1
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Xie Y, Mack ML. Reconciling category exceptions through representational shifts. Psychon Bull Rev 2024:10.3758/s13423-024-02501-8. [PMID: 38639836 DOI: 10.3758/s13423-024-02501-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/28/2024] [Indexed: 04/20/2024]
Abstract
Real-world categories often contain exceptions that disobey the perceptual regularities followed by other members. Prominent psychological and neurobiological theories indicate that exception learning relies on the flexible modulation of object representations, but the specific representational shifts key to learning remain poorly understood. Here, we leveraged behavioral and computational approaches to elucidate the representational dynamics during the acquisition of exceptions that violate established regularity knowledge. In our study, participants (n = 42) learned novel categories in which regular and exceptional items were introduced successively; we then fitted a computational model to individuals' categorization performance to infer latent stimulus representations before and after exception learning. We found that in the representational space, exception learning not only drove confusable exceptions to be differentiated from regular items, but also led exceptions within the same category to be integrated based on shared characteristics. These shifts resulted in distinct representational clusters of regular items and exceptions that constituted hierarchically structured category representations, and the distinct clustering of exceptions from regular items was associated with a high ability to generalize and reconcile knowledge of regularities and exceptions. Moreover, by having a second group of participants (n = 42) to judge stimuli's similarity before and after exception learning, we revealed misalignment between representational similarity and behavioral similarity judgments, which further highlights the hierarchical layouts of categories with regularities and exceptions. Altogether, our findings elucidate the representational dynamics giving rise to generalizable category structures that reconcile perceptually inconsistent category members, thereby advancing the understanding of knowledge formation.
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Affiliation(s)
- Yongzhen Xie
- Department of Psychology, University of Toronto, 100 St. George Street, Toronto, ON, M5S 3G3, Canada.
| | - Michael L Mack
- Department of Psychology, University of Toronto, 100 St. George Street, Toronto, ON, M5S 3G3, Canada
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2
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Reggev N. Motivation and prediction-driven processing of social memoranda. Neurosci Biobehav Rev 2024; 159:105613. [PMID: 38437974 DOI: 10.1016/j.neubiorev.2024.105613] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2023] [Revised: 12/09/2023] [Accepted: 02/28/2024] [Indexed: 03/06/2024]
Abstract
Social semantic memory guides many aspects of behavior. Individuals rely on acquired and inferred knowledge about personal characteristics and group membership to predict the behavior and character of social targets. These predictions then determine the expectations from, the behavior in, and the interpretations of social interactions. According to predictive processing accounts, mnemonic and attentional mechanisms should enhance the processing of prediction-violating events. However, empirical findings suggest that prediction-consistent social events are often better remembered. This mini-review integrates recent evidence from social and non-social memory research to highlight the role of motivation in explaining these discrepancies. A particular emphasis is given to the continuous nature of prediction-(in)consistency, the epistemic tendency of perceivers to maintain or update their knowledge, and the dynamic influences of motivation on multiple steps in prediction-driven social memory. The suggested framework provides a coherent outlook of existing work and offers promising future directions to better understand the ebb and flow of social memoranda.
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Affiliation(s)
- Niv Reggev
- Department of Psychology, Ben-Gurion University of the Negev, Beer Sheva, Israel; School of Brain and Cognitive Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel.
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3
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Spens E, Burgess N. A generative model of memory construction and consolidation. Nat Hum Behav 2024; 8:526-543. [PMID: 38242925 PMCID: PMC10963272 DOI: 10.1038/s41562-023-01799-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 12/05/2023] [Indexed: 01/21/2024]
Abstract
Episodic memories are (re)constructed, share neural substrates with imagination, combine unique features with schema-based predictions and show schema-based distortions that increase with consolidation. Here we present a computational model in which hippocampal replay (from an autoassociative network) trains generative models (variational autoencoders) to (re)create sensory experiences from latent variable representations in entorhinal, medial prefrontal and anterolateral temporal cortices via the hippocampal formation. Simulations show effects of memory age and hippocampal lesions in agreement with previous models, but also provide mechanisms for semantic memory, imagination, episodic future thinking, relational inference and schema-based distortions including boundary extension. The model explains how unique sensory and predictable conceptual elements of memories are stored and reconstructed by efficiently combining both hippocampal and neocortical systems, optimizing the use of limited hippocampal storage for new and unusual information. Overall, we believe hippocampal replay training generative models provides a comprehensive account of memory construction, imagination and consolidation.
