Biology subjects

Baumgartner, R.

Publications and source records attributed to Baumgartner, R..

10 recordsLinked to original sources

bioRxiv2025

Common marmosets (Callithrix jacchus) do not differentiate between familiar and unfamiliar conspecifics based on pitch contour information

Previous studies suggest that vocal-learning species use variations of prosodic cues, such as changes in pitch, amplitude, or duration, in the conveying of meaning and emotions as well as individual recognition. Although it is known that the long-distance contact calls ("phee" calls) of common marmosets, a vocal non-learner, vary in prosodic information depending on individual characteristics, evidence of the species use of this information only recently started to emerge. In this study we tested 18 captive common marmosets (Callithrix jacchus) reactions to playbacks of familiar and unfamiliar individuals phee calls and extracted pitch-contour information. The playbacks consisted of i) natural phee calls from group members or unfamiliar conspecifics, or ii) synthesized pitch contours of familiar or unfamiliar phee calls following a natural or artificial syllable order as well as pure tones of similar frequency and duration. We found that although individuals seemed to show different reactions towards the natural calls of familiar and unfamiliar individuals, we did not find group level differences. Marmosets furthermore show significantly reduced interest in synthesized pitch contours compared to natural phee calls and did not differentiate between pitch contour playbacks and pure tone control stimuli, indicating that they did not categorize the pitch contours as conspecific calls. Our results suggest that extracted pitch contour information alone is not sufficient for marmosets to recognise conspecifics, however further studies are required to investigate the exact mechanism of individual recognition in marmosets.

animal behavior and cognition↗

bioRxiv2025

Arousal-related mediation of perceptual belief updating across auditory domains

Belief updating refers to the integration of prior beliefs with incoming evidence and guides decision-making under uncertainty. In response to surprising events, this process is thought to be modulated by the locus-coeruleus-noradrenaline (LC-NA) arousal system, observable via pupil dilations (PDs). Pertinent literature has mostly focused on conscious, high-level decision-making and estimation processes, while assuming that the same principles apply to low-level sensory perceptual decision-making and generalize across tasks, domains and modalities. To address some of these assumptions, we devised a novel perceptual discrimination paradigm, investigating behavior and PDs across auditory domains. Participants were presented with auditory sequences of randomized length at a rapid pace, changing intermittently between two latent states: acceleration vs. deceleration (temporal group, N = 25) and clockwise vs. counterclockwise movement (spatial group, N = 22). Under high uncertainty, participants continuously inferred latent states to report the final state per sequence. To extract per-stimulus estimates of PDs during sequences, we fitted a deconvolution-based general linear model to the continuous pupil traces with a free amplitude parameter reflecting ongoing PDs. A Bayesian observer model was fitted to participants responses and used to estimate information gain and surprisal for every stimulus. Participants performance and PDs showed strong sensitivity to the occurrence of change-points. Both computational variables significantly predicted PDs in both domains, with information gain outperforming surprisal in a model comparison. Further model comparison revealed significant preference for models excluding possible domain-specific effects over models including them, pointing towards a constant effect over domains. We conclude that behavior and associated PDs observed in our purely perceptual auditory task align with Bayesian principles of belief updating. The observed lack of domain specificity supports the assumed generalizability of belief updating.

neuroscience↗

bioRxiv2024

Temporal expectations modulate coupling between frontal and sensory brain areas

Temporal prediction enhances perceptual processing by aligning neural excitability with expected sensory events. While local oscillatory mechanisms are known to support timing, less is understood about how large-scale functional brain networks dynamically coordinate predictive processes. In particular, it remains unclear how functional connectivity (FC)--the integration of information into network hubs--differs during expectation formation (post-cue) versus outcome evaluation (post-target), and how this varies across levels of predictability. To investigate this, we recorded electroencephalogram (EEG) while participants performed a cued auditory target-detection task with varying temporal predictability (80% and 50%). Event-related potential (ERP) results revealed that implicit temporal predictability primarily modulated later evaluative processes (P3b, frontal negativity), rather than early sensory components, consistent with context updating under uncertainty. FC was analyzed using a data-driven approach based on Normalized Directed Transfer Entropy (NDTE) applied to EEG difference waveforms between high- and low-predictability conditions. Connectivity was examined separately for the post-cue and post-target periods to distinguish prediction and evaluation phases. Behaviorally, higher temporal predictability facilitated faster reaction times. Connectivity analyses revealed largely overlapping but somewhat distinct network dynamics for prediction and evaluation phases of the signal processing.

neuroscience↗

bioRxiv2024

How relevant is the prior? Bayesian causal inference for dynamic perception in volatile environments

