Experience-dependent trends in hippocampal rhythms




Gereke, Brian Jeffrey

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The principal neurons of the hippocampus, “place cells”, are neurons with spatial receptive fields. In hippocampal subfield CA1, place cells have been shown to predict future locations. This anticipatory firing emerges with experience, across exposures to an environment, and is thought to be mediated by Hebbian plasticity in the CA3-CA1 network. Theta, slow gamma, and fast gamma rhythms are thought to route spatial information in the hippocampal formation and to coordinate place cell ensembles. Yet, it is unknown whether these rhythms exhibit experience-dependent changes that are concurrent with those observed in place cells. In this dissertation, I used extracellular tetrode recordings from mouse CA1 to show that experience-dependent changes in theta and slow gamma amplitude follow a similar time course as anticipatory place cell firing, with theta being elevated prior to, and slow gamma elevated alongside, the emergence of anticipatory anticipatory firing. I show that cross-frequency interactions between these rhythms, and their modulation by running speed, vary over time in similar experience-dependent ways. These results are in line with the view that theta rhythms promote acquisition of anticipatory firing, while slow gamma rhythms signal the growing efficacy of CA3 input to CA1 with experience. Other recent work from our lab showed that coordination of CA1 place cells by theta and slow gamma rhythms was disrupted in a triple transgenic (3xTg) mouse model of Alzheimer’s disease. As these mice typically display behavioral deficits in long term memory retrieval, I hypothesized that anticipatory place cell firing might be disrupted following long intervals (~24 hrs) between exposures to the environment. Experience-dependent trends in 3xTg place cell firing were at least as strong as those observed in control mice, and also were accompanied by trends in theta and slow gamma amplitude that were similar to controls. However, baseline theta amplitude, cross-frequency theta phase-gamma amplitude correlations, and theta amplitude-running speed correlations were abnormal in 3xTg mice. Abnormal hippocampal theta dynamics may, therefore, represent a biomarker for the early stages of Alzheimer’s disease. To obtain these findings, I applied the generalized additive model to the analysis of local field potential data, which to my knowledge has not been done previously. I therefore provide a practical introduction to the framework and its application to time-frequency analysis of local field potential recordings, and discuss extensions to point process models, which are suggested to be an important area for future development



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