Mixed Signals: On Separating Brain Signal from Noise

Research output: Contribution to journalShort survey

10 Citations (Scopus)

Abstract

Accurate description of human brain function requires the separation of true neural signal from noise. Recent work examining spatial and temporal properties of whole-brain fMRI signals demonstrates how artifacts from a variety of sources can persist after rigorous processing, and highlights the lack of consensus on how to address this challenge.

Original languageEnglish (US)
Pages (from-to)405-406
Number of pages2
JournalTrends in Cognitive Sciences
Volume21
Issue number6
DOIs
StatePublished - Jun 1 2017

Fingerprint

Brain
Artifacts
Magnetic Resonance Imaging

Keywords

  • artifact removal
  • functional connectivity
  • global signal regression
  • resting-state fMRI

ASJC Scopus subject areas

  • Neuropsychology and Physiological Psychology
  • Experimental and Cognitive Psychology
  • Cognitive Neuroscience

Cite this

Mixed Signals : On Separating Brain Signal from Noise. / Uddin, Lucina Q.

In: Trends in Cognitive Sciences, Vol. 21, No. 6, 01.06.2017, p. 405-406.

Research output: Contribution to journalShort survey

@article{20c00e4dfa014467bf7cd49ca658a9e5,
title = "Mixed Signals: On Separating Brain Signal from Noise",
abstract = "Accurate description of human brain function requires the separation of true neural signal from noise. Recent work examining spatial and temporal properties of whole-brain fMRI signals demonstrates how artifacts from a variety of sources can persist after rigorous processing, and highlights the lack of consensus on how to address this challenge.",
keywords = "artifact removal, functional connectivity, global signal regression, resting-state fMRI",
author = "Uddin, {Lucina Q}",
year = "2017",
month = "6",
day = "1",
doi = "10.1016/j.tics.2017.04.002",
language = "English (US)",
volume = "21",
pages = "405--406",
journal = "Trends in Cognitive Sciences",
issn = "1364-6613",
publisher = "Elsevier Limited",
number = "6",

}

TY - JOUR

T1 - Mixed Signals

T2 - On Separating Brain Signal from Noise

AU - Uddin, Lucina Q

PY - 2017/6/1

Y1 - 2017/6/1

N2 - Accurate description of human brain function requires the separation of true neural signal from noise. Recent work examining spatial and temporal properties of whole-brain fMRI signals demonstrates how artifacts from a variety of sources can persist after rigorous processing, and highlights the lack of consensus on how to address this challenge.

AB - Accurate description of human brain function requires the separation of true neural signal from noise. Recent work examining spatial and temporal properties of whole-brain fMRI signals demonstrates how artifacts from a variety of sources can persist after rigorous processing, and highlights the lack of consensus on how to address this challenge.

KW - artifact removal

KW - functional connectivity

KW - global signal regression

KW - resting-state fMRI

UR - http://www.scopus.com/inward/record.url?scp=85018249367&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85018249367&partnerID=8YFLogxK

U2 - 10.1016/j.tics.2017.04.002

DO - 10.1016/j.tics.2017.04.002

M3 - Short survey

C2 - 28461113

AN - SCOPUS:85018249367

VL - 21

SP - 405

EP - 406

JO - Trends in Cognitive Sciences

JF - Trends in Cognitive Sciences

SN - 1364-6613

IS - 6

ER -