Assessing Repeatability of NeuroCatch Platform™ Measurements: An Initial Assessment

EEG signals have been collected and studied since the early 1990's as a way of assessing brain function at a gross level. As early as the 1930's a derivative of the raw EEG signal - event-related potentials (ERPs) - have been computed. These scalp-recorded ERPs are the brains response to a stimulus of interest (e.g. a flashing checkerboard or an angry face). The timing and topographical location of ERP components lends insight into the timing and complexity of various cognitive processes. At NeuroCatch Inc., research is primarily focused on three ERP components: the N100, P300 and N400. To elicit the ERP components of interest in this study (N100, P300, N400), proprietary auditory stimulus sequences will be administered using the investigational device, the NeuroCatch Platform™. Each sequence consists of pure tones and word pairs to elicit the various components associated with different attention abilities (sensory processing, target detection \& semantic processing). A secondary objective of the study will be to validate the auditory stimulus sequences tested. Understanding the degree to which these neurophysiological components fluctuate over time is crucial to our understanding of typical brain functioning. Research and medicine is moving away from behavioural responses to assess brain health (e.g. verbal responses, reaction time, etc.) and are moving toward more neuroimaging focused measures, such as CT, and MRI scans. The strength of utilizing EEG technology is two-fold: i) it is portable and ii) has high temporal resolution. Looking forward, EEG-based brain assessment technology could be implemented field-side, at the site of an accident for a quick assessment of brain and cognitive functioning, or within a clinicians' office to evaluate treatment efficacy. However, for this type of technology to be useful in quantifying brain health, we must first quantify the degree to which a healthy brain naturally fluctuates in it processing capability. For example, sh