Biology subjects

Michelmann, S.

Publications and source records attributed to Michelmann, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Post-Learning Reactivation of Memories for Naturalistic Continuous Experiences

Memories are not static records of the past; rather, the act of remembering can change how an event is recalled. Intriguingly, several studies also suggest that memories may be reactivated during rest. However, reactivation has largely been studied for spatial tasks and discrete stimuli, and we know little about whether spontaneous reactivation occurs for long timescale naturalistic events and how reactivation affects retention. Using fMRI, we show that neural activity patterns in the hippocampus and the Default Mode Network during encoding of narrative events were spontaneously reactivated during rest. Contrary to predictions, reactivation did not strengthen recall of movie details, and instead exploratory analyses suggested that reactivation in the hippocampus was associated with more gist-like recall one week later. These findings support the idea that memories for complex events may be spontaneously reactivated, but they suggest that rather than simply strengthening episodic memories, reactivation might help transform them.

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bioRxiv2026

Learning distributed representations with complementary components - A generative approximation framework for episodic memory encoding

Episodic memory must preserve detail while storing memories efficiently. We propose a framework of memory encoding in which generative neural network models approximate input through their frozen weights, yielding starting points from which the same weights can reinstate the input. This removes the need for mutually invertible cortical-hippocampal mappings, realizes a tradeoff between computational effort and mnemonic precision, and uses statistical regularities of the stimulus space to find representations that are distributed across the network. We implement this principle with a toy model and with large image-generation AI models, operationalizing mnemonic precision as closer approximation. Our model reproduces key findings from the Mnemonic Similarity Task: shallow encoding selectively impairs lure rejection, as observed in aging populations. Encoding further benefits from expertise: domain-finetuned models need fewer approximation steps for images from their own domain than for images from other domains. Finally, the representational geometry of latent starting points resembles medial temporal lobe but reinstatement through the weights of the network traverses the visual hierarchy in reverse order. Our framework offers a parsimonious and flexible account of memory encoding, where a generative search for a reinstatement-capable starting point finds a path for retrieval directly.

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bioRxiv2026

Episodic memory rescues working memory via pattern separation, pattern completion, and predictive recall

Working memory is capacity-limited, but interactions with episodic memory may offset this constraint. We tested moment-by-moment contributions of episodic representations to working memory by combining the N-back and Mnemonic Similarity tasks. Thirty-one participants, undergoing eye-tracking, first encoded items in a one-back task, classifying them as "same" or "similar" to their predecessor. In a subsequent two-back task, mnemonic discrimination showed a graded, item-specific benefit of prior experience: performance was best for previously compared items, whereas recognition of identical repeats was unaffected. Successful discrimination of previously compared items was accompanied by greater pupil dilation, gradually emerging gaze patterns resembling those elicited by their similar pair-mate, and higher gaze-similarity between one-back and two-back target viewing. Diverging gaze patterns between pair-mates during one-back further predicted two-back discrimination. These findings challenge working memory's characterization as an isolated system, demonstrating how it recruits episodic computations - encoding distinct traces, predicting upcoming content, and reinstating it at retrieval.

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bioRxiv2026

Phase similarity between similar objects indicates representational merging across retrieval training but not sleep

Retrieval training (i.e., cued recall) is theorised to induce rapid memory consolidation, similarly to sleep. Across consolidation, related neural representations become increasingly similar; yet, this representational change has never been directly compared between sleep and retrieval training. In this study, 30 subjects (27F, 18-34, M=22.17) completed four separate sessions in which they (1) learnt object-word pairs, followed by (2) immediate recognition testing, (3) one of four 120-min interventions (retrieval training, restudy, sleep, or wake), and (4) delayed recognition testing. We compared EEG phase similarity between similar and different objects to assess the time, frequency, and anatomical distribution of representational similarity across encoding (learning to immediate recognition), and each intervention (immediate to delayed recognition). We hypothesised that EEG phase patterns for similar objects would become more similar (i.e., representational merging) across retrieval training and sleep interventions, and predict a greater endorsement of similar-object lures. Indeed, we found increased representational similarity between similar objects across the encoding shift in the theta-band and occipital sources. Crucially, additional representational merging was only observed across the retrieval training intervention, in the alpha-band and parieto-occipital sources. Despite retrieval training leading to reduced performance in discriminating similar-objects lures, greater representational merging across retrieval training predicted greater discrimination of similar-object lures. Together, these findings suggest that sleep and retrieval training induce different memory transformations across the same timescale. Retrieval training may generally provoke rapid gist extraction, with greater neocortical integration supporting episodic discrimination. Conversely, sleep may selectively maintain task-relevant episodic and semantic details in the short-term.

