Evidence map›Paper›PMID 37162878›Full record

ArticlemedRxiv : the preprint server for health sciences2023

A generalizable functional connectivity signature characterizes brain dysfunction and links to rTMS treatment response in cocaine use disorder.

Kanhao Zhao, Gregory A Fonzo, Hua Xie, Desmond J Oathes, Corey J Keller, Nancy Carlisle, Amit Etkin, Eduardo A Garza-Villarreal, Yu Zhang

Open access · greenAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed, 6 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors at 7 institutions in 2 countries.

Kanhao ZhaoDepartment of Bioengineering, Lehigh University, Bethlehem, PA, USA.
Gregory A FonzoCenter for Psychedelic Research and Therapy, Department of Psychiatry and Behavioral Sciences, Dell Medical School, The University of Texas at Austin, TX, USA.
Hua XieCenter for Neuroscience Research, Children's National Hospital, Washington, DC, USA.
Desmond J OathesCenter for Neuromodulation in Depression and Stress, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, PA, USA.
Corey J KellerWu Tsai Neuroscience Institute, Stanford University, Stanford, CA, USA.
Nancy CarlisleDepartment of Psychology, Lehigh University, Bethlehem, PA, USA.
Amit EtkinAlto Neuroscience, Inc., Los Altos, CA, USA.
Eduardo A Garza-VillarrealInstituto de Neurobiología, Universidad Nacional Autónoma de México campus Juriquilla, Querétaro, Mexico.
Yu ZhangDepartment of Bioengineering, Lehigh University, Bethlehem, PA, USA.
Lehigh University · USAlto Neuroscience (United States) · USGeorge Washington University · USMultidisciplinary Association for Psychedelic Studies · USNeurosciences Institute · USUniversidad Nacional Autónoma de México · MXUniversity of Pennsylvania · US

Funding

A “Circuits-First” Platform for Personalized Neurostimulation TreatmentDP1MH116506 · NIMH · STANFORD UNIVERSITY · PI ETKIN, AMIT · 2017 to 2021
$5.2M
1/2 Neurodevelopmental and clinical trajectories of youth at risk for bipolar I disorderR01MH125886 · NIMH · UNIVERSITY OF TEXAS AT AUSTIN · PI ALMEIDA, JORGE R C, STRAKOWSKI, STEPHEN M · 2021 to 2025
$4.3M
Validating of Machine Learning-Based EEG Treatment Biomarkers in DepressionR44MH123373 · NIMH · ALTO NEUROSCIENCE, INC. · PI ETKIN, AMIT · 2020 to 2022
$3.2M
Establishing Multimodal Brain Biomarkers Using Data-driven Analyticsfor Treatment Selection in DepressionR01MH129694 · NIMH · STANFORD UNIVERSITY · PI Yu Zhang · 2023 to 2026
$2.8M
Computational neuroimaging of reward in post-trauma psychopathologyK23MH114023 · NIMH · UNIVERSITY OF TEXAS AT AUSTIN · PI FONZO, GREGORY · 2018 to 2022
$957k
Identifying Transdiagnostic Functional Connectivity Biomarkers for Cognitive Health and PsychopathologyR21MH130956 · NIMH · LEHIGH UNIVERSITY · PI BERDICHEVSKY, YEVGENY · 2023 to 2024
$409k
NIMH NIH HHS DP1 MH116506NIMH NIH HHS K23 MH114023NIMH NIH HHS R01 MH125886NIMH NIH HHS R01 MH129694NIMH NIH HHS R21 MH130956NIMH NIH HHS R44 MH123373
6 · The paper itself

Abstract

Cocaine use disorder (CUD) is a prevalent substance abuse disorder, and repetitive transcranial magnetic stimulation (rTMS) has shown potential in reducing cocaine cravings. However, a robust and replicable biomarker for CUD phenotyping is lacking, and the association between CUD brain phenotypes and treatment response remains unclear. Our study successfully established a cross-validated functional connectivity signature for accurate CUD phenotyping, using resting-state functional magnetic resonance imaging from a discovery cohort, and demonstrated its generalizability in an independent replication cohort. We identified phenotyping FCs involving increased connectivity between the visual network and dorsal attention network, and between the frontoparietal control network and ventral attention network, as well as decreased connectivity between the default mode network and limbic network in CUD patients compared to healthy controls. These abnormal connections correlated significantly with other drug use history and cognitive dysfunctions, e.g., non-planning impulsivity. We further confirmed the prognostic potential of the identified discriminative FCs for rTMS treatment response in CUD patients and found that the treatment-predictive FCs mainly involved the frontoparietal control and default mode networks. Our findings provide new insights into the neurobiological mechanisms of CUD and the association between CUD phenotypes and rTMS treatment response, offering promising targets for future therapeutic development.

Identifiers

PMID37162878
PMCPMC10168499
OpenAlexW4367044754

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.