Biology subjects

Hamer, H.

Publications and source records attributed to Hamer, H..

14 recordsLinked to original sources

bioRxiv2026

Comparing re-referencing methods for human intracranial EEG

Stereo-electroencephalography (SEEG) involves the implantation of depth electrodes in the brain to monitor epileptic seizures for surgical feasibility. As the electrodes advance into deeper limbic structures, the macro contacts distributed along the shaft record electrical activity from more lateral sites, while a bundled array of microwires simultaneously captures highly localised signals from the tip of the electrode. In a clinical setting these electrical signals are recorded relative to a reference signal, which may be sub-optimal for subsequent analyses that are unrelated to clinical objectives. Therefore, a secondary re-referencing operation is often undertaken to transform the signal in relation to a specific hypothesis. Despite a recent surge in SEEG studies, comparative studies on the much-understudied issue of re-referencing are sparse. Here, we analyse data collected from 16 human patients during an episodic memory task and comparatively apply a range of re-referencing methods to both macro contact and micro-wire data. We find that the choice of method changes the proportion of trials that survive artefact rejection, low frequency power, and the aperiodic background against which that power is read. In the hippocampal recordings, however, no method differed from any other in the size of a memory effect in power or spike-field coherence. This early transformative decision therefore bears on how the signal is described. We found no evidence that it changes the detectability of the behavioural effects tested here, and no method reversed the direction of a memory effect.

neuroscience↗

bioRxiv2026

Beyond Rate: Hippocampal Phase Codes for Space and Memory

Place cells and concept neurons are defined by a rise in firing rate at a particular location or for a particular person or object. Neurons without such a rise remain unlabeled, although they keep firing during the task. Such neurons could still carry information in the timing of their spikes. Hippocampal theta provides a reference for this timing. We therefore asked whether the theta phase of a neuron's spikes depends on location or on the viewed image, even when its firing rate does not. We analysed hippocampal neurons in humans navigating a virtual city, rats running on a linear track, and humans viewing images of anima ls, faces, and places. In both navigation datasets, more neurons than expected by chance fired at a consistent theta phase at particular locations. This phase tuning remained after we excluded neurons whose firing rate depended on location. In human navigation, the spike phases of these remaining neurons improved location decoding beyond the firing rates of all neurons. More phase-tuned neurons than expected by chance also fired at progressively earlier theta phases as participants passed each neuron's preferred location. This pattern resembles phase precession, which classically occurs as an animal crosses the firing-rate field of a place cell. The neurons that showed it had no firing-rate field, so their phase shift was anchored to the location defined by phase tuning alone. During image viewing, more neurons than expected by chance changed the theta phase of their spikes after a particular image appeared. This effect remained after we removed, for each neuron, the images that changed its firing rate. Spike phases alone also predicted the image category above chance. Theta-relative spike timing therefore carries in formation about location and images that firing rate alone misses. We propose that weak input changes when a neuron fires with in the theta cycle, whereas strong input also raises its firing rate.

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bioRxiv2026

Hippocampal ripples evoke a stereotyped cortical response followed by spindle-mediated network synchronization.

Hippocampal sharp-wave ripples (SWRs) are thought to play a key role in systems memory consolidation by broadcasting reactivated memory content to distributed cortical networks while we sleep. Elucidating how this hippocampal-cortical dialogue unfolds at the brain-wide level is therefore essential to understanding how sleep transforms new experiences into lasting memories. Here we combined simultaneous hippocampal intracranial EEG and 21-channel scalp EEG during overnight sleep to characterize the large-scale cortical impact of hippocampal ripple events. We found that individual hippocampal ripples elicited a decodable, phase-locked cortical response at the scalp level. This cortical response was followed by increases in cortico-cortical synchronization and network density in the spindle-band. Mediation analyses revealed a sequential pathway in which ripple magnitude predicted large-scale cortical connectivity through this intermediate cortical response and subsequent spindle activity. These findings demonstrate that hippocampal ripples trigger a two-step cascade, i.e., an early stereotyped cortical response followed by spindle-mediated network synchronization, consistent with the view that SWRs co-activate distributed cortical nodes and potentiate the cortical-cortical connections that support memory consolidation. By demonstrating that ripple-related cortical responses are decodable noninvasively, our results moreover suggest a new strategy for inferring hippocampal ripple activity from scalp electrophysiology. Significance StatementHippocampal sharp-wave ripples are brief bursts of coordinated neural activity believed to support memory consolidation by coordinating communication between the hippocampus and the cortex during sleep. Although animal studies show that ripples influence widespread cortical activity, their large-scale cortical effects in humans have previously only been measurable through invasive brain recordings. By combining hippocampal intracranial recordings with scalp EEG, we show that hippocampal ripples evoke a cortical response decodable noninvasively, followed by widespread spindle-mediated synchronization across cortical networks. These findings reveal a temporally structured cascade linking hippocampal activity to large-scale cortical coordination during sleep and suggest that ripple-driven brain-wide responses can be monitored using non-invasive EEG recordings.

