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Buchberger ES, Joechner AK, Ngo CT, Lindenberger U, Werkle-Bergner M. Age differences in generalization, memory specificity, and their overnight fate in childhood. Child Dev 2024; 95:e270-e286. [PMID: 38516813 DOI: 10.1111/cdev.14089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/23/2024]
Abstract
Memory enables generalization to new situations, and memory specificity that preserves individual episodes. This study investigated generalization, memory specificity, and their overnight fate in 141 4- to 8-year-olds (computerized memory game; 71 females, tested 2020-2021 in Germany). The results replicated age effects in generalization and memory specificity, and a contingency of generalization on object conceptual properties and interobject semantic proximity. Age effects were stronger in generalization than in memory specificity, and generalization was more closely linked to the explicit regularity knowledge in older than in younger children. After an overnight delay, older children retained more generalized and specific memories and showed greater gains but only in generalization. These findings reveal distinct age differences in generalization and memory specificity across childhood.
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Affiliation(s)
- Elisa S Buchberger
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
| | - Ann-Kathrin Joechner
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
| | - Chi T Ngo
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
| | - Ulman Lindenberger
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany
| | - Markus Werkle-Bergner
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
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2
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Yates TS, Sherman BE, Yousif SR. More than a moment: What does it mean to call something an 'event'? Psychon Bull Rev 2023; 30:2067-2082. [PMID: 37407794 DOI: 10.3758/s13423-023-02311-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/14/2023] [Indexed: 07/07/2023]
Abstract
Experiences are stored in the mind as discrete mental units, or 'events,' which influence-and are influenced by-attention, learning, and memory. In this way, the notion of an 'event' is foundational to cognitive science. However, despite tremendous progress in understanding the behavioral and neural signatures of events, there is no agreed-upon definition of an event. Here, we discuss different theoretical frameworks of event perception and memory, noting what they can and cannot account for in the literature. We then highlight key aspects of events that we believe should be accounted for in theories of event processing--in particular, we argue that the structure and substance of events should be better reflected in our theories and paradigms. Finally, we discuss empirical gaps in the event cognition literature and what the future of event cognition research may look like.
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Affiliation(s)
- Tristan S Yates
- Department of Psychology, Yale University, New Haven, CT, USA.
| | - Brynn E Sherman
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA.
| | - Sami R Yousif
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA.
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3
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Forest TA, Abolghasem Z, Finn AS, Schlichting ML. Memories of structured input become increasingly distorted across development. Child Dev 2023; 94:e279-e295. [PMID: 37161780 DOI: 10.1111/cdev.13940] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Trajectories of cognitive and neural development suggest that, despite early emergence, the ability to extract environmental patterns changes across childhood. Here, 5- to 9-year-olds and adults (N = 211, 110 females, in a large Canadian city) completed a memory test assessing what they remembered after watching a stream of shape triplets: the particular sequence in which the shapes occurred and/or their group-level structure. After accounting for developmental improvements in overall memory, all ages remembered specific transitions, while memory for group membership was only observed in older children and adults (age by test-type interaction η2 = .05). Thus, while young children form memories for specifics of structured experience, memory for derived associations is refined later-underscoring that adults and young children form different memories despite identical experience.
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Affiliation(s)
| | - Zahra Abolghasem
- Department of Psychology, University of Toronto, Toronto, Ontario, Canada
| | - Amy S Finn
- Department of Psychology, University of Toronto, Toronto, Ontario, Canada
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4
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Ren X, Zhang H, Luo H. Dynamic emergence of relational structure network in human brains. Prog Neurobiol 2022; 219:102373. [DOI: 10.1016/j.pneurobio.2022.102373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 10/30/2022] [Accepted: 11/08/2022] [Indexed: 11/10/2022]
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Tsao A, Yousefzadeh SA, Meck WH, Moser MB, Moser EI. The neural bases for timing of durations. Nat Rev Neurosci 2022; 23:646-665. [PMID: 36097049 DOI: 10.1038/s41583-022-00623-3] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/19/2022] [Indexed: 11/10/2022]
Abstract
Durations are defined by a beginning and an end, and a major distinction is drawn between durations that start in the present and end in the future ('prospective timing') and durations that start in the past and end either in the past or the present ('retrospective timing'). Different psychological processes are thought to be engaged in each of these cases. The former is thought to engage a clock-like mechanism that accurately tracks the continuing passage of time, whereas the latter is thought to engage a reconstructive process that utilizes both temporal and non-temporal information from the memory of past events. We propose that, from a biological perspective, these two forms of duration 'estimation' are supported by computational processes that are both reliant on population state dynamics but are nevertheless distinct. Prospective timing is effectively carried out in a single step where the ongoing dynamics of population activity directly serve as the computation of duration, whereas retrospective timing is carried out in two steps: the initial generation of population state dynamics through the process of event segmentation and the subsequent computation of duration utilizing the memory of those dynamics.
