Martin J. Chadwick

Decoding Individual Episodic Memory Traces in the Human Hippocampus

Summary In recent years, multivariate pattern analyses have been performed on functional magnetic resonance imaging (fMRI) data, permitting prediction of mental states from local patterns of blood oxygen-level-dependent (BOLD) signal across voxels [1, 2]. We previously demonstrated that it is possible to predict the position of individuals in a virtual-reality environment from the pattern of activity across voxels in the hippocampus [3]. Although this shows that spatial memories can be decoded, substantially more challenging, and arguably only possible to investigate in humans [4], is whether it is feasible to predict which complex everyday experience, or episodic memory, a person is recalling. Here we document for the first time that traces of individual rich episodic memories are detectable and distinguishable solely from the pattern of fMRI BOLD signals across voxels in the human hippocampus. In so doing, we uncovered a possible functional topography in the hippocampus, with preferential episodic processing by some hippocampal regions over others. Moreover, our results imply that the neuronal traces of episodic memories are stable (and thus predictable) even over many re-activations. Finally, our data provide further evidence for functional differentiation within the medial temporal lobe, in that we show the hippocampus contains significantly more episodic information than adjacent structures.

Multi-voxel pattern analysis in human hippocampal subfields

A complete understanding of the hippocampus depends on elucidating the representations and computations that exist in its anatomically distinct subfields. High-resolution structural and functional MRI scanning is starting to permit insights into hippocampal subfields in humans. In parallel, such scanning has facilitated the use of multi-voxel pattern analysis (MVPA) to examine information present in the distributed pattern of activity across voxels. The aim of this study was to combine these two relatively new innovations and deploy MVPA in the hippocampal subfields. Delineating subregions of the human hippocampus, a prerequisite for our study, remains a significant challenge, with extant methods often only examining part of the hippocampus, or being unable to differentiate CA3 and dentate gyrus (DG). We therefore devised a new high-resolution anatomical scanning and subfield segmentation protocol that allowed us to overcome these issues, and separately identify CA1, CA3, DG, and subiculum (SUB) across the whole hippocampus using a standard 3T MRI scanner. We then used MVPA to examine fMRI data associated with a decision-making paradigm involving highly similar scenes that had relevance for the computations that occur in hippocampal subfields. Intra- and inter-rater scores for subfield identification using our procedure confirmed its reliability. Moreover, we found that decoding of information within hippocampal subfields was possible using MVPA, with findings that included differential effects for CA3 and DG. We suggest that MVPA in human hippocampal subfields may open up new opportunities to examine how different types of information are represented and processed at this fundamental level.

Normative Development of White Matter Tracts: Similarities and Differences in Relation to Age, Gender, and Intelligence

The white matter of the brain undergoes a range of structural changes throughout development; from conception to birth, in infancy, and onwards through childhood and adolescence. Several studies have used diffusion magnetic resonance imaging (dMRI) to investigate these changes, but a consensus has not yet emerged on which white matter tracts undergo changes in the later stages of development or what the most important driving factors are behind these changes. In this study of typically developing 8- to 16-year-old children, we use a comprehensive data-driven approach based on principal components analysis to identify effects of age, gender, and brain volume on dMRI parameters, as well as their relative importance. We also show that secondary components of these parameters predict full-scale IQ, independently of the age- and gender-related effects. This overarching assessment of the common factors and gender differences in normal white matter tract development will help to advance understanding of this process in late childhood and adolescence.

A Goal Direction Signal in the Human Entorhinal/Subicular Region

Summary Navigating to a safe place, such as a home or nest, is a fundamental behavior for all complex animals. Determining the direction to such goals is a crucial first step in navigation. Surprisingly, little is known about how or where in the brain this “goal direction signal” is represented. In mammals, “head-direction cells” are thought to support this process, but despite 30 years of research, no evidence for a goal direction representation has been reported [1, 2]. Here, we used fMRI to record neural activity while participants made goal direction judgments based on a previously learned virtual environment. We applied multivoxel pattern analysis [3–5] to these data and found that the human entorhinal/subicular region contains a neural representation of intended goal direction. Furthermore, the neural pattern expressed for a given goal direction matched the pattern expressed when simply facing that same direction. This suggests the existence of a shared neural representation of both goal and facing direction. We argue that this reflects a mechanism based on head-direction populations that simulate future goal directions during route planning [6]. Our data further revealed that the strength of direction information predicts performance. Finally, we found a dissociation between this geocentric information in the entorhinal/subicular region and egocentric direction information in the precuneus.

Decoding Overlapping Memories in the Medial Temporal Lobes Using High-Resolution fMRI.

The hippocampus is proposed to process overlapping episodes as discrete memory traces, although direct evidence for this in human episodic memory is scarce. Using green-screen technology we created four highly overlapping movies of everyday events. Participants were scanned using high-resolution fMRI while recalling the movies. Multivariate pattern analysis revealed that the hippocampus supported distinct representations of each memory, while neighboring regions did not, demonstrating that the human hippocampus maintains unique pattern-separated memory traces even when memories are highly overlapping. The hippocampus also contained representations of spatial contexts that were shared across different memories, consistent with a specialized role in processing space.