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bioRxiv2025

Canonical Representational Mapping for Cognitive Neuroscience

Understanding neural representations is central to cognitive neuroscience, yet isolating meaningful patterns from noisy or correlated data remains challenging. Canonical Representational Mapping (CRM) is a novel multivariate analysis method to identify neural patterns aligned with specific cognitive hypotheses. CRM maximizes correlations between multivariate datasets - similar to Canonical Correlation Analysis - while controlling for confounding sources of variance, such as shared noise or irrelevant task conditions. We validate CRM with simulations and apply it across diverse neurophysiological datasets: In one application, we use CRM to map large language model activations onto intracranial electroencephalography recordings during story listening, controlling for contextual autocorrelations. In another example, we factorize overlapping representations in functional Magnetic Resonance Imaging into distinct context and episode components. Finally, we uncover frequency-coupled representations shared between hippocampus and medial prefrontal cortex in navigating rodents. Our results introduce CRM as a powerful tool to isolate representations across modalities and species.

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bioRxiv2025

Perspective matters: using past experiences to understand others' insensitivity to physical pain.

Prior research has shown that autobiographical memory (AM) supports empathy, allowing individuals to use the self as a model for understanding others. However, when the subjective experience of an event diverges between observer and target, relying on AM may hinder empathic processes, rather than support them. In this study, we recorded electroencephalographic (EEG) data from 36 healthy young adults during a pain decision task to investigate empathy for individuals described as either sensitive to physical pain (like the participants) or clinically insensitive to physical pain. Participants reported lower empathy for insensitive than for sensitive targets, regardless of whether they had personally experienced the specific event that caused physical pain. Event-related potential (ERP) analyses revealed differences in neural responses to sensitive and insensitive targets at a late stage of processing, in the discending phase of the P300 component; these differences were positively correlated with individual differences in empathy. To determine the underlying mechanisms, we applied multivariate pattern analysis (MVPA) to assess whether empathy for physical painrelies on AM reactivation or instead engages active perspective taking. We observed that AM reactivation can serve as a flexible mechanism that supports empathy by enabling observers to shift perspective when direct experiential overlap is lacking.

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bioRxiv2025

Reliability and signal comparison of OPM-MEG, fMRI & iEEG in a repeated movie viewing paradigm

Optically pumped magnetometers (OPMs) offer a promising advancement in noninvasive neuroimaging via magnetoencephalography (MEG), but establishing their reliability and comparability to existing methods remains an ongoing endeavor. Here, we evaluated OPM recordings by assessing their test-retest reliability and comparing them to functional magnetic resonance imaging (fMRI) and intracranial electroencephalography (iEEG) recordings. Data were collected from three independent participant groups during repeated viewings of a movie segment. In 7 canonical frequency bands ({delta}: 0.5-4 Hz,{theta} : 4-8 Hz, : 8-12 Hz, {beta}: 12-28 Hz,{gamma} 1: 28-46 Hz,{gamma} 2: 55-70 Hz, and HF: 64-116 Hz), as well as a broadband (BB: 0.5-116 Hz) signal, we quantified the signal consistency (1) within individuals, (2) across subjects, and (3) across modalities. OPM exhibited widespread reliability, particularly in lower frequency bands; spatial patterns resembled those of fMRI and iEEG in visual and auditory regions. Cross-modal analyses revealed robust correspondence between OPM and both fMRI and iEEG, including inverse correlations at low frequencies and positive correlations at higher frequencies in the OPM-fMRI comparison, consistent with known relationships between oscillatory power and BOLD responses. Comparisons of signal-to-noise (SNR) estimates further revealed that in some regions, the SNR of cross-modal alignment exceeded within-modality reliability, suggesting that bridging between modalities can sometimes enhance SNR by attenuating reliably shared noise. Our findings demonstrate that OPM consistently captures stimulus-locked neural dynamics that converge with established modalities.

