The goal of computational modeling in behavioral and psychological science is using mathematical models to characterize behavioral (or neural) data. Over the past decade, this practice has revolutionized social psychological science (and neuroscience) by allowing researchers to formalize theories as constrained mathematical models and test specific hypotheses to explain unobservable aspects of complex social cognitive processes and behaviors. This course is composed of 4 modules in the format of Jupyter Notebooks. This course comprises lecture-based, discussion-based, and lab-based instruction. At least one-third of class sessions will be hands-on. We will discuss relevant book chapters and journal articles, and work with simulated and real data using the Python programming language (no prior programming experience necessary) as we survey some selected areas of research at the intersection of computational modeling and social behavior. These selected topics will span a broad set of social psychological abilities including (1) learning from and for others, (2) learning about others, and (3) social influence on decision-making and mental states. Rhoads, S. A. & Gan, L. (2022). Computational models of human social behavior and neuroscience - An open educational course and Jupyter Book to advance computational training.  ​​​Journal of Open Source Education, 5(47), 146. https://doi.org/10.21105/jose.00146

This lecture covers visualizing extracellular neurotransmitter dynamics

This brief video provides a welcome and short introduction to the outline of the INCF Short Course in Neuroinformatics, held Seattle, Washington in October 2023, in coordination with the West Big Data Hub and the University of Washington. 

This lecture will provide an overview of the INCF Training Suite, a collection of tools that embraces the FAIR principles developed by members of the INCF Community. This will include an overview of TrainingSpace, Neurostars, and KnowledgeSpace.

The International Brain Initiative (IBI) is a consortium of the world’s major large-scale brain initiatives and other organizations with a vested interest in catalyzing and advancing neuroscience research through international collaboration and knowledge sharing. This workshop introduces the IBI, the efforts of the Data Standards and Sharing Working Group,  and keynote lectures on the impact of data standards and sharing on large-scale brain projects, as well as a discussion on prospects and needs for neural data sharing.