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A key aspect of conceptual knowledge is that it can be flexibly applied at different levels of abstraction, implying a hierarchical organization. It is yet unclear how this hierarchical structure is acquired and represented in the brain. Here we investigate the computations underlying the acquisition and representation of the hierarchical structure of conceptual knowledge in the hippocampal-prefrontal system of 32 human participants (22 females). We assessed the hierarchical nature of learning during a novel tree-like categorization task via computational model comparisons. The winning model allowed to extract and quantify estimates for accumulation and updating of hierarchical compared with single-feature-based concepts from behavior. We find that mPFC tracks accumulation of hierarchical conceptual knowledge over time, and mPFC and hippocampus both support trial-to-trial updating. As a function of those learning parameters, mPFC and hippocampus further show connectivity changes to rostro-lateral PFC, which ultimately represented the hierarchical structure of the concept in the final stages of learning. Our results suggest that mPFC and hippocampus support the integration of accumulated evidence and instantaneous updates into hierarchical concept representations in rostro-lateral PFC. SIGNIFICANCE STATEMENT A hallmark of human cognition is the flexible use of conceptual knowledge at different levels of abstraction, ranging from a coarse category level to a fine-grained subcategory level. While previous work probed the representational geometry of long-term category knowledge, it is unclear how this hierarchical structure inherent to conceptual knowledge is acquired and represented. By combining a novel hierarchical concept learning task with computational modeling of categorization behavior and concurrent fMRI, we differentiate the roles of key concept learning regions in hippocampus and PFC in learning computations and the representation of a hierarchical category structure., (Copyright © 2021 the authors.)

Using contextual information to predict aversive events is a critical ability that protects from generalizing fear responses to safe contexts. Animal models have demonstrated the importance of spatial context representations within the hippocampal formation in contextualization of fear learning. The ventromedial prefrontal cortex (vmPFC) is known to play an important role in safety learning, possibly also through the incorporation of context information. However, if contextual representations are related to context-dependent expression of fear memory in humans remains unclear. Twenty-one healthy participants underwent functional MRI combined with a cue-context conditioning paradigm within a self-navigated virtual reality environment. The environment included two buildings (Threat and Safe context), which had distinct features outside but were identical inside. Within each context, participants saw two cues (CS+, CS-). The CS+ was consistently (100% reinforcement rate) paired with an electric shock in the Threat context, but never in the Safe context. The CS- was never paired with a shock. We found robust differential skin conductance responses (SCRs; CS+ ​> ​CS-) in the Threat context, but also within the Safe context, indicating fear generalization. Within the Safe context, vmPFC responses to the CS+ were larger than those in the Threat context. We furthermore found environment-specific representations for the two contexts in the training paradigm (i.e., before conditioning took place) in the hippocampus to be related to fear expression and generalization. Namely, participants with a weak context representation (z-score < 1.65) showed stronger fear generalization compared to participants with a strong context representation (z-score > 1.65). Thus, a weak neural representation strength of spatial context may explain overgeneralization of memory to safe contexts. In addition, our findings demonstrate that context-dependent regulation of fear expression engages ventromedial prefrontal pathways suggesting this involves a similar mechanism that is known to be involved in retrieval of extinction memory., (Copyright © 2019 Elsevier Inc. All rights reserved.)

