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Investigating the impact of memory reactivation on the successful forgetting of negative memories
Paula P. Brooks1,3, Justin Hulbert4, Arlene Lormestoire1, Maureen Ritchey3, & Kenneth Norman1,2
1Princeton Neuroscience Institute and 2Department of Psychology, Princeton University; 3Department of Psychology, Boston College; 4Department of Psychology, Bard College
Introduction
Hypothesis
Methodology
up to 5 s (ITI = 1 s)
Phase 1: Rating Scenes
6 s (ITI = 0.5 s)
Y or N? 1 2
CORRECT
< 4s
< 4s
2.5 s (ITI = 0.5 s)*Criterion test (70% learning criterion) not shown.
Phase 2: Study Face-Scene Pairs (incl. 3 Test-Feedback Cycles + Criterion Test)
2-hour break (± 30 min)
3 s
3 s (ITI = 1.5 – 4.5 s)
Phase 3: Think/No-Think Task
one-back image detection task
•negative scene•neutral scene•scrambled scene•object
Phase 4: Localizer Phase 5: Final Cued Recall Test
41+
41brown house on field…4 s
11 sbeep then ITI = 3s
N = 26 (target sample size = 50)Stopping an unwanted memory from coming to mind (i.e., memory suppression) might help to regulate negative memories. Memory suppression has commonly been studied using the think/no-think paradigm1.
Although multiple studies2 have demonstrated memory suppression effects, others have failed to replicate these findings3,4.
What causes the suppression of negative memories to succeed or fail?
DAY ONEDepression & anxiety questionnaires
DAY TWOStudy face-scene pairs
Think/no-think (TNT) memory suppression
Surprise memory test
• 1-7 days apart• Detailed schematic of
day two on the right
Relate memory reactivation during TNT task to subsequent memory performance (using Probabilistic Curve Induction and Testing)
Learning Phase TNT Phase Suppression Score =Baseline – No-Think
baseline no-think think
Perc
ent R
ecal
led
TNT Conditions
Anderson & Hanslmayr, 2014
We propose that differences in memory reactivation strength might lead to variability in suppression effects.
Nonmonotic plasticity hypothesis (NMPH)5,6
Some memories might be challenging to suppress because they are too strongly reactivated. In fact, individual variability (e.g., depression level) might impact memory reactivation and thus influence memory suppression effect.
Specifically, we predict an increase in memory reactivation as negative valence increases. We expect participants with more depression to reactivate negative stimuli more strongly than those with lower depression. In turn, this should affect subsequent memory performance.
Special thanks to Sam Nastase and Lizzie McDevitt for fMRI guidance.
[1] Anderson & Green, 2001; [2] Anderson & Hanslmayr, 2014; [3] Bulevich, et al., 2006; [4] Hertel & Mahan, 2008; [5] Detre et al., 2013; [6] Ritvo, Turk-Browne, & Norman, 2019; [7] Küpper et al., 2014
* Trials repeated 12x
Next Steps• Only use TNT trials that participants got correct in
the criterion test, in line with prior work7.• Take into account individual variability in
depression level, since this might impact the degree of memory reactivation.
• Relate memory reactivation during the TNT trials to memory performance during the surprise cued recall task ( ). We expect to see a relationship similar to the NMPH schematic.
3
1
23
Preliminary Results
1 Built logistic regression (L-2 regularized, penalty 𝜆 = 50) scene classifiers
2 Applied scene classifier TNT data
We looked at the response 3 and 4 TRs after cue onset (accounting for hemodynamic lag). As expected, there was a higher probability estimate for scenes for think versus no-think trials.
Surprisingly, there were no differences in scene prediction probability across negative valence level. However, any effect might be washed out by differences in depression level.
*used bilateral occipitotemporal mask*
Clas
sifie
r Lab
elne
gativ
e &
neut
ral s
cene
ssc
ram
bled
sc
enes
obje
cts
rest
negative scenes
scrambled scenes
objectsneutral scenes
rest0.0
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1.0
Real Category Label
Confusion Matrix
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Pred
icti
on P
roba
bilit
y
no-think thinkTNT Trial Condition
p < 0.001
Average probability estimate when applying the scene classifier
high medium low high medium low0.0
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Degree of Negative Valence Degree of Negative Valence
Pred
icti
on P
roba
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y
No-think trials Think trials
We also examined the time course of the prediction probability relative to the cue onset of the think and no-think trials. We see a peak in activity 3 and 4 TRs after the cue onset.
Asterisks denote significance.0.30
0.35
0.40
0.45
0.50
0.55
0.60
-1 0 1 2 3 4 5 6
no-think trialsthink trials
*
*
*
Average probability estimate for scene classifier across time
Pred
icti
on P
roba
bilit
y
Time (in TR, relative to cue onset)