Evidence map›Paper›PMID 37693592›Full record

ArticlebioRxiv : the preprint server for biology2023

Different methods to estimate the phase of neural rhythms agree, but only during times of low uncertainty.

Anirudh Wodeyar, François A Marshall, Catherine J Chu, Uri T Eden, Mark A Kramer

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 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.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Anirudh WodeyarDepartment of Mathematics & Statistics, Boston University, Boston MA, USA, 02215.
François A MarshallDepartment of Mathematics & Statistics, Boston University, Boston MA, USA, 02215.
Catherine J ChuDepartment of Neurology, Massachusetts General Hospital, Boston, MA; USA, 02215.
Uri T EdenDepartment of Mathematics & Statistics, Boston University, Boston MA, USA, 02215.
Mark A KramerDepartment of Mathematics & Statistics, Boston University, Boston MA, USA, 02215.

Funding

Understanding the Fast and Slow Spatiotemporal Dynamics of Human SeizuresR01NS110669 · NINDS · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI CASH, SYDNEY S, EDEN, URI TZVI · 2019 to 2023
$2.3M
Measuring, Modeling, and Modulating Cross-Frequency CouplingR01EB026938 · NIBIB · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI EDEN, URI TZVI, KRAMER, MARK ALAN · 2018 to 2020
$1.0M
NIBIB NIH HHS R01 EB026938NINDS NIH HHS R01 NS110669
6 · The paper itself

Abstract

Rhythms are a common feature of brain activity. Across different types of rhythms, the phase has been proposed to have functional consequences, thus requiring its accurate specification from noisy data. Phase is conventionally specified using techniques that presume a frequency band-limited rhythm. However, in practice, observed brain rhythms are typically non-sinusoidal and amplitude modulated. How these features impact methods to estimate phase remains unclear. To address this, we consider three phase estimation methods, each with different underlying assumptions about the rhythm. We apply these methods to rhythms simulated with different generative mechanisms and demonstrate inconsistency in phase estimates across the different methods. We propose two improvements to the practice of phase estimation: (1) estimating confidence in the phase estimate, and (2) examining the consistency of phase estimates between two (or more) methods.

Identifiers

PMID37693592
PMCPMC10491120

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.