 ({ri}) ri (x,t) r (x,t) r (t) A Simplified History of Neural Complexity Symbolic  ({ri}) (Noam Chomsky) 3 106 107 108 109 yrs infinite recursion         mammalian species         echidna CA1 CA3 DG platypus Memory ri (x,t) (David Marr) lizard 2 1 Spatial r (x,t) (Hubel & Wiesel) Chemical r (t) (e.g. Peter Dayan)

Let us concentrate on one step on our way out of the primordial neural tube first, a process of evagination

some slight change in our chips: and then… some slight change in our chips:

some slight change in our chips: and then… some slight change in our chips:

and then… some slight change in our chips: into the hippocampus the medial wall reorganized into the hippocampus

the reorganization includes a spatial migration... ...it does not lead to a new type of cortex...

but the reorganization of the hippocampus... ….occurs, fundamentally, through the detachment and granulation of the dentate gyrus (diagrams taken from the book by P. Gloor)

it is, at its core, a granulation! …self-similar across species

watch it frozen in its development, in the opossum

can we understand this granulation?

or even the whole circuitry in detail?

David Marr, over 30 years ago, suggested to start from the function In humans, the hippocampus had long been implicated in the formation of episodic and autobiographical memories (here, data by Graham & Hodges)

Over the last few years, imaging evidence has corroborated traditional neuropsychological evidence (here, fMRI study of verbal encoding into episodic memory by Fernandez et al)

In rats, the evidence from neurophysiological recordings indicates a primary role in spatial memory (here, data from simultaneous recordings by Matt Wilson & Bruce McNaughton)

(although a minority view has emphasized a more active role in spatial computation; here, data by Neil Burgess & John O’Keefe)

In monkeys, Edmund Rolls et al have found spatial view cells, suggestive of a hippocampal role intermediate between the human and the rat description

The extensive extrinsic connections of the hippocampus with the neocortex are consistent with a role in the formation of memories

(diagram by Jaap Murre, 1996) David Marr’s perspective was the same later adopted by most of his followers... (diagram by Jaap Murre, 1996)

Yet, birds use their hippocampus in a similar way...

So, let us follow the same functional hypothesis... …but let us try to be quantitative

What sort of device can…. generate, on line, appropriate (compressed) representations of each “snapshot” store these representations on line, in a single “shot” hold multiple representations simultaneously retrieve each representation from partial cues send back the retrieved information in a robust format ?

Icue=log2 p << Iitem  Niunit generate, on line, appropriate (compressed) representations of each “snapshot” store these representations on line, in a single “shot” hold multiple representations simultaneously to retrieve each representation from partial cues send back the retrieved information in a robust format requires a content addressable memory CAM Icue=log2 p << Iitem  Niunit

The analysis of large- scale recordings (here, by Skaggs & McNaughton) shows that the information content of hippocampal representations grows linearly with population size, before saturating at the ceiling set by the experiment. Francesco Battaglia has quantified the full Iitem for place cells, using an analytical model.

(Francesco has shown that with maps it is just the same) generate, on line, appropriate (compressed) representations of each “snapshot” to store representations on line, in a single “shot”, hold multiple representations simultaneously retrieve each representation from partial cues send back the retrieved information in a robust format (with neuronally plausible mechanisms) is something Hebbian associative networks can do ... p ~ 0.2 C / [a log(1/a)] (Francesco has shown that with maps it is just the same)

If LTP modifies the same synapses affected by learning... one may predict the effect of lower C values higher dp/dt

Carol Barnes found, contrasting young and old rats

multiple representations generate, on line, appropriate (compressed) representations of each “snapshot” to store representations on line, in a single “shot” multiple representations retrieve each representation from partial cues send back the retrieved information in a robust format are held most efficiently in a free autoassociator, which minimizes the components required for a given information content

CA3 is dominated by recurrent collaterals

the read-out of the retrieved information generate, on line, appropriate (compressed) representations of each “snapshot” store these representations on line, in a single “shot” hold multiple representations simultaneously retrieve each representation from partial cues the read-out of the retrieved information is greatly facilitated by expansion recoding with additional associative “polishing”

CA3 CA1 Analytical models predict an optimal plasticity level for CA3->CA1 (Schaffer) collaterals, but are not yet constrained enough to predict the observed memory activation differences CA3 CA1

…but, why do we need CA1, then? the answer may lie in the predictive ability that several models assign to the hippocampus (as well as to any associative network with time-asymmetric plasticity) although CA3 may predict future “contexts” as well as CA1, this may conflict with devoting its recurrent collaterals to retrieve the current “context”. We shall get back to this issue tomorrow…

generating information-rich compressed representations store these representations on line, in a single “shot” hold multiple representations simultaneously retrieve each representation from partial cues send back the retrieved information in a robust format requires a dedicated preprocessor that sparsifies and decorrelates input activity

Why the separation of a dentate gyrus? MF inputs (from DG) force an informative representation at storage and are irrelevant for retrieval PP inputs (from EC) modify during storage and relay the cue at retrieval

The crucial prediction is consistent with recordings from normal rats

but it is difficult to test it in dentate lesioned rats (Tucson data by Jim Knierim) but it is difficult to test it in dentate lesioned rats

Double dissociation Acquisition Index: Errors (T1-5 D1) - (T6-10 D1) Retrieval Index: Errors (T6-10 D1) - (T1-5 D2) Double dissociation