MGSC Website: http://math.uci.edu/~mgsc/
Calcium imaging of neurons in vivo allows simultaneous recording of large numbers of neurons, which communicate and execute computations implicit in the encoding of learning and memory. However, such in vivo optical recordings are typically subject to motion artifact and background contamination from other neurons, making it difficult to define single cell spatiotemporal dynamics. Here we introduce spatial constraints imposed on the extracted spatial footprints to improve ROI selection and reduce false discovery detection. Then we combine spatiotemporal correlation across recording sessions with a predictor corrector methodology to extract single cell neuronal data from long-term multi-session imaging experiments in different brain regions including prefrontal cortex, visual cortex and hippocampus. This new methodology is particularly suitable for extracting neural signals from weeks- and months-long longitudinal recordings, as demonstrated in our simulated and multi-session in vivo experimental recordings. Application of the new method allows for robust longitudinal analysis of contextual discrimination associated neural ensemble dynamics in hippocampal CA1, which reveals how hippocampal neuronal ensembles representing two environmental contexts evolve over the course of contextual discrimination conditioning. Additionally, we combine this methodology with neural decoding to understand changes induced by modulating neural circuits.
Kevin is a 4th year PhD student in math, working with several individuals in the neurobiology department. Outside of research, he likes to watch anime and cook.
Kevin's advisor is Qing Nie.
none
Pizza will be served after the talk.