Biology subjects

Kotz, S. A.

Publications and source records attributed to Kotz, S. A..

At least 37 records · Page 2Linked to original sources

bioRxiv2023

Parallel EEG assessment of different sound predictability levels in tinnitus

ObjectiveTinnitus denotes perception of a non-environmental sound and might result from aberrant auditory prediction. Successful prediction of formal (e.g. type) and temporal sound characteristics facilitates the filtering of irrelevant information ("sensory gating", SG). Here, we explored if and how parallel manipulations of formal and temporal predictability affect sensory gating in persons with and without tinnitus. MethodsAge-, education- and sex-matched persons with and without tinnitus (N = 52) participated and listened to paired-tone "oddball" sequences, varying in formal (standard vs. deviant pitch) and temporal predictability (isochronous vs. random timing). EEG was recorded from 128 channels and data were analyzed by means of temporal spatial principal component analysis (tsPCA). ResultsSG was observed in P50- and N100-like activity (amplitude suppression for the 2nd tone in the pair) in both timing conditions and groups. Correspondingly, deviants elicited overall larger amplitudes than standards. However, only in persons without tinnitus N100-like activity in response to deviants was enhanced with isochronous relative to random timing. ConclusionsPersons with tinnitus do not benefit similarly as persons without tinnitus from temporally predictable context in deviance processing. SignificanceThe current results indicate altered temporal sensitivity and selective attention allocation in persons with tinnitus. Highlights- Persons with tinnitus display altered auditory predictions affecting the processing of unexpected auditory input - Position predictions did not differ between persons with tinnitus and without - Temporal predictability facilitated deviance processing for P50-like activity in persons with tinnitus and without

neuroscience↗

bioRxiv2023

Mobile version of the Battery for the Assessment of Auditory Sensorimotor and Timing Abilities (BAASTA): Implementation and adult norms

Timing and rhythm abilities are complex and multidimensional skills that are highly widespread in the general population. This complexity can be partly captured by the Battery for the Assessment of Auditory Sensorimotor and Timing Abilities (BAASTA). The battery, consisting of 4 perceptual and 5 sensorimotor tests (finger tapping), has been used in healthy adults and in clinical populations (e.g., Parkinsons disease, ADHD, developmental dyslexia, stuttering), and shows sensitivity to individual differences and impairment. However, major limitations for the generalized use of this tool are the lack of reliable and standardized norms and of a version of the battery that can be used outside the lab. To circumvent these caveats we put forward a new version of BAASTA on a tablet device capable of ensuring lab-equivalent measurements of timing and rhythm abilities. We present normative data obtained with this version of BAASTA from over 100 healthy adults between the ages of 18 and 87 years in a test-retest protocol. Moreover, we propose a new composite score to summarize beat-based rhythm capacities, the Beat Tracking Index (BTI), with close to excellent test-retest reliability. BTI derives from two BAASTA tests (beat alignment, paced tapping), and offers a swift and practical way of measuring rhythmic abilities when research imposes strong time constraints. This mobile BAASTA implementation is more inclusive and far-reaching, while opening new possibilities for reliable remote testing of rhythmic abilities by leveraging accessible and cost-efficient technologies.

neuroscience↗

bioRxiv2023

Challenging age-related decline in brain function: Evidence from fast neuroimaging of musical sequence recognition

Aging is often associated with decline in brain processing power and neural predictive capabilities. To challenge this notion, we used the excellent temporal resolution of magnetoencephalography (MEG) to record the whole-brain activity of 39 older adults (over 60 years old) and 37 young adults (aged 18-25 years) during recognition of previously memorised and novel musical sequences. Our results demonstrate that independent of behavioural measures, older compared to young adults showed increased rapid auditory cortex responses (around 100 and 250 ms after each tone of the sequence) and decreased later responses (around 250 and 350 ms) in hippocampus, ventromedial prefrontal cortex and inferior frontal gyrus. Working memory abilities were associated with stronger brain activity for both young and older adults. Our findings unpick the complexity of the healthy aging brain, showing age-related neural transformations in predictive and memory processes and challenging simplistic notions that non-pathological aging merely diminishes neural predictive capabilities.

