Biology subjects

Bickel, S.

Publications and source records attributed to Bickel, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Neural latent representation of implicit perceptual decision confidence signatures from brain-wide intracranial EEG

Human perceptual decision confidence has been associated with brain-wide signalling, albeit with inconsistencies across studies. It remains unclear whether more robust neural latent representations exist, particularly for implicit confidence. We address this by applying complementary machine learning approaches to comprehensive, brain-wide intracranial electroencephalography (iEEG) data acquired without explicit confidence reports. Using explainable feature selection methods, we elucidated key spatiotemporal iEEG components, especially in the frontal cortex, that readily distinguished confidence characteristics related to decision correctness, difficulty, and speed, and that were transferable across motor modalities. Despite inconsistencies in the features identified across methods and conditions, dimensionality reductions revealed robust low-dimensional neural latent representations. Furthermore, their neural trajectories within a shared subspace enhanced the distinguishability of confidence characteristics. Overall, our results uncover low-dimensional spatial and temporal neural latent representations underlying human implicit perceptual decision confidence that are robust to analytical methods and decision conditions.

neuroscience↗

bioRxiv2026

Classification of image category based on spatially distributed, transient high-frequency events

Transient high-frequency activity (HFA) in local field potentials exhibits substantial variability across trials and behavioral states, yet its functional role in sensory representation remains poorly understood. Here, we tested whether transient HFA events carry stimulus-related information through their temporal, spectral, and phase-dependent properties. Using intracranial recordings from 21 human participants performing a visual localizer task, we extracted transient HFA events and quantified their features using information-theoretic and decoding analyses. Individual event features carried only modest information about stimulus identity, and response magnitude and morphology-related properties contributed minimally to decoding performance. Instead, decoding was dominated by temporal alignment and low-frequency phase. Critically, representing transient events as distributed low-frequency phase configurations across electrodes substantially improved cross-trial decoding performance, whereas disrupting distributed phase structure eliminated this decoding advantage. These findings indicate that stimulus-related structure in transient HFA does not primarily arise from isolated local event properties, but instead emerges through distributed, phase-dependent network dynamics. More broadly, the results provide a framework for understanding how transient high-frequency neural activity contributes to sensory representations across distributed cortical networks.

neuroscience↗

bioRxiv2026

Temporal Dynamics of BOLD fMRI Predict Intracranially-Confirmed Seizure Onset Zones in Drug-Resistant Epilepsy

ObjectiveIn individuals with drug-resistant epilepsy, accurately identifying the brain regions where seizures originate is a critical prerequisite to guide surgical treatment and achieve seizure freedom. To accomplish this, intracranial EEG is considered the gold standard, providing the spatiotemporal high-resolution data necessary to pinpoint epileptogenic activity. However, this precision is achieved through an invasive procedure with significant patient burden, which is fundamentally limited by the electrode placement and spatial coverage. MethodsIn this study, we investigated the potential utility of preoperative resting-state fMRI to non-invasively map alterations in brain dynamics at the whole brain level. Region-wise brain dynamics were quantified with complementary measures of local autocorrelation decay rates. We assessed the capacity of these derived features to effectively identify intracranial EEG confirmed seizure onset zones in 18 individuals with drug-resistant medial temporal lobe epilepsy. Overall, the study cohort contained 3867 implanted electrodes of which 159 classified as seizure onset zones by two independent board-certified epileptologists. ResultsOverall, our findings reveal more constrained temporal dynamics for brain regions associated with seizure onsets compared to non-seizure onset zones. Individual-level prediction showed a performance better than chance in 15 of the 18 patients. The overall predictive performance across all patients yielded a median AUC of 0.81, a median true positive rate of 0.75, and a median true negative rate of 0.83. Furthermore, in a subset of 13 patients, those with negative seizure outcomes showed higher probabilities of seizure onset zone predictions outside the resection area compared to those with good outcomes. SignificanceOverall, our findings suggest that altered temporal dynamics derived from preoperative resting-state fMRI represent a promising non-invasive approach for delineating epileptogenic tissue, potentially informing intervention strategies and guiding electrode placement.

