Evidence map›Paper›PMID 26400953›Full record

ArticleThe Journal of neuroscience : the official journal of the Society for Neuroscience2015

Age-Related Changes in 1/f Neural Electrophysiological Noise.

Bradley Voytek, Mark A Kramer, John Case, Kyle Q Lepage, Zechari R Tempesta, Robert T Knight, Adam Gazzaley

Abstract read
In one paragraph

Article in The Journal of neuroscience : the official journal of the Society for Neuroscience, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 402 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
402citing papers in PubMed, 2 pooled it
–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

402 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  18. Task-Related Aperiodic EEG (1/f) Activity in Autism.Autism research : official journal of the International Society for Autism Research · 2026
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342 more citing papers are in PubMed but not listed here.

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

7 authors.

Bradley VoytekDepartments of Neurology and bradley.voytek@gmail.com.ORCID http://orcid.org/0000-0003-1640-2525
Mark A KramerDepartment of Mathematics and Statistics, Boston University, Boston, Massachusetts 02215, and.
John CaseHelen Wills Neuroscience Institute and.
Kyle Q LepageDepartment of Mathematics and Statistics, Boston University, Boston, Massachusetts 02215, and.
Zechari R TempestaDepartments of Neurology and.
Robert T KnightHelen Wills Neuroscience Institute and Department of Psychology, University of California, Berkeley, California 94720.
Adam GazzaleyDepartments of Neurology and Physiology and Psychiatry and UCSF Center for Integrative Neuroscience, University of California, San Francisco, California 94158.

Funding

UCSF IRACDA Scholars ProgramK12GM081266 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Raymond M. Esquerra, HOLLY A. INGRAHAM · 2007 to 2026
$19.4M
ATTENTION, ORIENTATION, & THE HUMAN PREFRONTAL CORTEXR37NS021135 · NINDS · UNIVERSITY OF CALIFORNIA BERKELEY · PI KNIGHT, ROBERT THOMAS · 2013 to 2019
$3.6M
Multiscale analysis and modeling of spatiotemporal dynamics in human epilepsyR01NS072023 · NINDS · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI EDEN, URI TZVI, KRAMER, MARK ALAN · 2011 to 2015
$1.8M
NIGMS NIH HHS GM081266NIGMS NIH HHS K12 GM081266NINDS NIH HHS R01 NS072023NINDS NIH HHS R01NS072023NINDS NIH HHS R37 NS021135
6 · The paper itself

Abstract

Aging is associated with performance decrements across multiple cognitive domains. The neural noise hypothesis, a dominant view of the basis of this decline, posits that aging is accompanied by an increase in spontaneous, noisy baseline neural activity. Here we analyze data from two different groups of human subjects: intracranial electrocorticography from 15 participants over a 38 year age range (15-53 years) and scalp EEG data from healthy younger (20-30 years) and older (60-70 years) adults to test the neural noise hypothesis from a 1/f noise perspective. Many natural phenomena, including electrophysiology, are characterized by 1/f noise. The defining characteristic of 1/f is that the power of the signal frequency content decreases rapidly as a function of the frequency (f) itself. The slope of this decay, the noise exponent (χ), is often <-1 for electrophysiological data and has been shown to approach white noise (defined as χ = 0) with increasing task difficulty. We observed, in both electrophysiological datasets, that aging is associated with a flatter (more noisy) 1/f power spectral density, even at rest, and that visual cortical 1/f noise statistically mediates age-related impairments in visual working memory. These results provide electrophysiological support for the neural noise hypothesis of aging. Significance statement: Understanding the neurobiological origins of age-related cognitive decline is of critical scientific, medical, and public health importance, especially considering the rapid aging of the world's population. We find, in two separate human studies, that 1/f electrophysiological noise increases with aging. In addition, we observe that this age-related 1/f noise statistically mediates age-related working memory decline. These results significantly add to this understanding and contextualize a long-standing problem in cognition by encapsulating age-related cognitive decline within a neurocomputational model of 1/f noise-induced deficits in neural communication.

Indexed as

AgingNoiseAcoustic StimulationAdolescentAdultAgedBrainBrain MappingCognitionElectroencephalographyElectrophysiological PhenomenaFemaleHumansMaleMiddle AgedModels, Neurological1/fEEGelectrocorticographyneural noisephase/amplitude couplingworking memory

Identifiers

PMID26400953
PMCPMC4579381

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.