Distinct hippocampal mechanisms support concept formation and updating.

Learning systems must constantly decide whether to create new representations or update existing ones. For example, a child learning that a bat is a mammal and not a bird would be best served by creating a new representation, whereas updating may be best when encountering a second similar bat. Characterizing the neural dynamics that underlie these complementary memory operations requires identifying the exact moments when each operation occurs. We address this challenge by interrogating fMRI brain activation with a computational learning model that predicts trial-by-trial when memories are created versus updated. We found distinct neural engagement in anterior hippocampus and ventral striatum for model-predicted memory create and update events during early learning. Notably, the degree of this effect in hippocampus, but not ventral striatum, significantly related to learning outcome. Hippocampus additionally showed distinct patterns of functional coactivation with ventromedial prefrontal cortex and angular gyrus during memory creation and premotor cortex during memory updating. These findings suggest that complementary memory functions, as formalized in computational learning models, underlie the rapid formation of novel conceptual knowledge, with the hippocampus and its interactions with frontoparietal circuits playing a crucial role in successful learning. Significance statement: How do we reconcile new experiences with existing knowledge? Prominent theories suggest that novel information is either captured by creating new memories or leveraged to update existing memories, yet empirical support of how these distinct memory operations unfold during learning is limited. Here, we combine computational modeling of human learning behaviour with functional neuroimaging to identify moments of memory formation and updating and characterize their neural signatures. We find that both hippocampus and ventral striatum are distinctly engaged when memories are created versus updated; however, it is only hippocampus activation that is associated with learning outcomes. Our findings motivate a key theoretical revision that positions hippocampus is a key player in building organized memories from the earliest moments of learning.

Asynchronous development of memory integration and differentiation influences temporal memory organization.

Adults remember items with shared contexts as occurring closer in time to one another than those associated with different contexts, even when their objective temporal distance is fixed. Such temporal memory biases are thought to reflect within-event integration and between-event differentiation processes that organize events according to their contextual similarities and differences, respectively. Within-event integration and between-event differentiation are hypothesized to differentially rely on binding and control processes, which may develop at different ages. To test this hypothesis, 5- to 12-year-olds and adults (N = 134) studied quartets of image pairs that contained either the same scene (same-context) or different scenes (different-context). Participants remembered same-context items as occurring closer in time by older childhood (7-9 years), whereas different-context items were remembered as occurring farther apart by early adolescence (10-12 years). The differential emergence of these temporal memory biases suggests within-event integration and between-event differentiation emerge at different ages. RESEARCH HIGHLIGHTS: Children are less likely than adults to use contextual information (e.g., location) to organize their continuous experience in memory, as indicated by temporal memory biases. Biases reflecting within-event integration (i.e., remembering elements with a shared context as occurring closer together in time) emerged in late childhood. Biases reflecting between-event differentiation (i.e., remembering elements from different contexts as occurring farther apart in time) emerged in early adolescence. The differential emergence of biases reflecting within-event integration and between-event differentiation suggests they are distinct, yet complementary, processes that support developmental improvements in event memory organization.

Development of human hippocampal subfield microstructure and relation to associative inference.

The hippocampus is a complex brain structure composed of subfields that each have distinct cellular organizations. While the volume of hippocampal subfields displays age-related changes that have been associated with inference and memory functions, the degree to which the cellular organization within each subfield is related to these functions throughout development is not well understood. We employed an explicit model testing approach to characterize the development of tissue microstructure and its relationship to performance on 2 inference tasks, one that required memory (memory-based inference) and one that required only perceptually available information (perception-based inference). We found that each subfield had a unique relationship with age in terms of its cellular organization. While the subiculum (SUB) displayed a linear relationship with age, the dentate gyrus (DG), cornu ammonis field 1 (CA1), and cornu ammonis subfields 2 and 3 (combined; CA2/3) displayed nonlinear trajectories that interacted with sex in CA2/3. We found that the DG was related to memory-based inference performance and that the SUB was related to perception-based inference; neither relationship interacted with age. Results are consistent with the idea that cellular organization within hippocampal subfields might undergo distinct developmental trajectories that support inference and memory performance throughout development.

