Neuroenhancement in Military Personnel: Conceptual and Methodological Promises and Challenges
Bibliographic record
Abstract
Military personnel are subjected to prolonged operations in harsh and undesirable conditions characterized by severe environmental exposures, resource scarcity, and physical and mental encumbrance. Prolonged military operations under these conditions can degrade the already limited perceptual, cognitive, and emotional resources necessary to sustain performance on mission-related tasks. The complex multi-domain operations of the future battlespace are expected to further increase demands at even the lowest levels of the military echelon. These demands will be characterized with increasingly prolonged operations of small units in austere environments with limited resupply and degraded technological capabilities. It is therefore critical to identify new training and technological approaches to enable sustained, optimized, and/or enhanced performance of military personnel. Research in the international defence science community, academia, and industry has developed several promising neuroscientific strategies for pursuing this goal, including neuromodulatory and neurofeedback techniques. The present paper reviews the state of the art in cognitive neuroenhancement research and development from six participating nations: Canada, Germany, Italy, The Netherlands, United Kingdom, and the United States of America. Six neuromodulation techniques are reviewed, including transcranial magnetic stimulation (TMS), transcranial focused ultrasound stimulation (tFUS), transcranial electrical stimulation (tES), transcutaneous peripheral nerve stimulation (tPNS), photobiomodulation, and cranial electrotherapy stimulation (CES). Three neurofeedback techniques are considered, including the use of electroencephalography (EEG), functional magnetic resonance imaging (fMRI), and functional near-infrared spectroscopy (fNIRS) for monitoring brain states, with feedback loops enabled through machine learning and artificial intelligence. Participating nations summarize basic and applied research leveraging one or more of these neuromodulation and neurofeedback technologies for the purposes of enhancing Warfighter cognitive performance. The report continues by detailing the inherent methodological challenges of cognitive neuroenhancement and other considerations for conducting research, development, and engineering in this domain. The report concludes with a discussion of promising future directions in neuroenhancement, including biosensing, improved mechanistic and predictive modelling and software tools, developing non-invasive forms of deep-brain stimulation, testing emerging theoretical models of brain and behavior, and developing closed-loop neuroenhancement and humanmachine teaming methods. Emphasis is placed on the conceptual and methodological promises and challenges associated with planning, executing, and interpreting neuroenhancement research and development efforts in the context of Warfighter selection, training, operations, and recovery.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".