We all live under the same roof PALEOCORTEX p C / [a ln(1/a)] i p N a ln(1/a) I/CN O(1 bit)
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Transcript of We all live under the same roof PALEOCORTEX p C / [a ln(1/a)] i p N a ln(1/a) I/CN O(1 bit)
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