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- Datasets for 
"Serial dependence and representational momentum in single-trial perceptual decisions"
https://doi.org/10.1038/s41598-021-89432-9
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David Pascucci & Gijs Plomp
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Department of Psychology, University of Fribourg, Fribourg, Switzerland.
Laboratory of Psychophysics, Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland.
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The dataset of each experiment is stored in long format, .csv.
Rows indicate events in each trial, columns are variables. 

For Experiment 1-2:
- obs	   : subject identifier
- cond	   : trial condition (0 = random, 1 = rotational)
- theta    : last orientation presented in the sequence (target orientation)
- delta    : acute angle between the last and second to last orientation in the sequence
- deltar   : acute angle between the last reported orientation and the present target
- ori      : redundant, same as theta
- outliers : trials marked as outliers and excluded
- error	   : adjustment errors
- rt       : adjustment reaction times
- errorc   : errors after preprocessing with outliers as NaN (see Methods)
- rtc	   : RT with outleirs as NaN
- stop     : whether the sequence ended before the 6th stimulus (stop=1), 
 	     these trials are excluded from the main analysis
- expe     : whether the last orientation followed the rotation or not 
 	    (control trials subsequently excluded)
- testpos  : lenght of the gabor sequence (serial position of the test/target gabor)


Additional or different variables/labels for Experiment 3:
- nstim    : same as 'testpos' in Exp1-2
- condition: 'random' or 'rotational'
- resp 	   : raw adjustment responses
- error    : errors after preprocessing with outliers as NaN 
- condnum  : same as 'condition' but binary
- bad_subject: marks the excluded subject (num 8)

The script SD_RM_example_analysis.m
provides a general example of how to read the datasets in MATLAB (R2020b),
and how to compute individual averages for each condition
and group model-freee anaysis of serial dependence.