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bioRxiv2023

EEG resting state alpha dynamics predict individual proneness to auditory hallucinations

IntroductionAuditory verbal hallucinations (AVH) are a transdiagnostic phenomenon but also occur in the general population. The disposition to experience AVH is considered a continuous expression from non-clinical to clinical hallucination proneness (HP). Currently, little is known about the neurophysiology of the non-clinical HP part of the continuum. AVH might result from a heightened sensitivity to sensory inputs and a decreased ability to differentiate between externally and internally generated input. Resting state (RS) alpha band activity is associated with perceptual sensitivity, attentional shifts, and cognitive control. Accordingly, spontaneous alpha fluctuations might present as a HP correlate. To investigate the time-varying dynamics of alpha band activity, we deployed a novel method for brain state allocation. MethodsWe recorded RS electroencephalography (EEG) data from 33 individuals with varying levels of HP but without clinically relevant hallucinations and used a Hidden Semi-Markov Model (HsMM) to identify five recurrent alpha states with unique temporal dynamics and topographies. The states mean duration and occupancy were analyzed as a function of HP. The sources of each state were reconstructed to identify the most active brain areas and their correspondence with known resting state networks. ResultsOccupancy and mean duration of a state corresponding to sensorimotor, auditory, and default-mode network (DMN) areas significantly predicted auditory and auditory-verbal HP, but not general HP. The temporal dynamics of all other states did not relate to HP. ConclusionAlpha brain state sources align with prior results on the role of the alpha in the DMN. The temporal dynamics of alpha might reflect individual differences for attentional biases to internally generated sensory events and altered auditory perceptual sensitivity. Thus, changes in the temporal brain state dynamics of RS alpha oscillations could present as a neural marker of increased vulnerability to auditory hallucinatory experiences.

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bioRxiv2023

Modeling EEG Resting-State Brain Dynamics: A proof of concept for clinical studies

Functional brain imaging has shown that the awake brain, independent of a task, spontaneously switches between a small set of functional networks. How useful this dynamical view of brain activity is for clinical studies, e.g., as early markers of subsequent structural and/or functional change or for assessing successful training or intervention effects, remains unclear. Core to addressing this question is to assess the robustness and reproducibility of the analysis methods that model, characterize, or infer the features of brain dynamics, and the accuracy by which these features represent and classify specific cognitive or altered cognitive states. This is particularly key given inter- and intra-individual variability and measurement noise. Here we used resting-state EEG from persons with Parkinsons Disease (PD) and healthy matched controls to systematically assess the reliability, robustness, and sensitivity of Hidden semi-Markov models (HsMM). These models are an example of model-based probabilistic methods for Brain-State allocations that are estimated from observed data. The method estimates model parameters, if the M/EEG recording or observations, over the scale of minutes, are emissions from hidden states that persist over short durations, before switching or transitioning to other states. We introduce an analysis pipeline that leads to sets of reproducible features of neurophysiological dynamics at the individual level. These features can be used as discriminatory variables to classify individuals and to evaluate the effect of non-pharmacological training schemes like in the current example a music-gait exercise program for Parkinsons Disease. Given the method stochasticity and the data variability, we emphasize the importance of repeating the analysis to reliably identify brain states and their dynamical trajectories that subsequently can be related to individualized variables.

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bioRxiv2023

Unravelling individual rhythmic abilities using machine learning

Humans can easily extract the rhythm of a complex sound, like music, and move to its regular beat, for example in dance. These abilities are modulated by musical training and vary significantly in untrained individuals. The causes of this variability are multidimensional and typically hard to grasp with single tasks. To date we lack a comprehensive model capturing the rhythmic fingerprints of both musicians and non-musicians. Here we harnessed machine learning to extract a parsimonious model of rhythmic abilities, based on the behavioral testing (with perceptual and motor tasks) of individuals with and without formal musical training (n = 79). We demonstrate that the variability of rhythmic abilities, and their link with formal and informal music experience, can be successfully captured by profiles including a minimal set of behavioral measures. These profiles can shed light on individual variability in healthy and clinical populations, and provide guidelines for personalizing rhythm-based interventions.

bioinformatics↗

bioRxiv2023

The syntax-meter interface in spoken language and music: Same, different, or individually variable?

