Cognition refers to mental action or processes of acquiring knowledge through the senses and through experience or thought. Neuroscience encompasses any or all of the sciences that deal with the structure and function of the nervous system and brain. This course provides the scientific foundation for the understanding of cognitive neuroscience, including neuroanatomy, neural signaling, motor control systems, the visual pathway, and research and experimental methods. Emphasis will be on Visual Neuroscience.

Cognitive Neuroscience Seminar A is a weekly forum in which students will learn about and discuss historical and current topics in cognitive neuroscience. The course focuses on journal club discussions of papers selected by the students and faculty. It also includes oral presentations from students and faculty as well as visiting speakers from within and external to RIT. Students will prepare their own oral presentations and written assignments based on the course readings and independent research. Students will develop professional skills required for formal scientific presentations and writing.

Cognitive Neuroscience Seminar B is a weekly forum in which students will learn about and discuss historical and current topics in cognitive neuroscience. The course focuses on journal club discussions of papers selected by the students and faculty. It also includes oral presentations from students and faculty as well as visiting speakers from within and external to RIT. Students will prepare their own oral presentations and written assignments based on the course readings and independent research. Students will develop professional skills required for formal scientific presentations and writing.

Neuroscience has played a key role in the history of artificial intelligence (AI). The development of artificial neural networks was inspired by the knowledge gained from the study of brain functioning, with neuroscientists and psychologists, such as Donald Hebb, William McCulloch, and Geoff Hinton, contributing significantly to the establishment of the field. AI researchers aim to emulate human intelligence by building models and developing biologically-inspired architectures that can make decisions and solve problems in the same way that humans do. At the same time, artificial intelligence is increasingly used as a research tool in neuroscience to advance our understanding of how the human brain works and to accelerate neuroscience development. For example, by analyzing the massive amounts of experimental data on brain activity acquired using neuroimaging techniques, machine learning is used to uncover the patterns in brain activity and link them to specific cognitive and motor actions. This course reviews the fundamental ideas in computational neuroscience and connects the study of the brain to the concepts and research in artificial intelligence. The list of example topics includes neural coding, the biophysics of single neurons and neuron models, neural networks, biological and computational vision, adaptation and learning, machine learning, deep convolutional networks, memory, speech and language processing, and applications of computational neuroscience and artificial intelligence.

Art of Science of Art is a weekly forum in which students will be introduced to and discuss historical and current topics relating art and science with one another. Examples might include understanding human perception of the world in comparison with artistic renderings, the effects of lighting on the permanence and appearance of artwork, the creation of artists’ materials (e.g. the science of pigments), and art conservation/restoration in the physical and digital domains. This seminar provides an introductory and over-arching context for students in the Art of Science / Science of Art minor. It focuses on journal club discussions of readings selected by the students and faculty. It also includes oral presentations from students and faculty as well as visiting speakers from within and external to RIT. Students will complete oral presentations and written assignments based on the course readings and independent research.

Masters-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor.

Masters-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor.