Conference on Cognitive Computational Neuroscience

Abstract

Cognitive Computational Neuroscience (CCN) is an annual scientific meeting for neuroscientistscharacterizing the neural computations that underlie complex behavior. The goal is to develop computationally defined models of brain information processing that explain rich measurements of brain activity and behavior. Such models will ultimately have to perform feats of intelligence such as perception, internal modelling and memory of the environment, decision-making, planning, action, and motor control under naturalistic conditions. Historically, differentdisciplines have met subsets of these goals. Cognitive science has developed computational models at the cognitive level to explain aspects of complex behavior. Computational neuroscience has developed neurobiologically plausible computational models to explain neuronal responses to sensory stimuli and certain low-dimensional decision, memory, andcontrol processes. Cognitive neuroscience has mapped a broad range of cognitive processes onto brain regions. Artificial intelligence has developed models that perform feats of intelligence. The community must now put the pieces of the puzzle together, and CCN is unique in its focus on the intersection between these fields. CCN is envisioned not only as an engine for advancingresearch, but as a vehicle for making broader impacts on education and society. As evidenced by the recent trend of major corporate acquisitions of AI startups founded by neuroscientists, biological inspiration for electronics and software development is a growing trend with significant economic implications. In its early stages, the broader impact focus of CCN will be on increasing the visibility of female and underrepresented-minority scientists via speaking opportunities and travel awards; as another contribution toward this impact, the female fractions on the steering committee (4 of 9) and advisory committee (7 of 18) exceed those typical inrelevant fields~without compromise in qualifications. Conferences will include hands-on tutorials, and materials from these will propagate to various university curricula.

Document Details

Document Type
DoD Grant Award
Publication Date
Mar 03, 2017
Source ID
N000141712226

Entities

People

  • Alyson Fletcher

Organizations

  • Office of Naval Research
  • United States Navy
  • University of California, Los Angeles

Tags

Readers

  • Distributed Systems and Data Platform Development
  • Neuroscience
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy
  • Microelectronics