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This lecture by Meenakshi Khosla explores data-driven modeling in large-scale naturalistic neuroscience, focusing on the scale and complexity of data, stimuli, and measured brain activity. The research overview delves into how the brain processes the external world, scene and object perception, and large-scale data analysis. The lecture discusses the representation of brain activity, the use of artificial intelligence to understand brain computations, and the application of probabilistic models and deep learning. It also covers the discovery of neural selectivities for faces, places, bodies, words, and food, and the development of computational models to predict brain responses to external stimuli.