HPEN Scientific Community

We are building a non-profit interdisciplinary scientific community and a prototype system to increase the capacity for data-intensive research in the social, behavioral, and economic sciences. The emphasis is placed on converging resources and integrating scientific theoretical knowledge and methodologies from three main disciplinary fields: High Performance Computing (HPC), psychology, and the neurosciences. The ultimate goal is to facilitate large-scale data access, and develop next-generation open-source data resources and relevant analytic techniques to advance basic scientific knowledge and education across multiple disciplinary fields by enabling new types of high-performance computing and data-intensive research enterprises.


Understanding the brain mechanisms underlying social interaction represents an interdisciplinary effort that addresses one of the major scientific problems in the 21st century.  Neuroimaging has made it possible to exam the working brain in normal individuals, but among the limitations of most functional magnetic resonance imaging (fMRI) studies are the reliance on small numbers of participants (i.e., low statistically powered studies) and the information it provides about how functionally segregated regions are temporally structured and communicate with each other.


We seek to develop working prototypes for high-performance computing and data-intensive processing and imaging that will make tractable large-sample and otherwise computationally prohibitive analysis techniques, with an emphasis in Phase I of this initiative on high-density electrical neuroimaging to help address the limitations of fMRI. Specifically, we seek to build an interdisciplinary community of social, behavioral, and economic scientists, neuroscientists, and computer scientists who would work with this prototype and become involved in the design of both an open-source computing framework for electrical neuroimaging and a data repository that would facilitate large-scale sample high-performance data analyses of brain-behavior relationships.


This platform would promote transformational capabilities in functional neuroimaging and high density EEG/ERP data processing by establishing a common protocol and sharing mechanism for research data sets regardless of the location of data collection. 

These capacities would be designed to be compatible with and to complement existing open-source neuroimaging packages (e.g., SPM) and fMRI data repositories.