neuroscience↗

bioRxiv2026

During natural vision, semantic novelty modulates fixation-related processing in primate cortex

We sample visual scenes with short gaze fixations separated by saccades. While low-level integration is known, semantic integration of foveal vision across fixations remains unclear. We hypothesized that the brain responds to changes in semantic information from one fixation to the next, and therefore postulated a neural signal associated with semantic novelty for each saccade. Novelty was measured from different layers of a deep network on foveal vision. Only semantic, and not low- or mid-level, novelty modulated frontal and occipital fixation-related potentials in male and female human scalp EEG during natural viewing of full-length movies (3.4x106 saccades). Intracranial recordings in male and female humans (9.0x104 saccades) and female non-human primates (Macaca mulatta; 3.3x104 saccades) revealed broadband high-frequency activity modulations in scene-specific ventral visual and frontal brain areas only for semantic novelty. This modulation was stronger for movies than static images, and frontal modulation occurred early alongside occipital modulation, suggesting top-down effects. This modulation of fixation-related activity with novelty suggests that foveal representations are integrated across fixations to construct scene representations during natural viewing in primates.

neuroscience↗

bioRxiv2026

Neural Decoding of Musical Engagement Reveals Tension-Release Dynamics

Music listening is one of the most compelling and rewarding activities humans engage in spontaneously. But what exactly catches people"s attention when listening to music remains unclear. Musicologists have argued that tension-release dynamics in music constitute crucial features of the listening experience. They arise from the intertwining of different low-level and high-level features and sit at the core of music enjoyment by engaging listeners dynamically. This study aims to characterize the relationship between tension dynamics and engagement during naturalistic music listening. Using canonical correlation analysis, we decoded the music envelope from EEG and ECoG responses and found that musical tension patterns, as reported by listeners, were predictive of fluctuations in the coupling between the music and the neural response. Importantly, tension dynamics were significantly correlated with neural measures of envelope tracking even after controlling for loudness and musical expectations, confirming the specific and crucial role of musical tension in engaging listeners. These results shed new light on how musical structure gives rise to internal response modulations that, in turn, dynamically reflect musical engagement. This interplay may underlie the pervasive and emotionally rewarding nature of music. Significance StatementThis work addresses a fundamental question in cognition: how engagement dynamically modulates complex auditory input processing. We investigate this issue within the well-controlled yet ecologically valid context of music perception. At the core of the musical experience lies the perception of tension - the shifting sense of expectancy, instability, and resolution that guides listening across time. We show that fluctuations in musical tension, shaped by musical structure, reliably predict modulations of auditory engagement, thereby illuminating an understudied phenomenon: what makes music engaging.

neuroscience↗

bioRxiv2025

Speaker Identity is Robustly Encoded in Spatial Patterns of Intracranial EEG for Attention Decoding

The human auditory cortex robustly tracks attended speech, yet it remains unclear if speaker identity is encoded in spatial patterns of neural activity independent of temporal dynamics. Here, we demonstrate that the identity of an attended speaker is reliably reflected in distinct, time-invariant spatial activation maps in human intracranial EEG (iEEG). Leveraging these "neural fingerprints", we developed a novel framework for Auditory Attention Decoding (AAD) that shifts from traditional temporal envelope tracking to spatial speaker identification. By decoupling the decoding of "who" is speaking from "when" they are speaking, our modular system achieves state-of-the-art speech extraction, particularly in short time windows (<2 seconds) where temporal models typically fail. Furthermore, we observed a reciprocal shift in neural activity during attentional switches, confirming that these spatial codes dynamically track listener intent. These findings establish that speaker identity is a robust, spatially distributed feature in the auditory cortex, offering a high-speed, complementary mechanism for neuro-steered hearing technologies.

