A roadmap for focused ultrasound applications in psychiatry: Proceedings of the 2024 symposium on focused ultrasound in psychiatry (FUS-PULSE)
Bibliographic record
Abstract
Transcranial focused ultrasound (FUS) is an emerging neuromodulation modality that enables incisionless, spatially precise targeting of deep brain structures implicated in neuropsychiatric conditions. Growing clinical applications in FUS psychiatry encompass both transient and permanent bioeffects, including focal lesioning, neurostimulation, and targeted drug delivery. In response to rapid advances in the field, an in-person multidisciplinary symposium, FUS-PULSE, was held in Toronto, Canada from June 5-7 2024. The meeting convened over 70 international experts across neurosurgery, psychiatry, neurology, psychology, radiology, neuroimaging, physics, and industry to evaluate critical challenges and chart a strategic path forward for the field of FUS psychiatry. Key themes from FUS-PULSE are highlighted, including the need to integrate circuit-based precision psychiatry, navigating the evolving landscape of FUS devices and parameters, and advancing clinical applications across lesioning, neuromodulation, and drug delivery. FUS-based interventions can complement existing behavioral, pharmacological and neuromodulatory treatments to expand options for patients with refractory psychiatric conditions. However, significant barriers remain in optimizing the technology including treatment parameters and developing clinical protocols. The field must prioritize standardized reporting methodologies, protocol harmonization and real-time monitoring of target engagement. High-intensity FUS lesioning, particularly targeting the anterior limb of the internal capsule, shows promise for major depressive disorder and obsessive-compulsive disorder. Advancements in microbubble-assisted lesioning techniques and target mapping for optimal clinical response will further expand targeting possibilities and improve treatment efficacy. FUS neuromodulation and drug delivery applications remain at an early stage of development with promising potential. A deeper understanding of bioeffects across devices, parameters, and brain targets will be critical for successful clinical translation.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".