Brice A. Kuhl’s research while affiliated with University of Oregon and other places

Recent human neuroimaging studies of episodic memory have revealed a counterintuitive phenomenon in the hippocampus: when events are highly similar, corresponding hippocampal activity patterns are sometimes less correlated than activity patterns associated with unrelated events. This phenomenon— repulsion— is not accounted for by most theories of the hippocampus, and the conditions that trigger repulsion remain poorly understood. Here, we used a spatial route-learning task and high-resolution fMRI in humans to test whether hippocampal repulsion is fundamentally driven by internal beliefs about the environment. By precisely measuring participants’ internal beliefs and actively manipulating them, we show that repulsion selectively occurred in hippocampal subfields CA3 and dentate gyrus when visual input was ambiguous—or even identical —but internal beliefs were distinct. These findings firmly establish conditions that elicit repulsion and have broad relevance to theories of hippocampal function and to the fields of human episodic memory and rodent spatial navigation.

Introduction: Memory interference poses a challenge to accurate recall when memories share similarities. Previous research (e. g. Favila et al., 2016) has highlighted hippocampal repulsion as a mechanism to reduce interference. More specifically, Wanjia et al. (2021) have shown that hippocampal repulsion occurs precisely when memory interference is resolved. However, it is unclear how training (frequent studying of associations) affects hippocampal repulsion. When experiences are similar (overlapping), this can lead to interference-related forgetting. However, recent research has demonstrated that interference can be minimized via targeted differentiation of activity patterns in the hippocampus (e.g. Hulbert & Norman, 2015; Favila et al., 2016; Wanjia et al., 2021)—a phenomenon we term ‘hippocampal repulsion.’ Hippocampal repulsion is thought to critically depend on the degree of similarity between overlapping memories (Wammes et al., 2022) and the amount of experience with those memories (Favila et al., 2016), but in ways that are complex and not fully understood (Ritvo et al., 2019). Here, we sought to characterize potential interactions between stimulus similarity and experience in determining hippocampal repulsion. Method: Participants completed an experiment with three phases. During the study phase, participants learned unique associations between scene and object images. Importantly, the scene images were drawn from two categories (beaches vs. gazebos), where the image similarity is higher within, relative to between category scenes. Because we included 24 scenes per category, this allows us to investigate repulsion as a function of pairwise scene similarity. Participants received high training on associations from one category and low training on the other, counterbalanced across participants. FMRI was used to acquire the BOLD signal during the second phase, in which participants viewed the scene images. In the third phase, participants were presented with each scene object and had to select the associated object from a list. Results: Using pattern similarity analyses, we computed a relative similarity score of brain activity as the difference between within-scene-category similarity and between scene-category similarity. This score allows us to compare different brain regions. Congruent with previous observations on hippocampal repulsion, this score was more negative in the CA23DG relative to the early visual cortex and the parahippocampal place area, indicating hippocampal repulsion of similar memories. Training showed differential effects between these areas.

A stimulus can be familiar for multiple reasons. It might have been recently encountered, or is similar to recent experience, or is similar to ‘typical’ experience. Understanding how the brain translates these sources of similarity into memory decisions is a fundamental, but challenging goal. Here, using fMRI, we computed neural similarity between a current stimulus and events from different temporal windows in the past and future (from seconds to days). We show that trial-by-trial memory decisions (is this stimulus ‘old’?) were predicted by the difference in similarity to past vs. future events (temporal asymmetry). This relationship was (i) evident in lateral parietal and occipitotemporal cortices, (ii) strongest when considering events from the recent past (minutes ago), and (iii) most pronounced when veridical (true) memories were weak. These findings suggest a new perspective in which the brain supports memory decisions by comparing what actually occurred to what is likely to occur.

The Oxford Handbook of Human Memory covers the science of human memory, its application to clinical disorders, and its broader implications for learning and memory in real-world contexts. Written by field leaders, the handbook integrates behavioral, neural, and computational evidence with current theories of how humans learn and remember. Following a section of foundational chapters, subsequent sections include chapters that cover forms and attributes of memory, encoding and retrieval processes and their interactions, individual differences, memory disorders and therapies, learning and memory in educational settings, and the role of memory in society. The handbook’s authoritative chapters document the current state of knowledge and provide a roadmap for the next generation of memory scientists, established peers, and practitioners.

Remembering when events occur in time is fundamental to episodic memory. Yet, many experiences repeat over time creating the potential for interference when attempting to recall temporally specific memories. Here, we argue that temporal memories are protected, in part, by reinstatement of temporal context information that is triggered by stimulus repetitions. We motivate this argument by integrating seminal findings across several distinct literatures and methodologies. Specifically, we consider key insights from foundational behavioral studies of temporal memory, recent electrophysiological and neuroimaging approaches to measuring memory reinstatement, and computational models that describe how temporal context representations shape memory processes. We also note several open questions concerning how temporal context reinstatement might influence subsequent temporal memory, including potential mediating effects of event spacing and event boundaries. These ideas and questions have the potential to guide future research and, ultimately, to advance theoretical accounts of how we preserve temporal memories.