Memory reactivation and suppression modulate integration of the semantic features of related memories in hippocampus.

Encoding an event that overlaps with a previous experience may involve reactivating an existing memory and integrating it with new information or suppressing the existing memory to promote formation of a distinct, new representation. We used fMRI during overlapping event encoding to track reactivation and suppression of individual, related memories. We further used a model of semantic knowledge based on Wikipedia to quantify both reactivation of semantic knowledge related to a previous event and formation of integrated memories containing semantic features of both events. Representational similarity analysis revealed that reactivation of semantic knowledge related to a prior event in posterior medial prefrontal cortex (pmPFC) supported memory integration during new learning. Moreover, anterior hippocampus (aHPC) formed integrated representations combining the semantic features of overlapping events. We further found evidence that aHPC integration may be modulated on a trial-by-trial basis by interactions between ventrolateral PFC and anterior mPFC, with suppression of item-specific memory representations in anterior mPFC inhibiting hippocampal integration. These results suggest that PFC-mediated control processes determine the availability of specific relevant memories during new learning, thus impacting hippocampal memory integration.

Generalization of cognitive maps across space and time.

Prominent theories posit that associative memory structures, known as cognitive maps, support flexible generalization of knowledge across cognitive domains. Here, we evince a representational account of cognitive map flexibility by quantifying how spatial knowledge formed one day was used predictively in a temporal sequence task 24 hours later, biasing both behavior and neural response. Participants learned novel object locations in distinct virtual environments. After learning, hippocampus and ventromedial prefrontal cortex (vmPFC) represented a cognitive map, wherein neural patterns became more similar for same-environment objects and more discriminable for different-environment objects. Twenty-four hours later, participants rated their preference for objects from spatial learning; objects were presented in sequential triplets from either the same or different environments. We found that preference response times were slower when participants transitioned between same- and different-environment triplets. Furthermore, hippocampal spatial map coherence tracked behavioral slowing at the implicit sequence transitions. At transitions, predictive reinstatement of virtual environments decreased in anterior parahippocampal cortex. In the absence of such predictive reinstatement after sequence transitions, hippocampus and vmPFC responses increased, accompanied by hippocampal-vmPFC functional decoupling that predicted individuals' behavioral slowing after a transition. Collectively, these findings reveal how expectations derived from spatial experience generalize to support temporal prediction.

Interpersonal Family Dynamics Relate to Hippocampal CA Subfield Structure.

Social environments that are extremely enriched or adverse can influence hippocampal volume. Though most individuals experience social environments that fall somewhere in between these extremes, substantially less is known about the influence of normative variation in social environments on hippocampal structure. Here, we examined whether hippocampal volume tracks normative variation in interpersonal family dynamics in 7- to 12-year-olds and adults recruited from the general population. We focused on interpersonal family dynamics as a prominent feature of one's social world. Given evidence that CA1 and CA2 play a key role in tracking social information, we related individual hippocampal subfield volumes to interpersonal family dynamics. More positive perceptions of interpersonal family dynamics were associated with greater CA1 and CA2/3 volume regardless of age and controlling for socioeconomic status. These data suggest that CA subfields are sensitive to normative variation in social environments and identify interpersonal family dynamics as an impactful environmental feature.

Representations of Temporal Community Structure in Hippocampus and Precuneus Predict Inductive Reasoning Decisions.

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.

Developmental differences in memory reactivation relate to encoding and inference in the human brain.

Despite the fact that children can draw on their memories to make novel inferences, it is unknown whether they do so through the same neural mechanisms as adults. We measured memory reinstatement as participants aged 7-30 years learned new, related information. While adults brought memories to mind throughout learning, adolescents did so only transiently, and children not at all. Analysis of trial-wise variability in reactivation showed that discrepant neural mechanisms-and in particular, what we interpret as suppression of interfering memories during learning in early adolescence-are nevertheless beneficial for later inference at each developmental stage. These results suggest that while adults build integrated memories well-suited to informing inference directly, children and adolescents instead must rely on separate memories to be individually referenced at the time of inference decisions.