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bioRxiv2025

Spatiotemporal Patterns Differentiate Hippocampal Sharp-Wave Ripples from Interictal Epileptiform Discharges in Mice and Humans

Hippocampal sharp-wave ripples (SPW-Rs) are high-frequency oscillations critical for memory consolidation in mammals. Despite extensive characterization in rodents, their application as biomarkers to track and treat memory dysfunction in humans is limited by coarse spatial sampling, interference from interictal epileptiform discharges (IEDs), and lack of consensus on human SPW-R localization and morphology. We demonstrate that mouse and human hippocampal ripples share spatial, spectral and temporal features, which are clearly distinct from IEDs. In 1024-channel hippocampal recordings from APP/PS1 mice, SPW-Rs were distinguishable from IEDs by their narrow localization to the CA1 pyramidal layer, narrowband frequency peaks, and multiple ripple cycles on the unfiltered local field potential. In epilepsy patients, ripples showed similar narrowband frequency peaks and visible ripple cycles in CA1 and the subiculum but were absent in the dentate gyrus. Conversely, IEDs showed a broad spatial extent and wide-band frequency power. We introduce a semi-automated, human ripple detection toolbox ("ripmap") selecting optimal detection channels and separating event waveforms by low-dimensional embedding. Our approach improves ripple detection accuracy, providing a firm foundation for future human memory research.

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bioRxiv2024

Hippocampal ripples during offline periods predict human motor sequence learning

High-frequency bursts in the hippocampus, known as ripples (80-120 Hz in humans), have been shown to support episodic memory processes. However, converging recent evidence in rodent models as well as human neuroimaging suggests that the hippocampus may be involved in a wider range of memory domains, including motor sequence learning (MSL). Nevertheless, no direct link between hippocampal ripples and MSL has yet been established. Here, we recorded intracranial electroencephalography from the hippocampus in 20 epilepsy patients during a MSL task in which participants showed steady improvement across nine 30-second training blocks interspersed with 30-second rest ( offline) periods. We first demonstrate that ripple rates strongly increase during rest periods relative to training blocks. Importantly, ripple rates during rest periods tracked learning behaviour, both across blocks and across participants. These results suggest that hippocampal ripples during offline periods play a functional role in motor sequence learning and that the hippocampus may be involved in offline learning beyond episodic memory.

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bioRxiv2023

Intricate epileptiform discharges affect memory in an Alzheimer's Disease mouse model

Interictal epileptiform discharges (IEDs) are transient abnormal electrophysiological events commonly observed in epilepsy patients but are also present in other neurological disease, such as Alzheimers Disease (AD). Understanding the role IEDs have on the hippocampal circuit is important for our understanding of the cognitive deficits seen in epilepsy and AD. We characterize and compare the IEDs of human epilepsy patients from microwire hippocampal recording with those of AD transgenic mice with implanted multi-layer hippocampal silicon probes. Both the local field potential features and firing patterns of pyramidal cells and interneurons were similar in mouse and human. We found that as IEDs emerged from the CA3-1 circuits, they recruited pyramidal cells and silenced interneurons, followed by post-IED suppression. IEDs suppressed the incidence and altered the properties of physiological sharp-wave ripples (SPW-Rs), altered their physiological properties, and interfered with the replay of place field sequences in a maze. In addition, IEDs in AD mice inversely correlated with daily memory performance. Together, our work implicates that IEDs may present a common and epilepsy-independent phenomenon in neurodegenerative diseases that perturbs hippocampal-cortical communication and interferes with memory. Significant StatementPrevalence of neurodegenerative diseases and the number of people with dementia is increasing steadily. Therefore, novel treatment strategies for learning and memory disorders are urgently necessary. IEDs, apart from being a surrogate for epileptic brain regions, have also been linked to cognitive decline. Here we report that IEDs in human epilepsy patients and AD mouse models have similar local field potential characteristics and associated firing patterns of pyramidal cells and interneurons. Mice with more IEDs displayed fewer hippocampal SPW-Rs, poorer replay of spatial trajectories, and decreased memory performance. IED suppression is an unexplored target to treat cognitive dysfunction in neurodegenerative diseases.

