Biology subjects

Daume, J.

Publications and source records attributed to Daume, J..

12 recordsLinked to original sources

bioRxiv2026

Cellular code for mnemonic pattern separation in the human hippocampus is revealed by false memories

Theoretical models propose that pattern separation, a computation thought to be implemented by the hippocampus, allows us to differentiate between familiar and novel items. However, whether pattern separation operates in the human hippocampus remains contested, with no established single-cell correlate. We recorded the single neuron activity of 3506 neurons in the human brain while 97 patients performed a recognition memory task in which novel images similar to previously seen images led to false memories and associated behavioral errors. We identified two kinds of memory selective neurons distributed across the brain: those responding differently to falsely recognized novel and correctly recognized familiar images in a manner compatible with pattern separation, and the other signaling the subject's choice. At the population level, these cells predicted mnemonic ground truth in the hippocampus and the decision in the pre-supplementary motor area, illustrating the progression from mnemonic signals to decisions. Removing pattern separation-signaling cells abolished the continuous memory strength gradient present in the hippocampus, suggesting a role of these cells in separating memories of different strength. These results establish a single cell correlate for mnemonic pattern separation in the human hippocampus and show its behavioral relevance in episodic memory.

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bioRxiv2026

Oscillatory sensory stimulation in the delta-band enhancestemporal prediction performance

Predicting the time point when an event will occur is fundamental for adaptive behavior, yet it remains unresolved whether temporal prediction can be influenced by low-frequency rhythmic modulation of sensory stimuli. Here, we tested whether external rhythmic sensory stimulation at a frequency in the delta range (0.5 - 3 Hz) alters performance in a visual temporal prediction task. Participants judged whether a moving visual stimulus reappeared too early or too late after disappearing behind an occluder, while the temporal structure of crossmodal sensory input was manipulated across two behavioral sessions. Results indicated that in the visual-auditory conditions, oscillatory stimulation in either the visual or auditory modality improved performance, whereas decaying sensory intensity over time impaired performance. In visual-tactile conditions, oscillatory visual stimulation also enhanced sensitivity, but rhythmic tactile stimulation did not produce a comparable benefit in performance. Critically, tactile stimulation improved performance only when aligned to the expected disappearance of the visual stimulus, demonstrating that the phase relationship between sensory input and intrinsic delta oscillations is behaviorally relevant. Together, these findings indicate that temporal prediction depends on the temporal structure of sensory input and support the relevance of delta-band oscillations in predictive behavior across and within sensory modalities. Hence, rhythmic modulation of sensory stimuli may provide a tool to enhance temporal prediction accuracy by stimulating oscillatory neural dynamics.

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bioRxiv2025

Stimulus-specific recruitment of human amygdala neurons predicts episodic memory encoding success

Controlling whether a given experience is encoded into long-term memory and thus later remembered is a crucial component of our memory system whose failure is often at the root of memory disorders. One brain area that takes part in controlling which experiences are remembered is the amygdala, but the mechanisms by which it does so remain poorly understood. Here we examined single-neuron activity and local field potentials as human participants performed recognition memory tasks with visual stimuli. Category-selective amygdala neurons exhibited elevated firing rates during encoding of later remembered items versus forgotten items. This subsequent memory effect was restricted to images of the preferred category of a given cell, was stronger and appeared earlier in the amygdala compared to the hippocampus, and did not depend on the valence and arousal of the stimuli. In contrast, category selective cells immediately upstream in the ventral temporal cortex did not exhibit a subsequent memory effect, highlighting specificity to the amygdala. Successful memory formation was accompanied by enhanced spike-field coherence between the activity of category cells in the amygdala and hippocampal field potentials. These findings, replicated in two large independent datasets with two different tasks, demonstrate that recruitment of stimulus-specific amygdala representations predicts episodic memory formation, particularly in the right amygdala. This data suggests category cells in the right amygdala as a cellular target for interventions to treat memory disorders in humans.

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bioRxiv2025

Cross-region neuron co-firing mediated by ripple oscillations supports distributed working memory representations.

