Evidence map›Paper›PMID 32434212›Full record

ArticleNeuropsychopharmacology : official publication of the American College of Neuropsychopharmacology2020

Functional connectivity underpinnings of electroconvulsive therapy-induced memory impairments in patients with depression.

Danhong Wang, Yanghua Tian, Meiling Li, Louisa Dahmani, Qiang Wei, Tongjian Bai, Franziska Galiè, Jianxun Ren, Rai Khalid Farooq, Kangcheng Wang and 3 more

Open access · bronzeAbstract read
In one paragraph

Article in Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
2.7field-weighted citation impact, top 9% 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

18 citing papers in PubMed, 33 citations in OpenAlex.

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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

13 authors at 5 institutions in 3 countries.

Danhong Wang *Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.
Yanghua Tian *Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Meiling Li *Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.
Louisa Dahmani *Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.
Qiang WeiDepartment of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Tongjian BaiDepartment of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Franziska GalièAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.
Jianxun RenAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.
Rai Khalid FarooqInstitute for Research and Medical Consultations, Imam Abdulahman Bin Faisal University, Dammam, Saudi Arabia.
Kangcheng WangAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.
Jie LuDepartment of Radiology, Xuanwu Hospital, Beijing, China.
Kai WangDepartment of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China. wangkai1964@126.com.
Hesheng LiuAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA. hesheng.liu@mgh.harvard.edu.ORCID http://orcid.org/0000-0002-7233-1509
Harvard University · USAnhui Medical University · CNBeijing Xuanwu Traditional Chinese Medicine Hospital · CNImam Abdulrahman Bin Faisal University · SAMedical University of South Carolina · US

Funding

The neural network of OCD, linking NHP and human studiesP50MH106435 · NIMH · UNIVERSITY OF ROCHESTER · PI LISA D NICKERSON · 2015 to 2026
$28.9M
COCA: Project 4. Neurocircuit Strategy to Decrease Cocaine Cue ReactivityP50DA046373 · NIDA · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI HANLON, COLLEEN A · 2019 to 2023
$9.9M
Mapping the intrinsic functional organization of auditory cortex in individual subjects using 7T MRIR01DC017991 · NIDCD · MASSACHUSETTS GENERAL HOSPITAL · PI AHVENINEN, JYRKI · 2019 to 2023
$4.0M
Translating The Individualized Functional Connectome To Surgical PlanningR01NS091604 · NINDS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI LIU, HESHENG · 2015 to 2019
$2.1M
Understanding Functional Connectivity Abnormalities In Individual Patients with PsychosisK01MH111802 · NIMH · MASSACHUSETTS GENERAL HOSPITAL · PI WANG, DANHONG · 2017 to 2021
$931k
Cerebro-cerebellar circuitry in the pathophysiology of auditory hallucinations: dysmetria of auditory perceptual processing?R21MH121831 · NIMH · MCLEAN HOSPITAL · PI LIU, HESHENG, SHINN, ANN KYUNGAH · 2019 to 2020
$451k
National Natural Science Foundation of China (National Science Foundation of China) 81790650National Natural Science Foundation of China (National Science Foundation of China) 81790652NIDA NIH HHS P50 DA046373NIDCD NIH HHS R01 DC017991NIMH NIH HHS K01 MH111802NIMH NIH HHS P50 MH106435NIMH NIH HHS R21 MH121831NINDS NIH HHS R01 NS091604U.S. Department of Health & Human Services | National Institutes of Health (NIH) K01MH111802U.S. Department of Health & Human Services | National Institutes of Health (NIH) P50MH106435U.S. Department of Health & Human Services | National Institutes of Health (NIH) R01NS091604
6 · The paper itself

Abstract

Electroconvulsive therapy (ECT) is an effective treatment for severe medication-resistant depression. However, ECT frequently results in episodic memory impairments, causing many patients to discontinue treatment. The objective of this study was to explore the functional connectivity underpinnings of ECT-induced episodic memory impairments. We investigated verbal episodic memory and intrinsic functional connectivity in 24 patients with depression (13F, 11M) before and after ECT, and 1 month after treatment. We used a novel individual-oriented approach to examine functional connectivity, and trained a linear support vector regression model to estimate verbal memory performance based on connectivity. The model identified a set of brain connections that can predict baseline verbal memory performance (r = 0.535, p = 0.026). Importantly, we found a nonoverlapping set of brain connections whose changes after ECT can track patients' verbal memory impairments (r = 0.613, p = 0.008). These connections mainly involve the frontoparietal control, default mode, and hippocampal networks, suggesting that ECT affects broad functional networks that are involved in memory performance. In contrast, functional connectivity defined using traditional group-level analyses was unable to estimate either baseline memory performance or post-ECT verbal memory impairments. A parallel analysis using the same strategy did not identify a connectivity marker for overall mood improvement, suggesting that functional connectivity changes related to depressive symptoms may be highly heterogenous. Our findings shed light on the mechanism through which ECT impairs episodic memory, and additionally underline the importance of accounting for interindividual variability in the investigation of functional brain organization in patients with depression.

Indexed as

Electroconvulsive TherapyBrainBrain MappingDepressionHumansMagnetic Resonance ImagingTreatment Outcome

Identifiers

PMID32434212
PMCPMC7360738
OpenAlexW3027567188

What OpenQuestion holds

Textmetadata
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.