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Background of Example 1
The following example is based on a subset of participants from
Bovet, J., Lao, J., Bartholomée, O., Caldara, R., & Raymond, M. (2016). Mapping female bodily features of attractiveness. Scientific Reports, 6, 18551.doi: 10.1038/srep18551
In short, the example dataset consists of eye movement data from twenty male observers during a gaze-contingent study. Observers viewed computer rendered female bodies in different conditions and performed a behavioral task (i.e., subjective rating of bodily attractiveness). This is a within-subject design with two experimental manipulations: the viewing condition (three level: 2° spotlight, 4° spotlight, or natural viewing) and body orientation (two level: front view or back view). The aim of the study is to evaluate the visual information use for bodily attractiveness evaluation in the male observers. Other details of the experiment can be found in the paper.
Fixation durations were projected into the two-dimensional space according to their coordinates at the single-trial level. Fixation duration maps were first smoothed at 1° of visual angle. We used the “estimated” option by taking the expected values across trial within the same condition independently for each observer. To reduce the computational time, we down-sampled the fixation map to 256*205 pixels, and applied a mask to only model the pixels with average duration larger than half of the minimum fixation duration input.
You can follow the step to perform the analysis using the GUI, or run the analysis code here
This wiki is adapted from the original iMap4 guidebook.
If you have any questions about the iMap4 usage, please email [email protected]
Getting started
Theory
- Linear Mixed Models
- Pixel Wise Modeling and non-parametric statistics
- Family-wise error rate (FWER) under H0
- Power analysis of iMap4
Data structures and function usage
- Core functions
- Input Matrix
- LMMmap
- StatMap, Posthoc and figure outputs
- Other useful features and function
Example 1 (GUI)
- Background of Example 1
- Using the GUI (1): Import Data and label columns
- Using the GUI (2): Parameters and Conditions
- Using the GUI (3): Create smoothed fixation matrix
- Using the GUI (4): Optional for preprocessing
- Using the GUI (5): Descriptive Statistics Report
- Using the GUI (6): Spatial Mapping Using Linear Mixed Models
- Using the GUI (7): Hypothesis testing and Display results
- Using the GUI (8): Post-hoc analysis
Example 2 (Code)
Example 3 (Code)
Example 4 (Code)
Future development
Additional information