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Affiliation(s)
- Eleanor Spens
- UCL Institute of Cognitive Neuroscience, University College London, London, UK.
| | - Neil Burgess
- UCL Institute of Cognitive Neuroscience, University College London, London, UK.
- UCL Queen Square Institute of Neurology, University College London, London, UK.
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4
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Nolden S, Turan G, Güler B, Günseli E. Prediction error and event segmentation in episodic memory. Neurosci Biobehav Rev 2024; 157:105533. [PMID: 38184184 DOI: 10.1016/j.neubiorev.2024.105533] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2023] [Revised: 12/11/2023] [Accepted: 01/02/2024] [Indexed: 01/08/2024]
Abstract
Organizing the continuous flow of experiences into meaningful events is a crucial prerequisite for episodic memory. Prediction error and event segmentation both play important roles in supporting the genesis of meaningful mnemonic representations of events. We review theoretical contributions discussing the relationship between prediction error and event segmentation, as well as literature on episodic memory related to prediction error and event segmentation. We discuss the extent of overlap of mechanisms underlying memory emergence through prediction error and event segmentation, with a specific focus on attention and working memory. Finally, we identify areas in research that are currently developing and suggest future directions. We provide an overview of mechanisms underlying memory formation through predictions, violations of predictions, and event segmentation.
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Affiliation(s)
- Sophie Nolden
- Department for Developmental Psychology, Institute of Psychology, Goethe-University Frankfurt am Main, Germany; IDeA-Center for Research on Individual Development and Adaptive Education of Children at Risk, Frankfurt am Main, Germany.
| | - Gözem Turan
- Department for Developmental Psychology, Institute of Psychology, Goethe-University Frankfurt am Main, Germany; IDeA-Center for Research on Individual Development and Adaptive Education of Children at Risk, Frankfurt am Main, Germany
| | - Berna Güler
- Department of Psychology, Sabanci University, Istanbul, Turkey
| | - Eren Günseli
- Department of Psychology, Sabanci University, Istanbul, Turkey
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5
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Shing YL, Brod G, Greve A. Prediction error and memory across the lifespan. Neurosci Biobehav Rev 2023; 155:105462. [PMID: 37951515 DOI: 10.1016/j.neubiorev.2023.105462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 10/27/2023] [Accepted: 11/07/2023] [Indexed: 11/14/2023]
Abstract
The influence of Prediction Errors (PEs) on episodic memory has generated growing empirical and theoretical interest. This review explores how the relationship between PE and memory may evolve throughout lifespan. Drawing upon the predictive processing framework and the Predictive, Interactive Multiple Memory System (PIMMS) model in particular, the paper highlights the hierarchical organization of memory systems and the interaction between top-down predictions and bottom-up sensory input, proposing that PEs promote synaptic change and improve encoding and consolidation processes. We discuss the neuroscientific mechanisms underlying PE-driven memory enhancement, focusing on the involvement of the hippocampus, the entorhinal cortex-hippocampus pathway, and the noradrenergic sympathetic system. Recognizing the divergent trajectories of episodic and semantic memory across the lifespan is crucial when examining the effects of PEs on memory. This review underscores the heterogeneity of memory processes and neurocognitive mechanisms underlying PE-driven memory enhancement across age. Future research is suggested to directly compare neural networks involved in learning from PEs across different age groups and to contribute to a deeper understanding of PE-driven learning across age.