neuroscience↗

bioRxiv2025

Large Language Models Reveal the Neural Tracking of Linguistic Context in Attended and Unattended Multi-Talker Speech

Large language models (LLMs) capture long-range contextual structure in natural language and have recently been shown to align with the human brains contextualized linguistic encoding. This makes them a promising computational probe for studying how context-dependent linguistic information is represented during natural speech perception. Speech perception often occurs in multi-talker environments, where attention must dynamically select among competing streams, yet how contextual information from attended and unattended speech is neurally encoded remains underexplored. Here, we investigate how auditory attention modulates neural tracking of context-dependent linguistic representations using electrocorticography (ECoG) and stereoelectroencephalography (sEEG) recordings from three epilepsy patients engaged in a two-conversation "cocktail party" paradigm. To model neural responses to attended and unattended speech streams, we used contextual word embeddings generated by large language models. We find that LLM-derived features reliably predict brain activity for the attended stream and that contextual information from the unattended stream also contributes to neural prediction. Importantly, these contributions extend beyond low-level acoustic features and shallow syntactic information, and depend on the surrounding linguistic context. Moreover, neural tracking of the unattended stream reflects shorter-range contextual integration than that of the attended stream. Together, these findings indicate that neural responses to speech reflect context-dependent linguistic representations from multiple concurrent speech streams, with attention modulating the depth and timescale of contextual integration. Our results highlight the utility of LLMs for probing higher-level linguistic representations in complex, naturalistic listening environments.

neuroscience↗

bioRxiv2025

Meiotic cohesion requires Sirt1 and preserving its activity in aging oocytes reduces missegregation

Chromosome segregation errors in human oocytes increase dramatically as women age and premature loss of meiotic cohesion is one factor that contributes to a higher incidence of segregation errors in older oocytes. Here we show that cohesion maintenance during meiotic prophase in Drosophila oocytes requires the NAD+-dependent deacetylase, Sirt1. Knockdown of Sirt1 during meiotic prophase causes premature loss of arm cohesion and chromosome segregation errors. We have previously demonstrated that when Drosophila oocytes arrest and age in diplotene, segregation errors increase significantly. By quantifying acetylation of the Sirt1 substrate H4K16 on oocytes chromosomes, we find that Sirt1 deacetylase activity declines markedly during aging. However, if females are fed the Sirt1 activator SRT1720 as their oocytes age, the H4K16ac signal on oocyte DNA remains low in aged oocytes, consistent with preservation of Sirt1 activity during aging. Strikingly, age-dependent segregation errors are significantly reduced if mothers are fed SRT1720 while their oocytes age. Our data suggest that maintaining Sirt1 activity in aging oocytes may provide a viable therapeutic strategy to decrease age-dependent segregation errors.

cell biology↗

bioRxiv2025

Parallel hierarchical encoding of linguistic representations in the human auditory cortex and recurrent automatic speech recognition systems

Transforming continuous acoustic speech signals into discrete linguistic meaning is a remarkable computational feat accomplished by both the human brain and modern artificial intelligence. A key scientific question is whether these biological and artificial systems, despite their different architectures, converge on similar strategies to solve this challenge. While ASR systems now achieve human-level performance, research on their parallels with the brain has been limited by biologically implausible, non-causal models and comparisons that stop at predicting brain activity without detailing the alignment of the underlying representations. Furthermore, studies using text-based models overlook the crucial acoustic stages of speech processing. Here, using high-resolution intracranial recordings and a causal, recurrent ASR model, we bridge these gaps by uncovering a striking correspondence between the brains processing hierarchy and the models internal representations. Specifically, we demonstrate a deep alignment in their algorithmic approach: neural activity in distinct cortical regions maps topographically to corresponding model layers, and critically, the representational content at each stage follows a parallel progression from acoustic to phonetic, lexical, and semantic information. This work thus moves beyond demonstrating simple model-brain alignment to specifying the shared underlying representations at each stage of processing, providing direct evidence that both systems converge on a similar computational strategy for transforming sound into meaning.

