The Army Research Laboratory’s Neuroscience program seeks to enable revolutionary advances in Soldier-system performance by integrating modern neuroscience with human factors, cognitive science, and engineering to both enhance our understanding of Soldier function in complex operational settings and develop novel and effective means to enhance systems design. ARL’s neuroscience efforts focus on the scientific study of the brain and its interaction with technology. We are looking for post-doctoral colleagues to advance efforts in two major areas: (1) brain computer-interaction technologies and (2) brain structure-function couplings.
(1) Our laboratory is currently investigating applications of behavioral and neurophysiology measures in real-world applications such as driving and human-robot interaction using advanced machine learning techniques and electroencephalography. The successful applicant will work to characterize and integrate militarily-relevant data obtained from multiple measures and environments to develop real-time classification algorithms and implement those algorithms within cutting edge brain-computer interaction technologies. Representative measures include, but are not limited to, EEG, EMG, ECG, GSR, eye-tracking, vehicle dynamics, and behavioral responses.
(2) Recent advancements in neuroimaging methodologies have enabled the study of how individual differences in brain structure are coupled with individual differences in task performance (or brain function, more generally). One prominent approach to study couplings between brain structure and brain function uses a graph-theoretic approach. Here, the brain regions are treated as the nodes on a graph, and with connections between brain regions treated as the graph edges. These connections can be based on structural connections from the structural imaging data or the connections based on statistical correlations between regions from functional imaging data. We are currently exploring both fMRI and EEG functional and effective connectivity measures to investigate couplings with individual variations in structure.