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Affiliation(s)
- Yee Lee Shing
- Department of Psychology, Goethe University Frankfurt, Germany; IDeA-Center for Individual Development and Adaptive Education of Children at Risk, Frankfurt am Main, Germany.
| | - Garvin Brod
- Department of Psychology, Goethe University Frankfurt, Germany; IDeA-Center for Individual Development and Adaptive Education of Children at Risk, Frankfurt am Main, Germany; Department of Education and Human Development, DIPF, Leibniz Institute for Research and Information in Education, Germany
| | - Andrea Greve
- MRC Cognition and Brain Sciences Unit, University of Cambridge, United Kingdom
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6
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Moscovitch DA, Moscovitch M, Sheldon S. Neurocognitive Model of Schema-Congruent and -Incongruent Learning in Clinical Disorders: Application to Social Anxiety and Beyond. PERSPECTIVES ON PSYCHOLOGICAL SCIENCE 2023; 18:1412-1435. [PMID: 36795637 PMCID: PMC10623626 DOI: 10.1177/17456916221141351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/17/2023]
Abstract
Negative schemas lie at the core of many common and debilitating mental disorders. Thus, intervention scientists and clinicians have long recognized the importance of designing effective interventions that target schema change. Here, we suggest that the optimal development and administration of such interventions can benefit from a framework outlining how schema change occurs in the brain. Guided by basic neuroscientific findings, we provide a memory-based neurocognitive framework for conceptualizing how schemas emerge and change over time and how they can be modified during psychological treatment of clinical disorders. We highlight the critical roles of the hippocampus, ventromedial prefrontal cortex, amygdala, and posterior neocortex in directing schema-congruent and -incongruent learning (SCIL) in the interactive neural network that comprises the autobiographical memory system. We then use this framework, which we call the SCIL model, to derive new insights about the optimal design features of clinical interventions that aim to strengthen or weaken schema-based knowledge through the core processes of episodic mental simulation and prediction error. Finally, we examine clinical applications of the SCIL model to schema-change interventions in psychotherapy and provide cognitive-behavior therapy for social anxiety disorder as an illustrative example.
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Affiliation(s)
- David A. Moscovitch
- Department of Psychology and Centre for Mental Health Research & Treatment, University of Waterloo
| | - Morris Moscovitch
- Rotman Research Institute and Department of Psychology, Baycrest Centre for Geriatric Care
- Department of Psychology, University of Toronto
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7
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Bein O, Gasser C, Amer T, Maril A, Davachi L. Predictions transform memories: How expected versus unexpected events are integrated or separated in memory. Neurosci Biobehav Rev 2023; 153:105368. [PMID: 37619645 PMCID: PMC10591973 DOI: 10.1016/j.neubiorev.2023.105368] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Revised: 08/13/2023] [Accepted: 08/21/2023] [Indexed: 08/26/2023]
Abstract
Our brains constantly generate predictions about the environment based on prior knowledge. Many of the events we experience are consistent with these predictions, while others might be inconsistent with prior knowledge and thus violate our predictions. To guide future behavior, the memory system must be able to strengthen, transform, or add to existing knowledge based on the accuracy of our predictions. We synthesize recent evidence suggesting that when an event is consistent with our predictions, it leads to neural integration between related memories, which is associated with enhanced associative memory, as well as memory biases. Prediction errors, in turn, can promote both neural integration and separation, and lead to multiple mnemonic outcomes. We review these findings and how they interact with factors such as memory reactivation, prediction error strength, and task goals, to offer insight into what determines memory for events that violate our predictions. In doing so, this review brings together recent neural and behavioral research to advance our understanding of how predictions shape memory, and why.
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Affiliation(s)
- Oded Bein
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, United States.
| | - Camille Gasser
- Department of Psychology, Columbia University, New York, NY, United States.
| | - Tarek Amer
- Department of Psychology, University of Victoria, Victoria, Canada
| | - Anat Maril
- Department of Psychology, The Hebrew University of Jerusalem, Jerusalem, Israel; Department of Cognitive Science, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Lila Davachi
- Center for Clinical Research, The Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, United States
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8
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Rouhani N, Niv Y, Frank MJ, Schwabe L. Multiple routes to enhanced memory for emotionally relevant events. Trends Cogn Sci 2023; 27:867-882. [PMID: 37479601 DOI: 10.1016/j.tics.2023.06.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 06/13/2023] [Accepted: 06/15/2023] [Indexed: 07/23/2023]
Abstract
Events associated with aversive or rewarding outcomes are prioritized in memory. This memory boost is commonly attributed to the elicited affective response, closely linked to noradrenergic and dopaminergic modulation of hippocampal plasticity. Herein we review and compare this 'affect' mechanism to an additional, recently discovered, 'prediction' mechanism whereby memories are strengthened by the extent to which outcomes deviate from expectations, that is, by prediction errors (PEs). The mnemonic impact of PEs is separate from the affective outcome itself and has a distinct neural signature. While both routes enhance memory, these mechanisms are linked to different - and sometimes opposing - predictions for memory integration. We discuss new findings that highlight mechanisms by which emotional events strengthen, integrate, and segment memory.