A Platform for Cognitive Monitoring of Neurosurgical Patients During Hospitalization.

Intracranial recordings in epilepsy patients are increasingly utilized to gain insight into the electrophysiological mechanisms of human cognition. There are currently several practical limitations to conducting research with these patients, including patient and researcher availability and the cognitive abilities of patients, which limit the amount of task-related data that can be collected. Prior studies have synchronized clinical audio, video, and neural recordings to understand naturalistic behaviors, but these recordings are centered on the patient to understand their seizure semiology and thus do not capture and synchronize audiovisual stimuli experienced by patients. Here, we describe a platform for cognitive monitoring of neurosurgical patients during their hospitalization that benefits both patients and researchers. We provide the full specifications for this system and describe some example use cases in perception, memory, and sleep research. We provide results obtained from a patient passively watching TV as proof-of-principle for the naturalistic study of cognition. Our system opens up new avenues to collect more data per patient using real-world behaviors, affording new possibilities to conduct longitudinal studies of the electrophysiological basis of human cognition under naturalistic conditions.

Does memory reactivation during sleep support generalization at the cost of memory specifics?

Sleep is important for memory, but does it favor consolidation of specific details or extraction of generalized information? Both may occur together when memories are reactivated during sleep, or a loss of certain memory details may facilitate generalization. To examine these issues, we tested memory in participants who viewed landscape paintings by six artists. Paintings were cropped to show only a section of the scene. During a learning phase, each painting section was presented with the artist's name and with a nonverbal sound that had been uniquely associated with that artist. In a test of memory for specifics, participants were shown arrays of six painting sections, all by the same artist. Participants attempted to select the one that was seen in the learning phase. Generalization was tested by asking participants to view new paintings and, for each one, decide which of the six artists created it. After this testing, participants had a 90-minute sleep opportunity with polysomnographic monitoring. When slow-wave sleep was detected, three of the sound cues associated with the artists were repeatedly presented without waking the participants. After sleep, participants were again tested for memory specifics and generalization. Memory reactivation during sleep due to the sound cues led to a relative decline in accuracy on the specifics test, which could indicate the transition to a loss of detail that facilitates generalization, particularly details such as the borders. Generalization performance showed very little change after sleep and was unaffected by the sound cues. Although results tentatively implicate sleep in memory transformation, further research is needed to examine memory change across longer time periods.

Reinstatement of item-specific contextual details during retrieval supports recombination-related false memories.

Flexible retrieval mechanisms that allow us to infer relationships across events may also lead to memory errors or distortion when details of one event are misattributed to the related event. Here, we tested how making successful inferences alters representation of overlapping events, leading to false memories. Participants encoded overlapping associations ('AB' and 'BC'), each of which was superimposed on different indoor and outdoor scenes that were pre-exposed prior to associative learning. Participants were subsequently tested on both the directly learned pairs ('AB' and 'BC') and inferred relationships across pairs ('AC'). We predicted that when people make a correct inference, features associated with overlapping events may become integrated in memory. To test this hypothesis, participants completed a final detailed retrieval test, in which they had to recall the scene associated with initially learned 'AB' pairs (or 'BC' pairs). We found that the outcome of inference decisions impacted the degree to which neural patterns elicited during detailed 'AB' retrieval reflected reinstatement of the scene associated with the overlapping 'BC' event. After successful inference, neural patterns in the anterior hippocampus, posterior medial prefrontal cortex, and our content-reinstatement region (left inferior temporal gyrus) were more similar to the overlapping, yet incorrect 'BC' context relative to after unsuccessful inference. Further, greater hippocampal activity during inference was associated with greater reinstatement of the incorrect, overlapping context in our content-reinstatement region, which in turn tracked contextual misattributions during detailed retrieval. These results suggest recombining memories during successful inference can lead to misattribution of contextual details across related events, resulting in false memories.

