Behavioral and Eye-tracking Data for "Individual differences in belief updating and phasic arousal are related to psychosis proneness"

This dataset contains data for:

Murphy PR, Krkovic K, Monov G, Kudlek N, Lincoln, T & Donner TH (2024). Individual differences in belief updating and phasic arousal are related to psychosis proneness.

The dataset is composed of four .zip files (‘behaviourDM’, ‘eye-trackingDM’, ‘behaviourWM’ ‘questionnaire’ and ‘figures’) and one .csv file (‘questionnaire.csv’).

behaviourDM:

Contains behavioural and task data from the decision-making task described in the paper. It consists of subfolders containing all data for a single participant, organised by task session (S1, S2), and containing the following:

The Sample_seqs folder for each participant/session contains Matlab .mat files (labelled ID_SESS_BLOCK.mat, where ID is the participant ID, SESS is the experimental session and BLOCK is the block number within that session) with information about stimulus sequences presented to the participant on each trial of the decision-making task. The variables in each of these files are:

gen – structure containing the generative statistics of the task

stim – structure containing details about the physical presentation of the stimuli (see task script on Github for explanation of these)

timing – structure containing details about the timing of stimulus presentation (see task script on Github for explanation of these)

pshort – proportion of trials with stimulus sequences that were shorter than the full sequence length

stimIn – trials*samples matrix of stimulus locations (in polar angle with horizontal midline = 0 degrees; NaN marks trials sequences that were shorter than the full sequence length)

distseqs – trials*samples matrix of which generative distribution was used to draw each sample location

pswitch – trials*samples matrix of binary flags marking when a switch in generative distribution occurred

The Behaviour folder for each participant/session contains Matlab .mat files (same naming scheme as above) with information about the behaviour produced by the participant on each trial of the task. The main variable in each file is a matrix called Behav for which each row is a trial and columns are the following:

column 1 – the generative distribution used to draw the final sample location on each trial (and thus, the correct response)

column 2 – the response given by the participant

column 3 – the accuracy of the participant’s response

column 4 – response time relative to Go cue

column 5 – trial onset according to psychtoolbox clock

Each .mat file also contains a trials*samples matrix (tRefresh) of the timings of monitor flips corresponding to the onsets of each sample (and made relative to trial onset), as provided by psychtoolbox.

eye-trackingDM:

Contains raw data from a SMI RED 500 eye-tracker, recorded natively as .idf files (proprietary SMI format) and converted here to .txt files using the manufacturer’s IDF Converter utility. The folder contains data for all participants and experimental sessions, named according to the same scheme described above. For stimulus and response trigger information, see task scripts on Github.

behaviourWM:

Contains Matlab .mat files (one per participant) with information about the stimulus and participant behaviour on each trial of the working memory task. Each file contains a single variable (allbehav) containing the concatenated data across all blocks of the task performed by that participant. Each row is a trial and key columns are the following:

column 1 – polar angle of the sample stimulus (i.e. the memorandum)

column 2 – polar angle of the test stimulus

column 3 – working memory delay duration (1, 3 or 9 seconds)

column 4 – categorical trial type (1=match trial, 2=’near’ non-match, 3=’far’ non-match)

column 5 – the response given by the participant (1=”same”, -1=”different”)

column 6 – response accuracy

column 7 – response time relative to go cue

column 10 – trial number (usually 63 per trial; blocks of trials ordered consecutively)

questionnaire:

Contains anonymised participant IDs, age, sex, and prior psychosis diagnosis information for each participant, along with CAPE questionnaire data. Participants are rows in the spreadsheet, columns are different variables.

figures:

Contains data for generating all figures in the published manuscript, one (or in some cases, two/three) .mat file per figure.

Preprocessing and analysis code to accompany this dataset are available at https://github.com/murphyp7/2024_Murphy_Belief-updating-psychosis-proneness.