neuroscience↗

bioRxiv2024

The impact of musical expertise on disentangled and contextual neural encoding of music revealed by generative music models

Music perception involves the intricate processing of individual notes and their contextual relationships within a piece. However, how the brain encodes and organizes these features, particularly in relation to musical expertise, remains unclear. Using noninvasive and invasive electrophysiological recordings alongside generative music models, we reveal that musicians exhibit neural encoding that is more attuned to the separation and integration of complex musical structures, with a pronounced left-hemispheric bias compared to non-musicians. Invasive recordings further highlight a hierarchical and spatially organized representation of musical features and context across brain regions. These findings advance our understanding of how the brain processes music and the role of musical training in shaping auditory cognition.

neuroscience↗

bioRxiv2024

Motifs of human hippocampal and cortical high frequency oscillations structure processing and memory of naturalistic stimuli

The discrete events of our narrative experience are organized by the neural substrate that underlies episodic memory. This narrative process is segmented into discrete units by event boundaries. This permits a replay process that acts to consolidate each event into a narrative memory. High frequency oscillations (HFOs) are a potential mechanism for synchronizing neural activity during these processes. Here, we use intracranial recordings from participants viewing and freely recalling a naturalistic stimulus. We show that hippocampal HFOs increase following event boundaries and that coincident hippocampal-cortical HFOs (co-HFOs) occur in cortical regions previously shown to underlie event segmentation (inferior parietal, precuneus, lateral occipital, inferior frontal cortices). We also show that event-specific patterns of co-HFOs that occur during event viewing re-occur following the subsequent three event boundaries (in decaying fashion) and also during recall. This is consistent with models that support replay as a mechanism for memory consolidation. Hence, HFOs may coordinate activity across brain regions serving widespread event segmentation, encode naturalistic memory, and bind representations to assemble memory of a coherent, continuous experience.

neuroscience↗

bioRxiv2024

Intrinsic dynamics shape responses to external stimulation in the human brain

Sensory stimulation of the brain reverberates in its recurrent neural networks. However, current computational models of brain activity do not separate immediate sensory responses from this intrinsic dynamic. We apply a vector-autoregressive model with external input (VARX), combining the concepts of "functional connectivity" and "encoding models", to intracranial recordings in humans. This model captures the extrinsic effect of the stimulus and separates that from the intrinsic effect of the recurrent brain dynamic. We find that the intrinsic dynamic enhances and prolongs the neural responses to scene cuts, eye movements, and sounds. Failing to account for these extrinsic inputs, leads to spurious recurrent connections that govern the intrinsic dynamic. We also find that the recurrent connectivity during rest is reduced during movie watching. The model shows that an external stimulus can reduce intrinsic noise. It also shows that sensory areas have mostly outward, whereas higher-order brain areas mostly incoming connections. We conclude that the response to an external audiovisual stimulus can largely be attributed to the intrinsic dynamic of the brain, already observed during rest.

neuroscience↗

bioRxiv2024

Joint population coding and temporal coherence link an attended talker's voice and location features in naturalistic multi-talker scenes.