A growing body of work is investigating the use of mental maps during decision-making. Here we discuss how decision-making organizes experiences according to an internal model of the current task, thereby structuring memory. Likewise, we consider how the structure of mental maps contributes to decision-making., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Integration of separate memories forms the basis of inferential reasoning--an essential cognitive process that enables complex behavior. Considerable evidence suggests that both hippocampus and medial prefrontal cortex (mPFC) play a crucial role in memory integration. Although previous studies indicate that theta oscillations facilitate memory processes, the electrophysiological mechanisms underlying memory integration remain elusive. To bridge this gap, we recorded magnetoencephalography data while participants performed an inference task and employed novel source reconstruction techniques to estimate oscillatory signals from the hippocampus. We found that hippocampal theta power during encoding predicts subsequent memory integration. Moreover, we observed increased theta coherence between hippocampus and mPFC. Our results suggest that integrated memory representations arise through hippocampal theta oscillations, possibly reflecting dynamic switching between encoding and retrieval states, and facilitating communication with mPFC. These findings have important implications for our understanding of memory-based decision making and knowledge acquisition., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Our memories are remarkably dynamic and allow us to reinterpret the past once new information comes to light. Gaining novel insights can lead to mental reorganization of previously unrelated events, thus linking them into narratives. The hippocampus and medial prefrontal cortex (mPFC) support integration of partially overlapping events, but the neural mechanisms underlying the reorganization of memories for the formation of coherent narratives remain elusive. Here, we combine fMRI with The Sims 3 videos of life-like animated events, which could either be integrated into narratives or not. We show that insight triggers the emergence of de novo mnemonic representations of the narratives and is associated with increased neural similarity between linked event representations in the posterior hippocampus, mPFC, and autobiographical-memory network. Simultaneously, events irrelevant to the newly established memory of the narrative were pruned out. This process was accompanied by increased neural dissimilarity between non-linked event representations in the posterior hippocampus and mPFC and was additionally signaled by a mismatch response in the anterior hippocampus. Our results demonstrate that insight leads to neural reconfiguration of representational networks within a memory space and have implications for knowledge acquisition in educational settings., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Memory retrieval is believed to involve a disparate network of areas, including medial prefrontal and medial temporal cortices, but the mechanisms underlying their coordination remain elusive. One suggestion is that oscillatory coherence mediates inter-regional communication, implicating theta phase and theta-gamma phase-amplitude coupling in mnemonic function across species. To examine this hypothesis, we used non-invasive whole-head magnetoencephalography (MEG) as participants retrieved the location of objects encountered within a virtual environment. We demonstrate that, when participants are cued with the image of an object whose location they must subsequently navigate to, there is a significant increase in 4-8 Hz theta power in medial prefrontal cortex (mPFC), and the phase of this oscillation is coupled both with ongoing theta phase in the medial temporal lobe (MTL) and perceptually induced 65-85 Hz gamma amplitude in medial parietal cortex. These results suggest that theta phase coupling between mPFC and MTL and theta-gamma phase-amplitude coupling between mPFC and neocortical regions may play a role in human spatial memory retrieval., (© 2014 The Authors. Hippocampus Published by Wiley Periodicals, Inc.)

It is a topic of current interest whether learning in humans relies on the acquisition of abstract rule knowledge (rule-based learning) or whether it depends on superficial item-specific information (instance-based learning). Here, we identified brain regions that mediate either of the two learning mechanisms by combining fMRI with an experimental protocol shown to be able to dissociate both learning mechanisms. Subjects had to learn object-position conjunctions in several trials and blocks. In a learning condition, either objects (Experiment 1) or positions (Experiment 2) were held constant within-blocks. In contrast to a control condition in which object-position conjunctions were trial-unique, a performance increase within and across-blocks was observed in the learning condition of both experiments. We hypothesized that within-block learning mainly relies on instance-based processes, whereas across-block learning might depend on rule-based mechanisms. A within-block parametric fMRI analysis revealed a learning-related increase of lateral prefrontal and striatal activity and a learning-related decrease of hippocampal activity in both experiments. By contrast, across-block learning was associated with an activation modulation in distinct prefrontal-striatal brain regions, but not in the hippocampus. These data indicate that hippocampal and prefrontal-striatal brain regions differentially contribute to instance-based and rule-based learning.

Using functional magnetic resonance imaging, the neural correlates of context-specific memories and invariant memories about regularities across episodes were investigated. Volunteers had to learn conjunctions between objects and positions. In an invariant learning condition, positions were held constant, enabling subjects to learn regularities across trials. By contrast, in a context-specific condition object-position conjunctions were trial unique. Performance increase in the invariant learning condition was paralleled by a learning-related increase of inferior frontal gyrus activation and ventral striatal activation and a decrease of hippocampus activation. Conversely, in the context-specific condition hippocampal activation was constant across trials. We argue that the learning-related hippocampal activation pattern might be due to reduced relational binding requirements once regularities are extracted. Furthermore, we propose that the learning-related prefrontal modulation reflects the requirement to extract and maintain regularities across trials and the adjustment of object-position conjunctions on the basis of the extracted knowledge. Finally, our data suggest that the ventral striatum encodes the increased predictability of spatial features as a function of learning. Taken together, these results indicate a transition of the relative roles of distinct brain regions during learning regularities across multiple episodes: regularity learning is characterized by a shift from a hippocampal to a prefrontal-striatal brain system.