High-frequency ([~]90Hz) ripple oscillations may promote integrative processing in mammalian brains. Previous work has demonstrated that the co-occurrence of these ripple oscillations is associated with enhanced temporal binding of neural activity between nearby human cortical neurons. However, it remains unclear whether such co-ripple facilitation of neuronal coupling supports cognitive processing, or if it occurs at greater distances. Here, we analyze intracranial recordings from patients implanted with microwire electrodes in the hippocampus, amygdala, ventromedial prefrontal cortex, anterior cingulate cortex, and pre-supplementary motor area, bilaterally, during a working memory task. We demonstrate that ripple oscillations significantly increase in all recorded regions, during encoding, maintenance and retrieval. Furthermore, co-occurrence of ripples increases between brain regions, associated with [~]30% increases in cross-region co-firing, both without decrement over distances up to 220 mm. These increases in cross-regional co-rippling and associated co-firing scale with memory load during maintenance and retrieval. During retrieval, co-ripples promote the reinstatement of the stimulus-specific long-distance co-firing patterns observed during encoding, especially during rapid recognition. Our findings reveal that co-occurring ripple oscillations orchestrate long-range neural communication that supports distributed neural representations during human cognition.

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bioRxiv2025

Hippocampal stimulation reveals causal role of persistent neural activity in human working memory

Working memory (WM) enables the temporary maintenance and manipulation of information, supporting flexible, goal-directed behavior. While converging evidence suggests that persistent activity in the hippocampus and other areas of the brain contributes to WM storage, this link has not been examined by manipulating neural activity experimentally. Here, we combined simultaneous intracranial single-neuron recordings with focal electrical stimulation in the human hippocampus to test the role of memoranda-selective persistent neural activity for WM. Thirty patients with implanted hybrid depth electrodes performed a WM task with images as memoranda. Electrical stimulation (2 s, 50 Hz, 1 mA) was delivered to the hippocampus during the maintenance period on a subset of trials. Behaviorally, stimulation impaired WM performance, increasing response times especially in low-load conditions. Neuronally, stimulation reduced memoranda-selective activity in hippocampus and ventral temporal cortex (VTC), thereby disrupting content-specific neural representations of WM content. The extent of stimulation-induced change in firing rate mediated trial-by-trial impaired WM-related behavior, linking disrupted neural selectivity to impaired WM. At the population level, stimulation shifted neural trajectories farther from attractor states, consistent with degraded mnemonic fidelity. Together, these data provide evidence that selective persistent activity of individual neurons in hippocampus and VTC supports WM maintenance in humans. Our results demonstrate that hippocampal stimulation disrupts both single-neuron coding and population-level attractor stability, linking cellular mechanisms to behavior and highlighting the contributions of persistent activity to WM maintenance.

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bioRxiv2025

Differential contributions of low-frequency phase and power in crossmodal temporal prediction: A MEG study

