Abstract
The purpose of this functional magnetic resonance imaging (fMRI) study was to investigate the effects of smoothing kernel size and the extent of physiological noise correction on neuronal activity estimation. The fMRI data acquired from heavy smokers were used to evaluate the effect of preprocessing options. Three different smoothing kernel sizes (i.e., 4, 6, and 8 mm) were applied to compare neuronal activation between two different conditions (e.g., abstained and satiated conditions). In addition, the physiological noise was extracted from white matter and cerebrospinal fluid via principal component analysis and different numbers of the principal components (PCs) were removed (i.e., 0, 1, 3, and 5). As results, as smoothing kernel size increased, the more number of voxels survived in a group-level analysis. Also, removing 3 noise-related PCs leaded to the largest statistical value within activated foci compared to the other cases.
| Original language | English |
|---|---|
| Title of host publication | 3rd International Winter Conference on Brain-Computer Interface, BCI 2015 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Print) | 9781479974948 |
| DOIs | |
| Publication status | Published - 2015 Mar 30 |
| Event | 2015 3rd International Winter Conference on Brain-Computer Interface, BCI 2015 - Gangwon-Do, Korea, Republic of Duration: 2015 Jan 12 → 2015 Jan 14 |
Other
| Other | 2015 3rd International Winter Conference on Brain-Computer Interface, BCI 2015 |
|---|---|
| Country/Territory | Korea, Republic of |
| City | Gangwon-Do |
| Period | 15/1/12 → 15/1/14 |
Keywords
- Functional magnetic resonance imagine (fMRI)
- physiological noise
- preprocessing
- principal component anlaysis
- smoothing kernel
ASJC Scopus subject areas
- Human-Computer Interaction
- Cognitive Neuroscience
- Sensory Systems