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The Neuroscience Statistics Research Lab (NSRL) at the Massachusetts Institute of Technology focuses on the development of statistical methods and signal-processing algorithms for neuroscience data analysis. With recent technological advances, the lab aims to analyze neural signals with sophisticated techniques such as likelihood, Bayesian methods, state-space, and time-series point process approaches. The laboratory's primary research initiatives include characterizing hippocampal neuron firing patterns to understand spatial information representation, relating changes in neural activity to procedural learning performance, and constructing algorithms for neural prosthetic control using fMR imaging. Additional research areas encompass the understanding of general anesthesia, where the lab investigates the drug-induced state that includes unconsciousness and anti-nociception, along with the dynamics of human biological states. The NSRL's work integrates statistical and computational methodologies to enhance signal extraction from various neural recordings, including EEG and MEG, during cognitive and motor tasks.