The processing of compound radial frequency patters (model functions used in Schmidtmann, Kingdom, & Loffler (2019)
The expositions below refer to data and models utilized in:
The accessible folder (Compound RF - Data and Models; see Access Link below) contains the raw data and model functions for the Radial Frequency Compound pattern summation study by Schmidtmann, Kingdom and Loffler (2019) as MatLab scripts and functions. The key script is called "Analyse_Data.m". Please read the documentation in the script. The function "RF_compound_data.m" contains the raw data. The “Models” folder contains all model simulations, superimposed on individual data for all subjects, as Matlab figures (.fig). The models are divided into fixed - and matched attention window scenarios (FAW, MAW). A separate folder shows the model simulations for the condition where the transducer exponents are fixed (Fixed Transducers). We also provide model simulations for a single channel model. Please see Schmidtmann, Kingdom and Loffler (2019) for details.
The models described in Schmidtmann, Kingdom & Loffler (2019) employ additional functions from the Palamedes Toolbox (Prins & Kingdom, 2018), to determine whether the data from a 5-PF (psychometric function) summation square experiment, for the detection of two stimuli in the target interval, accords more with probability summation (PS) or additive summation (AS) under the assumptions of signal-detection-theory (SDT) and assuming that the observer is monitoring both channels sensitive to the two stimuli.
Palamedes function (PF) fitting routines:
Palamedes SDT PS (probability) and AS (additive)
Palamedes PF fitting routines:
Prins, N. & Kingdom, F. A. A. (2018) Applying the Model-Comparison Approach to Test Specific Research Hypotheses in Psychophysical Research Using the Palamedes Toolbox. Frontiers in Psychology, 9:1250. d
McGill Face Database
“I understand that this database may not be used
for commercial purposes without express permission from the
authors, and cannot be reproduced and/or distributed in original or
modified form under a different name and/or authorship”
Schmidtmann, G., Jennings, B. J., Sandra, D. A., Pollock, J., & Gold, I. (2019). The McGill Face Database: validation and insights into the recognition of facial expressions of complex mental states. BioRxiv, 586453. https://doi.org/10.1101/586453 [PDF]