Listeners effortlessly extract multidimensional auditory objects, such as a localized talker, from complex acoustic scenes. However, the neural mechanisms that enable simultaneous encoding and linking of distinct sound features--such as a talkers voice and location--are not fully understood. Using invasive intracranial recordings in neurosurgical patients, we investigated how the human auditory cortex processes and integrates these features during naturalistic multi-talker scenes. We found that cortical sites exhibit a gradient of feature sensitivity, ranging from single-feature sensitive sites (responsive primarily to voice or location) to dual-feature sensitive sites (responsive to both features). At the population level, neural response patterns from both single- and dual-feature sensitive sites jointly encoded the attended talkers voice and location. Notably, single-feature sensitive sites encoded their primary feature with greater precision but also represented coarse information about the secondary feature. Sites selectively tracking a single, attended speech stream concurrently encoded both voice and location features, demonstrating a link between selective attention and feature integration. Additionally, attention selectively enhanced temporal coherence between voice- and location-sensitive sites, suggesting that temporal synchronization serves as a mechanism for linking these features. Our findings highlight two complementary neural mechanisms--joint population coding and temporal coherence-- that enable the integration of voice and location features in the auditory cortex. These results provide new insights into the distributed, multidimensional nature of auditory object formation during active listening in complex environments. SIGNIFICANCE STATEMENTIn everyday life, listeners effortlessly extract individual sound sources from complex acoustic scenes which contain multiple sound sources. Yet, how the brain links the different features of a particular sound source to each other - such as a talkers voice characteristics and location - is poorly understood. Here, we show that two neural mechanisms contribute to encoding and integrating voice and location features in multi-talker sound scenes: (1) some neuronal sites are sensitive to both voice and location and their activity patterns encode these features jointly; (2) the responses of neuronal sites that process only one sound feature - that is, location or voice - align temporally to form a stream that is segregated from the other talker. HIGHLIGHTSO_LIAuditory cortex exhibits a gradient of feature sensitivity, with some sites encoding only voice or location features, while others encode both simultaneously (dual-feature sensitive sites). C_LIO_LIDual-feature sensitive sites integrate voice and location features of an attended talker with equal accuracy, providing a unified representation in multi-talker scenes. C_LIO_LISingle-feature sensitive sites primarily encode their preferred feature with high precision but also represent coarse information about other features, contributing to population-level integration. C_LIO_LITemporal coherence selectively enhances synchronization between voice- and location-sensitive sites, providing another mechanism for integrating an auditory objects features. C_LIO_LIMulti-dimensional auditory object formation relies on complementary neural mechanisms: joint population coding and temporal coherence. C_LI

neuroscience↗

bioRxiv2024

Hippocampal sharp wave ripples and coincident cortical ripples orchestrate human semantic networks

Episodic memory function is predicated upon the precise coordination between the hippocampus and widespread cortical regions. However, our understanding of the neural mechanisms involved in this process is incomplete. In this study, human subjects undergoing intracranial electroencephalography (iEEG) monitoring performed a list learning task. We show sharp-wave ripple (SWR)-locked reactivation of specific semantic processing regions during free recall. This cortical activation consists of both broadband high frequency (non-oscillatory) and cortical ripple (oscillatory) activity. SWRs and cortical ripples in the anterior temporal lobe, a major semantic hub, co-occur and increase in rate prior to recall. Coincident hippocampal-ATL ripples are associated with a greater increase in cortical reactivation, show specificity in location based on recall content, and are preceded by cortical theta oscillations. These findings may represent a reactivation of hippocampus and cortical semantic regions orchestrated by an interplay between hippocampal SWRs, cortical ripples, and theta oscillations.

neuroscience↗

bioRxiv2024

Brain-controlled augmented hearing for spatially moving conversations in multi-talker environments