Concept formation as a computational cognitive process.

Hippocampus and entorhinal cortex form cognitive maps that represent relations among memories within a multidimensional space. While these relational maps have long been proposed to contribute to episodic memory, recent work suggests that they also support concept formation by representing relevant features for discriminating among related concepts. Cognitive maps may be refined by medial prefrontal cortex, which selects dimensions to represent based on their behavioral relevance. Hippocampal pattern completion, which is critical for retrieval of episodic memories, may also contribute to generalization of existing concepts to new exemplars. Navigation within hippocampal cognitive maps, which is guided by grid coding in entorhinal cortex, may contribute to imagination through recombination of event elements or concept features.

Semantic Knowledge of Famous People and Places Is Represented in Hippocampus and Distinct Cortical Networks.

Studies have found that anterior temporal lobe (ATL) is critical for detailed knowledge of object categories, suggesting that it has an important role in semantic memory. However, in addition to information about entities, such as people and objects, semantic memory also encompasses information about places. We tested predictions stemming from the PMAT model, which proposes there are distinct systems that support different kinds of semantic knowledge: an anterior temporal (AT) network, which represents information about entities; and a posterior medial (PM) network, which represents information about places. We used representational similarity analysis to test for activation of semantic features when human participants viewed pictures of famous people and places, while controlling for visual similarity. We used machine learning techniques to quantify the semantic similarity of items based on encyclopedic knowledge in the Wikipedia page for each item and found that these similarity models accurately predict human similarity judgments. We found that regions within the AT network, including ATL and inferior frontal gyrus, represented detailed semantic knowledge of people. In contrast, semantic knowledge of places was represented within PM network areas, including precuneus, posterior cingulate cortex, angular gyrus, and parahippocampal cortex. Finally, we found that hippocampus, which has been proposed to serve as an interface between the AT and PM networks, represented fine-grained semantic similarity for both individual people and places. Our results provide evidence that semantic knowledge of people and places is represented separately in AT and PM areas, whereas hippocampus represents semantic knowledge of both categories.SIGNIFICANCE STATEMENT Humans acquire detailed semantic knowledge about people (e.g., their occupation and personality) and places (e.g., their cultural or historical significance). While research has demonstrated that brain regions preferentially respond to pictures of people and places, less is known about whether these regions preferentially represent semantic knowledge about specific people and places. We used machine learning techniques to develop a model of semantic similarity based on information available from Wikipedia, validating the model against similarity ratings from human participants. Using our computational model, we found that semantic knowledge about people and places is represented in distinct anterior temporal and posterior medial brain networks, respectively. We further found that hippocampus, an important memory center, represented semantic knowledge for both types of stimuli.

Memory Reactivation during Learning Simultaneously Promotes Dentate Gyrus/CA2,3 Pattern Differentiation and CA1 Memory Integration.

Events that overlap with previous experience may trigger reactivation of existing memories. However, such reactivation may have different representational consequences within the hippocampal circuit. Computational theories of hippocampal function suggest that dentate gyrus and CA2,3 (DG/CA2,3) are biased to differentiate highly similar memories, whereas CA1 may integrate related events by representing them with overlapping neural codes. Here, we tested whether the formation of differentiated or integrated representations in hippocampal subfields depends on the strength of memory reactivation during learning. Human participants of both sexes learned associations (AB pairs, either face-shape or scene-shape), and then underwent fMRI scanning while they encoded overlapping associations (BC shape-object pairs). Both before and after learning, participants were also scanned while viewing indirectly related elements of the overlapping memories (A and C images) in isolation. We used multivariate pattern analyses to measure reactivation of initial pair memories (A items) during overlapping pair (BC) learning, as well as learning-related representational change for indirectly related memory elements in hippocampal subfields. When prior memories were strongly reactivated during overlapping pair encoding, DG/CA2,3 and subiculum representations for indirectly related images (A and C) became less similar, consistent with pattern differentiation. Simultaneously, memory reactivation during new learning promoted integration in CA1, where representations for indirectly related memory elements became more similar after learning. Furthermore, memory reactivation and subiculum representation predicted faster and more accurate inference (AC) decisions. These data show that reactivation of related memories during new learning leads to dissociable coding strategies in hippocampal subfields, in line with computational theories.SIGNIFICANCE STATEMENT The flexibility of episodic memory allows us to remember both the details that differentiate similar events and the commonalities among them. Here, we tested how reactivation of past experience during new learning promotes formation of neural representations that might serve these two memory functions. We found that memory reactivation during learning promoted formation of differentiated representations for overlapping memories in the dentate gyrus/CA2,3 and subiculum subfields of the hippocampus, while simultaneously leading to the formation of integrated representations of related events in subfield CA1 Furthermore, memory reactivation and subiculum representation predicted success when inferring indirect relationships among events. These findings indicate that memory reactivation is an important learning signal that influences how overlapping events are represented within the hippocampal circuit.