Considerable debate surrounds syntactic processing similarities in language and music. Yet few studies have investigated how syntax interacts with meter considering that metrical regularity varies across domains. Furthermore, there are reports on individual differences in syntactic and metrical structure processing in music and language. Thus, a direct comparison of individual variation in syntax and meter processing across domains is warranted. In a behavioral (Experiment 1) and EEG study (Experiment 2), participants engaged in syntactic processing tasks with sentence- and melody stimuli that were more or less metrically regular, and followed a preferred or non-preferred (but correct) syntactic structure. We further employed a range of cognitive diagnostic tests, parametrically indexed verbal- and musical abilities using a principal component analysis, and correlated cognitive factors with the behavioral and ERP results (Experiment 3). Based on previous results in the language domain, we expected that a regular meter would facilitate the syntactic integration of non-preferred syntax. While syntactic discrimination was better in regular than irregular meter conditions in both domains (Experiment 1), a P600 effect indicated different integration costs during the processing of syntactic complexities in the two domains (Experiment 2). Metrical regularity altered the P600 response to preferred syntax in language while it modulated non-preferred syntax processing in music. Moreover, experimental results yielded within-domain individual differences, and identified continuous metrics of musical ability more beneficial than grouping musicians or non-musicians (Experiment 3). These combined results suggest that the meter-syntax interface differs uniquely in how it forms syntactic preferences in language and music.

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bioRxiv2022

Aesthetic and physiological effects of naturalistic multimodal music listening

Compared to audio only (AO) conditions, audiovisual (AV) information can enhance the aesthetic experience of a music performance. However, such beneficial multimodal effects have yet to be studied in naturalistic music performance settings. Further, peripheral physiological correlates of aesthetic experiences are not well-understood. Here, participants were invited to a concert hall for piano performances of Bach, Messiaen, and Beethoven, which were presented in two conditions: AV and AO. They rated their aesthetic experience (AE) after each piece (Experiment 1 and 2), while peripheral signals (cardiorespiratory measures, skin conductance, and facial muscle activity) were continuously measured (Experiment 2). Factor scores of AE were significantly higher in the AV condition in both experiments. LF/HF ratio, a heart rhythm that represents activation of the sympathetic nervous system, was higher in the AO condition, suggesting increased arousal, likely caused by less predictable sound onsets in the AO condition. We present partial evidence that breathing was faster and facial muscle activity was higher in the AV condition, suggesting that observing a performers movements likely enhances motor mimicry in these more voluntary peripheral measures. Further, zygomaticus ( smiling) muscle activity was a significant predictor of AE. Thus, we suggest physiological measures are related to AE, but at different levels: the more involuntary measures (i.e., heart rhythms) may reflect more sensory aspects, while the more voluntary measures (i.e., muscular control of breathing and facial responses) may reflect the liking aspect of an AE. In summary, we replicate and extend previous findings that AV information enhances AE in a naturalistic music performance setting. We further show that a combination of self-report and peripheral measures benefit a meaningful assessment of AE in naturalistic music performance settings.

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bioRxiv2022

The spatiotemporal dynamics of recognition memory for complex versus simple auditory sequences

Differently from visual recognition, auditory recognition is a process relying on the organization of single elements that evolve in time. Here, we aimed to discover the spatiotemporal dynamics of this cognitive function by adopting a novel strategy for varying the complexity of musical sequences. We selected traditional tonal musical sequences and altered the distance between pitches to obtain matched atonal sequences. We then recorded the brain activity of 71 participants using magnetoencephalography (MEG) while they listened to and later recognized auditory sequences constructed according to simple (tonal) or complex (atonal) conventions. Results reveal qualitative changes in neural activity dependent on stimulus complexity: recognition of tonal sequences engaged hippocampal and cingulate areas, whereas recognition of atonal sequences mainly activated the auditory processing network. Our findings highlight the involvement of a cortico-subcortical brain network for auditory recognition and support the idea that stimulus complexity qualitatively alters the neural pathways of recognition memory.