Interpreting sensory prediction errors can be challenging in volatile environments because they can be caused by stochastic noise or by outdated predictions. Noisy signals should be integrated with prior beliefs to improve precision, but the two should be segregated when environmental changes render prior beliefs irrelevant. Bayesian causal inference provides a statistically optimal solution to deal with uncertainty about the causes of prediction errors. However, the method quickly becomes memory intensive and computationally intractable when applied sequentially. Here, we systematically evaluate the predictive performance of Bayesian causal inference for perceptual decisions in a spatial prediction task based on noisy audiovisual sequences with occasional changepoints. We elucidate the simplifying assumptions of a previously proposed reduced Bayesian observer model, and we compare it to an extensive set of models based on alternative simplification strategies. Model-free analyses revealed the hallmarks of Bayesian causal inference: participants seem to have integrated sensory evidence with prior beliefs to improve accuracy when prediction errors were small, but prior influence decreased gradually as prediction errors increased, signalling probable irrelevance of the priors due to changepoints. Model comparison results indicated that participants computed probability-weighted averages over the causal options (noise or changepoint), akin to the reduced Bayesian observer model. However, participants reliance on prior beliefs was systematically smaller than expected, and this was best explained by individually fitting lower-than-optimal parameters for the a-priori probability of prior relevance. We conclude that perceptual decision makers utilize priors flexibly to the extent that they are deemed relevant, though also conservatively with a lower tendency to bind than ideal observers. Simplified consecutive Bayesian causal inference predicts key characteristics of belief updating in changepoint environments and forms a suitable foundation for modelling dynamic perception in a changing world.

neuroscience↗

bioRxiv2024

Bayesian Prior Uncertainty and Surprisal Elicit Distinct Neural Patterns During Sound Localization in Dynamic Environments

Estimating the location of a stimulus is a key function in sensory processing, and widely considered to result from the integration of prior information and sensory input according to Bayesian principles. A deviation of sensory input from the prior elicits surprisal, depending on the uncertainty of the prior. While this mechanism is increasingly understood in the visual domain, much less is known about its implementation in audition, especially regarding spatial localization. Here, we combined human EEG with computational modeling to study auditory spatial inference in a noisy, volatile environment and analyzed behavioral and neural patterns associated with prior uncertainty and surprisal. First, our results demonstrate that participants indeed used prior information during periods of stable environmental statistics, but showed evidence of surprisal and discarded prior information following environmental changes. Second, we observed distinct EEG activity patterns associated with prior uncertainty and surprisal in both the time- and time-frequency domain, which are in line with previous studies using visual tasks. Third, these EEG activity patterns were predictive of our participants sound localization error, response uncertainty, and prior bias on a trial-by-trial basis. In summary, our work provides novel behavioral and neural evidence for Bayesian inference during dynamic auditory localization.

neuroscience↗

bioRxiv2024

Threat-Related Corticocortical Connectivity Elicited by Rapid Auditory Looms

While sounds of approaching objects are generally more salient than those of receding ones, the traditional association of this auditory looming bias with threat perception is subject to debate. Differences between looming and receding sounds may also be learned through non-threatening multisensory information, or influenced by confounding stimulus characteristics. To investigate, we analyzed corticocortical connectivity patterns from electroencephalography, examining the preferential processing of looming sounds under different attentional states. To simulate rapid distance changes we used complementary distance cues, previously studied in the looming bias literature. Notably, despite the absence of conscious threat perception, we observed crucial involvement of frontal cortical regions typically associated with threat and fear responses. Our findings suggest an underlying bias towards the ventral what stream over the dorsal where stream in auditory information processing, even when the participants task was solely focused on the discrimination of movement direction. These results support the idea, that the perceptual bias towards looming sounds reflects an auditory threat detection mechanism, while offering insights into the neural function involved in processing ecologically relevant environmental cues.

neuroscience↗

bioRxiv2022

A Bayesian model for human directional localization of broadband and static sound sources

Humans estimate sound-source directions by combining prior beliefs with sensory evidence. Prior beliefs represent statistical knowledge about the environment while sensory evidence is acquired from auditory features such as interaural disparities and monaural spectral shapes. Models of directional sound localization often impose constraints on the contribution of these features to either the horizontal or vertical dimension. Instead, we propose a Bayesian model that more flexibly incorporates each feature according to its spatial precision and integrates prior beliefs in the inference process. We applied the model to directional localization of a single, broadband, stationary sound source presented to a static human listener in an anechoic environment. We simplified interaural features to be broadband and compared two model variants, each considering a different type of monaural spectral features: magnitude profiles and gradient profiles. Both model variants were fitted to the baseline performance of five listeners and evaluated on the effects of localizing with non-individual head-related transfer functions (HRTFs) and sounds with rippled spectrum. The model variant with spectral gradient profiles outperformed other localization models. This model variant appears particularly useful for the evaluation of HRTFs and may serve as a basis for future extensions towards modeling dynamic listening conditions.

