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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, QKKF08], 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, we give several arguments that make such an
extreme interpretation unlikely.
...
MTL neurons are situated at the juncture of transformation of percepts into constructs that can be
consciously recollected. These cells respond to percepts rather than to the detailed information falling
on the retina. Thus, their activity reflects the full transformation that visual information undergoes
through the ventral pathway. A crucial aspect of this transformation is the complementary development
of both selectivity and invariance. The evidence presented here, obtained from recordings of single-neuron
activity in humans, suggests that a subset of MTL neurons possesses a striking invariant representation
for consciously perceived objects, responding to abstract concepts rather than more basic metric details.
This representation is sparse, in the sense that responsive neurons fire only to very few stimuli (and are
mostly silent except for their preferred stimuli), but it is far from a Grandmother-cell representation.
The fact that the MTL represents conscious abstract information in such a sparse and invariant way is
consistent with its prominent role in the consolidation of long-term semantic memories.

It’s interesting to note how inadequate the [QKKF08] data really is for exploring the notion
of glocal memory in the brain. Suppose it’s the case that individual visual memories corre-
spond to keys consisting of small neuronal subnetworks, and maps consisting of larger neuronal
subnetworks. Then it would be not at all surprising if neurons in the “key” network corre-
sponding to a visual concept like “Bill Clinton’s face” would be found to respond differentially
to the presentation of appropriate images. Yet, it would also be wrong to overinterpret such
data as implying that the key network somehow comprises the “representation” of Bill Clinton’s
face in the individual’s brain. In fact this key network would comprise only one aspect of said
representation.

In the glocal memory hypothesis, a visual memory like “Bill Clinton’s face” would be hypoth-
esized to correspond to an attractor spanning a significant subnetwork of the individual’s brain
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