BACKGROUNDOur representation of time is embedded within multisensory perception, based on sight, sound, or touch. However, despite being a crucial aspect of daily life, the neural dynamics of cross-modal temporal predictions remain elusive. The objective of this study was to investigate neural correlates of tactile-to-visual influences on temporal prediction using magnetencephalography (MEG). We hypothesized to observe increased inter-trial phase consistency (ITPC) in the low-frequency delta range (0.5-4 Hz) due to their involvement in temporal prediction. In addition, stronger ITPC values should correlate with a steeper slope of the psychometric function, indicating phase alignments as a likely cause of more consistent temporal predictions. METHODSThe study was conducted within one MEG session employing a modified version of the time prediction task by Roth et al. [2013] and Daume et al. [2021]. Participants (N=23) observed a visual stimulus moving towards an occluder. Shortly before reaching the occluder, the visual stimulus faded in luminance to make the visual offset less informative. Instead, participants received a brief tactile stimulus to the ipsilateral hand at the time point of disappearance, generating a temporal expectation regarding its reappearance on the opposite side of the occluder. After variable time intervals, a visual stimulus reappeared, and participants had to indicate whether this was too early or too late compared to the movement before disappearance. A non-predictive control condition involved participants judging the variable luminance of the reappearing visual stimulus compared to its initial luminance at the beginning of the trial. Psychometric curves were fitted to the behavioral data of each participant and condition, and MEG recordings were analyzed using time-frequency representations obtained by wavelet convolution. To compare spectral power and ITPC estimates between conditions within frequency bands showing significant differences to the pre-stimulus baseline, we used cluster-based permutation statistics. Pearsons correlations were used to examine the relationship between ITPC or power estimates and the steepness of each participants psychometric function. RESULTSITPC analysis revealed strong increases in the delta range around stimulus disappearance and reappearance. Delta ITPC was significantly stronger during temporal prediction compared to the control condition. Only delta ITPC, but not delta power, correlated with the consistency of temporal prediction. Furthermore, temporal prediction led to increased alpha power in the dorsolateral and medial prefrontal cortex, as well as the right superior temporal sulcus and middle temporal gyrus, whereas beta power did not show differences between conditions. CONCLUSIONOur findings suggest that increased delta ITPC is likely caused by phase resets driven by the temporal prediction process rather than evoked neural activity. Furthermore, our findings indicate that phase alignments occur during crossmodal visuo-tactile-to-visual temporal predictions, even with a combination of non-rhythmic and discrete stimulation. This highlights the broad applicability of phase resets of neural oscillations as a mechanism for predicting timing across various types of stimuli.

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bioRxiv2024

Persistent activity during working memory maintenance predicts long-term memory formation in the human hippocampus

Working Memory (WM) and Long-Term Memory (LTM) are often viewed as separate cognitive systems. Little is known about how these systems interact when forming memories. We recorded single neurons in the human medial temporal lobe while patients maintained novel items in WM and a subsequent recognition memory test for the same items. In the hippocampus but not the amygdala, the level of WM content-selective persist activity during WM maintenance was predictive of whether the item was later recognized with high confidence or forgotten. In contrast, visually evoked activity in the same cells was not predictive of LTM formation. During LTM retrieval, memory-selective neurons responded more strongly to familiar stimuli for which persistent activity was high while they were maintained in WM. Our study suggests that hippocampal persistent activity of the same cell supports both WM maintenance and LTM encoding, thereby revealing a common single-neuron component of these two memory systems.

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bioRxiv2023

Control of working memory maintenance by theta-gamma phase amplitude coupling of human hippocampal neurons

Retaining information in working memory (WM) is a demanding process that relies on cognitive control to protect memoranda-specific persistent activity from interference. How cognitive control regulates WM storage, however, remains unknown. We hypothesized that interactions of frontal control and hippocampal persistent activity are coordinated by theta-gamma phase amplitude coupling (TG-PAC). We recorded single neurons in the human medial temporal and frontal lobe while patients maintained multiple items in WM. In the hippocampus, TG-PAC was indicative of WM load and quality. We identified cells that selectively spiked during nonlinear interactions of theta phase and gamma amplitude. These PAC neurons were more strongly coordinated with frontal theta activity when cognitive control demand was high, and they introduced information-enhancing and behaviorally relevant noise correlations with persistently active neurons in the hippocampus. We show that TG-PAC integrates cognitive control and WM storage to improve the fidelity of WM representations and facilitate behavior.

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bioRxiv2022

Changes of oscillatory and aperiodic neuronal activity in working memory following anaesthesia: a prospective observational study

