Optical and behavioural tools to investigate the neural correlates of learning and memory

Abstract

Events in our everyday life are encoded as memories that can be consciously recollected and remembered, although our ability to retrieve the specific details associated with these events diminish with time. Such losses present itself as an inability to distinguish between closely related events. Studying this phenomenon requires development of sensitive tools and methods that can measure and follow these changes at neuronal as well as behavioural scales. We have developed the above tools as a part of my thesis towards specifically addressing how multiple memories that share common content are organised in brain preserving their identity. First, we developed a general method to distinguish neurons that took part in multiple temporally separated events. We modelled the dynamics of Immediate Early Genes (IEG) expression, a marker for neuronal plasticity, as a consecutive, irreversible first order reaction with a limiting substrate. This model along with two-photon in vivo imaging of the retrosplenial cortex in cFOS-GFP transgenic mice allowed us to follow the dynamic cellular changes resulting from contextual fear conditioning (CFC) behaviour and identify the underlying neuronal subsets. This enabled us to establish representation of context in retrosplenial cortex at the cellular scale following memory acquisition and address how a retrieval event interacts with a new context presented close in time (60-min). Secondly, we developed a sensitive measure to assess spatial memory in Morris wate maze behaviour paradigm. We used the velocity vector field to describe the search pattern of the mice and develop quantitative measures, namely, accuracy, uncertainty, and intensity of search. These measures reflect the degree of impairment in the memory rather than just identifying if there is an impairment. We demonstrate the usefulness of these measures using four different datasets including comparisons between different strains of mice, an analysis of two mouse models of Noonan syndrome (Ptpn11 D61G and Ptpn11 N308D/+),...