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bioRxiv2025

Hippocampal ripples initiate cortical dimensionality expansion for memory retrieval

How are past experiences reconstructed from memory? Learning is thought to compress external inputs into low-dimensional hippocampal representations, later expanded into high-dimensional cortical activity during recall. Hippocampal ripples, brief high-frequency bursts linked to retrieval, may initiate this expansion. Analysing intracranial EEG data from patients with pharmaco-resistant epilepsy during an episodic memory task, we found that cortical dimensionality increased following ripple events during correct, but not incorrect, retrieval. This expansion correlated with faster reaction times and reinstatement of the target association. Crucially, hippocampal theta and cortical gamma phase-amplitude coupling emerged after ripples but before cortical expansion, suggesting a mechanism for ripple-driven communication. Ripple events also marked the separation of task-relevant variables in cortical state space, revealing how hippocampal output reshapes the geometry of memory representations to support successful recall.

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bioRxiv2025

The "Podcast" ECoG dataset for modeling neural activity during natural language comprehension

Naturalistic electrocorticography (ECoG) data are a rare but essential resource for studying the brains linguistic capabilities. ECoG offers a high temporal resolution suitable for investigating processes at multiple temporal timescales and frequency bands. It also provides broad spatial coverage, often along critical language areas. Here, we share a dataset of nine ECoG participants with 1,330 electrodes listening to a 30-minute audio podcast. The richness of this naturalistic stimulus can be used for various research endeavors, from auditory perception to semantic integration. In addition to the neural data, we extract linguistic features of the stimulus ranging from phonetic information to large language model word embeddings. We use these linguistic features in encoding models that relate stimulus properties to neural activity. Finally, we provide detailed tutorials for preprocessing raw data, extracting stimulus features, and running encoding analyses that can serve as a pedagogical resource or a springboard for new research.

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bioRxiv2025

Fast-timescale hippocampal processes bridge between slowly unfurling neocortical states during memory search

Prior behavioral work showed that event structure supports our ability to search through continuous naturalistic memories. We hypothesized that, neurally, this memory search process involves a division of labor between slowly unfurling neocortical states representing event knowledge and fast hippocampal-neocortical communication supporting retrieval of new information at transitions between events. In a sample of ten intracranial EEG patients we tracked slow neural state-patterns as patients viewed a movie and then searched their memories in a structured naturalistic interview. As patients answered questions ("after A, when does B happen next?"), state-patterns from movie-viewing were reinstated in neocortex. During the critical memory-search period, states unfurled in a forward direction, realizing a trajectory from A to B in memory. Punctate moments of state-transition during memory-search were marked by low-frequency power decreases in cortex and preceded by power decreases in hippocampus that correlated with reinstatement. Connectivity-analysis revealed information-flow from hippocampus to cortex underpinning state-transitions.

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bioRxiv2023

A shared linguistic space for transmitting our thoughts from brain to brain in natural conversations

Effective communication hinges on a mutual understanding of word meaning in different contexts. The embedding space learned by large language models can serve as an explicit model of the shared, context-rich meaning space humans use to communicate their thoughts. We recorded brain activity using electrocorticography during spontaneous, face-to-face conversations in five pairs of epilepsy patients. We demonstrate that the linguistic embedding space can capture the linguistic content of word-by-word neural alignment between speaker and listener. Linguistic content emerged in the speakers brain before word articulation, and the same linguistic content rapidly reemerged in the listeners brain after word articulation. These findings establish a computational framework to study how human brains transmit their thoughts to one another in real-world contexts.