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bioRxiv2022

Deep learning based decoding of local field potential events

How is information processed in the cerebral cortex? To answer this question a lot of effort has been undertaken to create novel and to further develop existing neuroimaging techniques. Thus, a high spatial resolution of fMRI devices was the key to exactly localize cognitive processes. Furthermore, an increase in time-resolution and number of recording channels of electro-physiological setups has opened the door to investigate the exact timing of neural activity. However, in most cases the recorded signal is averaged over many (stimulus) repetitions, which erases the fine-structure of the neural signal. Here, we show that an unsupervised machine learning approach can be used to extract meaningful information from electro-physiological recordings on a single-trial base. We use an auto-encoder network to reduce the dimensions of single local field potential (LFP) events to create interpretable clusters of different neural activity patterns. Strikingly, certain LFP shapes correspond to latency differences in different recording channels. Hence, LFP shapes can be used to determine the direction of information flux in the cerebral cortex. Furthermore, after clustering, we decoded the cluster centroids to reverse-engineer the underlying prototypical LFP event shapes. To evaluate our approach, we applied it to both neural extra-cellular recordings in rodents, and intra-cranial EEG recordings in humans. Finally, we find that single channel LFP event shapes during spontaneous activity sample from the realm of possible stimulus evoked event shapes. A finding which so far has only been demonstrated for multi-channel population coding.

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bioRxiv2021

Hippocampal neurons code individual memory episodes in humans

The hippocampus is an essential hub for episodic memory processing. However, how human hippocampal single neurons code multi-element associations remains unknown. Some argue that each hippocampal neuron codes for an invariant element within an episode. Instead, others have proposed that hippocampal neurons bind together all elements present in a discrete episodic memory. Here, we provide evidence for the latter. We show that individual neurons, which we term Episode Specific Neurons (ESNs), code discrete episodic memories using either a rate code or a temporal firing code. We find evidence for these neurons exclusively in the hippocampus. Importantly, these ESNs do not reflect the coding of a particular element in the episode (i.e., concept or time). Instead, they code for the conjunction of the different elements that make up the episode. One-Sentence SummaryIndividual neurons in the hippocampus code for discrete episodic memories.

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bioRxiv2021

Oscillations support co-firing of neurons in the service of human memory formation

Theta and gamma oscillations in the medial temporal lobe are suggested to play a critical role for human memory formation via establishing synchrony in neural assemblies. Arguably, such synchrony facilitates efficient information transfer between neurons and enhances synaptic plasticity, both of which benefit episodic memory formation. However, to date little evidence exists from humans that would provide direct evidence for such a specific role of theta and gamma oscillations for episodic memory formation. Here we investigate how oscillations shape the temporal structure of neural firing during memory formation in the medial temporal lobe. We measured neural firing and local field potentials in human epilepsy patients via micro-wire electrode recordings to analyze how brain oscillations promote co-incidences of firing between neurons during successful and unsuccessful encoding of episodic memories. The results show that phase-coupling of neurons to faster theta and gamma oscillations correlates with co-firing at short latencies ([~]20-30 ms) and occurs during successful memory formation. Phase-coupling at slower oscillations in these same frequency bands, in contrast, correlates with longer co-firing latencies and occurs during memory failure. Thus, our findings provide evidence which implicate neural oscillations into the synchronization of neural firing in the medial temporal lobe during the encoding of episodic memories.

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bioRxiv2020

Theta rhythmicity governs the timing of behavioral and hippocampal responses in humans specifically during memory-dependent tasks

1.Memory formation and reinstatement are thought to lock to the hippocampal theta rhythm, predicting that encoding and retrieval processes appear rhythmic themselves. Here, we show that rhythmicity can be observed in behavioral responses from memory tasks, where participants indicate, using button presses, the timing of encoding or retrieval of cue-object associative memories. We found no evidence for rhythmicity in button presses for visual tasks using the same stimuli, or for questions about already retrieved objects. The oscillations for correctly remembered trials center in the slow theta frequency range (1-5 Hz), while responses from later forgotten trials do not lock to the behavioral oscillation. Using intracranial EEG recordings, we show that the memory task induces temporally extended phase consistency in hippocampal local field potentials at slow theta frequencies, but only for correctly remembered trials, providing a mechanistic underpinning for the theta oscillations found in behavioral responses.

