Learning-related representational changes reveal dissociable integration and separation signatures in the hippocampus and prefrontal cortex

Schlichting, Margaret L.; Mumford, Jeanette A.; Preston, Alison R.

doi:10.1038/ncomms9151

Cited by 309 publications

(485 citation statements)

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“…In particular, left anterior HPC showed greater functional connectivity during the early phase of learning with regions of mPFC, a finding predicted by SUSTAIN's neural framework (11). These results are also consistent with episodic memory findings that PFC biases encoding and retrieval of mnemonic information in HPC (9,27,28) and a recent proposal (29) that memories for individual experiences are updated through HPC-mPFC interactions to create generalized knowledge that supports complex behaviors like inference (8,30). We also found that early-learning HPC activation was coupled with regions implicated in a neural hierarchy of cognitive control along the rostral-caudal axis of lateral PFC (26,57,58).…”

Section: Discussionsupporting

confidence: 79%

“…It is noteworthy that our findings were localized to the anterior portion of the HPC. Recent rodent (38) and human (8,54) evidence suggests episodic memories are encoded according to a gradient of generalization along the HPC anterior-posterior axis. Posterior HPC has been shown to exhibit distinct representations for individual episodes, whereas anterior HPC codes for integrated representations that generalize across related episodes (8,22,38,54).…”

Section: Discussionmentioning

confidence: 99%

“…Recent rodent (38) and human (8,54) evidence suggests episodic memories are encoded according to a gradient of generalization along the HPC anterior-posterior axis. Posterior HPC has been shown to exhibit distinct representations for individual episodes, whereas anterior HPC codes for integrated representations that generalize across related episodes (8,22,38,54). The current study builds on these observations to show that anterior HPC representations are not limited to spatial contexts (19,38,55,56) or overlap between related episodes (8), but can also integrate attention-weighted object information across extended learning experiences.…”

Section: Discussionmentioning

confidence: 99%

“…Recent findings suggest HPC plays an important role in forming representations that integrate across shared features of experiences (6,(8)(9)(10)), yet there is little understanding about how HPC representations evolve when conceptual knowledge changes. Prominent computational theories posit that concept formation in HPC is influenced by selective attention mechanisms that favor goal-relevant features from our experiences (1,11,12).…”

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confidence: 99%

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Dynamic updating of hippocampal object representations reflects new conceptual knowledge

Mack

Love

Preston

2016

Proc. Natl. Acad. Sci. U.S.A.

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Concepts organize the relationship among individual stimuli or events by highlighting shared features. Often, new goals require updating conceptual knowledge to reflect relationships based on different goal-relevant features. Here, our aim is to determine how hippocampal (HPC) object representations are organized and updated to reflect changing conceptual knowledge. Participants learned two classification tasks in which successful learning required attention to different stimulus features, thus providing a means to index how representations of individual stimuli are reorganized according to changing task goals. We used a computational learning model to capture how people attended to goal-relevant features and organized object representations based on those features during learning. Using representational similarity analyses of functional magnetic resonance imaging data, we demonstrate that neural representations in left anterior HPC correspond with model predictions of concept organization. Moreover, we show that during early learning, when concept updating is most consequential, HPC is functionally coupled with prefrontal regions. Based on these findings, we propose that when task goals change, object representations in HPC can be organized in new ways, resulting in updated concepts that highlight the features most critical to the new goal.category learning | attention | computational modeling | hippocampus | fMRI C oncepts are organizing principles that define how items or events are similar to one another. Goals are critical to shaping concepts, by emphasizing some shared features over others. When goals change, previously experienced events may be organized in new ways, resulting in an updated concept that highlights the features most critical to the new goal. For instance, consider purchasing a home. One must learn which features make for the most desirable home. A young couple seeking a cosmopolitan lifestyle may organize potential houses based on trendy features like exposed brick walls, a wet bar, and room for vintage record collections. However, with the news of a baby on the way, the couple's goals are likely to shift. After pouring through parenting books and web forums to learn what makes for a child-friendly home, they may look at those previously seen potential homes in a different light. Instead, family-oriented features such as whether or not a home has a bathtub, is within walking distance to a park, and is in a well-respected school district may matter more resulting in a reorganization of which homes are a good buy. At the core of this example are the fundamental challenges we face in flexible goaldirected learning. When learning new concepts (e.g., child-friendly instead of a trendy house), attention changes focus to different information and items that were conceptually dissimilar (e.g., two houses with and without a wet bar) may become more similar (e.g., they both are close to a park) and vice versa (1). Understanding how conceptual knowledge is created and updated during learning is a cen...

