This is a set of code for administering cognitive tasks behaviorally and within the functional MRI environment.

The code is all written in Psychopy http://www.psychopy.org/; therefore, Psychopy needs to be installed first :). This code was originally written to use python 2.7 and Psychopy 1.903. This version is in release https://github.com/NCMlab/CognitiveTasks/releases/tag/v1.1. The master branch of the code is updated to use Psychopy 3.0 and python 3.5.

There are multiple GUIs, in the GUI folder, which are used for calling all of the individual tasks. However, the tasks can also be run independently. The GUI ensures that all result data files are created with the same participant ID and are stored inthe same location.

When the tasks are run data files will be created. These will be placed in a top level folder called data. If this folder does not exist it will be created. Within this data folder one folder will be created for each participant ID. By default the participant ID is 9999999. Every data file is named with the format: [Task Name]_[Participant ID]_[Year]_[Month]_[Day]_[Time].csv

There are two GUIs for task delivery.

This is a GUI which runs all neuropsychological tests that the NCM lab uses. In this repository there are other tasks that have been developed but did not make it into our final battery. The test items for some of these tasks are not in the public domain and are therefore not distributed here. The code is available but the images used as test items are not.

This is a subset of the battery that is administered again when a research participant is in the MRI.

Immediate, delayed and recognition phases.

These test items are not publicly available.

Short term verbal memory

Executive function using color, word and color/word

Executive function

Short term spatial memory

These test items are not publicly available.

Working memory

Working memory span

Cognitive speed of processing

And therefore no gurantee that they work!

This is an event-related task presenting words. The task has 60 words and takes approximately 8:30 minutes. The ITI is jittered and the ITI durations and the trial order is optimized based on thousands of simulations. The simulations identify the Gamma distribution of ITIs that minimize the BOLD response required to significantly detect task related signal change. This optimization used multiple contrasts and the optimization aimed to find the smallest average BOLD signal required across all contrasts of interest.

This experiment is trial based where image pairs are presented and the participant determines whether the two images are of the same person. Face pairs are presented for 2500 milliseconds with a 500 ms intertrial interval in blocks of twelve trials each. Within a block of trials, all face pairs will have the same level of degradation. Blocks will be separated by 5 seconds of rest where the participant views a fixation cross-hair at the center of the screen. Successive blocks will present images with larger levels of degradation. Responses are recorded via a keyboard press.

Degradation of the faces is performed by adding noise to each image. This experiment used phase-scrambled noise by randomizing the phase component of the image in the frequency domain (Oppenheim & Lim, 1981; Thomson, 1999). This process preserves the frequency component of the image, while making the noise image. Different levels of degradation are created using different additive proportions of image and noise so that the total is always 100%. For example, an image with a noise level of ‘40’ is calculated as: 0.6image + 0.4noise.

Faces for this study are from the Karolinska Directed Emotional Faces (KDEF), which were developed for use in psychological and medical research (Lundqvist, Flykt, & Öhman, 1998). This is a set of 4900 photographs of 70 different people displaying various emotional expressions. Images were taken from various perspectives around the person. For this experiment, only neutral expressions are used. Images on the left of the screen will be displayed with the face turned towards the center of the screen. Images on the right of the screen will also be displayed with the face turned towards the center of the screen. In this manner, even if the two images are of the same person they are not the same image. This design attempts to ensure the participant matches the images based on the person and not on other spatial aspects of the images.