KRNS, an IARPA program

The goal of the Knowledge Representation in Neural Systems (KRNS) Program is to develop and rigorously evaluate theories that explain how the human brain represents conceptual knowledge.

In part the evaluation will rest on how well concepts can be interpreted from neural activity patterns using algorithms derived from the theories. In addition to new theories and algorithms, KRNS seeks the development of innovative protocols for evoking and measuring concept-related neural activity using neural imaging methods such as (but not limited to) fMRI, and MEG.

HRL Laboratories – ISSL & CNES

HRL Laboratories's Information and Systems Sciences lab (ISSL) conducts groundbreaking research in neuromorphic computing, robotic manipulation, brain-machine interfaces, trusted computing, multi-sensor object recognition, and automated knowledge and content extraction.

The Center for Neural and Emergent Systems (CNES), part of ISSL, is dedicated to exploring and developing an innovative neural & emergent computing paradigm for creating intelligent, efficient machines that can interact with, react and adapt to, evolve, and learn from their environments.

Catherine Cotell, PhD – IARPA

Director, IARPA Incisive Analysis (IA) Office

Dr. Cotell’s career has been dedicated to delivering innovative technology-based solutions to both the Intelligence Community (IC) and the Department of Defense. Dr. Cotell holds seminal patents in the field of laser deposition of biocompatible coatings for medical implants.

R. Jacob Vogelstein

Program Manager, Office of Safe and Secure Operations, Intelligence Advanced Research Projects Activity (IARPA)
Multi-Council Working Group (staff), BRAIN Initiative

As an IARPA Program Manager, Dr. Vogelstein's areas of interest include neural computing, neuromorphic hardware, neuromimetic algorithms, brain-computer interfaces, neural prosthetics, and other topics in applied neuroscience.

Carnegie Mellon ‘BrainHub’

The Carnegie Mellon University (CMU) BrainHub initiative spans across CMU’s colleges and schools, involving nearly 50 faculty and over 150 scientists.

A major facet of this initiative is increasing collaboration among faculty from disciplines such as computer science and engineering with those taking biological and behavioral approaches to neuroscience. Linking brain science to behavior via the application of machine learning, statistics, and computational modeling will be a hallmark of CMU’s efforts, along with commercialization of the new technologies and applications.

Siemens Healthcare

Dr. Francisco Pereira, staff scientist at Siemens Healthcare, leads the IARPA KRNS team which comprises 12 people across five institutions (Siemens, Princeton University, MIT, MGH and Harvard University).

Their models are based on learning distributed representations of individual words from text corpora, as well as resources such as FrameNet and WordNet, and using recursive neural network approaches and other techniques to assemble them into the representation of a sentence. The models are validated by decoding mental content from brain imaging data acquired with our own experiments.

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