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Affiliation(s)
- Nina Rouhani
- Division of Biology and Biological Engineering and Division of Humanities and Social Sciences, California Institute of Technology, Pasadena, CA, USA
| | - Yael Niv
- Department of Psychology and Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Michael J Frank
- Department of Cognitive, Linguistic & Psychological Sciences and Carney Institute for Brain Science, Brown University, Providence, RI, USA
| | - Lars Schwabe
- Department of Cognitive Psychology, Institute of Psychology, Universität Hamburg, Hamburg, Germany.
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9
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Rouhani N, Stanley D, Adolphs R. Collective events and individual affect shape autobiographical memory. Proc Natl Acad Sci U S A 2023; 120:e2221919120. [PMID: 37432994 PMCID: PMC10629560 DOI: 10.1073/pnas.2221919120] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Accepted: 06/06/2023] [Indexed: 07/13/2023] Open
Abstract
How do collective events shape how we remember our lives? We leveraged advances in natural language processing as well as a rich, longitudinal assessment of 1,000 Americans throughout 2020 to examine how memory is influenced by two prominent factors: surprise and emotion. Autobiographical memory for 2020 displayed a unique signature: There was a substantial bump in March, aligning with pandemic onset and lockdowns, consistent across three memory collections 1 y apart. We further investigated how emotion, using both immediate and retrieved measures, predicted the amount and content of autobiographical memory: Negative affect increased recall across all measures, whereas its more clinical indices, depression and posttraumatic stress disorder, selectively increased nonepisodic recall. Finally, in a separate cohort, we found pandemic news to be better remembered, surprising, and negative, while lockdowns compressed remembered time. Our work connects laboratory findings to the real world and delineates the effects of acute versus clinical signatures of negative emotion on memory.
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Affiliation(s)
- Nina Rouhani
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA91125
- Division of Humanities and Social Sciences, California Institute of Technology, Pasadena, CA91125
| | - Damian Stanley
- Division of Humanities and Social Sciences, California Institute of Technology, Pasadena, CA91125
- Derner School of Psychology, Adelphi University, New York, NY11530
| | | | - Ralph Adolphs
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA91125
- Division of Humanities and Social Sciences, California Institute of Technology, Pasadena, CA91125
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10
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Brod G, Greve A, Jolles D, Theobald M, Galeano-Keiner EM. Explicitly predicting outcomes enhances learning of expectancy-violating information. Psychon Bull Rev 2022; 29:2192-2201. [PMID: 35768657 PMCID: PMC9722848 DOI: 10.3758/s13423-022-02124-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/08/2022] [Indexed: 11/08/2022]
Abstract
Predictive coding models suggest that the brain constantly makes predictions about what will happen next based on past experiences. Learning is triggered by surprising events, i.e., a prediction error. Does it benefit learning when these predictions are made deliberately, so that an individual explicitly commits to an outcome before experiencing it? Across two experiments, we tested whether generating an explicit prediction before seeing numerical facts boosts learning of expectancy-violating information relative to doing so post hoc. Across both experiments, predicting boosted memory for highly unexpected outcomes, leading to a U-shaped relation between expectedness and memory. In the post hoc condition, memory performance decreased with increased unexpectedness. Pupillary data of Experiment 2 further indicated that the pupillary surprise response to highly expectancy-violating outcomes predicted successful learning of these outcomes. Together, these findings suggest that generating an explicit prediction increases learners' stakes in the outcome, which particularly benefits learning of those outcomes that are different than expected.
