Summer School

Methods in Neuroscience at Dartmouth (MIND) 2018 Computational Summer School

We are delighted to announce our second Methods in Neuroscience at Dartmouth (MIND) Computational Summer School, to be held July 30-August 7, 2018. The theme of this year's summer school is Narratives and Naturalistic Contexts.

There has been renewed interest in extending the study of neural and psychological phenomena in highly controlled laboratory settings to more naturalistic paradigms that more closely reflect the rich spatiotemporal structure of the real world.  Bridging this divide requires developing new experiments and analytic methods. The goal of our summer school is to provide a forum for gaining hands-on experience with some of the latest computational tools that can help gain insight into understanding how our brains process naturalistic stimuli and contexts. We will offer a mix of expertise at a broad range of spatiotemporal scales and domains (e.g. behavioral, cognitive, social; circuit, whole-brain, and social networks; etc.). In addition, we will maintain our special focus on training students to use and contribute to open-source tools, data sharing, and other “best practices” for open science.

Methods in Neuroscience at Dartmouth (MIND) 2017 Computational Summer School

We are delighted to announce our inaugural Methods in Neuroscience at Dartmouth (MIND) Computational Summer School, to be held August 13-20. The theme of this year's summer school is Network Dynamics at Multiple Spatiotemporal Scales. 

There is a growing gap between how graduate students in psychology and neuroscience are trained and what they actually need to know to do cutting edge work.  In addition, there is increasing interest in supplementing the traditional reductionist approach to studying the elements of brain, cognition, and behavior in isolation, to integrating how these elements interact as a cohesive complex system. This entails considering not just which elements in a network interact, but also the content of the interaction, and the dynamics of how this information flows through networks over time. This general issue is present in multiple domains, with an accompanying need for similar tools: neurophysiologists studying spiking activity in ensembles of single neurons, cognitive neuroscientists studying whole-brain activity levels, and social psychologists studying group interactions.