The hippocampus extrapolates beyond the view in scenes: An fMRI study of boundary extension

Boundary extension (BE) is a pervasive phenomenon whereby people remember seeing more of a scene than was present in the physical input, because they extrapolate beyond the borders of the original stimulus. This automatic embedding of a scene into a wider context supports our experience of a continuous and coherent world, and is therefore highly adaptive. BE, whilst occurring rapidly, is nevertheless thought to comprise two stages. The first involves the active extrapolation of the scene beyond its physical boundaries, and is constructive in nature. The second phase occurs at retrieval, where the initial extrapolation beyond the original scene borders is revealed by a subsequent memory error. The brain regions associated with the initial, and crucial, extrapolation of a scene beyond the view have never been investigated. Here, using functional MRI (fMRI) and a classic BE paradigm, we found that this extrapolation of scenes occurred rapidly around the time a scene was first viewed, and was associated with engagement of the hippocampus (HC) and parahippocampal cortex (PHC). Using connectivity analyses we determined that the HC in particular seemed to drive the BE effect, exerting top–down influence on PHC and indeed as far back down the processing stream as early visual cortex (VC). These cortical regions subsequently displayed activity profiles that tracked the trial-by-trial subjective perception of the scenes, rather than physical reality, thereby reflecting the behavioural expression of the BE error. Together our results show that the HC is involved in the active extrapolation of scenes beyond their physical borders. This information is then automatically and rapidly channelled through the scene processing hierarchy as far back as early VC. This suggests that the anticipation and construction of scenes is a pervasive and important aspect of our online perception, with the HC playing a central role.

Decoding Information in the Human Hippocampus: A User's Guide.

Multi-voxel pattern analysis (MVPA), or ‘decoding’, of fMRI activity has gained popularity in the neuroimaging community in recent years. MVPA differs from standard fMRI analyses by focusing on whether information relating to specific stimuli is encoded in patterns of activity across multiple voxels. If a stimulus can be predicted, or decoded, solely from the pattern of fMRI activity, it must mean there is information about that stimulus represented in the brain region where the pattern across voxels was identified. This ability to examine the representation of information relating to specific stimuli (e.g., memories) in particular brain areas makes MVPA an especially suitable method for investigating memory representations in brain structures such as the hippocampus. This approach could open up new opportunities to examine hippocampal representations in terms of their content, and how they might change over time, with aging, and pathology. Here we consider published MVPA studies that specifically focused on the hippocampus, and use them to illustrate the kinds of novel questions that can be addressed using MVPA. We then discuss some of the conceptual and methodological challenges that can arise when implementing MVPA in this context. Overall, we hope to highlight the potential utility of MVPA, when appropriately deployed, and provide some initial guidance to those considering MVPA as a means to investigate the hippocampus.

Representations of Recent and Remote Autobiographical Memories in Hippocampal Subfields

The hippocampus has long been implicated in supporting autobiographical memories, but little is known about how they are instantiated in hippocampal subfields. Using high‐resolution functional magnetic resonance imaging (fMRI) combined with multivoxel pattern analysis we found that it was possible to detect representations of specific autobiographical memories in individual hippocampal subfields. Moreover, while subfields in the anterior hippocampus contained information about both recent (2 weeks old) and remote (10 years old) autobiographical memories, posterior CA3 and DG only contained information about the remote memories. Thus, the hippocampal subfields are differentially involved in the representation of recent and remote autobiographical memories during vivid recall.

CA3 size predicts the precision of memory recall

Significance How does the brain allow us to recall numerous life experiences despite there often being a high degree of similarity between memories? This is a key question in neuroscience. Moreover, there is also keen interest in understanding why some people are able to recall memories with greater clarity than other people. In this study, we identified a specific brain region, CA3, an area within a structure called the hippocampus, and a mechanism within it that helps to explain individual differences in recollection. These findings have relevance for all of us in elucidating memory muddles in general, in aging, and possibly also in conditions such as dementia, where confusion about the past is often evident. There is enduring interest in why some of us have clearer memories than others, given the substantial individual variation that exists in retrieval ability and the precision with which we can differentiate past experiences. Here we report novel evidence showing that variation in the size of human hippocampal subfield CA3 predicted the amount of neural interference between episodic memories within CA3, which in turn predicted how much retrieval confusion occurred between past memories. This effect was not apparent in other hippocampal subfields. This shows that subtle individual differences in subjective mnemonic experience can be accurately gauged from measurable variations in the anatomy and neural coding of hippocampal region CA3. Moreover, this mechanism may be relevant for understanding memory muddles in aging and pathological states.

Semantic representations in the temporal pole predict false memories

Significance False memories can arise in daily life through a mixture of factors, including misinformation and prior conceptual knowledge. This can have serious consequences in settings, such as legal eyewitness testimony, which depend on the accuracy of memory. We investigated the brain basis of false memory with fMRI, and found that patterns of activity in the temporal pole region of the brain can predict false memories. Furthermore, we show that each individual has unique patterns of brain activation that can predict their own idiosyncratic set of false-memory errors. Together, these results suggest that the temporal pole may be responsible for the conceptual component of illusory memories. Recent advances in neuroscience have given us unprecedented insight into the neural mechanisms of false memory, showing that artificial memories can be inserted into the memory cells of the hippocampus in a way that is indistinguishable from true memories. However, this alone is not enough to explain how false memories can arise naturally in the course of our daily lives. Cognitive psychology has demonstrated that many instances of false memory, both in the laboratory and the real world, can be attributed to semantic interference. Whereas previous studies have found that a diverse set of regions show some involvement in semantic false memory, none have revealed the nature of the semantic representations underpinning the phenomenon. Here we use fMRI with representational similarity analysis to search for a neural code consistent with semantic false memory. We find clear evidence that false memories emerge from a similarity-based neural code in the temporal pole, a region that has been called the “semantic hub” of the brain. We further show that each individual has a partially unique semantic code within the temporal pole, and this unique code can predict idiosyncratic patterns of memory errors. Finally, we show that the same neural code can also predict variation in true-memory performance, consistent with an adaptive perspective on false memory. Taken together, our findings reveal the underlying structure of neural representations of semantic knowledge, and how this semantic structure can both enhance and distort our memories.