Zamboni-2016

Data and analysis code for Zamboni et al (2016) manuscript. "Do perceptual biases emerge early or late in visual processing?"

View the Project on GitHub schluppeck/zamboni-2016

Zamboni-2016

Overview

Data and analysis code for Zamboni et al (2016) manuscript.

Do perceptual biases emerge early or late in visual processing?

Elisa Zamboni, Timothy Ledgeway, Paul V McGraw & Denis Schluppeck

School of Psychology, University of Nottingham University Park, Nottingham, NG7 2RD, UK

File description

Data files are provided as comma-separated files. The conventions for the data files included with this code are:

Discrimination data

subject[ID]-discrimination.csv

Each row contains data obtained at particular stimulus direction (data were pooled across a 5º range of stimulus directions). There are 4 columns:

  1. Binned delta: stimulus direction
  2. Proportion CW: proportion of "clock-wise" responses
  3. SE: standard error of the "Proportion CW" data
  4. Coherence (one of 4 levels)

Estimation data

subject[ID]-reference-[absent|present|shifted].csv
subjectA-reference-absent.csv

Each row contains a trial. For present|absent data, there are 3 columns:

  1. (true) stimulus direction
  2. estimated direction
  3. coherence levels:

For the data obtained in the "shifted" condition, there are 4 columns

  1. (true) stimulus direction
  2. estimated direction
  3. shift (-6º, 0º, +6º)
  4. coherence levels

Implementation of the model

If you just want to have a quick look at an example output from running one of the notebooks, you have a look at a rendered version in the github preview.

To run the model and visualize the data:

  1. Install a version of Julia from http://julialang.org/downloads/
  2. either clone the repository: git clone https://github.com/schluppeck/zamboni-2016.git
  3. or (if you want to avoid git), download a zip archive of the repository and unpack it. https://github.com/schluppeck/zamboni-2016/archive/master.zip
  4. Under Mac OSX, there is a double-clickable application (/Applications/Julia.app). Alternatively, you could create an command line alias with alias julia='/Applications/Julia-0.4.2.app/Contents/Resources/julia/bin/julia' 
cd zamboni-2016
julia # to start julia

Then, from inside the Julia shell, launch the notebook server:

# install and update packages
Pkg.add("IJulia")
Pkg.update()
# start using them
using IJulia
notebook()
# this will launch the Jupyter notebook interface in   your web browser

Select the notebook in the browser window
Notebook selection

... and start stepping through the code by executing cells in turn (Shift-Return).

Notebook selection