Evidence map›Paper›PMID 36993350›Full record

ArticleResearch square2023

Impaired long-range excitatory time scale predicts abnormal neural oscillations and cognitive deficits in Alzheimer's disease.

Parul Verma, Kamalini Ranasinghe, Janani Prasad, Chang Cai, Xihe Xie, Hannah Lerner, Danielle Mizuiri, Bruce Miller, Katherine Rankin, Keith Vossel and 3 more

Open access · greenAbstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in Research square, 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, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors at 4 institutions in 2 countries.

Parul VermaDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA.ORCID 0000-0001-9956-4954
Kamalini RanasingheMemory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA.
Janani PrasadAmador Valley High School, Pleasanton, CA, USA.
Chang CaiDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA.
Xihe XieDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA.
Hannah LernerMemory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA.
Danielle MizuiriDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA.
Bruce MillerMemory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA.
Katherine RankinMemory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA.
Keith VosselMemory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA.
Steven W CheungDepartment of Otolaryngology-Head and Neck Surgery, University of California San Francisco, San Francisco, CA, USA.
Srikantan NagarajanDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA.
Ashish RajDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA.
University of California, San Francisco · USGreen Valley High School · USSan Francisco VA Medical Center · USUniversity of California, Los Angeles · US

Funding

The Human Connectome Project (HCP)U01MH093765 · NIMH · MASSACHUSETTS GENERAL HOSPITAL · PI ROSEN, BRUCE R · 2010 to 2014
$12.1M
Project 4P41EB015896 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI ROSEN, BRUCE R · 2012 to 2018
$9.8M
Understanding the dynamic interactions between tau pathology and microgliamediated inflammation in Alzheimer's DiseaseR01AG072753 · NIA · WEILL MEDICAL COLL OF CORNELL UNIV · PI BUTLER, TRACY A., GUPTA, AJAY · 2021 to 2025
$5.3M
The role of the cerebellum in speechR01DC017091 · NIDCD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI John Francis Houde, RICHARD IVRY · 2019 to 2026
$4.5M
In Vivo Studies of the Epileptic HippocampusRF1NS033310 · NINDS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ENGEL, JEROME NONE, STABA, RICHARD · 2023 to 2023
$3.6M
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
Predictive model of spread of Parkinson's pathology using network diffusionR01NS092802 · NINDS · WEILL MEDICAL COLL OF CORNELL UNIV · PI GUPTA, AJAY, RAJ, ASHISH · 2016 to 2020
$2.8M
A Storage Area Network for Structural and Functional Image AnalysisS10RR023401 · NCRR · MASSACHUSETTS GENERAL HOSPITAL · PI FISCHL, BRUCE · 2009 to 2009
$2.0M
Preventing Seizures and Associated Memory Loss in Alzheimer's Disease by Blocking Tau Interactions with SH3-containing Proteins.R01AG058820 · NIA · UNIVERSITY OF MINNESOTA · PI VOSSEL, KEITH ALAN · 2019 to 2023
$1.9M
Imaging sensorimotor adaptation and compensation of speechR01DC013979 · NIDCD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HOUDE, JOHN FRANCIS, NAGARAJAN, SRIKANTAN S. · 2014 to 2018
$1.7M
Multimodal modeling framework for fusing structural and functional connectome dataR01EB022717 · NIBIB · WEILL MEDICAL COLL OF CORNELL UNIV · PI NAGARAJAN, SRIKANTAN S., RAJ, ASHISH · 2016 to 2018
$1.6M
NCRR NIH HHS S10 RR019307NCRR NIH HHS S10 RR023043NCRR NIH HHS S10 RR023401NIA NIH HHS R01 AG058820NIA NIH HHS R01 AG072753NIA NIH HHS RF1 AG062196NIA NIH HHS UH2 AG083254NIBIB NIH HHS P41 EB015896NIBIB NIH HHS R01 EB022717NIDCD NIH HHS R01 DC013979NIDCD NIH HHS R01 DC017091NIMH NIH HHS U01 MH093765NINDS NIH HHS R01 NS092802NINDS NIH HHS R01 NS100440NINDS NIH HHS RF1 NS033310
6 · The paper itself

Abstract

Alzheimer's disease (AD) is the most common form of dementia, progressively impairing memory and cognition. While neuroimaging studies have revealed functional abnormalities in AD, how these relate to aberrant neuronal circuit mechanisms remains unclear. Using magnetoencephalography imaging we documented abnormal local neural synchrony patterns in patients with AD. To identify abnormal biophysical mechanisms underlying these abnormal electrophysiological patterns, we estimated the parameters of a spectral graph-theory model (SGM). SGM is an analytic model that describes how long-range fiber projections in the brain mediate the excitatory and inhibitory activity of local neuronal subpopulations. The long-range excitatory time scale was associated with greater deficits in global cognition and was able to distinguish AD patients from controls with high accuracy. These results demonstrate that long-range excitatory time scale of neuronal activity, despite being a global measure, is a key determinant in the spatiospectral signatures and cognition in AD.

Indexed as

Alzheimer’s diseasebrain activitycognitive declinemagnetoencephalographyspectral graph theory

Identifiers

PMID36993350
PMCPMC10055509
OpenAlexW4353040019

What OpenQuestion holds

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Registered trials

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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.