Representations of common event structure in medial temporal lobe and frontoparietal cortex support efficient inference.

Prior work has shown that the brain represents memories within a cognitive map that supports inference about connections between individual related events. Real-world adaptive behavior is also supported by recognizing common structure among numerous distinct contexts; for example, based on prior experience with restaurants, when visiting a new restaurant one can expect to first get a table, then order, eat, and finally pay the bill. We used a neurocomputational approach to examine how the brain extracts and uses abstract representations of common structure to support novel decisions. Participants learned image pairs (AB, BC) drawn from distinct triads (ABC) that shared the same internal structure and were then tested on their ability to infer indirect (AC) associations. We found that hippocampal and frontoparietal regions formed abstract representations that coded cross-triad relationships with a common geometric structure. Critically, such common representational geometries were formed despite the lack of explicit reinforcement to do so. Furthermore, we found that representations in parahippocampal cortex are hierarchical, reflecting both cross-triad relationships and distinctions between triads. We propose that representations with common geometric structure provide a vector space that codes inferred item relationships with a direction vector that is consistent across triads, thus supporting faster inference. Using computational modeling of response time data, we found evidence for dissociable vector-based retrieval and pattern-completion processes that contribute to successful inference. Moreover, we found evidence that these processes are mediated by distinct regions, with pattern completion supported by hippocampus and vector-based retrieval supported by parahippocampal cortex and lateral parietal cortex.

Ventromedial prefrontal cortex compression during concept learning.

Prefrontal cortex (PFC) is thought to support the ability to focus on goal-relevant information by filtering out irrelevant information, a process akin to dimensionality reduction. Here, we test this dimensionality reduction hypothesis by relating a data-driven approach to characterizing the complexity of neural representation with a theoretically-supported computational model of learning. We find evidence of goal-directed dimensionality reduction within human ventromedial PFC during learning. Importantly, by using computational predictions of each participant's attentional strategies during learning, we find that that the degree of neural compression predicts an individual's ability to selectively attend to concept-specific information. These findings suggest a domain-general mechanism of learning through compression in ventromedial PFC.

Predictability Changes What We Remember in Familiar Temporal Contexts.

The human brain constantly anticipates the future based on memories of the past. Encountering a familiar situation reactivates memory of previous encounters, which can trigger a prediction of what comes next to facilitate responsiveness. However, a prediction error can lead to pruning of the offending memory, a process that weakens its representation in the brain and leads to forgetting. Our goal in this study was to evaluate whether memories are spared from such pruning in situations that allow for accurate predictions at the categorical level, despite prediction errors at the item level. Participants viewed a sequence of objects, some of which reappeared multiple times ("cues"), followed always by novel items. Half of the cues were followed by new items from different (unpredictable) categories, while others were followed by new items from a single (predictable) category. Pattern classification of fMRI data was used to identify category-specific predictions after each cue. Pruning was observed only in unpredictable contexts, while encoding of new items was less robust in predictable contexts. These findings demonstrate that how associative memories are updated is influenced by the reliability of abstract-level predictions in familiar contexts.

