1. Introduction
2. Neuroimaging Datasets
2.1. Image Datasets
2.2. Video Datasets
2.3. Video & Speech Datasets
2.4. Sound & Speech Datasets
2.5. Music Datasets
3. Brain Regions
3.1. Visual Cortex
3.2. Auditory Cortex
3.3. Language Cortex
4. Generative Models
4.1. Diffusion Models
4.2. Generative Adversarial Networks
4.3. Variational Autoencoders
4.4. Convolutional Autoencoders
4.5. Autoregressive Models
5. AIGC-Brain Methodology Taxonomy
5.1. Map
5.2. Brain-Pretrain & Finetune & Align
5.3. Brain-Pretrain & Map
5.4. Map & Train & Finetune
5.5. End-to-End
5.6. Convolutional-Autoencoder & Align
6. AIGC-Brain Tasks & Implementations
6.1. Image-Brain-Image
6.2. Video-Brain-Video
6.3. Sound-Brain-Sound
6.4. Music-Brain-Music
6.5. Image & Video & Speech-Brain-Text
6.6. Other Tasks
7. AIGC-Brain Results
7.1. Qualitative Results
7.2. Quantitative Results
8. Conclusions and Prospects