Previous electrophysiological and neuroimaging studies suggest that the mismatch negativity (MMN) is generated by a temporofrontal network subserving preattentive auditory change detection. In two experiments we employed event-related brain potentials (ERP) and event-related functional magnetic resonance imaging (fMRI) to examine neural and hemodynamic activity related to deviance processing, using three types of deviant tones (small, medium, and large) in both a pitch and a space condition. In the pitch condition, hemodynamic activity in the right superior temporal gyrus (STG) increased as a function of deviance. Comparisons between small and medium and between small and large deviants revealed right prefrontal activation in the inferior frontal gyrus (IFG; BA 44/45) and middle frontal gyrus (MFG; BA 46), whereas large relative to medium deviants led to left and right IFG (BA 44/45) activation. In the ERP experiment the amplitude of the early MMN (90-120 ms) increased as a function of deviance, by this paralleling the right STG activation in the fMRI experiment. A U-shaped relationship between MMN amplitude and the degree of deviance was observed in a late time window (140-170 ms) resembling the right IFG activation pattern. In a subsequent source analysis constrained by fMRI activation foci, early and late MMN activity could be modeled by dipoles placed in the STG and IFG, respectively. In the spatial condition no reliable hemodynamic activation could be observed. The MMN amplitude was substantially smaller than in the pitch condition for all three spatial deviants in the ERP experiment. In contrast to the pitch condition it increased as a function of deviance in the early and in the late time window. We argue that the right IFG mediates auditory deviance detection in case of low discriminability between a sensory memory trace and auditory input. This prefrontal mechanism might be part of top-down modulation of the deviance detection system in the STG.

How valuable a choice option is often changes over time, making the prediction of value changes an important challenge for decision making. Prior studies identified a cognitive map in the hippocampal-entorhinal system that encodes relationships between states and enables prediction of future states, but does not inherently convey value during prospective decision making. In this fMRI study, participants predicted changing values of choice options in a sequence, forming a trajectory through an abstract two-dimensional value space. During this task, the entorhinal cortex exhibited a grid-like representation with an orientation aligned to the axis through the value space most informative for choices. A network of brain regions, including ventromedial prefrontal cortex, tracked the prospective value difference between options. These findings suggest that the entorhinal grid system supports the prediction of future values by representing a cognitive map, which might be used to generate lower-dimensional value signals to guide prospective decision making. Values of choice options often change over time. Here, the authors show that during prospective decision making the entorhinal cortex encodes changing values using a grid-like representation, suggesting the formation of a cognitive value map. [ABSTRACT FROM AUTHOR]

Planning spatial paths through our environment is an important part of everyday life and is supported by a neural system including the hippocampus and prefrontal cortex. Here we investigated the precise functional roles of the components of this system in humans by using fMRI as participants performed a simple goal-directed route-planning task. Participants had to choose the shorter of two routes to a goal in a visual scene that might contain a barrier blocking the most direct route, requiring a detour, or might be obscured by a curtain, requiring memory for the scene. The participant's start position was varied to parametrically manipulate their proximity to the goal and the difference in length of the two routes. Activity in medial prefrontal cortex, precuneus, and left posterior parietal cortex was associated with detour planning, regardless of difficulty, whereas activity in parahippocampal gyrus was associated with remembering the spatial layout of the visual scene. Activity in bilateral anterior hippocampal formation showed a strong increase the closer the start position was to the goal, together with medial prefrontal, medial and posterior parietal cortices. Our results are consistent with computational models in which goal proximity is used to guide subsequent navigation and with the association of anterior hippocampal areas with nonspatial functions such as arousal and reward expectancy. They illustrate how spatial and nonspatial functions combine within the anterior hippocampus, and how these functions interact with parahippocampal, parietal, and prefrontal areas in decision making and mnemonic function. [ABSTRACT FROM AUTHOR]

The medial (MEC) and lateral entorhinal cortex (LEC), widely studied in rodents, are well defined and characterized. In humans, however, the exact locations of their homologues remain uncertain. Previous functional magnetic resonance imaging (fMRI) studies have subdivided the human EC into posteromedial (pmEC) and anterolateral (alEC) parts, but uncertainty remains about the choice of imaging modality and seed regions, in particular in light of a substantial revision of the classical model of EC connectivity based on novel insights from rodent anatomy. Here, we used structural, not functional imaging, namely diffusion tensor imaging (DTI) and probabilistic tractography to segment the human EC based on differential connectivity to other brain regions known to project selectively to MEC or LEC. We defined MEC as more strongly connected with presubiculum and retrosplenial cortex (RSC), and LEC as more strongly connected with distal CA1 and proximal subiculum (dCA1pSub) and lateral orbitofrontal cortex (OFC). Although our DTI segmentation had a larger medial-lateral component than in the previous fMRI studies, our results show that the human MEC and LEC homologues have a border oriented both towards the posterior-anterior and medial-lateral axes, supporting the differentiation between pmEC and alEC. [ABSTRACT FROM AUTHOR]