Grant: Master's Award: Canada Graduate Scholarships

Neurodegenerative disease is a debilitating affliction, which affects a growing number of our aging population. Early intervention may present the best course to prevent the onset of this irreversible disease, but few early biomarkers are available to inform medical practitioners. Recently, oscillatory coupling has emerged as one such potential early biomarker of neurodegeneration. Coupling of electromagnetic brain oscillations occurs when the rhythmic electric discharges of neuronal populations at different frequencies spontaneously synchronize. It is thought to represent the intercommunication of widely dispersed neuronal populations, possibly subserving cognition and memory function. Indeed, increased coupling of low-frequency theta and high-frequency gamma rhythms have been observed during place learning in animals, as well as in working memory in humans. Two recent studies of particular interest concern theta-gamma coupling. In a first study, disruptions in theta-gamma coupling were shown to precede the onset of Alzheimer's disease in an animal model. In the second study, irregularities in theta and gamma rhythms were associated with the onset of dementia three years later, in humans. However, this last study did not measure phase coupling, but instead looked at power ratios of these rhythms. Considering these studies together, it seems likely that theta-gamma coupling may be a good predictor of neurodegeneration in aging. Furthermore, this phenomenon is especially pronounced during rapid-eye-movement (REM) sleep in animals, and sleep is otherwise known to be important for memory formation and the maintenance of cognitive function. Theta-gamma coupling may then represent an important mechanism underlying sleep-dependent cognitive processes. No study has yet measured theta-gamma coupling during sleep in humans. Hence, the present research project aims to investigate theta-gamma coupling during sleep in relation to aging and cognitive function. We suspect that oscillatory coupling will be most pronounced in younger adults, and will wane with age. Furthermore, we predict that the level of theta-gamma coupling in a given individual will correlate with that individual's cognitive performance, as measured by an overnight sleep-dependent memory task. Overall, we hypothesize that a decline in theta-gamma coupling with age will be paralleled by a decline in cognitive performance. Both young and elderly participants will undergo electroencephalographic (EEG) recordings of their sleep following learning of a memory task. The next day, their performance on the task will be assessed, and will be compared to the rate of theta-gamma coupling measured by EEG. In this way, we hope to discern whether theta-gamma coupling does indeed predict memory performance. Also, by comparing young and old groups, we can determine whether there is a change in the degree of theta-gamma coupling with age. These results could potentially provide valuable information about the progression of neurodegenerative disease. In a first instance, theta-gamma coupling may provide us with an early marker of disease progression, allowing medical attention to be better allocated. In a second instance, an understanding of the neural mechanisms underlying neurodegeneration may eventually lead to insights about pathology and treatment. Ultimately, we hope this research will improve longevity and quality of life in the elderly.