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Section: Discussionsupporting

confidence: 79%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

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Dynamic updating of hippocampal object representations reflects new conceptual knowledge

Mack

Love

Preston

2016

Proc. Natl. Acad. Sci. U.S.A.

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206

248

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“…Other studies have demonstrated neural differentiation from learning of interrelated materials (Schapiro et al, 2012;Schlichting et al, 2015;Favila et al, 2016). The key contribution of the present work is that we provide a mechanism for differentiation (described above).…”

Section: Introductionmentioning

confidence: 99%

Neural Differentiation of Incorrectly Predicted Memories

2017

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When an item is predicted in a particular context but the prediction is violated, memory for that item is weakened (Kim et al., 2014). Here, we explore what happens when such previously mispredicted items are later reencountered. According to prior neural network simulations, this sequence of events-misprediction and subsequent restudy-should lead to differentiation of the item's neural representation from the previous context (on which the misprediction was based). Specifically, misprediction weakens connections in the representation to features shared with the previous context and restudy allows new features to be incorporated into the representation that are not shared with the previous context. This cycle of misprediction and restudy should have the net effect of moving the item's neural representation away from the neural representation of the previous context. We tested this hypothesis using human fMRI by tracking changes in item-specific BOLD activity patterns in the hippocampus, a key structure for representing memories and generating predictions. In left CA2/3/DG, we found greater neural differentiation for items that were repeatedly mispredicted and restudied compared with items from a control condition that was identical except without misprediction. We also measured prediction strength in a trial-by-trial fashion and found that greater misprediction for an item led to more differentiation, further supporting our hypothesis. Therefore, the consequences of prediction error go beyond memory weakening. If the mispredicted item is restudied, the brain adaptively differentiates its memory representation to improve the accuracy of subsequent predictions and to shield it from further weakening.

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Elucidating behavioral and functional connectivity markers of aberrant threat discrimination in PTSD

Keefe

Suarez‐Jimenez

Lee

et al. 2022

Depression and Anxiety

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Background Patients with posttraumatic stress disorder (PTSD) tend to overgeneralize threat to safe stimuli, potentially reflecting aberrant stimuli discrimination. Yet, it is not clear whether threat overgeneralization reflects general discrimination deficits, or rather a specific bias related to aversive stimuli. Here we tested this question and characterized the neural correlates of threat discrimination. Methods One‐hundred and eight participants (33 PTSD; 43 trauma‐exposed controls; 32 healthy controls) completed an emotionally neutral complex shape discrimination task involving identifying in 42 similar pairs the previously observed shape; and an emotionally aversive discrimination task, involving providing risk ratings for an aversive conditioned stimulus (CS+), and for several stimuli gradually differing in size from the original CS+. Resting state functional connectivity (rsFC) was collected before completing the tasks. Results No group differences emerged on the emotionally neutral task. Conversely, on the emotionally aversive task, individuals with PTSD had steeper linear risk rating slopes as the stimuli more resembled the conditioned stimulus. Finally, lower rsFC of amygdala‐default mode network (DMN) and DMN‐salience network (SN) were associated with steeper risk slopes, while for hippocampus‐SN, lower rsFC was found only among participants with PTSD. Conclusions Individuals with PTSD show deficits in discrimination only when presented with aversive stimuli. Dysregulated discrimination pattern may relate to a lack of input from regulatory brain areas (e.g., DMN/hippocampus) to threat‐related brain areas (e.g., SN/amygdala).

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Learning-related representational changes reveal dissociable integration and separation signatures in the hippocampus and prefrontal cortex

Cited by 309 publications

References 70 publications

Dynamic updating of hippocampal object representations reflects new conceptual knowledge

Dynamic updating of hippocampal object representations reflects new conceptual knowledge

Neural Differentiation of Incorrectly Predicted Memories

Elucidating behavioral and functional connectivity markers of aberrant threat discrimination in PTSD

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