Does prediction error drive one-shot declarative learning?

Greve, Andrea; Cooper, Elisa; Kaula, Alexander; Anderson, Michael C.; Henson, Richard N.

doi:10.1016/j.jml.2016.11.001

Cited by 149 publications

(203 citation statements)

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“…Here, larger PEs were associated with a relative decrease in responding with locations that were consistent with the old schema, apparent in reduced evidence of responses -90 degrees from the current schema (i.e., at the position of the old schema for the inconsistent conditions) compared to what was observed in the consistent conditions. My work reveals that similar neural mechanisms underlie PE-based updating of long-term memory schemas, and short-term beliefs (Bennett et al, 2015;Jepma et al, 2018Jepma et al, , 2016Kolossa et al, 2015), consistent with what has been proposed in the literature (van Kesteren et al, 2012), and what has been shown for other types of memory (Greve et al, 2017(Greve et al, , 2019Pine et al, 2018;Sinclair & Barense, 2018.…”

Section: Discussionsupporting

confidence: 85%

“…Henson & Gagnepain, 2010;van Kesteren, Ruiter, Fernández, & Henson, 2012): When a predicted outcome does not match our experience, the resulting PE provides us with a surprise signal that is believed to guide learning. Recent findings suggest that PEbased learning underlies memory updating in many contexts: the updating of schematic rules (Greve, Cooper, Tibon, & Henson, 2019), of episodic memories (Greve, Cooper, Kaula, Anderson, & Henson, 2017;Sinclair & Barense, 2018, and of single semantic facts (Pine, Sadeh, Ben-Yakov, Dudai, & Mendelsohn, 2018).…”

Section: Introductionmentioning

confidence: 99%

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Prediction errors indexed by the P3 track the updating of complex long-term memory schemas

Richter

2019

Preprint

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Schemas are higher-level knowledge structures that store an abstraction of multiple previous experiences. They allow us to retain a multitude of information, but without the cost of storing every detail. Schemas are believed to be relatively stable, but occasionally have to be updated to remain useful in the face of changing environmental conditions. Once a schema is consolidated, schema updating has been proposed to be the result of a prediction error (PE) based learning mechanism, similar to the updating of less complex knowledge. However, for schema memory this hypothesis has so far been difficult to test since the tools to track small modifications to abstracted memory schemas have not been sensitive enough. Moreover, existing research on electrophysiological correlates of updating have focused on short-term belief updating tasks. Here I am using EEG and continuous memory measures recorded during the encoding of new schema consistent and inconsistent material to test the behavioural and neural correlates of schema updating. Schema updating was assessed in a memory test 24 hours after encountering inconsistent information, demonstrating the long-term effect of such PE-based learning. I observed a stronger relationship between behavioural PE and schema updating measures for inconsistent compared to consistent material, in line with the idea that more updating is required when a schema changes. Moreover, the P3 EEG signal tracked both the PE at the time of learning, as well as the updating of the memory schema one day later in the inconsistent condition. These results demonstrate that schema updating in the face of inconsistent information is indeed driven by PE-based mechanisms, and that similar neural mechanisms underlie the updating of consolidated long-term schemas and short-term belief structures.

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Section: Discussionsupporting

confidence: 85%

Section: Introductionmentioning

confidence: 99%

Prediction errors indexed by the P3 track the updating of complex long-term memory schemas

Richter

2019

Preprint

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“…Indeed, top-down expectation plays a significant role in guiding adaptive behaviour [9][10][11][12] . Recently, there has been growing interest in how expectation drives memory processes [13][14][15] . Consequently, the advantageous effect of contextual surprise on memory has been observed in numerous studies [16][17][18] .…”

Section: Introductionmentioning

confidence: 99%

“…Recently, there has been growing interest in how expectation drives memory processes [13][14][15] . Consequently, the advantageous effect of contextual surprise on memory has been observed in numerous studies [16][17][18] . The hippocampus, perhaps through interaction with the dopaminergic system [19][20][21][22] , is believed to support this effect by engaging an encoding state, leading to improved memory performance 21,[23][24][25] .…”

Section: Introductionmentioning

confidence: 99%

“…Despite the fact that expectation can be elicited and violated in different ways, to the best of our knowledge, research to date has only focused on external (contextual) expectation [16][17][18] and has not distinguished between different sources of expectation. However, employing a behavioural pattern separation task, with several foils of different levels of similarity to each target, also enables us to explore mnemonic-attribution expectation.…”

Section: Introductionmentioning

confidence: 99%

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Pattern separation is the key driver of expectation-modulated memory

Frank

Montaldi

2019

Preprint

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The hippocampus uses pattern separation and pattern completion in a continuous manner to successfully encode and retrieve memories 1,2 . However, whether and how cognitive factors might modulate the dynamics between these types of computation is not well understood. Here we examine the role of expectation in shifting the hippocampus to perform pattern separation. Expectation can be built up through multiple contextual exposures leading to prediction (as in a learnt contingency) or through logical deduction based on a previous mnemonic response. Participants first learned a contingency between a cue and an object's category (man-made or natural). Then, at encoding, one third of the cues that preceded the to-be-memorised objects violated the studied rule. At test, participants performed an old/new recognition task with old items (targets) and a set of parametrically manipulated (very similar to dissimilar) new foils for each object. We explored the effects of both contextual expectation, manipulated at initial encoding, and mnemonic-attribution expectation, driven by the mnemonic decisions taken on previous retrieval trials. For example, a target would be unexpected if in a previous trial a similar foil had been erroneously accepted as old. Memory was found to be better for foils of high and mid similarity to contextually unexpected targets at encoding, compared to expected ones. Additionally, violations of mnemonic-attribution expectation also yielded improved memory performance when the level of foil similarity was high. These results suggest that violations of both contextual expectation and mnemonic-attribution expectation engage pattern separation, resulting in better discrimination performance for these items. Importantly, this mechanism is engaged when input differentiation is required in order to make a correct recognition decision.

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False memories for true and false vaccination information form in line with pre‐existing vaccine opinions

Greene

Laurent

Hegarty

et al. 2022

Applied Cognitive Psychology

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Misinformation continually threatens efforts to control the COVID‐19 pandemic, with vaccine misinformation now a key concern. False memories for misinformation can influence behavioural intentions, yet little is known about the factors affecting (false) memories for vaccine‐related news items. Across two experiments (total n = 1481), this paper explores the effects of pre‐existing vaccine opinions on reported memories for true and false news items. In Study 1, participants ( n = 817) were exposed to fabricated pro‐ or anti‐vaccine news items, and then asked if they have a memory of this news event having occurred. In Study 2, participants ( n = 646) viewed true pro‐ or anti‐vaccine news items. News items were more likely to be remembered when they aligned with participants' pre‐existing vaccine beliefs, with stronger effects for pro‐vaccine information. We conclude by encouraging researchers to consider the role of attitudinal bias when developing interventions to reduce susceptibility to misinformation.

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Does prediction error drive one-shot declarative learning?

Abstract: HighlightsRole of prediction errors (PE) in human one-shot declarative learning.PE is manipulated via previous experiences (priors) and sensory inputs (evidence).PE leads to superior memory across 5 different experiments.Support for Predictive Interactive Multiple Memory Signals (PIMMS).

Cited by 149 publications

References 40 publications

Prediction errors indexed by the P3 track the updating of complex long-term memory schemas

Prediction errors indexed by the P3 track the updating of complex long-term memory schemas

Pattern separation is the key driver of expectation-modulated memory

False memories for true and false vaccination information form in line with pre‐existing vaccine opinions

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