Real-World Neuroimaging Technologies

Abstract

Decades of heavy investment in laboratory-based brain imaging and neuroscience have led to foundational insights into how humans sense, perceive, and interact with the external world. However, it is argued that fundamental differences between laboratory-based and naturalistic human behavior may exist. Thus, it remains unclear how well the current knowledge of human brain function translates into the highly dynamic real world. While some demonstrated successes in real-world neurotechnologies are observed, particularly in the area of brain-computer interaction technologies, innovations and developments to date are limited to a small science and technology community. We posit that advancements in real world tools for use by a broad-based workforce will dramatically enhance applications that have the potential to radically alter human-system interactions across all aspects of everyday life. We discuss the efforts of a joint government-academic-industry team to take an integrative, interdisciplinary, and multi-aspect approach to translate current technologies into devices that are truly wieldable across a range of environments. Results from initial work, described here, show promise for dramatic advances in the field that will rapidly enhance our ability to assess brain activity in real-world scenarios.

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Document Details

Document Type
Technical Report
Publication Date
May 10, 2013
Accession Number
ADA606616

Entities

People

  • Chin-Teng Lin
  • Kaleb Mcdowell
  • Keith W. Whitaker
  • Kelvin S. Oie
  • Shao-wei Lu
  • Shih-Yu Li
  • Stephen M. Gordon
  • Tzyy-Ping Jung
  • W. D. Hairston

Organizations

  • University of California, San Diego

Tags

Communities of Interest

  • Advanced Electronics
  • Autonomy
  • Human Systems
  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Cognitive Science
  • Cognitive Systems Engineering
  • Computational Science
  • Electrical Engineering
  • Engineers
  • Health Services
  • Human Systems Integration
  • Human-Computer Interaction
  • Information Science
  • Information Systems
  • Machine Learning
  • Medical Personnel
  • Neuroimaging
  • Neurotechnology
  • Psychology
  • Supervised Machine Learning
  • Virtual Reality

Fields of Study

  • Computer science

Readers

  • Sensor Fusion and Tracking Systems.
  • Systems Analysis and Design
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.