A High-Density Brain Electrophysiological Recording Facility for Queen's University

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Recording of brain electrical signals - the electroencephalogram or EEG - is a widely used, first-line method for connecting neurological functioning to psychological experience. Robust EEG recordings can be conducted non-invasively from passive electrodes that can be positioned on the scalp within a short period of time at a very low per-use cost. In most applications, EEG provides an real-time record of the timing of neural activity synchronized to stimulus events with millisecond accuracy. When combined with equipment that allows for adequate spatial sampling of the brain electrical fields EEG recording and analysis is a first line method for basic research on the connections between regional cortical functioning and psychological behaviour, particularly in sensitive populations including infants and children. EEG recording is also one of the most flexible methods for measuring neurocognitive functioning. Because the equipment used to record EEG is transportable, high-quality recordings can be made in a wide variety of settings and circumstances and integrated with other behavioural and peripheral physiological measures. At Queen's University there are a number of federally funded researchers and research programs that currently use EEG recordings as a principal research method, and still others who seek to integrate EEG recordings with their primary assessments to discover novel brain-behaviour relations. The goal of this proposal is to provide funds for state-of-the-art equipment that will create, improve, and extend opportunities for high-quality EEG collection and analysis for this group of researchers whose goals are to discover the neurophysiological bases of social, cognitive, and emotional functioning across a range of vital psychological domains. Acquisition of this equipment will support the training of HQP from a number of active laboratories in skill sets directly relevant to bio-electrical recording and interpretation across a number of valued settings (i.e., health care, research), and in transferable skills such as management of large data sets, signal processing, and tomographic analysis.