG characteristics with converging evidence from multimodal studies (e.g., magnetic resonance imaging and magnetic resonance spectroscopy) will augment the neurobiologic interpretation of the observed MEG features, and thus define a path toward the development of ‘biological markers’ for use in diagnosis, prognosis and treatment development and evaluation.


Spectral Analysis of ECoG in Humans
Jonathan Winawer, New York University

There are many tools available to measure activity in the living human brain. The two most widely studied human brain responses are the blood-oxygen-level-dependent (BOLD)signal, typically measured with functional magnetic resonance imaging (fMRI), and perturbations in electromagnetic fields, measured with magnetoencephalography and electroencephalography (EEG), including subdural electroencephalography (ECoG).

Both the BOLD response and field perturbations arise from the activity of large populations of neurons. Understanding how each of these two signals depends on neural activity, and how the signals relate to one another, is a matter of considerable importance in human neuroscience. Jonathan Winawer will review methods and empirical findings in the spectral analyses of ECoG data, and propose links between components of the ECoG signal, the BOLD signal and the underlying cortical circuitry.

Advancing Research in Basic Science and MathematicsSubscribe to our newsletters to receive news & updates