Computational Cognitive Neuroscience and Its Applications Introduction and motivation.pdfVIP

Computational Cognitive Neuroscience and Its Applications Laurent Itti University of Southern Calif ornia Introduction and motivation A number of tasks which can be effortlessly achieved by humans and other animals have until recently remained seemingly intractable for computers. Striking examples of such tasks exist in the visual and auditory domains. These include recognizing the face of a friend in a photograph, understanding whether a new, never-seen object is a car or an airplane, quickly finding objects or persons of interest like ones child in a crowd, understanding fluent speech while also deciphering the emotional state of the speaker, or reading cursive handwriting. In fact, several of these tasks have become the hallmark of human intelligence, while other, seemingly more complex and more cognitively involved tasks, such as playing checkers or chess, solving differential equations, or proving theorems have been mastered by machines to a reasonable degree (Samuel, 1959; Newell Simon, 1972). An everyday demonstration of this state of affairs is the use of simple image, character, or sound recognition in CAPTCHA tests (Completely Automated Public Turing Tests to Tell Computers and Humans Apart) used by many web sites to ensure that a human, rather than a software robot, is accessing the site (CAPTCHA tests, for example, are used by web sites providing free email accounts to registered users, and are a simple yet imperfect way to prevent spammers from opening thousands of email accounts using an automated script). To some extent, these machine-intractable tasks are the cause for our falling short on the early promises made in the 1950s by the founders of Artificial Intelligence, Computer Vision, and Robotics (Minsky, 1961). Although tremendous progress has been made in just a half century, and one is beginning to see cars that can drive on their own or robots that