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bioRxiv2022

Test-Retest Reliability of the Human Connectome: An OPM-MEG study

Magnetoencephalography with optically pumped magnetometers (OPM-MEG) offers a new way to record electrophysiological brain function, with significant advantages over conventional MEG including adaptability to head shape/size, free movement during scanning, better spatial resolution, increased signal, and no reliance on cryogenics. However, OPM-MEG remains in its infancy, with significant questions to be answered regarding optimal system design and robustness. Here, we present an open-source dataset acquired using a newly constructed OPM-MEG system with a triaxial sensor design averaging 168 channels. Using OPM-optimised magnetic shielding and active background-field control, we measure the test-retest reliability of the human connectome. We employ amplitude envelope correlation to measure whole-brain functional connectivity in 10 individuals whilst they watch a 600 s move clip. Our results show high repeatability between experimental runs at the group level, with a correlation coefficient of 0.81 in the theta, 0.93 in alpha and 0.94 in beta frequency ranges. At the individual subject level, we found marked differences between individuals, but high within-subject robustness (correlations of 0.56 {+/-} 0.25, 0.72 {+/-} 0.15 and 0.78 {+/-} 0.13 in theta, alpha and beta respectively). These results compare well to previously reported findings using conventional MEG; they show that OPM-MEG is a viable way to characterise whole brain connectivity and add significant weight to a growing argument that OPMs can overtake cryogenic sensors as the fundamental building block of MEG systems.

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bioRxiv2020

Moment-by-moment tracking of naturalistic learning and its underlying hippocampo-cortical interactions

Every day our memory system achieves a remarkable feat: We form lasting memories of stimuli that were only encountered once. Here we investigate such learning as it naturally occurs during story listening, with the goal of uncovering when and how memories are stored and retrieved during processing of continuous, naturalistic stimuli. In behavioral experiments we confirm that, after a single exposure to a naturalistic story, participants can learn about its structure and are able to recall upcoming words in the story. In patients undergoing electrocorticographic recordings, we then track mnemonic information in high frequency activity (70 - 200Hz) as patients listen to a story twice. In auditory processing regions we demonstrate the rapid reinstatement of upcoming information after a single exposure; this neural measure of predictive recall correlates with behavioral measures of event segmentation and learning. Connectivity analyses on the neural data reveal information-flow from cortex to hippocampus at the end of events. On the second time of listening information-flow from hippocampus to cortex precedes moments of successful reinstatement.

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bioRxiv2020

The hippocampus as the switchboard between perception and memory

Adaptive memory recall requires a rapid and flexible switch from external perceptual reminders to internal mnemonic representations. However, owing to the limited temporal or spatial resolution of brain imaging modalities used in isolation, the hippocampal-cortical dynamics supporting this process remain unknown. We thus employed an object-scene cued recall paradigm across two studies, including intracranial Electroencephalography (iEEG) and high-density scalp EEG. First, a sustained increase in hippocampal high gamma power (60-110 Hz) emerged 500 ms after cue onset and distinguished successful vs. unsuccessful recall. This increase in gamma power for successful recall was followed by a decrease in hippocampal alpha power (8-12 Hz). Intriguingly, the hippocampal gamma power increase marked the moment at which extrahippocampal activation patterns shifted from perceptual cue towards mnemonic target representations. In parallel, source-localised EEG alpha power revealed that the recall signal progresses from hippocampus to posterior parietal cortex and then to medial prefrontal cortex. Together, these results identify the hippocampus as the switchboard between perception and memory and elucidate the ensuing hippocampal-cortical dynamics supporting the recall process. SignificanceHow do we adaptively switch from perceiving the external world to retrieving goal-relevant internal memories? To tackle this question, we used - in a cued-recall paradigm - direct intracranial recordings from the human hippocampus complemented by high-density scalp Electroencephalography (EEG). We found that a hippocampal signal ~500 ms after a perceptual cue marks the conversion from external (perceptual) to internal (mnemonic) representations. This sets in motion a recall cascade involving posterior parietal and medial prefrontal cortex, revealed via source-localised and time-resolved EEG alpha power. Together, these results unveil the hippocampal-cortical dynamics supporting rapid and flexible memory recall.

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bioRxiv2020

Modelling the Replay of Dynamic Memories from Cortical Alpha Oscillations with the Sync-Fire / deSync Model.