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Affiliation(s)
- Garvin Brod
- DIPF | Leibniz Institute for Research and Information in Education, Rostocker Str. 6, 60323, Frankfurt am Main, Germany.
- Department of Psychology, Goethe University, Frankfurt, Germany.
| | - Andrea Greve
- MRC Cognition & Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Dietsje Jolles
- Institute of Education and Child Studies, Universiteit Leiden, Leiden, The Netherlands
| | - Maria Theobald
- DIPF | Leibniz Institute for Research and Information in Education, Rostocker Str. 6, 60323, Frankfurt am Main, Germany
| | - Elena M Galeano-Keiner
- DIPF | Leibniz Institute for Research and Information in Education, Rostocker Str. 6, 60323, Frankfurt am Main, Germany
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11
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Sherman BE, Graves KN, Huberdeau DM, Quraishi IH, Damisah EC, Turk-Browne NB. Temporal Dynamics of Competition between Statistical Learning and Episodic Memory in Intracranial Recordings of Human Visual Cortex. J Neurosci 2022; 42:9053-9068. [PMID: 36344264 PMCID: PMC9732826 DOI: 10.1523/jneurosci.0708-22.2022] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 10/10/2022] [Accepted: 10/13/2022] [Indexed: 11/09/2022] Open
Abstract
The function of long-term memory is not just to reminisce about the past, but also to make predictions that help us behave appropriately and efficiently in the future. This predictive function of memory provides a new perspective on the classic question from memory research of why we remember some things but not others. If prediction is a key outcome of memory, then the extent to which an item generates a prediction signifies that this information already exists in memory and need not be encoded. We tested this principle using human intracranial EEG as a time-resolved method to quantify prediction in visual cortex during a statistical learning task and link the strength of these predictions to subsequent episodic memory behavior. Epilepsy patients of both sexes viewed rapid streams of scenes, some of which contained regularities that allowed the category of the next scene to be predicted. We verified that statistical learning occurred using neural frequency tagging and measured category prediction with multivariate pattern analysis. Although neural prediction was robust overall, this was driven entirely by predictive items that were subsequently forgotten. Such interference provides a mechanism by which prediction can regulate memory formation to prioritize encoding of information that could help learn new predictive relationships.SIGNIFICANCE STATEMENT When faced with a new experience, we are rarely at a loss for what to do. Rather, because many aspects of the world are stable over time, we rely on past experiences to generate expectations that guide behavior. Here we show that these expectations during a new experience come at the expense of memory for that experience. From intracranial recordings of visual cortex, we decoded what humans expected to see next in a series of photographs based on patterns of neural activity. Photographs that generated strong neural expectations were more likely to be forgotten in a later behavioral memory test. Prioritizing the storage of experiences that currently lead to weak expectations could help improve these expectations in future encounters.
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Affiliation(s)
- Brynn E Sherman
- Department of Psychology, Yale University, 2 Hillhouse Avenue, New Haven, CT 06520
| | - Kathryn N Graves
- Department of Psychology, Yale University, 2 Hillhouse Avenue, New Haven, CT 06520
| | - David M Huberdeau
- Department of Psychology, Yale University, 2 Hillhouse Avenue, New Haven, CT 06520
| | - Imran H Quraishi
- Department of Neurology, Yale University, 800 Howard Avenue, New Haven, CT 06519
| | - Eyiyemisi C Damisah
- Department of Neurosurgery, Yale University, 333 Cedar Street, New Haven, CT 06510
| | - Nicholas B Turk-Browne
- Department of Psychology, Yale University, 2 Hillhouse Avenue, New Haven, CT 06520
- Wu Tsai Institute, Yale University, 100 College Street, New Haven, CT 06510
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12
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Rusk RD. An Adaptive Motivation Approach to Understanding the 'How' and 'Why' of Wellbeing. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:12784. [PMID: 36232083 PMCID: PMC9566260 DOI: 10.3390/ijerph191912784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 09/26/2022] [Accepted: 09/27/2022] [Indexed: 06/16/2023]
Abstract
