---
dataset_info:
  features:
  - name: volume_id
    dtype: int32
  - name: slice_id
    dtype: int32
  - name: age
    dtype: int32
  - name: sex
    dtype: string
  - name: iq
    dtype: float32
  - name: diagnosis
    dtype: string
  - name: with_auditory_hallucinations
    dtype: bool
  - name: image
    dtype: image
  splits:
  - name: train
    num_bytes: 93925657.16
    num_examples: 12780
  download_size: 90962829
  dataset_size: 93925657.16
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
license: cc0-1.0
language:
- en
task_categories:
- image-classification
tags:
- mri
- medical
pretty_name: Brain Correlates of Speech Perception in Schizophrenia
size_categories:
- 10K<n<100K
---
# Brain Correlates of Speech Perception in Schizophrenia

This dataset contains materials from the study *"Brain correlates of speech perception in schizophrenia patients with and without auditory hallucinations"* by Soler-Vidal et al. (2022), aimed at studying the neural activation patterns associated with speech perception in healthy participants and individuals with schizophrenia, with and without auditory hallucinations.


## 🧠 Dataset Description

This repository provides a **2D slice-based version** of the original t1w dataset, designed for efficient deep learning and representation learning workflows.

Each entry corresponds to a **single 2D t1w slice** extracted from a volume and includes both imaging metadata and participant-level clinical information.


## 📦 Dataset Structure

Each dataset entry contains:

- `volume_id` → Unique identifier for the t1w volume/participant  
- `slice_id` → Index of the slice within the volume  
- `image` → 2D fMRI slice  
- `age` → Participant age  
- `sex` → Participant sex  
- `iq` → Intelligence quotient score  
- `diagnosis` → Clinical diagnosis (`healthy` or `schizophrenia`)  
- `with_auditory_hallucinations` → Boolean indicating whether the participant experiences auditory hallucinations  

## Use

```python
from datasets import load_dataset
import matplotlib.pyplot as plt

dataset = load_dataset("chehablaborg/schizophrenia_speech_perception", split="train")

sample_id = 314

image = dataset[sample_id]["image"]
diagnosis = dataset[sample_id]["diagnosis"]

plt.imshow(image, cmap="gray")
plt.title(diagnosis)
plt.show()
```

## 📚 Citation

If you use this dataset, please mention us https://chehablab.com in an acknowledgement and cite the original publication:

```bibtex
@article{solervidal2022speechperception,
  title={Brain correlates of speech perception in schizophrenia patients with and without auditory hallucinations},
  author={Soler-Vidal, J. and Fuentes-Claramonte, P. and Salgado-Pineda, P. and Ramiro, N. and García-León, M. Á. and Torres, M. L. and Arévalo, A. and Guerrero-Pedraza, A. and Munuera, J. and Sarró, S. and Salvador, R. and Hinzen, W. and McKenna, P. and Pomarol-Clotet, E.},
  journal={PLOS ONE},
  volume={17},
  number={12},
  pages={e0276975},
  year={2022},
  doi={10.1371/journal.pone.0276975},
  url={https://doi.org/10.1371/journal.pone.0276975}
}
```

## 📜 License
This dataset is released under the **Creative Commons CC0 1.0 Universal (CC0 1.0) Public Domain Dedication**.
You may copy, modify, distribute, and use the data, even for commercial purposes, without asking permission.
[![CC0 1.0](https://licensebuttons.net/p/zero/1.0/88x31.png)](https://creativecommons.org/publicdomain/zero/1.0/)

[Chehab Lab](https://chehablab.com) @ 2026