Evidence map›Paper›PMID 42100763›Full record

ArticleImaging neuroscience (Cambridge, Mass.)

A neuroscientist's guide to neural burst detection.

Lindsey Power, Idil Aydin, Timothy Bardouille, Sylvain Baillet

Abstract read
In one paragraph

Article in Imaging neuroscience (Cambridge, Mass.). 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

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

4 authors.

Lindsey PowerMcConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.ORCID https://orcid.org/0000-0001-9262-7668
Idil AydinMcConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.
Timothy BardouilleDepartment of Physics & Atmospheric Science, Dalhousie University, Halifax, Nova Scotia, Canada.
Sylvain BailletMcConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Neural bursts-brief episodes of heightened oscillatory activity-are increasingly studied as fundamental building blocks of brain function, with relevance to perception, cognition, and disease. As such, detecting and characterizing these bursts in electrophysiological recordings have driven rapid methodological innovation in neuroscience research. However, the growing number of analysis techniques can be overwhelming, making it difficult for researchers to select the most appropriate method for their specific goals. In this review, we provide a structured and practical guide for neuroscientists to measure and interpret neural burst data. We offer an overview of current detection methods, accompanied by a suite of tutorials, including code notebooks and data, to enable concrete implementation and critical evaluation. We then conclude with actionable recommendations to help researchers select the best burst detection strategy in diverse research contexts. This guide is intended for newcomers to the field as well as more experienced neuroscientists seeking to expand their methodological toolkit.

Indexed as

electrophysiologymethodsneural burststransient eventstutorial

Identifiers

PMID42100763
PMCPMC13146973

What Socratic 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 Socratic graph.