BackgroundAnaesthesia and surgery can lead to cognitive decline, especially in the elderly. However, to date, the neurophysiological underpinnings of perioperative cognitive decline remain unknown. MethodsWe included male patients, who were 60 years or older scheduled for elective radical prostatectomy under general anaesthesia. We obtained neuropsychological (NP) tests as well as a visual match-to-sample working memory (WM) task with concomitant 62-channel scalp electroencephalography (EEG) before and after surgery. ResultsA total number of 26 patients completed neuropsychological assessments and EEG pre- and postoperatively. Behavioural performance declined in the neuropsychological assessment after anaesthesia (total recall; t-tests: t25 = -3.25, Bonferroni-corrected p = 0.015 d = -0.902), while WM performance showed a dissociation between match and mis-match accuracy (rmANOVA: match*session F1,25 = 3.866, p = 0.060). Distinct EEG signatures tracked behavioural performance: Better performance in the NP assessment was correlated with an increase of non-oscillatory (aperiodic) activity, reflecting increased cortical activity (cluster permutation tests: total recall r = 0.66, p = 0.029, learning slope r = 0.66, p = 0.015), while WM accuracy was tracked by distinct temporally-structured oscillatory theta/alpha (7 - 9 Hz), low beta (14 - 18 Hz) and high beta/gamma (34 - 38 Hz) activity (cluster permutation tests: matches: p < 0.001, mis-matches: p = 0.022). ConclusionsOscillatory and non-oscillatory (aperiodic) activity in perioperative scalp EEG recordings track distinct features of perioperative cognition. Aperiodic activity provides a novel electrophysiological biomarker to identify patients at risk for developing perioperative neurocognitive decline.

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bioRxiv2019

Dynamic Predictions: Oscillatory Mechanisms Underlying Multisensory Sequence Processing

Neural oscillations have been proposed to be involved in predictive processing, however less addressed in the multisensory context. In the present study, we recorded cortical activity using magnetoencephalography during an audiovisual serial prediction task in which participants had to acquire stimulus sequences and to monitor whether subsequent probe items complied with the sequence. In a given trial, either visual or auditory features of the bimodal stimuli were task-relevant. Task-related changes of power and coupling of neural oscillations were analyzed using a data-driven clustering approach. We observed prediction-related theta-band (5-7 Hz) coupling in a network involving the cingulate, premotor, prefrontal, and superior temporal regions. The behavioral performance of participants varied as a function of the phase delay of the coupling between different regions in this network. . Two additional spectro-temporal clusters were detected in which beta power (11-16 Hz and 16-22 Hz, respectively) was stronger if the previous or the following stimuli were the same as the current one in the sequence. These clusters spatially overlapped with the theta-band prediction cluster, and interacted with it through cross-frequency coupling. Our results offer novel insights into the multi-timescale neural dynamics underlying multisensory predictions, suggesting that oscillations in multiple frequency ranges, as well as coupling within and across frequencies, may be critical for multisensory sequence processing.

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bioRxiv2019

An oscillator ensemble model of sequence learning

Learning and memorizing sequences of events is an important function of the human brain and the basis for forming expectations and making predictions. Learning is facilitated by repeating a sequence several times, causing rhythmic appearance of the individual sequence elements. This observation invites to consider the resulting multitude of rhythms as a spectral fingerprint which characterizes the respective sequence. Here we explore the implications of this perspective by developing a neurobiologically plausible computational model which captures this fingerprint by attuning an ensemble of neural oscillators. In our model, this attuning process is based on a number of oscillatory phenomena that have been observed in electrophysiological recordings of brain activity like synchronization, phase locking and reset as well as cross-frequency coupling. We compare the learning properties of the model with behavioral results from a study in human participants and observe good agreement of the errors for different levels of complexity of the sequence to be memorized. Finally, we suggest an extension of the model for processing sequences that extend over several sensory modalities.

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bioRxiv2019

Delta phase resetting mediates non-rhythmic temporal prediction

The phase of neural oscillatory activity aligns to the predicted onset of upcoming stimulation. Whether such phase alignments represent phase resets of underlying neural oscillations or just rhythmically evoked activity, and whether they can be observed in a rhythm-free visual context, however, remains unclear. Here, we recorded the magnetoencephalogram while participants were engaged in a temporal prediction task judging the visual or tactile reappearance of a uniformly moving stimulus. The prediction conditions were contrasted with a control condition to dissociate phase adjustments of neural oscillations from stimulus-driven activity. We observed stronger delta band inter-trial phase consistency (ITPC) in a network of sensory, parietal and frontal brain areas, but no power increase reflecting stimulus-driven or prediction-related processes. Delta ITPC further correlated with prediction performance in the cerebellum and visual cortex. Our results provide evidence that phase alignments of low-frequency neural oscillations underlie temporal predictions in a non-rhythmic visual and crossmodal context.

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