Mixed Signals: On Separating Brain Signal from Noise

Lucina Q. Uddin

doi:10.1016/j.tics.2017.04.002

Mixed Signals: On Separating Brain Signal from Noise

Lucina Q. Uddin

Psychology

Research output: Contribution to journal › Short survey › peer-review

22 Scopus citations

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 language	English (US)
Pages (from-to)	405-406
Number of pages	2
Journal	Trends in Cognitive Sciences
Volume	21
Issue number	6
DOIs	https://doi.org/10.1016/j.tics.2017.04.002
State	Published - Jun 2017

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

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10.1016/j.tics.2017.04.002

Cite this

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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",

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Mixed Signals: On Separating Brain Signal from Noise

Abstract

Keywords

ASJC Scopus subject areas

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