1 Introduction
2 Stimulus Representations
3 Naturalistic Neuroscience Datasets
4 Brain Regions
5 Evaluation Metrics
5.1 Metrics for Brain Encoding Models
5.2 Metrics for Brain Decoding Models
6 Brain Encoding
6.1 Encoding Task Settings
6.2 Voxelwise Encoding Model
6.3 Interpreting Brain Recordings through the Robustness of DNN Model Representations
6.4 Linguistic Encoding
6.5 Auditory Encoding
6.6 Visual Encoding
6.7 Multimodal Brain Encoding
7 Brain Decoding
7.1 Problem Formulation
7.2 Data Preprocessing
7.3 Decoder Architectures
7.4 Impact of Large Models on Brain Decoding
7.5 Linguistic Decoding
7.6 Auditory Decoding
7.7 Visual Decoding
7.8 Key Takeaways
8 Conclusion, Limitations, and Future Trends