predicting not to predict too much: how the cellular machinery of the brain

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Predicting not to predict too much: How the cellular machinery of the brain may anticipate the uncertain future Yadin Dudai Department of Neurobiology The Weizmann Institute of Science

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Predicting not to predict too much: How the cellular machinery of the brain may anticipate the uncertain future. Yadin Dudai Department of Neurobiology The Weizmann Institute of Science. The textbook account of the biography of a memory: - PowerPoint PPT Presentation

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Page 1: Predicting not to predict too much: How the cellular machinery of the brain

Predicting not to predict too much:How the cellular machinery of the brain

may anticipate the uncertain future

Yadin DudaiDepartment of Neurobiology

The Weizmann Institute of Science

Page 2: Predicting not to predict too much: How the cellular machinery of the brain

Consolidation

STM

LTM

Time

(The dual-trace hypothesis)

Storage

(Combining Ribot 1882, Muller & Pilzecker 1900, Hebb 1949, McGaugh 2000, Dudai 2004)

The textbook account of the biography of a memory: Items mature from a short-term into a long-term, stable state,

via consolidation, which occurs just once per item.

(The consolidation hypothesis)

Page 3: Predicting not to predict too much: How the cellular machinery of the brain

Active Memory Inactive Memory

(After Lewis 1973, Dudai 2004, Nader 2005)

An alternative account:

(The recurrent phases hypothesis)

(The reconsolidation hypothesis)

What do the data indicate?

Page 4: Predicting not to predict too much: How the cellular machinery of the brain

0

20

40

60

80

100

Ave

rsio

n I

nd

ex

LiCl ip

NaCl ip

An Experimental System: Conditioned Taste Aversion (CTA)

Taste CS Toxicosis US Aversion CR

Hrs Hrs - Yrs

Central gustatory area, insular cortex

(Same magnitude of memoryeven if first test performed

after several months)

Page 5: Predicting not to predict too much: How the cellular machinery of the brain

The algorithm for the formation of long-term memory in cortex and its molecular implementation

(Berman, Lamprecht, Rosenblum, Naor, Bahar, Kobilo, Shema & Dudai, 1996-2009)

consolidation

consolidation

I will now demonstrate 4 ways to alter long-term CTA memory in cortex

Prima facie, this model fits the classic, unidirectional, account of LTM

But do the data support such ‘deterministic’ interpretation?

Triggering memory encoding

Page 6: Predicting not to predict too much: How the cellular machinery of the brain

Taste memory consolidates in the insular cortex

Time

Mem

ory

STM

LTM

Consolidation

(Fits, but does not prove,the dual-trace hypothesis)

(A, taste exposure; B, CTA training. Data compiled from Rosenblum et al. 1993, Naor& Dudai 1996, Berman et al. 1998, Kobilo-Moav & Dudai unpublished, Elkobi et al. 2008)

180 240

ERK1/2Elk-1 PSD95

90 1206030

ScopolamineAnisomycin

Time after training (min)

Mag

nit

ude o

f obse

rved e

ffect

0.5

0.5

B. Blockade of long-term memory in cortex

A. Molecular changes in cortex following encoding

96h

Method No. 1: Disruption of consolidation

(Note time windows of consolidation)(Note time windows of consolidation)

Page 7: Predicting not to predict too much: How the cellular machinery of the brain

Long-term taste memory extinguishes with use in the insular cortex

Time

Mem

ory

STM

LTM

Consolidation

(Agnostic to thedual-trace hypothesis)

Non-reinforced retrieval

1 54 6Days

Retr

ieval

Tra

inin

g

Days

(untested control doesn’t decline in 4 months)

(Eisenberg et al. 2003, Stehberg & Dudai unpublished)

Method No. 2: Experimental ‘extinction’

Page 8: Predicting not to predict too much: How the cellular machinery of the brain

(Eisenberg et al. 2003)

