Evidence map›Paper›PMID 37363755›Full record

ArticleFrontiers in pain research (Lausanne, Switzerland)2023

Network targets for therapeutic brain stimulation: towards personalized therapy for pain.

Julian C Motzkin, Ishan Kanungo, Mark D'Esposito, Prasad Shirvalkar

Open access · goldAbstract read
In one paragraph

Article in Frontiers in pain research (Lausanne, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
3.3field-weighted citation impact, top 7% of its field
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

12 citing papers in PubMed, 19 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Mimicking opioid analgesia in cortical pain circuits.bioRxiv : the preprint server for biology · 2025
    Article
  9. Pathophysiology and Management of Refractory Trigeminal Neuralgia.Current neurology and neuroscience reports · 2024
    Review
  10. Review
  11. Review
  12. Article
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

4 authors at 3 institutions in 1 country.

Julian C MotzkinDepartments of Neurology and Anesthesia and Perioperative Care (Pain Management), University of California, San Francisco, San Francisco, CA, United States.
Ishan KanungoDepartment of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States.
Mark D'EspositoDepartment of Psychology, University of California, Berkeley, Berkeley, CA, United States.
Prasad ShirvalkarDepartments of Neurology and Anesthesia and Perioperative Care (Pain Management), University of California, San Francisco, San Francisco, CA, United States.
University of California, San Francisco · USNeurological Surgery · USUniversity of California, Berkeley · US

Funding

NINDS Research Education Programs for Residents and Fellows in Neurology, Neurosurgery, Neuropathology, Neuroradiology and Emergency Medicine (R25)R25NS070680 · NINDS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI JOSEPHSON, SCOTT ANDREW · 2010 to 2023
$6.8M
NINDS NIH HHS R25 NS070680
6 · The paper itself

Abstract

Precision neuromodulation of central brain circuits is a promising emerging therapeutic modality for a variety of neuropsychiatric disorders. Reliably identifying in whom, where, and in what context to provide brain stimulation for optimal pain relief are fundamental challenges limiting the widespread implementation of central neuromodulation treatments for chronic pain. Current approaches to brain stimulation target empirically derived regions of interest to the disorder or targets with strong connections to these regions. However, complex, multidimensional experiences like chronic pain are more closely linked to patterns of coordinated activity across distributed large-scale functional networks. Recent advances in precision network neuroscience indicate that these networks are highly variable in their neuroanatomical organization across individuals. Here we review accumulating evidence that variable central representations of pain will likely pose a major barrier to implementation of population-derived analgesic brain stimulation targets. We propose network-level estimates as a more valid, robust, and reliable way to stratify personalized candidate regions. Finally, we review key background, methods, and implications for developing network topology-informed brain stimulation targets for chronic pain.

Indexed as

chronic paindeep brain stimulation (DBS)graph theorynetwork neuroscienceneuromodulationpainprecision medicinetranscranial magnetic stimulation (TMS)

Identifiers

PMID37363755
PMCPMC10286871
OpenAlexW4380053013

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.