DOI: 10.5061/dryad.hhmgqnkr1
title: Data from: Multisensory perceptual and causal inference is largely preserved in medicated post-acute individuals with schizophrenia

description: Hallucinations and perceptual abnormalities in psychosis are thought to
 arise from imbalanced integration of prior information and sensory inputs.
 We combined psychophysics, Bayesian modelling and electroencephalography
 (EEG) to investigate potential changes in perceptual and causal inference
 in response to audiovisual flash-beep sequences in medicated individuals
 with schizophrenia who exhibited limited psychotic symptoms. Seventeen
 participants with schizophrenia and 23 healthy controls reported either
 the number of flashes or the number of beeps of audiovisual sequences that
 varied in their audiovisual numeric disparity across trials. Both groups
 balanced sensory integration and segregation in line with Bayesian causal
 inference rather than resorting to simpler heuristics. Both also showed
 comparable weighting of prior information regarding the signals’ causal
 structure, although the schizophrenia group slightly overweighted prior
 information about the number of flashes or beeps. At the neural level,
 both groups computed Bayesian causal inference through dynamic encoding of
 independent estimates of the flash and beep counts, followed by estimates
 that flexibly combine audiovisual inputs. Our results demonstrate that the
 core neurocomputational mechanisms for audiovisual perceptual and causal
 inference in number estimation tasks are largely preserved in our limited
 sample of medicated post-acute individuals with schizophrenia. Future
 research should explore whether these findings generalize to unmedicated
 patients with acute psychotic symptoms.
description: The repository contains raw behavioral, EEG, demographical and
 clinical data as well as code to present AV stimuli in the experimental
 paradigm, fit the BCI model to behavioral data and analyze the behavioral
 data. 
description: # Multisensory perceptual and causal inference is largely preserved in
 medicated post-acute individuals with schizophrenia
 [https://doi.org/10.5061/dryad.hhmgqnkr1](https://doi.org/10.5061/dryad.hhmgqnkr1) ## Description of the data and file structure In a sound-induced flash-illusion (SIFI) paradigm, we presented healthy control (HC) and schizophrenia (SCZ) individuals with flash-beep sequences and their unisensory counterparts. Across trials, the number of beeps and flashes varied independently according to a four (1 to 4 flashes) × four (1 to 4 beeps) factorial design (see paper, Fig. 1A, B). Thereby, the paradigm yielded numerically congruent or incongruent flash-beep sequences at four levels of audiovisual numeric disparity. In an inter-sensory selective attention task, observers reported either the number of beeps or flashes. The repository contains: 1. All raw EEG data measured during the SIFI paradigm. 2. Behavioral data from the SIFI paradigm and some limited demographical  and clinical data . 3. The code to present the audiovisual stimuli in the experimental paradigm, to fit the BCI model to the behavioural data and analyse the behavioural data in the repository. ### Files and variables #### File: [Data\_-\_Rohe\_\_Hesse\_\_Ehlis\_\_Noppeney\_(2024).zip](https://datadryad.org/stash/downloads/file_stream/3424351) **Description:** The data is organized in three folders. Please note that all data is accompanied by data-specific readme files that describe the data structures in detail.  **BehavioralDataAndModelFit -  Behavioral data for model fitting** 1. BehavioralData.mat: Behavioral data (i.e. numeric reports) as well as experimental variables from the SIFI paradigm. The .mat files can be opened using Matlab or open-source GNU Octave. 2. Readme for behavioral data.docx: Readme that explains all variables of the data structure. **Demographical and clinical data - limited demographical and clinical data** 1. DemographicalClinicalData.mat: Limited demographical (e.g. age range, sex) and clinical data (e.g., diagnosis, symptom scales). The .mat files can be opened using Matlab or open-source GNU Octave. 2. Readme for demographical and clinical data.docx: Readme that explains all variables of the data structure. **EEG raw data - EEG raw data for all runs of all participants** 1. EEG data from all runs of all participants (including healthy controls, n = 23, schizophrenia patients, n = 17, and schizoaffective patients, n = 6). EEG data was recorded with BrainVision Recorder (BrainProducts). .eeg files contain the actual EEG data, .vmrk contain the stimulus triggers from all conditions, .vhdr contains information on the electrode setup. The EEG data can be opened with open-source programs like Brainstorm ([https://neuroimage.usc.edu/brainstorm/](https://neuroimage.usc.edu/brainstorm/) ) or EEG Lab ([https://sccn.ucsd.edu/eeglab/index.php](https://sccn.ucsd.edu/eeglab/index.php) ) that run under Matlab or GNU Octave. 2. Readme for EEG raw data.docx: Readme that explains details of the EEG measurement and the coding of stimulus triggers, linking the 40 experimental conditions to specific trigger codes. ## Code/software #### File: [Code\_-\_Rohe\_\_Hesse\_\_Ehlis\_\_Noppeney\_(2024).zip](https://datadryad.org/stash/downloads/zenodo_file/3424350) The .zip file contains 3 folder with code to 1. **Experimental paradigm:** present the audiovisual stimuli in the experimental SIFI paradigm which requires Psychotoolbox (psychtoolbox.org) running under Matlab or GNU Octave. 2. **BCI model:** fit the BCI model to the behavioural data which requires BADS toolbox ([https://github.com/lacerbi/bads](https://github.com/lacerbi/bads)) and Matlab or GNU Octave. 3. **Behavioral data:** analyse the behavioural data which requires Matlab or GNU Octave.