Abstract
Definitions of what constitutes the ‘signal of interest’ in neuroscience can be controversial, due in part to continuously evolving notions regarding the significance of spontaneous neural activity. This review highlights how the challenge of separating brain signal from noise has led to new conceptualizations of brain functional organization at both the micro- and macroscopic level. Recent debates in the functional neuroimaging community surrounding artifact removal processes have revived earlier discussions surrounding how to appropriately isolate and measure neuronal signals against a background of noise from various sources. Insights from electrophysiological studies and computational modeling can inform current theory and data analytic practices in human functional neuroimaging, given that signal and noise may be inextricably linked in the brain.
Original language | English (US) |
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Pages (from-to) | 734-746 |
Number of pages | 13 |
Journal | Trends in Cognitive Sciences |
Volume | 24 |
Issue number | 9 |
DOIs | |
State | Published - Sep 2020 |
Keywords
- artifact removal
- brain signal variability
- dynamical system
- global signal regression
- resting state fMRI
- spontaneous neural activity
ASJC Scopus subject areas
- Neuropsychology and Physiological Psychology
- Experimental and Cognitive Psychology
- Cognitive Neuroscience