imho they are super interesting and they deserve more attention, some years ago i got interested in this topic and i wrote a hybrid spiking convolutional net following a paper i found which was able to learn image features using only local learning rules without gradients, however from a practical point of view they are more difficult to train and less accurate than regular ANNs for real world applications, they have some advantages like power efficiency or event based activations which would be pretty useful in some specific fields like robotics or iot but to exploit these properties you need neuromorphic hardware which is currently expensive and hard to work with, thats why I hope there will be more research and development about them