qEEG in freely behaving people

Summary

Principal Investigator: Jose Luis Contreras-Vidal, University of Houston
Title: Assaying neural individuality and variation in freely behaving people based on qEEG
BRAIN Category: Individuality and Variation

The goals of this research are to uncover neural signals associated with the passive and interactive perception/production of art and to assess the long-term stability of neural activity acquired via quantitative electroencephalography (or qEEG).

Principal Investigator: Jose Luis Contreras-Vidal, University of Houston Neuroscience
Title:  Assaying neural individuality and variation in freely behaving people based on qEEG
BRAIN Category: Individuality and Variation

The goals of this research are to uncover neural signals associated with the passive and interactive perception/production of art and to assess the long-term stability of neural activity acquired via quantitative electroencephalography (or qEEG).

Image from article "Your Brain on Dance: Professors make art from science"

Image from article “Your Brain on Dance: Professors make art from science”

Abstract

Award Number:#1533691

This project will deploy noninvasive Mobile Brain-body Imaging devices (MoBI) in a public museum with the goal of assaying individuality and variation in neural activity as it occurs (e.g., “in action and context”) in a large and diverse group of people, including children, experiencing fixed and interactive art exhibits. A natural setting such as an art museum attracts thousands of people with rich demographic factors such as age, sex, education level, occupation, and other factors such as health, medication and neurological status, thereby providing a unique opportunity to study the population distribution, accuracy and stability of neural activity and advance understanding of the dynamics of complex neural and cognitive systems in natural environments. The broader impacts of this research include integrating the arts, science and engineering to advance brain science; advancing the regulatory science of biomedical devices by uncovering biometric neural data as objective endpoints to investigate cognition, perception and action; supporting and promoting STEM education, and advancing the field through dissemination and data sharing of products generated in this research. Importantly, the efficacy and related safety of MoBI-based diagnostics and therapeutics depend on scientific understanding of neural variability and individuality. In the same way that individual variation in gene sequences makes certain drugs more or less effective for certain people, giving rise to the need for pharmacogenomics, individual variation in brain activity will not only affect the assessment of drugs which use these endpoints, but will also strongly affect the safety and efficacy of therapeutic medical devices. Despite this critical importance, there is no concerted effort elsewhere to address these basic questions that are holding back the research and development of novel noninvasive biomedical devices with all of its diagnostic benefits that could also contribute to reverse engineer brain mechanisms.

A big-data analytics approach for investigating neural variability and individuality in brain data from a large number of diverse participants could help advance development of biomedical devices while filling knowledge gaps in brain science. Three research objectives will be pursued to produce this science while developing novel tools for discovery. First, this project entails the acquisition of multi-modal data from a thousand participants from the diverse Greater Houston area. Second, the research will develop novel algorithms for analyzing, inspecting, visualizing, representing, parsing, and searching high-dimensional patterns from the multi-modal datasets acquired in a public setting at the Blaffer museum. The goals are to uncover neural signals associated with the passive and interactive perception/production of art and to assess the long-term stability of neural activity acquired via quantitative electroencephalography (or qEEG). The proposed project will lead to innovative time-resolved methods and tools to study the population distribution, accuracy and stability of neural activity. Third, the project will generate a unique big dataset, and algorithms that will be shared with the scientific community. This research opens new scientific and educational horizons for addressing empirical problems (e.g., the acquisition of multimodal data from freely behaving subjects in public settings), and normative problems (e.g., decoding human intent and emotion from patterns of brain activity) in science. Moreover, the project will enable K-12 to postdoctoral training of a diverse population of students/trainees.

NSF Project Information

NSF webpage:  http://www.nsf.gov/awardsearch/showAward?AWD_ID=1533691&HistoricalAwards=false

NSF Org: BCS    Division Of Behavioral and Cognitive Sci

Start Date:  September 1, 2015      End Date: August 31, 2016(Estimated)

Awarded Amount to Date: $300,000.00

Investigator(s): Jose Contreras-Vidal jlcontreras-vidal@uh.edu (Principal Investigator)
Badrinath Roysam (Co-Principal Investigator)
Saurabh Prasad (Co-Principal Investigator)

NSF Program(s): BIOMEDICAL ENGINEERING, IntgStrat Undst Neurl&Cogn Sys

Program Reference Code(s): 004E, 8089, 8091, 8551

Sponsor: University of Houston
4800 Calhoun Boulevard
Houston, TX 77204-2015 (713)743-5773

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