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I'm a Postdoctoral Fellow at the Rotman Research Institute of Baycrest Hospital in Toronto, Ontario, where I work with Drs. Rosanna Olsen, Jennifer Ryan, and Jed Meltzer. My work is funded by a postdoctoral fellowship from the Natural Sciences and Engineering Research Council of Canada (NSERC), with additional support from the Data Sciences Institute of the University of Toronto.

My research aims to understand how the human brain accesses and encodes information in memory. This includes situations in which we recognize meaningful objects, people, and scenes during visual perception, and when we understand the meanings of words during language comprehension. Each of these examples is supported by specialized brain systems that map perceptual information about items (i.e., the lines, edges, and colors that make up an object) to knowledge stored in our memories (i.e., how that object is used, where it is found, etc.), allowing us to piece together and understand more complex representations, like the meaning of a visual scene in front of us. Importantly, our brains not only retrieve this knowledge while we're currently experiencing the perception, but also encode new knowledge about that experience into our memories, which we may be able to access later in time. My research aims to develop mechanistic accounts of how these processes are implemented and balanced in the human brain.

To do so, I use several methods from cognitive neuroscience, including electrophysiological recordings (M/EEG), brain imaging (MRI), and eye-tracking, to study human behaviour and brain activity. I often combine these with computational tools from artificial intelligence research, such as artificial neural network models, to analyze and understand the resulting data. Ongoing projects, supported by students and volunteers, examine (1) how visual systems in occipitotemporal cortex enable the recognition and combination of word meanings during natural reading; (2) how oscillations in neural activity couple with the timing of eye movements to support episodic memory encoding; and (3) how brain responses to audiovisual films, measured with M/EEG and eye-tracking, may offer insights into cognitive differences between younger and older adults.

Prior Education: I received my PhD in Cognition & Perception from New York University, where I worked with Dr. Liina Pylkkänen. During my graduate training, my research focused on word recognition and semantic processing in language comprehension, using a combination of magnetoencephalography (MEG), eye-tracking, and magnetic resonance imaging (MRI). Prior to graduate school, I earned my Bachelor's degree in Neuroscience from Dalhousie University, and then spent three years as a Lab Manager in the Magnetoencephalography Lab at New York University Abu Dhabi. In 2022, I completed an internship with the Human-Centered Artificial Intelligence team at IBM Research, where I developed computational pipelines to detect cognitive decline in Alzheimer's disease patients, based on samples of natural speech.

Contact: gflick @ research [dot] baycrest [dot] org

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