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Affiliation(s)
- Albert Tsao
- Department of Biology, Stanford University, Stanford, CA, USA.
| | | | - Warren H Meck
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - May-Britt Moser
- Centre for Neural Computation, Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway
| | - Edvard I Moser
- Centre for Neural Computation, Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway.
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Pudhiyidath A, Morton NW, Viveros Duran R, Schapiro AC, Momennejad I, Hinojosa-Rowland DM, Molitor RJ, Preston AR. Representations of Temporal Community Structure in Hippocampus and Precuneus Predict Inductive Reasoning Decisions. J Cogn Neurosci 2022; 34:1736-1760. [PMID: 35579986 PMCID: PMC10262802 DOI: 10.1162/jocn_a_01864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Our understanding of the world is shaped by inferences about underlying structure. For example, at the gym, you might notice that the same people tend to arrive around the same time and infer that they are friends that work out together. Consistent with this idea, after participants are presented with a temporal sequence of objects that follows an underlying community structure, they are biased to infer that objects from the same community share the same properties. Here, we used fMRI to measure neural representations of objects after temporal community structure learning and examine how these representations support inference about object relationships. We found that community structure learning affected inferred object similarity: When asked to spatially group items based on their experience, participants tended to group together objects from the same community. Neural representations in perirhinal cortex predicted individual differences in object grouping, suggesting that high-level object representations are affected by temporal community learning. Furthermore, participants were biased to infer that objects from the same community would share the same properties. Using computational modeling of temporal learning and inference decisions, we found that inductive reasoning is influenced by both detailed knowledge of temporal statistics and abstract knowledge of the temporal communities. The fidelity of temporal community representations in hippocampus and precuneus predicted the degree to which temporal community membership biased reasoning decisions. Our results suggest that temporal knowledge is represented at multiple levels of abstraction, and that perirhinal cortex, hippocampus, and precuneus may support inference based on this knowledge.
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Neurophysiological Evidence for Cognitive Map Formation during Sequence Learning. eNeuro 2022; 9:ENEURO.0361-21.2022. [PMID: 35105662 PMCID: PMC8896554 DOI: 10.1523/eneuro.0361-21.2022] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Revised: 12/03/2021] [Accepted: 01/03/2022] [Indexed: 12/29/2022] Open
Abstract
Humans deftly parse statistics from sequences. Some theories posit that humans learn these statistics by forming cognitive maps, or underlying representations of the latent space which links items in the sequence. Here, an item in the sequence is a node, and the probability of transitioning between two items is an edge. Sequences can then be generated from walks through the latent space, with different spaces giving rise to different sequence statistics. Individual or group differences in sequence learning can be modeled by changing the time scale over which estimates of transition probabilities are built, or in other words, by changing the amount of temporal discounting. Latent space models with temporal discounting bear a resemblance to models of navigation through Euclidean spaces. However, few explicit links have been made between predictions from Euclidean spatial navigation and neural activity during human sequence learning. Here, we use a combination of behavioral modeling and intracranial encephalography (iEEG) recordings to investigate how neural activity might support the formation of space-like cognitive maps through temporal discounting during sequence learning. Specifically, we acquire human reaction times from a sequential reaction time task, to which we fit a model that formulates the amount of temporal discounting as a single free parameter. From the parameter, we calculate each individual's estimate of the latent space. We find that neural activity reflects these estimates mostly in the temporal lobe, including areas involved in spatial navigation. Similar to spatial navigation, we find that low-dimensional representations of neural activity allow for easy separation of important features, such as modules, in the latent space. Lastly, we take advantage of the high temporal resolution of iEEG data to determine the time scale on which latent spaces are learned. We find that learning typically happens within the first 500 trials, and is modulated by the underlying latent space and the amount of temporal discounting characteristic of each participant. Ultimately, this work provides important links between behavioral models of sequence learning and neural activity during the same behavior, and contextualizes these results within a broader framework of domain general cognitive maps.
