Evidence map›Paper›PMID 38657038›Full record

ReviewAccounts of chemical research2024

Force-Based Neuromodulation.

Lauren Cooper, Marigold Gil Malinao, Guosong Hong

Abstract readReview
In one paragraph

Review in Accounts of chemical research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Organoid Brain-Machine-Interface Devices for Central Nervous System Repair.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  2. Review
  3. Review
  4. Genetics-Based Targeting Strategies for Precise Neuromodulation.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Lauren CooperDepartment of Mechanical Engineering, Stanford University, Stanford, California 94305, United States.
Marigold Gil MalinaoWu Tsai Neurosciences Institute, Stanford University, Stanford, California 94305, United States.
Guosong HongWu Tsai Neurosciences Institute, Stanford University, Stanford, California 94305, United States.ORCID 0000-0002-8858-4471

Funding

Graduate Training Program in BiotechnologyT32GM141819 · NIGMS · STANFORD UNIVERSITY · PI Eric Andrew Appel, Fan Yang · 2021 to 2026
$1.9M
Rapid brain-wide optogenetic screening with a noninvasive, dynamically programmable in vivo light sourceRF1NS126076 · NINDS · STANFORD UNIVERSITY · PI BUTTS-PAULY, KIM, CHEN, XIAOKE · 2022 to 2022
$1.8M
NIGMS NIH HHS T32 GM141819NINDS NIH HHS RF1 NS126076
6 · The paper itself

Abstract

Technologies for neuromodulation have rapidly developed in the past decade with a particular emphasis on creating noninvasive tools with high spatial and temporal precision. The existence of such tools is critical in the advancement of our understanding of neural circuitry and its influence on behavior and neurological disease. Existing technologies have employed various modalities, such as light, electrical, and magnetic fields, to interface with neural activity. While each method offers unique advantages, many struggle with modulating activity with high spatiotemporal precision without the need for invasive tools. One modality of interest for neuromodulation has been the use of mechanical force. Mechanical force encapsulates a broad range of techniques, ranging from mechanical waves delivered via focused ultrasound (FUS) to torque applied to the cell membrane.Mechanical force can be delivered to the tissue in two forms. The first form is the delivery of a mechanical force through focused ultrasound. Energy delivery facilitated by FUS has been the foundation for many neuromodulation techniques, owing to its precision and penetration depth. FUS possesses the potential to penetrate deeply (∼centimeters) into tissue while maintaining relatively precise spatial resolution, although there exists a trade-off between the penetration depth and spatial resolution. FUS may work synergistically with ultrasound-responsive nanotransducers or devices to produce a secondary energy, such as light, heat, or an electric field, in the target region. This layered technology, first enabled by noninvasive FUS, overcomes the need for bulky invasive implants and also often improves the spatiotemporal precision of light, heat, electrical fields, or other techniques alone. Conversely, the second form of mechanical force modulation is the generation of mechanical force from other modalities, such as light or magnetic fields, for neuromodulation via mechanosensitive proteins. This approach localizes the mechanical force at the cellular level, enhancing the precision of the original energy delivery. Direct interaction of mechanical force with tissue presents translational potential in its ability to interface with endogenous mechanosensitive proteins without the need for transgenes.In this Account, we categorize force-mediated neuromodulation into two categories: 1) methods where mechanical force is the primary stimulus and 2) methods where mechanical force is generated as a secondary stimulus in response to other modalities. We summarize the general design principles and current progress of each respective approach. We identify the key advantages of the limitations of each technology, particularly noting features in spatiotemporal precision, the need for transgene delivery, and the potential outlook. Finally, we highlight recent technologies that leverage mechanical force for enhanced spatiotemporal precision and advanced applications.

Indexed as

Ultrasonic WavesAnimalsHumans

Identifiers

PMID38657038
PMCPMC11401649

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.