ABERDEEN PROVING GROUND, Md. -- The human brain’s activity, in its complexity, cannot be summarized with any single method -- researchers must take into account the chemical, electrical and historical aspects of brain activity -- from neural communication to learning and development.Army scientists from the U.S. Army Combat Capabilities Development Command’s Army Research Laboratory along with academics at the Salk Institute for Biological Studies in La Jolla, California, are researching new methods to characterize brain activity to predict future behavior or cognitive state, borrowing methods from clinical settings. While studying the possibility of a new method of brain dynamics, they said they have been successful in predicting clinical seizures using recording electrodes placed directly on brain tissue.“One low-parameterization method allows us to reduce really complex neural processes to a simpler metric that can predict other neural events much later (~20mins) and it has been developed and used by our collaborators at the Salk,” said Dr. Javier Garcia, a laboratory neuroscience researcher. “In porting this to other interventions, knowing what will happen so far in advance would be hugely beneficial to future technologies, especially if the method is also computationally inexpensive.”However, in trying to translate these algorithms to something that can be used from non-invasive neural (or other physiological) sensors, there are many challenges to overcome, Garcia said.“One field that has really stretched the analytical limits is in seizure prediction,” he said. “We are interested in extending this computational method to scalp recordings which suffer from what we call volume conduction, or what happens to the electrical signals that come from the brain, but are filtered through other tissues (skull, scalp, etc.) and distance, as well as potentially combining the method with other analytical tools such as a computational simulation and modelling of brain networks.”Researchers said they are consistently looking to other methods that may uniquely describe neural behavior to gain predictive power, whether that’s in a variety of tasks, across different environmental contexts or even in different states (e.g., sleepy).“Epileptic seizure is a great model to study the predictive power in neural measurements, because seizure is a dramatic state with already some proven interventions,” Garcia said. “If you imagine moving these methods to other contexts, we might be able to predict complex neural states and then intervene to mitigate behavioral performance degradation with something that is computationally inexpensive and easily integrated into other technologies without time and effort required by other methods.”Researchers want to extend this method beyond what’s been done on brain recording below the scalp and on the brain and said they are trying to tweak it to work on scalp recordings and in everyday human behavior.“Understanding how our thoughts and actions arise from communications within and between brain areas is a major goal in neuroscience,” said Dr. Nuttida Rungratsameetaweemana, recent PhD graduate from The University of California, San Diego and lead author on the work. “To investigate the intricate neural dynamics that underlie these communications, we applied a network science-based computational modelling technique as well as a non-linear dynamical approach to neural data with high spatio-temporal resolution recorded from patients with epilepsy. Our results suggest that seizure-related activities can be indexed not only through network instability but also through an emergence of dynamical chimera states where a certain population of neurons fire in synchrony while the rest remains desynchronized.”This research is a collaborative effort with researchers Prof. Terrence Sejnowski and Dr. Claudia Lainscsek at the Salk Institute for Biological Sciences. Rungratsameetaweemana and the team previously published: Cortical chimera states predict epileptic seizures. Chaos: An Interdisciplinary Journal of Nonlinear Science. 29: 121106.“If these researchers are successful in translating many of these methods to non-invasive scalp measurements of neural activity, we could see high impact in predicting future behavioral outcomes, given physiological measurements, a critical goal in creating future autonomy that may observe, decide and intervene in teams within complex battlefield contexts,” Garcia said.CCDC Army Research Laboratory is an element of the U.S. Army Combat Capabilities Development Command. As the Army’s corporate research laboratory, ARL discovers, innovates and transitions science and technology to ensure dominant strategic land power. Through collaboration across the command’s core technical competencies, CCDC leads in the discovery, development and delivery of the technology-based capabilities required to make Soldiers more lethal to win the nation’s wars and come home safely. CCDC is a major subordinate command of the U.S. Army Futures Command.