Biology subjects

Herbst, S. K.

Publications and source records attributed to Herbst, S. K..

7 recordsLinked to original sources

bioRxiv2026

Synergistic yet dissociable roles of temporal and spectral predictions in auditory detection

Predictive processing enables the brain to anticipate both when and what sensory events will occur. Although temporal and spectral predictions are both known to facilitate perception, their functional contributions and interaction remain poorly understood, particularly in uncertain listening conditions where predictions must be inferred from implicit statistical regularities rather than explicit cues or rhythms. Here, we orthogonalized temporal and spectral predictability in a non-rhythmic auditory detection task and used a signal-detection framework to dissociate perceptual and decisional processes in humans of either sex. Temporal predictions primarily increased response readiness: predictable target timing led to faster responses and more hits but also more false alarms, reflecting a liberal shift in response bias. Spectral predictions, in contrast, selectively enhanced perceptual sensitivity without a comparable speeding of responses. Crucially, despite their distinct behavioral effects, temporal and spectral predictions interacted synergistically, such that perceptual sensitivity was greatest when both sound timing and frequency were predictable, consistent with a spectrotemporal filter mechanism. Furthermore, temporal and spectral variability were encoded differently: performance adapted strongly to the distribution of foreperiod durations but remained largely stable across the spectral distribution, suggesting that the brain exploits temporal and spectral statistics in distinct ways when forming predictions under uncertainty. Together, these findings demonstrate that temporal and spectral predictions make complementary contributions to auditory decision-making, interact synergistically to improve perceptual sensitivity, and rely on distinct encoding strategies for temporal and spectral variability.

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bioRxiv2025

Alpha power indexes working memory load for durations

Timing, that is estimating, comparing, or remembering how long events last, requires the temporary storage of durations. How durations are stored in working memory is unknown, despite the widely held view of memory systems central role in timing. Here, we investigated the neural signatures of a sequence of durations (n-item sequence) held in working memory. We recorded human participants using magnetoencephalography (MEG) while they performed an n-item delayed reproduction task, which required to encode a sequence of durations, maintain it, and then reproduce it. The number of items in a sequence (one or three) and the duration of the sequence were orthogonalized. Our results show that during working memory maintenance, the number of durations, not the duration of the sequence, affected recall precision and could be decoded from alpha and beta oscillatory activity. Parieto-occipital alpha power showed a direct link with the precision of temporal reproduction. Our results extend earlier behavioral findings suggesting that durations are itemized in working memory and that their number, not their duration, modulates recall precision (Herbst et al., 2025). Crucially, we establish that alpha power reflects a universal signature of working memory load and mediates recall precision, even for abstract information such as duration.

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bioRxiv2022

Characterizing endogenous delta oscillations non-invasively in humans

Rhythmic activity in the delta frequency range (0.5 - 3 Hz) is a prominent feature of brain dynamics. Here, we examined whether spontaneous delta oscillations, as found in invasive recordings in awake animals, can be observed in non-invasive recordings pewwrformed in humans with magnetoencephalography (MEG). In humans, delta activity is commonly reported when processing rhythmic sensory inputs, with direct relationships to behaviour. However, rhythmic brain dynamics observed during rhythmic sensory stimulation cannot be interpreted as an endogenous oscillation. To test for endogenous delta oscillations we analysed human MEG data during rest. For comparison, we additionally analysed two conditions in which participants engaged in spontaneous finger tapping and silent counting, arguing that internally rhythmic behaviours could incite an otherwise silent neural oscillator. A novel set of analysis steps allowed us to show narrow spectral peaks in the delta frequency range in rest, and during overt and covert rhythmic activity. Additional analyses in the time domain revealed that only the resting state condition warranted an interpretation of these peaks as endogenously periodic neural dynamics. In sum, this work shows that using advanced signal processing techniques, it is possible to observe endogenous delta oscillations in non-invasive recordings of human brain dynamics.

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bioRxiv2022

Implicit versus explicit timing - separate or shared mechanisms?

AO_SCPLOWBSTRACTC_SCPLOWTime implicitly shapes cognition, but time is also explicitly represented, for instance in the form of durations. Parsimoniously, the brain could use the same mechanisms for implicit and explicit timing. Yet, the evidence has been equivocal, revealing both joint versus separate signatures of timing. Here, we directly compared implicit and explicit timing using magnetoencephalography, whose temporal resolution allows investigating the different stages of the timing processes. Implicit temporal predictability was induced in an auditory paradigm by a manipulation of the foreperiod. Participants received two consecutive task instructions: discriminate pitch (indirect measure of implicit timing) or duration (direct measure of explicit timing). The results show that the human brain efficiently extracts implicit temporal statistics of sensory environments, to enhance the behavioral and neural responses to auditory stimuli, but that those temporal predictions did not improve explicit timing. In both tasks, attentional orienting in time during predictive foreperiods was indexed by an increase in alpha power over visual and parietal areas. Furthermore, pre-target induced beta power in sensorimotor and parietal areas increased during implicit compared to explicit timing, in line with the suggested role for beta oscillations in temporal prediction. Interestingly, no distinct neural dynamics emerged when participants explicitly paid attention to time, compared to implicit timing. Our work thus indicates that implicit timing shapes the behavioral and sensory response in an automatic way, and is reflected in oscillatory neural dynamics, while the translation of implicit temporal statistics to explicit durations remains somewhat inconclusive, possibly due to the more abstract nature of this task.