A new model provides insight into the 'how' and 'why' of wellbeing to better understand the 'what'. Informed by evolutionary psychology and neuroscience, it proposes that systems for adaptive motivation underpin experiential and reflective wellbeing. The model proposes that the brain learns to predict situations, and errors arise between the predictions and experience. These prediction errors drive emotional experience, learning, motivation, decision-making, and the formation of wellbeing-relevant memories. The model differentiates four layers of wellbeing: objective, experiential, reflective, and narrative, which relate to the model in different ways. Constituents of wellbeing, human motives, and specific emotions integrate into the model. A simple computational implementation of the model reproduced several established wellbeing phenomena, including: the greater frequency of pleasant to unpleasant emotions, the stronger emotional salience of unpleasant emotions, hedonic adaptation to changes in circumstances, heritable influences on wellbeing, and affective forecasting errors. It highlights the importance of individual differences, and implies that high wellbeing will correlate with the experience of infrequent, routine, and predictable avoidance cues and frequent, varied, and novel approach cues. The model suggests that wellbeing arises directly from a system for adaptive motivation. This system functions like a mental dashboard that calls attention to situational changes and motivates the kinds of behaviours that gave humans a relative advantage in their ancestral environment. The model offers a set of fundamental principles and processes that may underlie diverse conceptualisations of wellbeing.
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Affiliation(s)
- Reuben D Rusk
- Centre for Wellbeing Science, University of Melbourne, Melbourne, VIC 3010, Australia
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13
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The hippocampal formation and action at a distance. Proc Natl Acad Sci U S A 2021; 118:2119670118. [PMID: 34916299 DOI: 10.1073/pnas.2119670118] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/15/2021] [Indexed: 11/18/2022] Open
Abstract
The question of why our conceptions of space and time are intertwined with memory in the hippocampal formation is at the forefront of much current theorizing about this brain system. In this article I argue that animals bridge spatial and temporal gaps through the creation of internal models that allow them to act on the basis of things that exist in a distant place and/or existed at a different time. The hippocampal formation plays a critical role in these processes by stitching together spatiotemporally disparate entities and events. It does this by 1) constructing cognitive maps that represent extended spatial contexts, incorporating and linking aspects of an environment that may never have been experienced together; 2) creating neural trajectories that link the parts of an event, whether they occur in close temporal proximity or not, enabling the construction of event representations even when elements of that event were experienced at quite different times; and 3) using these maps and trajectories to simulate possible futures. As a function of these hippocampally driven processes, our subjective sense of both space and time are interwoven constructions of the mind, much as the philosopher Immanuel Kant postulated.
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14
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Prediction errors disrupt hippocampal representations and update episodic memories. Proc Natl Acad Sci U S A 2021; 118:2117625118. [PMID: 34911768 DOI: 10.1073/pnas.2117625118] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/05/2021] [Indexed: 11/18/2022] Open
Abstract
The brain supports adaptive behavior by generating predictions, learning from errors, and updating memories to incorporate new information. Prediction error, or surprise, triggers learning when reality contradicts expectations. Prior studies have shown that the hippocampus signals prediction errors, but the hypothesized link to memory updating has not been demonstrated. In a human functional MRI study, we elicited mnemonic prediction errors by interrupting familiar narrative videos immediately before the expected endings. We found that prediction errors reversed the relationship between univariate hippocampal activation and memory: greater hippocampal activation predicted memory preservation after expected endings, but memory updating after surprising endings. In contrast to previous studies, we show that univariate activation was insufficient for understanding hippocampal prediction error signals. We explain this surprising finding by tracking both the evolution of hippocampal activation patterns and the connectivity between the hippocampus and neuromodulatory regions. We found that hippocampal activation patterns stabilized as each narrative episode unfolded, suggesting sustained episodic representations. Prediction errors disrupted these sustained representations and the degree of disruption predicted memory updating. The relationship between hippocampal activation and subsequent memory depended on concurrent basal forebrain activation, supporting the idea that cholinergic modulation regulates attention and memory. We conclude that prediction errors create conditions that favor memory updating, prompting the hippocampus to abandon ongoing predictions and make memories malleable.
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