The Center for Cognitive Neuroscience pursues a vision – cracking the neural code – through building an interdisciplinary community of scientists and scholars at Dartmouth who are engaged in cognitive neuroscience education and research.

Vision: Cracking the neural code

All aspects of our mental lives – our perceptions, thoughts, emotions, and knowledge; our attitudes and intentions; our decisions and actions – are encoded in patterns of brain activity and the structure of brain circuits. Understanding the neural code – how information is encoded in brain activity and structure – is a collaborative and interdisciplinary effort that involves neuroscientists, engineers, and computational scientists, among others. Cracking the neural code will have revolutionary effects on science and society, reaching beyond neuroscience to the social sciences, humanities, arts, public policy, and medicine.

Community building

The CCN builds the cognitive neuroscience community at Dartmouth and the Upper Valley with community outreach, events, workshops, a summer school, and an annual retreat.


The CCN organizes a series of talks through the academic year, some of which are geared to experts in cognitive neuroscience, and others at a broader audience in the Dartmouth community. The CCN also organizes summer workshops on a variety of topics,ranging from neural decoding to semantic processing and semantic knowledge. The CCN website hosts videos of the presentations from the CCN talks and workshops, as well as instructional videos on research methods. The CCN also supports a summer school whose vision is to train the next generation of psychological and brain scientists in the latest mathematical modeling and analysis tools for studying the mind


The CCN encourages and facilitates interdisciplinary collaborative research in cognitive neuroscience. Such collaborations have involved projects with investigators from cognitive neuroscience, education, engineering, philosophy, and music.
The CCN also supports research through the development and management of research infrastructure, such as brain imaging facilities and software systems for neuroscience computing.