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bioRxiv2018

Implicit temporal predictability biases slow oscillatory phase in auditory cortex and enhances pitch discrimination sensitivity

Can human listeners use strictly implicit temporal contingencies in auditory input to form temporal predictions, and if so, how are these predictions represented endogenously? To assess this question, we implicitly manipulated foreperiods in an auditory pitch discrimination task. Unbeknownst to participants, the pitch of the standard tone could either be deterministically predictive of the onset of the target tone, or convey no predictive information. Both conditions were presented interleaved in one stream, and separated by variable inter-stimulus intervals such that there was no dominant stimulus rhythm throughout. Even though participants were unaware of the implicit temporal contingencies, pitch discrimination sensitivity (i.e. the slope of the psychometric function) increased when the onset of the target tone was predictable in time (N = 49). Concurrently recorded EEG data (N = 24) revealed that standard tones which initiated temporal predictions evoked a more negative N1 component than non-predictive standards, and were followed by an increase in delta power during the foreperiod. Furthermore, the phase angle of delta oscillations (1-3Hz) evoked by the standard tone predicted pitch discrimination sensitivity at the target tone (1.75 s later on average), which suggests that temporal predictions can be initiated by an optimized delta phase reset. In sum, we show that auditory perception benefits from implicit temporal contingencies, and provide evidence for a role of slow neural oscillations in the endogenous representation of temporal predictions, in absence of exogenously driven entrainment to rhythmic input. Significance StatementTemporal contingencies are ubiquitous in sensory environments, especially in the auditory domain, and have been shown to facilitate perception and action. Yet, how these contingencies in exogenous inputs are transformed into an endogenous representation of temporal predictions is not known. Here, we implicitly induced temporal predictability in the absence of a rhythmic input structure, that is without exogenously driven entrainment of neural oscillations. Our results show that even implicit and non-rhythmic temporal predictions are extracted and used by human observers, underlining the role of timing in sensory processing. Furthermore, our EEG results point towards an instrumental role of delta oscillations in initiating temporal predictions by an optimized phase reset in response to a temporally predictive cue.

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bioRxiv2017

Unfolding of a noise-invariant neural representation of attended speech

Listening requires selective neural processing of the incoming sound mixture, which in humans is borne out by a surprisingly clean representation of attended-only speech in auditory cortex. How this neural selectivity is achieved even at negative signal-to-noise ratios (SNR) remains unclear. We show that, under such conditions, a late cortical representation (i.e., neural tracking) of the ignored acoustic signal is key to successful separation of attended and distracting talkers (i.e., neural selectivity). We recorded and modelled the electroencephalographic response of 18 participants who attended to one of two simultaneously presented stories, while the SNR between the two talkers varied dynamically. The neural tracking showed an increasing early-to-late attention-biased selectivity. Importantly, acoustically dominant ignored talkers were tracked neurally by late involvement of fronto-parietal regions, which contributed to enhanced neural selectivity. This neural selectivity by way of representing the ignored talker poses a mechanistic neural account of attention under real-life acoustic conditions.

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bioRxiv2017

Tracking temporal hazard in the human electroencephalogram using a forward encoding model

Human observers automatically extract temporal contingencies from the environment and predict the onset of future events. Temporal predictions are modelled by the hazard function, which describes the instantaneous probability for an event to occur given it has not occurred yet. Here, we tackle the question of whether and how the human brain tracks continuous temporal hazard on a moment-to-moment basis, and how flexibly it adjusts to strictly implicit variations in the hazard function. We applied an encoding-model approach to human electroencephalographic (EEG) data recorded during a pitch-discrimination task, in which we implicitly manipulated temporal predictability of the target tones by varying the interval between cue and target tone (the foreperiod). Critically, temporal predictability was either solely driven by the passage of time (resulting in a monotonic hazard function), or was modulated to increase at intermediate foreperiods (resulting in a modulated hazard function with a peak at the intermediate foreperiod). Forward encoding models trained to predict the recorded EEG signal from different temporal hazard functions were able to distinguish between experimental conditions, showing that implicit variations of temporal hazard bear tractable signatures in the human electroencephalogram. Notably, this tracking signal was reconstructed best from the supplementary motor area (SMA), underlining this areas link to cognitive processing of time. Our results underline the relevance of temporal hazard to cognitive processing, and show that the predictive accuracy of the encoding-model approach can be utilised to track abstract time-resolved stimuli.\n\nSignificance StatementExtracting temporal predictions from sensory input allows to process future input more efficiently and to prepare responses in time. In mathematical terms, temporal predictions can be described by the hazard function, modelling the probability of an event to occur over time. Here, we show that the human EEG tracks temporal hazard in an implicit foreperiod paradigm. Forward encoding models trained to predict the recorded EEG signal from different temporal-hazard functions were able to distinguish between experimental conditions that differed in their build-up of hazard over time. These neural signatures of tracking temporal hazard converge with the extant literature on temporal processing and provide new evidence that the supplementary motor area tracks hazard under strictly implicit timing conditions.

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