More than a century of research shows that spaced learning improves long-term memory. Yet, there remains debate concerning why. A major limitation to resolving theoretical debates is the lack of evidence for how neural representations change as a function of spacing. Here, leveraging a massive-scale 7T human fMRI dataset, we tracked neural representations and behavioral expressions of memory as participants viewed thousands of natural scene images that repeated at lags ranging from seconds to many months. We show that spaced learning increases the similarity of human ventromedial prefrontal cortex representations across stimulus encounters and, critically, these increases parallel and predict the behavioral benefits of spacing. Additionally, we show that these spacing benefits critically depend on remembering and, in turn, ‘re-encoding’ past experience. Collectively, our findings provide fundamental insight into how spaced learning influences neural representations and why spacing is beneficial.

Neuroimaging studies of human memory have consistently found that univariate responses in parietal cortex track episodic experience with stimuli (whether stimuli are ‘old’ or ‘new’). More recently, pattern-based fMRI studies have shown that parietal cortex also carries information about the semantic content of remembered experiences. However, it is not well understood how memory-based and content-based signals are integrated within parietal cortex. Here, we used voxel-wise encoding models and a recognition memory task to predict the fMRI activity patterns evoked by complex natural scene images based on (a) the episodic history and (b) the semantic content of each image in humans (males and females). Models were generated and compared across distinct subregions of parietal cortex and for occipitotemporal cortex. We show that parietal and occipitotemporal regions each encode memory and content information, but they differ in how they combine this information. Among parietal subregions, angular gyrus was characterized by robust and overlapping effects of memory and content. Moreover, subject-specific semantic tuning functions revealed that successful recognition shifted the amplitude of tuning functions in angular gyrus but did not change the selectivity of tuning. In other words, effects of memory and content were additive in angular gyrus. This pattern of data contrasted with occipitotemporal cortex where memory and content effects were interactive: memory effects were preferentially expressed by voxels tuned to the content of a remembered image. Collectively, these findings provide unique insight into how parietal cortex combines information about episodic memory and semantic content. SIGNIFICANCE STATEMENT: Neuroimaging studies of human memory have identified multiple brain regions that not only carry information about ‘whether’ a visual stimulus is successfully recognized but also ‘what’ the content of that stimulus includes. However, a fundamental and open question concerns how the brain integrates these two types of information (memory and content). Here, using a powerful combination of fMRI analysis methods, we show that parietal cortex—particularly, the angular gyrus—robustly combines memory- and content-related information, but these two forms of information are represented via additive, independent signals. In contrast, memory effects in high-level visual cortex critically depend on (and interact with) content representations. Together, these findings reveal multiple and distinct ways in which the brain combines memory- and content-related information.

Converging, cross-species evidence indicates that memory for time is supported by hippocampal area CA1 and entorhinal cortex. However, limited evidence characterizes how these regions preserve temporal memories over long timescales (e.g., months). At long timescales, memoranda may be encountered in multiple temporal contexts, potentially creating interference. Here, using 7T fMRI, we measured CA1 and entorhinal activity patterns as human participants viewed thousands of natural scene images distributed, and repeated, across many months. We show that memory for an image’s original temporal context was predicted by the degree to which CA1/entorhinal activity patterns from the first encounter with an image were re-expressed during re-encounters occurring minutes to months later. Critically, temporal memory signals were dissociable from predictors of recognition confidence, which were carried by distinct medial temporal lobe expressions. These findings suggest that CA1 and entorhinal cortex preserve temporal memories across long timescales by coding for and reinstating temporal context information.

Human neuroimaging studies have shown that the contents of episodic memories are represented in distributed patterns of neural activity. However, these studies have mostly been limited to decoding simple, unidimensional properties of stimuli. Semantic encoding models, in contrast, offer a means for characterizing the rich, multidimensional information that comprises episodic memories. Here, we extensively sampled four human fMRI subjects to build semantic encoding models and then applied these models to reconstruct content from natural scene images as they were viewed and recalled from memory. First, we found that multidimensional semantic information was successfully reconstructed from activity patterns across visual and lateral parietal cortices, both when viewing scenes and when recalling them from memory. Second, whereas visual cortical reconstructions were much more accurate when images were viewed versus recalled from memory, lateral parietal reconstructions were comparably accurate across visual perception and memory. Third, by applying natural language processing methods to verbal recall data, we showed that fMRI-based reconstructions reliably matched subjects' verbal descriptions of their memories. In fact, reconstructions from ventral temporal cortex more closely matched subjects' own verbal recall than other subjects' verbal recall of the same images. Fourth, encoding models reliably transferred across subjects: memories were successfully reconstructed using encoding models trained on data from entirely independent subjects. Together, these findings provide evidence for successful reconstructions of multidimensional and idiosyncratic memory representations and highlight the differential sensitivity of visual cortical and lateral parietal regions to information derived from the external visual environment versus internally-generated memories.