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Mixed Signals: On Separating Brain Signal from Noise
1Department of Psychology, University of Miami, Coral Gables, FL 33124, USA; Neuroscience Program, University of Miami Miller School of Medicine, Miami, FL 33136, USA.
Trends in Cognitive Sciences
|May 3, 2017
Summary
Separating true neural signals from noise is crucial for understanding human brain function using functional MRI (fMRI). Artifacts can persist even after processing, and there is no agreement on how to handle them.
Area of Science:
- Neuroimaging
- Brain Signal Analysis
Background:
- Accurate human brain function studies depend on distinguishing neural signals from noise.
- Whole-brain functional MRI (fMRI) signals contain artifacts that persist despite processing.
Purpose of the Study:
- To highlight the challenge of artifact removal in fMRI data.
- To underscore the lack of consensus in addressing persistent artifacts in neuroimaging.
Main Methods:
- Examination of spatial and temporal properties of whole-brain fMRI signals.
- Analysis of artifact persistence after standard processing.
Main Results:
- Artifacts from various sources remain in fMRI data post-processing.
- Significant challenges exist in artifact identification and removal.
Conclusions:
- Effective separation of neural signal from noise in fMRI remains an open problem.
- Further research and consensus-building are needed to address persistent artifacts in brain imaging.
