Instructor: Gabriel Kreiman
Course Numbers: Neurobiology 130, Neurobiology 230, GSAS 78454
Course Level: Graduate, Undergraduate
Prerequisites: (Harvard) Life Sciences 1a (or Life and Physical Sciences A), Life Sciences 1b (or equivalent). Recommended: Math (Maa/Mab, Math 1A,1B, Math 19a or equivalent), Physical Sciences 1, MCB 80
Course Website: https://cbmm.mit.edu/visual-object-recognition
Visual recognition is essential for most everyday tasks including navigation, reading and socialization, and is also important for engineering applications such as automatic analysis of clinical images, face recognition by computers, security tasks and automatic navigation. In spite of the enormous increase in computational power over the last decade, humans still outperform the most sophisticated engineering algorithms in visual recognition tasks. This course examines how circuits of neurons in visual cortex represent and transform visual information, covering the following topics: functional architecture of visual cortex, lesion studies, physiological experiments in humans and animals, visual consciousness, computational models of visual object recognition, computer vision algorithms.