We all live under the same roof

PALEOCORTEX

p C / [a ln(1/a)] ip N a ln(1/a) I/CN O(1 bit)

DG

CA3 CA1

platypus

What makes us non-lizards?

hippocampal reorganization includes a spatial migration...

...it does not lead to a new type of cortex...

but it is, fundamentally, a granulation.

the medial wall of cortexreorganizes into the hippocampusby inserting the fascia dentata,with its granule cells, at the input

note that the granule cells are (excitatory) interneurons

watch evolution on-line,

in the opossum

David Marr, over 30 years ago, suggested to start from the function

In humans, the hippocampushad long been implicatedin the formation of episodic andautobiographicalmemories

(here, data byGraham & Hodges)

Over the last fewyears, imagingevidence hascorroboratedtraditionalneuropsychologicalevidence

(here, fMRI studyof verbal encodinginto episodic memoryby Fernandez et al)

In rats, the evidencefrom neurophysiologicalrecordings indicatesa primary role inspatial memory

(here, data fromsimultaneousrecordings byMatt Wilson & Bruce McNaughton)

(although aminority viewhas emphasizeda more activerole in spatialcomputation;

here, data byNeil Burgess &John O’Keefe)

In monkeys,Edmund Rollset al have foundspatial view cells,suggestive of a hippocampalrole intermediatebetween thehuman and the rat description

David Marr’s perspective was the same

adopted by most of his followers...

(diagram by Jaap Murre, 1996)

If the Marr approach is correct

the functionshould explainthis structure

Yet, birds use their hippocampus, which

has a simpler structure, in a similar way ?!?

So, let us follow the same functional hypothesis...

…but let us try to be quantitative

is a Content Addressable Memory, which can be minimally implemented as an autoassociator with Hebbian plasticity on its recurrent collaterals.

A device able to:• generate, on line, compressed representations of cortical activity

store them on line, in a single “shot”hold multiple representations retrieve each one from partial cues• send back the retrieved information in a robust format

I ~ N a ln(1/a)CAM

associative

(CA3?)

CA3 is dominated by recurrent collaterals

The analysis of large-scale recordings(here, by Skaggs & McNaughton) shows that the information content of hippocampal representations grows linearly with populationsize, before saturating at the ceiling set by the experiment.

Francesco Battaglia hasquantified the full Iitem for place cells, usingan analytical model, and hehas shown how to map thestorage capacity for continuous attractors (“charts”) into that fordiscrete ones (“episodes”).

requires a dedicated preprocessor that sparsifies and decorrelates input activity

generate, on line, compressed representations store them on line, in a single “shot” hold multiple representations retrieve each one from partial cues• send back the retrieved information in a robust format

PP inputs (from EC) modify duringstorage and relay the cue at retrieval

MF inputs (from DG) force informativestorage and are irrelevant for 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)

is greatly facilitated by expansion recoding with additional associative ‘polishing’

generate, on line, compressed representations store them on line, in a single “shot” hold multiple representations retrieve each one from partial cues

the read-out of the information retrieved in CA3

CA3DG ?

CA3

CA1

Analytical models predict anoptimal plasticity level for CA3->CA1 (Schaffer)collaterals, but are not yetconstrained enough topredict the observed memoryactivation differences

information gain

Why the CA3-CA1 differentiation?

the answer may lie in the predictive abilitythat several models assign to the hippocampus.An undifferentiated CA network can both retrieve and predict, but a differentiation may help: although CA3 may predict future “contexts” as well as CA1, this may conflict with devoting its recurrent collaterals to retrieve the current “context”.

It could be, thus, that a CA3-CA1 differentiation brings about a quantitative advantage.

A simplified neural network simulation is themost efficient approach to address the issue.

CA1 CA3 DG

perforant path

uniform

mossy fibers

collaterals

PP

differentiated

RCSC

MF

CA

2noisy input cue `bump’ moves 0.5cm=0.2 unit per 12.5msec iteration

mossy fibers point-to-point, and active only during training

perforant path modifies with no trace rule

CA1

CA3

EC(DG)

the model connections (initially all random)

20 units

collaterals: come only from CA3 in the differentiated model, and are 66% suppressed in training

LTP(STDP)

present

presentpast

pastfuture

+ present

p f

A1

presentpast

pastfuture

+ future

adaptation

B

storage retrieval

LTP

present

past

pastfuture

pres.

reverb.

p f

no rev.

+ present

A2

but first, whatmechanism canyield prediction?

there are atleast 3candidates...

LTP(STDP)

present

presentpast

pastfuture

+ present

p f

A1

storage retrieval

STDP (at least whenmodelled with a simpletrace rule) is not quiteeffective enough, here,to produce prediction

STDP

LTP

present

past

pastfuture

pres.

reverb.

p f

no rev.

+ present

A2

storage retrieval

reverberationdelays

are no good either

modulated atretrieval

storage

presentpast

pastfuture

+ future

adaptation

B

firing rate adaptation can do it!

presentpast

pastfuture

+ future

adaptation

B

and differentiation does not help

though it does improve localization, just a bit

the advantage depends on the relative strengthof collateral connections during storage...

and during retrieval, in a non-trivial way

each representation has its optimal sparsity:

CADGEC

The mammalian hippocampus appears to be handsomely crafted

but why it needed 2 separate CA fields, we do not quite

understand

Gyuri Buzsaki might know

and Lokendra Shastri would have us believe there are even

more...

...and should anyone take awayfrom such words and predictions,

God shall take away his partout of the book of life,and out of the holy city

Revelations of John, XXII, 19-20

The last words

Says the experimenter this:Yes, I shall come quickly

Moser lab,Trondheim

Knierim lab,Texas

CA3 CA1