This course is designed to introduce basic computation methods and their application in understanding the nervous system and how it functions. It explores the computational principles that govern various aspects of memory, vision, sensor-motor control, learning, and sensory-motor control. The course covers topics such as the representation of information using spiking neurons and processing information in neural networks. It also includes algorithms for adapting and learning.
The course utilizes Matlab, Octave, and Python exercises and demonstrations to enhance understanding. The target audience for this course includes third- and fourth-year undergraduates, beginning graduate students, and professional and distance learners interested in gaining insights into how information flows through the brain.
By combining the fields of neuroscience and computer science, this course offers a unique perspective on computational neurobiology. It delves into the intersection between these two disciplines, providing students with a comprehensive understanding of how computation plays a role in understanding the brain.
Overall, this course is a valuable resource for individuals interested in neuroscience and computer science, offering a deep dive into computational neuroscience. Whether you are seeking to expand your knowledge in these areas or looking to apply computational methods to understand the inner workings of the brain, this course provides the foundational knowledge and tools necessary to embark on that journey.