1 2 65 7 8Days

Retr

ieval

Anisomycin into cortex

Anisomycin

Vehicle

Post-retrieval test days

Training

Long-term taste memory reconsolidates in the insular cortex

Time

Mem

ory

STM

LTM

Consolidation

(Does not fit the original dual-trace- and consolidation hypotheses)

Reconsolidation

Retrieval

Method No. 3: Disruption of ‘Reconsolidation’

Boundary conditions on reconsolidation:Extinction – No, New encoding - Yes

(Background: Misanin 1968, Sara 2000, Nader et al. 2000)

Page 9: Predicting not to predict too much: How the cellular machinery of the brain

(Berman, Lamprecht, Rosenblum, Naor, Bahar, Kobilo, Shema & Dudai, 1996-2009)

It now appears that there might bepotential plastic opportunities even in the absence of retrieval

consolidation

Method No. 4: Disruption of persistence

Page 10: Predicting not to predict too much: How the cellular machinery of the brain

Protein kinase M zeta (PKM) is an autonomous form of the atypical PKC, PKC, synthesized from PKMmRNA

(after Hernandez et al. 2003)

PKM can be inhibited by the pseudosubstrate peptide, ZIP

Page 11: Predicting not to predict too much: How the cellular machinery of the brain

Long-term taste memory is quickly erased by an inhibitor of PKM

Time

Mem

ory

STM

LTM

Consolidation

(Demonstrates that very-LTM requires persistent enzyme activity and is capable of rapid alterations)

100

20

60

Avers

ion index

Time from training to ZIP

Time

Tra

inin

g

Mem

ory

(Data compiled from Shema, Sacktor & Dudai. 2007, Shema, Sacktor, Hazvi & Dudai 2009)

3 MonthsCtrl1 MonthCtrl

Time from ZIP to test

ZIP

Tra

inin

g

Mem

ory

ZIP

Back to Method No. 4: Disruption of persistence

(Background: Pastalkova et al. 2006)

Page 12: Predicting not to predict too much: How the cellular machinery of the brain

Effect of ZIP on CTA memory in cortex:

• Once erased, memory can be reacquired – and re-erased• Not prevented by very intensive training• Not rescued by spontaneous recovery and US-reinstatement• Applies to multiple past taste-associations• Does not apply to taste recognition• Undetected before the taste association is established• Undetected within the first hour after training (i.e.,

consolidates)• Not replicated by a general serine/threonine kinase inhibtior

(H7)• Not replicated by microinfusions into the hippocampus• A manifestation of a physiological regulatory process?

Page 13: Predicting not to predict too much: How the cellular machinery of the brain

A cellular model: PKM increases insertion of AMPA receptorsinto the membrane via phosphorylation of scaffold/trafficking proteins

(Drawing modified from Hernandez et al. 2003)The weakest link?

Page 14: Predicting not to predict too much: How the cellular machinery of the brain

•There are multiple opportunities for a long-term memory trace to change in cortex :in consolidation ,

in extinction (where it is mostly the expression that changes) ,in post-retrieval reconsolidation ,and possibly also in the absence of retrieval .

•This modifiability of the cellular substrate of memory seems a basic attribute of memory. It is tempting to propose that it reflects the need to update and integrate new information into old, i.e., the need of memory systems to prepare forthe unpredictable demands of the future .

Take home message

Page 15: Predicting not to predict too much: How the cellular machinery of the brain

Memory models: which is closer to reality?

The dual-trace model: Consolidation just once per item, deterministic

The cyclic model: multiple windows of plasticity,trace modifiable in reactivation (reconsolidation)

The extended cyclic model: multiple windows of plasticity,trace modifiable in the presence and in the absence of reactivation

Ite

m a

cce

ssib

ility

Page 16: Predicting not to predict too much: How the cellular machinery of the brain

WIS

Reut ShemaShoshi HazviEfrat FurstOrit FurmanKelly LudmerDaniel LevyAvi MendelsohnUri NiliDana BezalelAya Ben-YakovMicah EdelsonYossi ChalamishYaara YeshurunShiri Ron

NYU

Joe LeDouxLila DavachiNava Rubin

SUNYTodd Sacktor