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bioRxiv2020

Mosaic trisomy of chromosome 1q in human brain tissue associates with unilateral polymicrogyria, very early-onset focal epilepsy, and severe developmental delay

Polymicrogyria (PMG) is a developmental cortical malformation characterized by an excess of small and frustrane gyration and abnormal cortical lamination. PMG frequently associates with seizures. The molecular pathomechanisms underlying PMG development are not yet understood. About 40 genes have been associated with PMG, and small copy number variations have also been described in selected patients. We recently provided evidence that epilepsy-associated structural brain lesions can be classified based on genomic DNA methylation patterns. Here we analyzed 26 PMG patients employing array-based DNA-methylation profiling on formalin-fixed paraffin-embedded material. A series of 62 well-characterized non-PMG cortical malformations (focal cortical dysplasia type 2a/b and hemimegalencephaly), temporal lobe epilepsy, and non-epilepsy autopsy controls was used as reference cohort. Unsupervised dimensionality reduction and hierarchical cluster analysis of DNA methylation profiles showed that PMG formed a distinct DNA methylation class. Copy number profiling from DNA methylation data identified a uniform duplication spanning the entire long arm of chromosome 1 in 7 out of 26 PMG patients, which was verified by additional fluorescence in situ hybridization analysis. In respective cases about 50% of nuclei in the center of the PMG lesion were 1q triploid. No chromosomal imbalance was seen in adjacent, architecturally normal-appearing tissue indicating mosaicism. Clinically, PMG 1q patients presented with a unilateral frontal or hemispheric PMG without hemimegalencephaly, a severe form of intractable epilepsy with seizure onset in the first months of life, and severe developmental delay. Our results show that PMG can be classified among other structural brain lesions according to their DNA methylation profile. One subset of PMG with distinct clinical features exhibits a duplication of chromosomal arm 1q.

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bioRxiv2018

Spectral fingerprints or spectral tilt? Evidence for distinct oscillatory signatures of memory formation

Decreases in low frequency power (2-30 Hz) alongside high frequency power increases (>40 Hz) have been demonstrated to predict successful memory formation. Parsimoniously this change in the frequency spectrum can be explained by one factor, a change in the tilt of the power spectrum (from steep to flat) indicating engaged brain regions. A competing view is that the change in the power spectrum contains several distinct brain oscillatory fingerprints, each serving different computations. Here, we contrast these two theories in a parallel MEG-intracranial EEG study where healthy participants and epilepsy patients, respectively, studied either familiar verbal material, or unfamiliar faces. We investigated whether modulations in specific frequency bands can be dissociated in time, space and by experimental manipulation. Both, MEG and iEEG data, show that decreases in alpha/beta power specifically predicted the encoding of words, but not faces, whereas increases in gamma power and decreases in theta power predicted memory formation irrespective of material. Critically, these different oscillatory signatures of memory encoding were evident in different brain regions. Moreover, high frequency gamma power increases occurred significantly earlier compared to low frequency theta power decreases. These results speak against a \"spectral tilt\" and demonstrate that brain oscillations in different frequency bands serve different functions for memory encoding.

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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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bioRxiv2017

Data-driven re-referencing of intracranial EEG based on independent component analysis (ICA)

Intracranial recordings from patients implanted with depth electrodes are a valuable source of information in cognitive neuroscience. They allow for the unique opportunity to record brain activity with a high spatial and temporal resolution. To extract the local signal of interest in stereotactic EEG (S-EEG) data, a common pre-processing choice is to re-reference the data with a bipolar montage.\n\nWith bipolar reference, each channel is subtracted from its neighbour in order to reduce commonalities between channels and isolate activity that is spatially confined. We here challenge the assumption that bipolar reference can effectively perform this task. We argue that in order to extract local activity, the distribution of the signal source of interest, as well as the distribution of interfering distant signals and noise sources need to be considered. Those can have a variable spatial extent and are modulated by electrode spacing, location and anatomical characteristics. Those factors are not accounted for by a fixed referencing scheme and bipolar reference can therefore not only decrease the signal to noise ratio (SNR) of the data, but also lead to mislocalization of activity and consequently to misinterpretation of results.\n\nWe promote the perspective of regarding referencing as a spatial filtering operation with fixed coefficients. As an alternative, we propose to use Independent Component Analysis (ICA), to derive filter coefficients that reflect the statistical dependencies of the data at hand. We argue that ICA performs the same task that bipolar referencing pursues, namely undoing the linear superposition of activity and can therefore be used to identify activity that is local. We first describe and demonstrate this procedure on human S-EEG recordings. In a simulation with real data, we then quantitatively show that ICA outperforms the bipolar referencing operation in sensitivity and importantly in specificity when it comes to revealing local time series from the superposition of neighbouring channels.

neuroscience↗