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Broschard MB, Kim J, Love BC, Wasserman EA, Freeman JH. Prelimbic cortex maintains attention to category-relevant information and flexibly updates category representations. Neurobiol Learn Mem 2021; 185:107524. [PMID: 34560284 PMCID: PMC8633767 DOI: 10.1016/j.nlm.2021.107524] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Accepted: 09/15/2021] [Indexed: 11/23/2022]
Abstract
Category learning groups stimuli according to similarity or function. This involves finding and attending to stimulus features that reliably inform category membership. Although many of the neural mechanisms underlying categorization remain elusive, models of human category learning posit that prefrontal cortex plays a substantial role. Here, we investigated the role of the prelimbic cortex (PL) in rat visual category learning by administering excitotoxic lesions before category training and then evaluating the effects of the lesions with computational modeling. Using a touchscreen apparatus, rats (female and male) learned to categorize distributions of category stimuli that varied along two continuous dimensions. For some rats, categorizing the stimuli encouraged selective attention towards a single stimulus dimension (i.e., 1D tasks). For other rats, categorizing the stimuli required divided attention towards both stimulus dimensions (i.e., 2D tasks). Testing sessions then examined generalization to novel exemplars. PL lesions impaired learning and generalization for the 1D tasks, but not the 2D tasks. Then, a neural network was fit to the behavioral data to examine how the lesions affected categorization. The results suggest that the PL facilitates category learning by maintaining attention to category-relevant information and updating category representations.
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Affiliation(s)
- Matthew B Broschard
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, IA 52242, USA.
| | - Jangjin Kim
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, IA 52242, USA
| | - Bradley C Love
- Department of Experimental Psychology and The Alan Turing Institute, University College London, London, UK
| | - Edward A Wasserman
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, IA 52242, USA
| | - John H Freeman
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, IA 52242, USA
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Ngo CT, Benear SL, Popal H, Olson IR, Newcombe NS. Contingency of semantic generalization on episodic specificity varies across development. Curr Biol 2021; 31:2690-2697.e5. [PMID: 33887184 PMCID: PMC8222141 DOI: 10.1016/j.cub.2021.03.088] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 02/10/2021] [Accepted: 03/26/2021] [Indexed: 11/28/2022]
Abstract
Semantic memory-general knowledge of ideas and concepts-includes generalization processes that support inference. Episodic memory, on the other hand, preserves the specificity of individual events by binding together unique combinations of elements from an episode and relies on pattern separation to distinguish similar experiences. These two memory systems play complementary roles, supporting different mnemonic goals, but the nature and extent of their interdependence is unclear.1,2 Some models suggest that new information is encoded initially as hippocampus-dependent episodic memory and then, either through repetition or gist extraction, becomes semantic over time.3,4 These models also posit a neocortical route to semantic memory acquisition exists that can bypass the hippocampus.3 Both proposed routes are slow learning mechanisms, yet generalization can occur rapidly. Recent models suggest that fast generalization relies, in part, on the retrieval of individual but related episodes.5,6 Such episodic memory gating mechanisms render fast generalization contingent on the memory specificity of instances, a pattern that has been observed in adults.7,8 None of these models take into account the observation that generalization and episodic specificity have asynchronous developmental profiles, with generalization emerging years before episodic memory.9,10 We ask two questions about generalized and specific memory during early childhood: first, is rapid generalization contingent on remembering specific past memories? And second, does the strength or nature of this contingency differ across development? We found that the interdependence of generalization and episodic memory varies across development: generalization success in adults, but not in children, was contingent on context binding.
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Affiliation(s)
- Chi T Ngo
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany.
| | - Susan L Benear
- Department of Psychology, Temple University, Philadelphia, PA, USA
| | - Haroon Popal
- Department of Psychology, Temple University, Philadelphia, PA, USA
| | - Ingrid R Olson
- Department of Psychology, Temple University, Philadelphia, PA, USA
| | - Nora S Newcombe
- Department of Psychology, Temple University, Philadelphia, PA, USA
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10
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Kan IP, Rosenbaum RS, Verfaellie M. Schema processing across the lifespan: From theory to applications. Cogn Neuropsychol 2020; 37:1-7. [PMID: 32106740 DOI: 10.1080/02643294.2020.1736019] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Affiliation(s)
- Irene P Kan
- Department of Psychological & Brain Sciences, Villanova University, Villanova, PA, USA
| | - R Shayna Rosenbaum
- Department of Psychology, Vision: Science to Applications (VISTA) Program, York University, Toronto, Canada.,Rotman Research Institute, Baycrest, Toronto, Canada
| | - Mieke Verfaellie
- Memory Disorders Research Center, VA Boston Healthcare System and Boston University School of Medicine, Boston, MA, USA
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