We here propose a neural network model to explore how neural oscillations might regulate the replay of memory traces. We simulate the encoding and retrieval of a series of events, where temporal sequences are uniquely identifiable by analysing population activity, as several recent EEG/MEG studies have shown. Our model comprises three parts, each considering distinct hypotheses. A cortical region actively represents sequences through the disruption of an intrinsically generated alpha rhythm, where a desynchronisation marks information-rich operations as the literature predicts. A binding region converts each event into a discrete index, enabling repetitions through a sparse encoding of events. We also instantiate a temporal region, where an oscillatory "ticking-clock" made up of hierarchical synfire chains discretely indexes a moment in time. By encoding the absolute timing between events, we show how one can use cortical desynchronisations to dynamically detect unique temporal signatures as they are replayed in the brain.

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bioRxiv2019

Autobiographical memory reactivation in empathy

Empathy relies on the ability to mirror and to explicitly infer others inner states. Theoretical accounts suggest that memories play a role in empathy but direct evidence of a reactivation of autobiographical memories (AM) in empathy is yet to be shown. We addressed this question in two experiments. In experiment 1, electrophysiological activity (EEG) was recorded from 28 participants who performed an empathy task in which targets for empathy were depicted in contexts for which participants either did or did not have an AM, followed by a task that explicitly required memory retrieval of the AM and non-AM contexts. The retrieval task was implemented to extract the neural fingerprints of AM and non-AM contexts, which were then used to probe data from the empathy task. An EEG pattern classifier was trained and tested across tasks and showed evidence for AM reactivation when participants were preparing their judgement in the empathy task. Participants self-reported higher empathy for people depicted in situations they had experienced themselves as compared to situations they had not experienced. A second independent fMRI experiment replicated this behavioural finding and showed the predicted activation in the brain networks underlying both AM retrieval and empathy: precuneus, posterior parietal cortex, superior and inferior parietal lobule and superior frontal gyrus. Together, our study reports behavioural, electrophysiological and fMRI evidence that robustly supports the involvement of AM reactivation in empathy.

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bioRxiv2018

Speed of time-compressed forward replay flexibly changes in human episodic memory

Remembering information from continuous past episodes is a complex task. On the one hand, we must be able to recall events in a highly accurate way that often includes exact timing; on the other hand, we can ignore irrelevant details and skip to events of interest. We here track continuous episodes, consisting of different sub-events, as they are recalled from memory. In behavioral and MEG data, we show that memory replay is temporally compressed and proceeds in a forward direction. Neural replay is characterized by the reinstatement of temporal patterns from encoding. These fragments of activity reappear on a compressed timescale. Herein, the replay of sub-events takes longer than the transition from one sub-event to another. This identifies episodic memory replay as a dynamic process in which participants replay fragments of fine-grained temporal patterns and are able to skip flexibly across sub-events.

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bioRxiv2018

Hippocampal synchrony and neocortical desynchrony cooperate to encode and retrieve episodic memories

Episodic memories hinge upon our ability to process a wide range of multisensory information and bind this information into a coherent, memorable representation. On a neural level, these two processes are thought to be supported by neocortical alpha/beta desynchronisation and hippocampal theta/gamma synchronisation, respectively. Intuitively, these two processes should couple to successfully create and retrieve episodic memories, yet this hypothesis has not been tested empirically. We address this by analysing human intracranial EEG data recorded during two associative memory tasks. We find that neocortical alpha/beta (8-20Hz) power decreases reliably precede and predict hippocampal \"fast\" gamma (60-80Hz) power increases during episodic memory formation; during episodic memory retrieval however, hippocampal \"slow\" gamma (40-50Hz) power increases reliably precede and predict later neocortical alpha/beta power decreases. We speculate that this coupling reflects the flow of information from neocortex to hippocampus during memory formation, and hippocampal pattern completion inducing information reinstatement in the neocortex during memory retrieval.\n\nSignificance StatementEpisodic memories detail our personally-experienced past. The formation and retrieval of these memories has long been thought to be supported by a division of labour between the neocortex and the hippocampus, where the former processes event-related information and the latter binds this information together. However, it remains unclear how the two regions interact. We uncover directional coupling between these regions, with power decreases in the neocortex that precede and predict power increases in the hippocampus during memory formation. Fascinatingly, this process reverses during memory retrieval, with hippocampal power increases preceding and predicting neocortical power decreases. These results suggest a bidirectional flow of information between the neocortex and hippocampus is fundamental to the formation and retrieval of episodic memories.

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