Evidence map›Paper›PMID 38546337›Full record

ArticleeLife2024

Neurophysiological trajectories in Alzheimer's disease progression.

Kiwamu Kudo, Kamalini G Ranasinghe, Hirofumi Morise, Faatimah Syed, Kensuke Sekihara, Katherine P Rankin, Bruce L Miller, Joel H Kramer, Gil D Rabinovici, Keith Vossel and 2 more

Open access · goldAbstract read
In one paragraph

Article in eLife, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
1.2field-weighted citation impact, top 20% 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

20 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.

  1. Tracking electrophysiological signatures of Alzheimer's disease: a systematic review of multimodal studies.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors at 2 institutions in 2 countries.

Kiwamu Kudo *Biomagnetic Imaging Laboratory, Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, United States.ORCID https://orcid.org/0000-0002-5732-7229
Kamalini G Ranasinghe *Memory and Aging Center,UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, United States.ORCID https://orcid.org/0000-0002-4217-8785
Hirofumi MoriseBiomagnetic Imaging Laboratory, Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, United States.
Faatimah SyedMemory and Aging Center,UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, United States.
Kensuke SekiharaSignal Analysis Inc, Hachioji, Japan.
Katherine P RankinMemory and Aging Center,UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, United States.
Bruce L MillerMemory and Aging Center,UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, United States.
Joel H KramerMemory and Aging Center,UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, United States.
Gil D RabinoviciMemory and Aging Center,UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, United States.
Keith VosselMemory and Aging Center,UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, United States.
Heidi E KirschBiomagnetic Imaging Laboratory, Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, United States.
Srikantan S NagarajanBiomagnetic Imaging Laboratory, Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, United States.ORCID https://orcid.org/0000-0001-7209-3857
University of California, San Francisco · USUniversity of California, Los Angeles · US

Funding

Research Education ComponentP30AG062422 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Jennifer S Yokoyama · 2019 to 2026
$36.9M
Understanding disorder-specific neural pathophysiology in laryngeal dystonia and voice tremorP50DC019900 · NIDCD · MASSACHUSETTS EYE AND EAR INFIRMARY · PI Kristina Simonyan · 2021 to 2026
$11.9M
The role of the cerebellum in speechR01DC017091 · NIDCD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI John Francis Houde, RICHARD IVRY · 2019 to 2026
$4.5M
Dynamic Brain Imaging of Speech in Primary Progressive AphasiaR01NS100440 · NINDS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MARIA LUISA GORNO TEMPINI, John Francis Houde · 2017 to 2026
$3.6M
Network Modelling of Multimodal Dynamics in Alzheimer’s Disease and DementiaRF1AG062196 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI NAGARAJAN, SRIKANTAN S., RAJ, ASHISH · 2019 to 2019
$3.0M
Dynamic Brain Imaging of Speech in Primary Progressive AphasiaRF1NS100440 · NINDS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GORNO TEMPINI, MARIA LUISA, HOUDE, JOHN FRANCIS · 2023 to 2023
$2.4M
Neurophysiological Assessments of Network Dysfunction in Alzheimer's DiseaseK08AG058749 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI RANASINGHE, KAMALINI GAYATHREE · 2019 to 2023
$859k
Mechanisms and Treatment of Network Dysfunction in Alzheimer's DiseaseK23AG038357 · NIA · J. DAVID GLADSTONE INSTITUTES · PI VOSSEL, KEITH ALAN · 2011 to 2015
$764k
Multimodal imaging measures to assess synaptic dysfunction in Alzheimer's diseaseR21AG077498 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI RANASINGHE, KAMALINI GAYATHREE · 2022 to 2022
$484k
Alzheimer's Association AARG-21-849773Alzheimer's Association PCTRB-13-288476 made possible by Part the CloudTMNIA NIH HHS K08 AG058749NIA NIH HHS K23 AG038357NIA NIH HHS P30 AG062422NIA NIH HHS R21 AG077498NIA NIH HHS RF1 AG062196NIDCD NIH HHS P50 DC019900NIDCD NIH HHS R01 DC017091NIH HHS K08AG058749NIH HHS K23AG038357NIH HHS P30AG062422NIH HHS P50DC019900NIH HHS R01AG062196NIH HHS R01DC017091NIH HHS R01NS100440NIH HHS R21AG077498NINDS NIH HHS R01 NS100440NINDS NIH HHS RF1 NS100440
6 · The paper itself

Abstract

Alzheimer's disease (AD) is characterized by the accumulation of amyloid-β and misfolded tau proteins causing synaptic dysfunction, and progressive neurodegeneration and cognitive decline. Altered neural oscillations have been consistently demonstrated in AD. However, the trajectories of abnormal neural oscillations in AD progression and their relationship to neurodegeneration and cognitive decline are unknown. Here, we deployed robust event-based sequencing models (EBMs) to investigate the trajectories of long-range and local neural synchrony across AD stages, estimated from resting-state magnetoencephalography. The increases in neural synchrony in the delta-theta band and the decreases in the alpha and beta bands showed progressive changes throughout the stages of the EBM. Decreases in alpha and beta band synchrony preceded both neurodegeneration and cognitive decline, indicating that frequency-specific neuronal synchrony abnormalities are early manifestations of AD pathophysiology. The long-range synchrony effects were greater than the local synchrony, indicating a greater sensitivity of connectivity metrics involving multiple regions of the brain. These results demonstrate the evolution of functional neuronal deficits along the sequence of AD progression.

Indexed as

Alzheimer DiseaseAmyloid beta-PeptidesBenchmarkingBrainHumanstau ProteinsAmyloid beta-Peptidestau ProteinsAlzheimer's diseasebiomarkerselectrophysiologyfunctional connectivityhumanmagnetoencephalographyneuroscience

Identifiers

PMID38546337
PMCPMC10977971
OpenAlexW4387448082

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.