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There are many areas of the brain that have very different properties from each other. This makes sense when you consider that they likely solve different (sub)
by RootGenerated 8y ago
There are many areas of the brain that have very different properties from each other. This makes sense when you consider that they likely solve different (sub) problems. While a distributed representation is very useful for things like semantics clustering, it actually hurts the ability to discriminate between similar things when you need to remember a specific relationship between things. This is the case in the hippocampus where we store memories of events, as well as the structure of the world (e.g. a map of sorts as mentioned in this article). So, an artificial neural network probably isn't the best model for this.
- IshKebab 8y agoArtificial neural networks also have different regions that have very different properties from each other. They have convolutional layers and fully connected layers, and some architectures have separate semantic labelling and visual processing parts. Take a look at Mask R-CNN for example: https://medium.com/@jonathan_hui/image-segmentation-with-mask-r-cnn-ebe6d793272 https://medium.com/@jonathan_hui/image-segmentation-with-mas... I don't think that is evidence that the brain doesn't use distributed representations.