Neuroscience is not my specialty, I only understand the ML side of it. My understanding is that when our machine learning architectures are specially crafted

Neuroscience is not my specialty, I only understand the ML side of it. My understanding is that when our machine learning architectures are specially crafted to model specific types of data, we observe similar neurons as those in the brain because they converge to the same optimal solution to handle this data. For example, taking into account the translational invariance of image data with convolutional layers leads to similar neurons as the V1 cortex. Training recurrent layers on navigation tasks lead to grid-cells similar to those in the brain. Some references: https://arxiv.org/abs/1803.07770 https://arxiv.org/abs/1803.07770 https://hal.inria.fr/hal-01389809/document https://hal.inria.fr/hal-01389809/document https://www.biorxiv.org/content/10.1101/296301v1.full https://www.biorxiv.org/content/10.1101/296301v1.full