264 13 Local, Global and Glocal Knowledge Representation does imply constraints on how knowledge representation in the brain may work, but these are relatively loose constraints. These constraints do imply that, for instance, the brain is neither a relational database (in which information is stored in a wholly localized manner) nor a collection of “grandmother neurons” that respond individually to high-level percepts or concepts; nor a simple Hopfield type neural net (in which all memories are attractors globally distributed across the whole network). But they don’t tell us nearly enough to, for instance, create a formal neural net model that can confidently be said to represent knowledge in the manner of the human brain. As a first example of the current state of knowledge, we’ll discuss here a series of papers regarding the neural representation of visual stimuli [QaGKKF05, QKIKF 08], which deal with the fascinating discovery of a subset of neurons in the medial temporal lobe (MTL) that are selectively activated by strikingly different pictures of given individuals, landmarks or objects, and in some cases even by letter strings. For instance, in their 2005 paper titled "Invariant visual representation by single neurons in the human brain”, it is noted that in one case, a unit responded only to three completely different images of the ex-president Bill Clinton. Another unit (from a different patient) responded only to images of The Beatles, another one to cartoons from The Simpson’s television series and another one to pictures of the basketball player Michael Jordan. Their 2008 follow-up paper backed away from the more extreme interpretation in the title as well as the conclusion, with the title “Sparse but not ‘Grandmother-cell’ coding in the medial temporal lobe.” As the authors emphasize there, Given the very sparse and abstract representation of visual information by these neurons, they could in principle be considered as ‘grandmother cells’. However,