Topic: spatiotemporal Transformer

Mapping and understanding the functional differences between neuron types is crucial for advancing our knowledge of neural circuits and brain function. However, classifying neuron types in vivo remains challenging due to the difficulty of collecting reliable labels and the complexity of deciphering how neuronal activity varies across different conditions and stimuli. Even when labeled data is available, it is often hard to identify subtle functional differences between neuron classes. To address these challenges, we introduce a novel spatiotemporal Transformer-based architecture that learns a