Mnemonic prediction errors promote detailed memories.
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Citations
Statistical prediction of the future impairs episodic encoding of the present
Prediction Errors Disrupt Hippocampal Representations and Update Episodic Memories
Temporal Dynamics of Competition between Statistical Learning and Episodic Memory in Intracranial Recordings of Human Visual Cortex
Temporal Dynamics of Competition between Statistical Learning and Episodic Memory in Intracranial Recordings of Human Visual Cortex
Explicitly predicting outcomes enhances learning of expectancy-violating information
References
The Psychophysics Toolbox.
The VideoToolbox software for visual psychophysics: transforming numbers into movies.
A Neural Substrate of Prediction and Reward
Why there are complementary learning systems in the hippocampus and neocortex: insights from the successes and failures of connectionist models of learning and memory.
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Frequently Asked Questions (11)
Q2. What are the future works in this paper?
When the authors encounter a surprising event that violates their expectations, it is adaptive to update their memory in order to facilitate more accurate predictions in the future ( Ergo et al., 2020 ; Friston, 2018 ; Henson & Gagnepain, 2010 ; Niv & Schoenbaum, 2008 ; Rescorla & Wagner, 1972 ; Sinclair & Barense, 2019 ). Future research could further explore how attention and goals interact with memory in the processing of prediction errors ( Garlitch & Wahlheim, 2020 ; Kafkas et al., 2018b ; Ortiz-Tudela et al., 2018 ). Future research, potentially using fMRI, could evaluate predictions in the moment to better elucidate the conditions by which pruning of violated predictions occurs. Future research, potentially with additional measures ( e. g., memory dependency, Horner & Burgess, 2013, 2014 ), could better elucidate the specific relationship between memory for new events and prior memories ( see also Bein, Reggev, et al.
Q3. What did the authors find in Experiment 3?
In Experiment 3 the authors reduced prediction strength by lowering associative binding during encoding and found that while item memory remained intact overall, the memory advantage for violations was diminished.
Q4. What did the participants do to evoke expectations?
To evoke expectations, the authors employed a statistical learning paradigm in which participants were repeatedly presented with a stream of objects.
Q5. How many images were used to compose the original predictive pairs?
Of the total number of images, 180 images were allocated as images to compose the original predictive pairs, later to be violated or not violated (of these, 90 were classified as big objects and 90 were classified as small objects for the learning task, see below).
Q6. Why did the authors exclude participants based on low memory of the original pairs?
because this experiment aimed to examine item memory for the violation of weaklyencoded predictions, the authors did not exclude participants based on low memory of the original pairs (also note that on average, memory rates were approximately .4, which was their exclusion criterion in the previous experiments, see below).
Q7. What is the main reason for the memory advantage for items that violate category-level predictions?
These studies suggest that generating a memory prediction may reduce processing of external details as long as these predictions are met, and thus impair memory of external details like the specific item presented (see also Bein, Duncan, et al., 2020).
Q8. What is the effect of mnemonic prediction errors on the memory of items?
Another study found that mnemonic prediction errors enhanced recollection judgements for the violation item— perhaps reflecting additional details that were remembered from encoding—but did not enhance familiarity judgements that would reflect only item recognition (Kafkas & Montaldi, 2018a).
Q9. How does the complementary learning systems framework show that mnemonic prediction errors result in catastrophic interference?
the complementary learning systems framework shows computationally that the absence of a separated memory trace for mnemonic prediction errors results in catastrophic interference – incorrectly erasing previous memories (Kumaran et al., 2016; McClelland et al., 1995).
Q10. What is the interesting result by Kim et al.?
An interesting result by Kim et al. (2020) suggests that the memory advantage for violations might be attributed (at least in part) to reduced memory of prediction-consistent items.
Q11. What was the significance of the interaction between memory rates for identical old items?
Memory rates for identical old items were entered to a repeated-measures ANOVA with Original-Pair Memory (remembered or forgotten) and Response (‘old’ or ’similar’), which revealed a significant interaction (Exp 1.: F(1,26) = 5.58, p = .026; ηp2 = 0.18; Exp. 2: F(1,26) = 6.12, p = .020; ηp2 = 0.19).