Focusing on a specific conversation amidst multiple interfering talkers presents a significant challenge, especially for the hearing-impaired. Brain-controlled assistive hearing devices aim to alleviate this problem by separating complex auditory scenes into distinct speech streams and enhancing the attended speech based on the listeners neural signals using auditory attention decoding (AAD). Departing from conventional AAD studies that relied on oversimplified scenarios with stationary talkers, we present a realistic AAD task that mirrors the dynamic nature of acoustic settings. This task involves focusing on one of two concurrent conversations, with multiple talkers taking turns and moving continuously in space with background noise. Invasive electroencephalography (iEEG) data were collected from three neurosurgical patients as they focused on one of the two moving conversations. We propose an enhanced brain-controlled assistive hearing system that combines AAD and a binaural speaker-independent speech separation model. The separation model unmixes talkers while preserving their spatial location and provides talker trajectories to the neural decoder to improve auditory attention decoding accuracy. Our subjective and objective evaluations show that the proposed system enhances speech intelligibility and facilitates conversation tracking while maintaining spatial cues and voice quality in challenging acoustic environments. This research demonstrates the potential of our approach in real-world scenarios and marks a significant step towards developing assistive hearing technologies that adapt to the intricate dynamics of everyday auditory experiences. TAKEAWAYS- Brain-controlled hearing device for scenarios with moving conversations in multi-talker settings, closely mimicking real-world listening environments - Developed a binaural speech separation model that separates speech of moving talkers while retaining their spatial locations, enhancing auditory perception and auditory attention decoding - Proposed system enhances speech intelligibility and reduces listening effort in realistic acoustic scenes

neuroscience↗

bioRxiv2023

Intracranial electroencephalography reveals effector-independent evidence accumulation dynamics in multiple human brain regions

Neural representations of perceptual decision formation that are abstracted from specific motor requirements have previously been identified in humans using non-invasive electrophysiology, however, it is currently unclear where these originate in the brain. Here, we capitalized on the high spatiotemporal precision of intracranial EEG to localize such abstract decision signals. Presurgical epilepsy patients judged the direction of random-dot stimuli and responded either with a speeded button press (N=23), or vocally, after a randomized delay (N=11). We found a widely distributed motor-independent network of regions where high-frequency activity exhibited key characteristics consistent with evidence accumulation, including a gradual build-up that was modulated by the strength of the sensory evidence, and an amplitude that predicted subjects choice accuracy and response time. Our findings offer a new view on the brain networks governing human decision making.

neuroscience↗

bioRxiv2023

The neural activity of auditory conscious perception

Although recent work has made significant headway in understanding the temporal and spatial dynamics of the neural mechanisms of conscious perception, much of that work has focused on visual paradigms. To determine whether there are shared mechanisms for perceptual consciousness across sensory modalities, here we developed a task to test within the auditory domain. Participants (n=31) completed an auditory perceptual threshold task while undergoing intracranial electroencephalography (icEEG) for intractable epilepsy. Intracranial recordings from over 2,800 grey matter electrodes representing widespread cortical coverage were analyzed for power in the high gamma range (40-115 Hz)--a frequency range that reflects local neural activity. For trials that were perceived, we find activity in early auditory regions which is accompanied by activity in the right caudal middle frontal gyrus, and shortly thereafter by activity in non-auditory thalamus. This is followed by a wave of activity that sweeps through the higher auditory association regions and into parietal and frontal cortices, similar to the wave observed in our visual conscious perception paradigm. However, for not perceived trials, we find that significant activity is restricted to early auditory regions (and areas immediately adjacent to the Sylvian fissure). These findings show that the broad anatomical regions of cortical and subcortical networks involved in auditory perception are similar to the networks observed with vision, suggesting shared general mechanisms for conscious perception.

neuroscience↗

bioRxiv2022

Semantic novelty modulates neural responses to visual change across the human brain

Our continuous visual experience in daily life is dominated by change. Previous research has focused on visual change due to stimulus motion, eye movements or unfolding events, but not their combined impact across the brain, or their interactions with semantic novelty. We investigate the neural responses to these sources of novelty during film viewing. We analyzed intracranial recordings in humans across 6328 electrodes from 23 individuals. Responses associated with saccades and film cuts were dominant across the entire brain. Film cuts at semantic event boundaries were particularly effective in the temporal and medial temporal lobe. Saccades to visual targets with high visual novelty were also associated with strong neural responses. Specific locations in higher-order association areas showed selectivity to either high or low-novelty saccades. We conclude that neural activity associated with film cuts and eye movements is widespread across the brain and is modulated by semantic novelty.

neuroscience↗