After decades of procognitive research in SZ, an FDA approved procognitive drug is yet to be identified. However, a bottom-up targeted cognitive training (TCT) is found to be effective in improving cognition and functional outcome in SZ patients. Nonetheless, TCT is time and labor-intensive, expensive, and only beneficial to about half of the patients. This underscores the need to identify predictive biomarkers of TCT sensitivity. In a recent report, mismatch negativity (MMN), an electroencephalogram (EEG)- based measure of early auditory information processing (EAIP) predicted TCT response in treatment-refractory SZ patients, albeit, with modest power. To this end, an important question is, can we enhance the ability of EAIP ?biomarkers? to predict cognitive and functional gains from TCT in SZ patients? EAIP measures, MMN and auditory steady state response (ASSR), are presumably measuring information processing capacity within complex, real-life environments. In everyday life, complex sound stimuli are processed in the context in which they are perceived. However, all methods to measure MMN and ASSR have utilized isolated sound fragments (clicks, tones), removed from any environmental context beyond a laboratory test chair. It is possible that EEG measures generated using contextually relevant naturalistic sound stimuli might be better predictors of TCT sensitivity. However, MMN and ASSR measures require millisecond- level stimulus control within a structured test session ? that is not easily achieved in a naturalistic setting. Virtual reality (VR) technology provides both the naturalistic context and tight experimental control needed to generate and assess more informative measures of EAIP. This application takes the critical step toward developing an ecologically valid VR-based EEG paradigm to measure EAIP by using naturalistic sound stimuli (e.g. footsteps, jack hammer) presented in familiar VR- delivered contexts (e.g. walking from point A to B, construction site). The VR-EEG task will be developed in collaboration with the Computer Sciences Department during months 0-4. The validity, reliability and biomarker potential of the VR-based MMN and ASSR will be determined in healthy subjects (HS) and SZ patients (N=40, HS:SZ= 20:20) during project months 5-20. Carefully screened, eligible study participants will complete a comprehensive neurocognitive and functional assessment, laboratory- and VR- based EEG tasks before and after a one-hour ?sound sweeps? TCT session in a randomized, order-balanced, single test day study. Findings will test the hypotheses that: 1) VR-based MMN and ASSR are reliable and valid measures of EAIP deficits in SZ, 2) the VR-based EEG measures will predict auditory perceptual learning after 1-hour of TCT session and 3) VR-based EEG measures will predict cognitive and functional state in SZ. Evidence suggesting ecological validity of these VR-based biomarkers of EAIP will provide basis for future VR-EEG guided studies of targeted procognitive therapeutics.
Neurophysiologic measures of early auditory information processing (EAIP) are found to modestly predict cognitive gains with targeted cognitive training in schizophrenia (SZ) patients. The proposed study seeks to improve the predictive power of EAIP measures by developing a novel naturalistic virtual reality (VR) task paired with simultaneous recording of brain electrical activity that will simulate real life activities such as walking to doctor's office while listening to sounds from nature. Findings will provide strong basis for VR-guided studies of targeted cognitive training in SZ patients.
