Dr. Lauren Petley, Assistant Professor of Psychology at Clarkson University
Will present a talk entitled:
Event-Related Potentials and Neurodiagnostics: Challenges in Clinical Translation
Abstract: Since its discovery in 1924 by Hans Berger, electroencephalography (EEG) has made a major impact on both research and clinical practice. While the unprocessed, or “raw” EEG can be used to infer changes in a patient’s state (e.g., sleep monitoring) or to detect major neuropathologies, further treatment of the data is necessary to reveal discrete neural events related to the information processing capabilities of the brain. First observed in 1935, event-related potentials (ERPs) have served an important role in advancing our understanding of human sensation, perception, and cognition. Yet despite their popularity in basic research, very few ERPs have been successfully translated to clinical practice. While there are many contributing factors to this problem, one barrier stands out – the challenge of ERP computation. Namely, their small size versus other neural “noise” necessitates long stimulation protocols to yield sufficient data for averaging to improve their SNR. This talk will cover the basic steps of ERP computation, describe a variety of ERPs that might have clinical utility, and give a brief overview of some promising approaches at signal denoising which could help improve the feasibility of clinical translation.
Bio: Dr. Lauren Petley is a cognitive neuroscientist and assistant professor in the Department of Psychology at Clarkson University. Her expertise lies in measuring auditory processing and its interactions with cognition using event-related potentials. After receiving her doctorate from the University of Ottawa, Dr. Petley spent a decade as a career scientist in clinical, industry-partnered, and industry contexts, working to develop novel neurotechnologies for applications in brain injury and hearing. While her current research focuses attention and cognition, these experiences in technology development continue to fuel a desire for innovation in this field.
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Meeting ID: 914 8632 6582
Passcode: 668640
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Friday, March 19th 2021
4pm
*Co-Sponsored by IEEE student branch and HKN