Contact Information

Traumatic Injury Research Program


Uniformed Services University of the Health Sciences
4301 Jones Bridge Road
Bethesda, Maryland 20814
MEM Office: C1039
Phone (301) 295-3720
Toll Free: (888) 826-3126
FAX (301) 295-6773

Contact Information

Paul Rapp, Ph.D.
Email: paul.rapp@usuhs.edu
Phone: (301) 295-3590
Fax: (301) 295-6773
Bibliography

David Keyser, Ph.D.
Email: david.keyser@usuhs.edu
Phone: (301) 295-3467
Fax: (301) 295-6773
Bibliography

Kylee Bashirelahi, B.S.
Email: kylee.bashirelahi.ctr@usuhs.edu
Phone: (301) 319-4249
Fax: (301) 295-6773

Dominic Nathan, Ph.D.
Email: dominic.nathan.ctr@usuhs.edu
Phone: (301) 295-9376
Fax: (301) 295-6773
Bibliography

Dynamical Analysis

Participants

  • Alfonso M. Albano, Ph.D. Bryn Mawr College (Emeritus)recent papers
  • Christopher J. Cellucci, Ph.D. Aquinas LLC recent papers
  • Paul E. Rapp, Ph.D., Uniformed Services University (Group Leader) recent papers

Measuring Synchronization

It has been hypothesized that cognitive processes are implemented by transient coalitions of neurons formed by the synchronization of neural oscillators. In the specific context of traumatic brain injury, it is hypothesized that the loss of connectivity and diffuse neuron loss can result in the failure to form these synchronous networks. It is further hypothesized that these network failures will be reflected in abnormalities in event-related synchronization and desynchronization and in abnormalities of inter-regional synchronization of brain electrical activity. The effects of severe blast-induced injury are immediately obvious. In contrast, the effects of intermediate and low-level exposure, which can nonetheless become very serious, are not always obvious at the time of injury. Animal studies indicate that diffuse axonal injury can progress for up to a year following injury. This is consistent with clinical experience.

Concept Map for Oscillatory Synchronization: The concept map shows the relationships between different mathematical procedures for characterizing synchronization. The procedures in the left branch are used to quantify stimulus-dependent changes in a signal recorded at a single electrode. Multichannel synchronization procedures are used to quantify phase relationship between signals recorded simultaneously at different electrode sites.

Concept Map for Oscillatory Synchronization: The concept map shows the relationships between different mathematical procedures for characterizing synchronization. The procedures in the left branch are used to quantify stimulus-dependent changes in a signal recorded at a single electrode. Multichannel synchronization procedures are used to quantify phase relationship between signals recorded simultaneously at different electrode sites.

Detecting Transitions

Mental chronometry, the study of the structure of stimulus-response coupling in speeded decision-making processes, is an extremely active area of research in contemporary cognitive psychology. In the past, research in this area was implemented in reaction time studies. Over the past 30 years, measures of reaction time have been combined with measures of ERP activity to increase the precision with which mental chronometric processes can be articulated. The power of this combined experimental approach can be augmented by the application of mathematical techniques to identify stimulus- and response-dependent transitions in brain electrical behavior. Subtle changes in transition dynamics may be diagnostic of early stage mild traumatic brain injury. This mathematical work is an essential component of our research efforts.

Concept Map for Transition Detection: This concept map presents procedures for detecting dynamically significant transitions in EEG and ERP signals. Six principal subgroups are shown. More than one method can be combined to increase the resolving power of the analysis.

Concept Map for Transition Detection: This concept map presents procedures for detecting dynamically significant transitions in EEG and ERP signals. Six principal subgroups are shown. More than one method can be combined to increase the resolving power of the analysis.

Quantifying Causality

Between channel measures like mutual information, correlation and spectral coherence can identify the presence of a nonrandom relationship between two signals, for example between ERPs recorded at two electrodes. However, these measures do not provide an indication of causal relationships, that is, the direction of control. Procedures for examining causality are being developed and applied to electrophysiological data. As in the case of synchronization and transition dynamics, abnormalities in causal relationships may follow brain injury.

Concept Map for Quantifying Causality: Causality measures are used to identify control relationships between signals. Three principal groups of measures based on linear regression, information theory and the geometry of embedded data are being examined. Causality analysis should be preceded by an examination of transition chronometry in order to identify dynamically homogeneous subepochs.

Concept Map for Quantifying Causality: Causality measures are used to identify control relationships between signals. Three principal groups of measures based on linear regression, information theory and the geometry of embedded data are being examined. Causality analysis should be preceded by an examination of transition chronometry in order to identify dynamically homogeneous subepochs.