neuroscience↗

bioRxiv2022

Benefits of individualized brain anatomies and EEG electrode positions for auditory cortex localization

Due to its high temporal resolution and non-invasive nature, electroencephalography (EEG) is considered a method of great value for the field of auditory cognitive neuroscience. In performing source space analyses, localization accuracy poses a bottleneck, which precise forward models based on individualized attributes such as subject anatomy or electrode locations aim to overcome. Yet acquiring anatomical images or localizing EEG electrodes requires significant additional funds and processing time, making it an oftentimes inaccessible asset. Neuroscientific software offers template solutions, on which analyses can be based. For localizing the source of auditory evoked responses, we here compared the results of employing such template anatomies and electrode positions versus the subject-specific ones, as well as combinations of the two. All considered cases represented approaches commonly used in electrophysiological studies. We considered differences between two commonly used inverse solutions (dSPM, sLORETA) and targeted the primary auditory cortex; a notoriously small cortical region that is located within the lateral sulcus, thus more prone to errors in localization. Through systematical comparison of the outcomes in terms of auditory activity attributes and leakage quantification, we assessed how the individualization steps impacted the analyses outcomes. Both electrode locations as well as subject anatomies were found to have an effect, which though varied based on the configuration considered. When comparing the inverse solutions, we moreover found that dSPM more consistently benefited from individualization of subject characteristics. Based on the scientific question considered, our results may be used to facilitate the planning of auditory neuroscientific experiments in terms of expected infrastructure, personnel and funds.

neuroscience↗

bioRxiv2020

Decision making in auditory externalization perception

Under natural conditions, listeners perceptually attribute sounds to external objects in their environment. This core function of perceptual inference is often distorted when sounds are produced via hearing devices such as headphones or hearing aids, resulting in sources being perceived unrealistically close or even inside the head. Psychoacoustic studies suggest a mixed role of various monaural and interaural cues contributing to the externalization process. We developed a model framework for perceptual externalization able to probe the contribution of cue-specific expectation errors and to contrast dynamic versus static strategies for combining those errors within static listening environments. Effects of reverberation and visual information were not considered. The model was applied to various acoustic distortions as tested under various spatially static conditions in five previous experiments. Most accurate predictions were obtained for the combination of monaural and interaural spectral cues with a fixed relative weighting (approximately 60% of monaural and 40% of interaural). That model version was able to reproduce the externalization rating of the five experiments with an average error of 12% (relative to the full rating scale). Further, our results suggest that auditory externalization in spatially static listening situations underlie a fixed weighting of monaural and interaural spectral cues, rather than a dynamic selection of those auditory cues.

neuroscience↗

bioRxiv2019

Impoverished auditory cues fail to engage brain networks controlling spatial selective attention

Spatial selective attention enables listeners to process a signal of interest in natural settings. However, most past studies on auditory spatial attention used impoverished spatial cues: presenting competing sounds to different ears, using only interaural differences in time (ITDs) and/or intensity (IIDs), or using non-individualized head-related transfer functions (HRTFs). Here we tested the hypothesis that impoverished spatial cues impair spatial auditory attention by only weakly engaging relevant cortical networks. Eighteen normal-hearing listeners reported the content of one of two competing syllable streams simulated at roughly +30 {degrees} and -30{degrees} azimuth. The competing streams consisted of syllables from two different-sex talkers. Spatialization was based on natural spatial cues (individualized HRTFs), individualized IIDs, or generic ITDs. We measured behavioral performance as well as electroencephalographic markers of selective attention. Behaviorally, subjects recalled target streams most accurately with natural cues. Neurally, spatial attention significantly modulated early evoked sensory response magnitudes only for natural cues, not in conditions using only ITDs or IIDs. Consistent with this, parietal oscillatory power in the alpha band (8-14 Hz; associated with filtering out distracting events from unattended directions) showed significantly less attentional modulation with isolated spatial cues than with natural cues. Our findings support the hypothesis that spatial selective attention networks are only partially engaged by impoverished spatial auditory cues. These results not only suggest that studies using unnatural spatial cues underestimate the neural effects of spatial auditory attention, they also illustrate the importance of preserving natural spatial cues in assistive listening devices to support robust attentional control.

neuroscience↗