# Learning Neural Markers of Schizophrenia Disorder Using Recurrent Neural Networks

arXiv: https://arxiv.org/abs/1712.00512 · HTML: https://mlsanity.com/paper/1712.00512/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Dec 2017.

## Built on by (most cited first, 7 of 7)

- [Self-Supervised Transformers for fMRI representation](https://mlsanity.com/paper/2112.05761/) (2021)
- [STNAGNN: Data-driven Spatio-temporal Brain Connectivity beyond FC](https://mlsanity.com/paper/2406.12065/) (2024)
- [JGAT: a joint spatio-temporal graph attention model for brain decoding](https://mlsanity.com/paper/2306.05286/) (2023)
- [Multi-site Diagnostic Classification Of Schizophrenia Using 3D CNN On Aggregated Task-based fMRI Data](https://mlsanity.com/paper/2210.05240/) (2022)
- [Self-Supervised Pretraining on Paired Sequences of fMRI Data for Transfer Learning to Brain Decoding Tasks](https://mlsanity.com/paper/2305.09057/) (2023)
- [Sequential Transfer Learning to Decode Heard and Imagined Timbre from fMRI Data](https://mlsanity.com/paper/2305.13226/) (2023)
- [Cognitive Networks and Performance Drive fMRI-Based State Classification Using DNN Models](https://mlsanity.com/paper/2409.00003/) (2024)

## Abstract (arXiv)

Smart systems that can accurately diagnose patients with mental disorders and identify effective treatments based on brain functional imaging data are of great applicability and are gaining much attention. Most previous machine learning studies use hand-designed features, such as functional connectivity, which does not maintain the potential useful information in the spatial relationship between brain regions and the temporal profile of the signal in each region. Here we propose a new method based on recurrent-convolutional neural networks to automatically learn useful representations from segments of 4-D fMRI recordings. Our goal is to exploit both spatial and temporal information in the functional MRI movie (at the whole-brain voxel level) for identifying patients with schizophrenia.