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Description:
This week we are hosting James Hubbard (Texas A&M) and Zhao Sun (Hampton U.) to feature collaboration through our Research Institute in Tactical Autonomy.
Abstract:
The Music of the Mind: A modal approach to mapping and understanding the space time dynamics of human cognition
The long term goal of this work is to develop and refine a rigorous, canonical modelling approach for mapping and analysing spatial-temporal brain wave dynamics, in near real-time, using contemporary biomarkers such as electroencephalogram (EEG). These mappings can then be correlated with human cognitive states like emotions, attention, decision making etc. More specifically the approach involves the use of modern output only system identification techniques to resolve a true state space model with the brain mapping produced as brain wave modal images for analysis. The nonlinear, nonstationary behaviour of the associated brain wave measures and general uncertainty associated with the brain makes it difficult to apply modern system identification techniques to such systems. In preliminary work an adaptive state estimator was introduced to resolve this difficulty and has been shown to produce high fidelity models with less
than 1% error when compared to the concomitant EEG output. While there is a substantial amount of literature on the use of stationary analyses for brain waves, relatively less work has considered the real-time estimation and imaging of brain waves from non-invasive measurements. This work addresses the issue of modelling and imaging brain waves and biomarkers generally, treating the nonlinear and nonstationary dynamics in near real-time. This modal state-space formulation leads to intuitive, physically significant models which has broad applicability for analysis, classification and diagnosis. This research falls under the general category of Engineering Medicine (EnMed). An emerging field of study that can offer new, innovative and effective solutions to modern healthcare challenges. This requires novel approaches that integrate all of science and engineering. The long-term benefits to DoD are broadly in the area of Human Machine Interaction and Teaming, Brain Computer Interfaces and intelligent machine agents. This work will allow these agents to seamlessly integrate with humans while conducting DoD missions.
Key Moments and Questions in the video include:
Introduction on how Dr. Hubbard, an engineer, got into human cognition
Modern Motivations toward BCI/HMI Applications
Human Machine Interaction and Decision Making
Emotions Drive Decision Making
We Need an Analytical Architecture
Valence Arousal Model
Human Cognition and Emotion inform Decision Making
Perhaps there are Cognitive “Eigen” States
Are there analytical EXTENSIONS in Hilbert Space
Jymn’s Definition
EEG and Human Cognition
System Identification and Exotic Aircraft Concepts
Eigen Decomposition and System Identification
A Database for Emotion Analysis Using Physiological Signals: DEAP
Operational Modal Analysis (OMA) is the Key
OMA and Complexity Plots
Model Prediction versus Actual EEG Signal
Proof of Concept via Brain Wave Fingerprinting
The Default Mode network
Real Eigenvectors and EEG
Humans share certain modes
Default Mode Network and Decision making
Traveling Brain Wave Patterns
Relevance to Diagnostics
DEAP Emotion Classification
The Music of the Mind
Mentions of Joy Sun’s collaboration
State Estimation and Sparse Arrays
Questions
| Date Taken: | 06.28.2024 |
| Date Posted: | 08.07.2025 15:23 |
| Category: | Video Productions |
| Video ID: | 973076 |
| VIRIN: | 240628-F-BA826-7347 |
| Filename: | DOD_111217355 |
| Length: | 00:52:17 |
| Location: | US |
| Downloads: | 4 |
| High-Res. Downloads: | 4 |
This work, QuEST (2024-06-28) James Hubbard/Zhao (Joy) Sun - The Music of the Mind, by Kevin D Schmidt, identified by DVIDS, must comply with the restrictions shown on https://www.dvidshub.net/about/copyright.