Developmental differences in temporal schema acquisition impact reasoning decisions.

Schemas capture patterns across multiple experiences, accumulating information about common event structures that guide decision making in new contexts. Schemas are an important principle of leading theories of cognitive development; yet, we know little about how children and adolescents form schemas and use schematic knowledge to guide decisions. Here, we show that the ability to acquire schematic knowledge based on the temporal regularities of events increases during childhood and adolescence. Furthermore, we show that temporally mediated schematic knowledge biases reasoning decisions in an age-dependent manner. Participants with greater temporal schematic knowledge were more likely to infer that temporally related items shared other, non-temporal properties, with adults showing the greatest relationship between schema knowledge and reasoning choices. These data indicate that the mechanisms underlying schema formation and expression are not fully developed until adulthood and may reflect the ongoing maturation of hippocampus and prefrontal cortex through adolescence.

Performance of semi-automated hippocampal subfield segmentation methods across ages in a pediatric sample.

Episodic memory function has been shown to depend critically on the hippocampus. This region is made up of a number of subfields, which differ in both cytoarchitectural features and functional roles in the mature brain. Recent neuroimaging work in children and adolescents has suggested that these regions may undergo different developmental trajectories-a fact that has important implications for how we think about learning and memory processes in these populations. Despite the growing research interest in hippocampal structure and function at the subfield level in healthy young adults, comparatively fewer studies have been carried out looking at subfield development. One barrier to studying these questions has been that manual segmentation of hippocampal subfields-considered by many to be the best available approach for defining these regions-is laborious and can be infeasible for large cross-sectional or longitudinal studies of cognitive development. Moreover, manual segmentation requires some subjectivity and is not impervious to bias or error. In a developmental sample of individuals spanning 6-30 years, we assessed the degree to which two semi-automated segmentation approaches-one approach based on Automated Segmentation of Hippocampal Subfields (ASHS) and another utilizing Advanced Normalization Tools (ANTs)-approximated manual subfield delineation on each individual by a single expert rater. Our main question was whether performance varied as a function of age group. Across several quantitative metrics, we found negligible differences in subfield validity across the child, adolescent, and adult age groups, suggesting that these methods can be reliably applied to developmental studies. We conclude that ASHS outperforms ANTs overall and is thus preferable for analyses carried out in individual subject space. However, we underscore that ANTs is also acceptable and may be well-suited for analyses requiring normalization to a single group template (e.g., voxelwise analyses across a wide age range). Previous work has supported the use of such methods in healthy young adults, as well as several special populations such as older adults and those suffering from mild cognitive impairment. Our results extend these previous findings to show that ASHS and ANTs can also be used in pediatric populations as young as six.

Functional connectivity between memory and reward centers across task and rest track memory sensitivity to reward.

External motivation, such as a promise of future monetary reward for remembering an event, can affect which events are remembered. Reward-based memory modulation is thought to result from encoding and post-encoding interactions between dopaminergic midbrain, signaling reward, and hippocampus and parahippocampal cortex, supporting episodic memory. We asked whether hippocampal and parahippocampal interactions with other reward-related regions are related to reward modulation of memory and whether such relationships are stable over time. Individuals' memory sensitivity to reward was measured using a monetary incentive encoding task in which a cue indicated potential monetary reward (penny, dime, or dollar) for remembering an upcoming object pair. Functional connectivity between memory and reward regions was measured before, during, and following the task. Reward-related regions of interest were generated using a meta-analysis of existing studies on reward and included ventral striatum, medial and orbital prefrontal cortices and anterior cingulate cortex, in addition to midbrain. The results showed that connectivity between memory and reward regions tracked individual differences in reward modulation of memory, irrespective of when connectivity was measured. Connectivity patterns of anterior cingulate, orbitofrontal cortex, and ventral striatum covaried together and tracked behavior most strongly. These findings implicate a broader set of reward regions in reward modulation of memory than considered previously and provide new evidence that stable connectivity patterns between memory and reward centers relate to individual differences in how reward impacts memory.