neuroscience↗

bioRxiv2022

Individual neurophysiological signatures of spontaneous rhythm processing

When sensory input conveys rhythmic regularity, we can form predictions about the timing of upcoming events. Although rhythm processing capacities differ considerably between individuals, these differences are often obscured by participant- and trial-level data averaging procedures in M/EEG research. Here, we systematically assessed the neurophysiological variability displayed by individuals listening to isochronous equitone sequences interspersed with unexpected deviant tones. We first focused on rhythm tracking and tested the anticipatory phase alignment of delta-band activity to expected tone onsets. These analyses confirmed that individuals encode temporal regularities and form temporal predictions, but highlight clear inter- and intra-participant variability. This observation may indicate individual and flexible tracking mechanisms, which show consistency at the single-trial level, but variability over trials. We then modelled single-trial time-locked neural responses in the beta-band to investigate individual tendencies to spontaneously employ binary grouping ("tic-toc effect"). This approach identified binary (strong-weak), ternary (strong-weak-weak), and mixed accentuation patterns, confirming the superimposition of a basic beat pattern. Furthermore, we characterized individual grouping preferences and tendencies to use binary, ternary, or combined patterns over trials. Importantly, the processing of standard and deviant tones was modulated by the employed pattern. The current approach supports individualized neurophysiological profiling as a sensitive strategy to identify dynamically evolving neural signatures of rhythm and beat processing. We further suggest that close examination of neurophysiological variability is critical to improve our understanding of the individual and flexible mechanisms underlying the capacities to rapidly evaluate and adapt to environmental rhythms. Significance statementFor decades, music, speech and rhythm research investigated how humans process, predict, and adapt to environmental rhythms. By adopting a single-trial and -participant approach, we avert the common pooling of EEG data in favor of individual time-varying neural signatures of rhythm tracking and beat processing. The results highlight large inter- and intra-individual differences in rhythm tracking, arguing against the typically documented phase-specificity for entrainment. On top of that, we characterize individual variability in beat processing, by showing that binary, ternary and other accentuation patterns are used over time, and ultimately affect the processing of (un-)expected auditory events. The approach aids individual neural profiling and may therefore allow identifying altered neural activity and its consequences in natural listening contexts.

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bioRxiv2021

Variability in white matter structure relates to hallucination proneness

Hallucinations are a prominent transdiagnostic psychiatric symptom but are also prevalent in individuals who do not require clinical care. Moreover, persistent psychosis-like experience in otherwise healthy individuals may be related to increased risk to transition to a psychotic disorder. This suggests a common etiology across clinical and non-clinical individuals along a multidimensional psychosis continuum that may be detectable in structural variations of the brain. The current diffusion tensor imaging study assessed healthy individuals to identify possible differences in white matter associated with hallucination proneness (HP). This approach circumvents potential confounds related to medication, hospitalization, and disease progression common in clinical individuals. We determined how HP relates to white matter integrity in selected association, commissural, and projection fiber pathways putatively linked to psychosis. Increased HP was associated with enhanced fractional anisotropy (FA) in the right uncinate fasciculus, the right anterior and posterior arcuate fasciculus, and the corpus callosum. Although FA in cortico-cerebellar pathways revealed no relationship, streamline quantity between the left cerebellum and the right motor cortex positively correlated with HP. These findings support the notion of a psychosis continuum, providing first evidence of structural white matter variability associated with HP in healthy individuals. Furthermore, alterations in the targeted pathways likely indicate an association between HP-related structural variations and the putative salience and attention mechanisms that these pathways subserve.

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bioRxiv2021

Phonological and temporal regularities lead to differential ERP effects in self- and externally generated speech

Some theories of predictive processing propose reduced sensory and neural responses to anticipated events. Support comes from M/EEG studies, showing reduced auditory N1 and P2 responses to self-compared to externally generated events, or when stimulus properties are more predictable (e.g. prototypical). The current study examined the sensitivity of N1 and P2 responses to statistical regularities of speech. We employed a motor-to-auditory paradigm comparing ERP responses to externally and self-generated pseudowords, varying in phonotactic probability and syllable stress. We expected to see N1 and P2 suppression for self-generated stimuli, with greater suppression effect for more predictable features such as high phonotactic probability and first syllable stress in pseudowords. We observe an interaction between phonotactic probability and condition on the N1 amplitude, with an enhanced effect of phonotactic probability in processing self-generated stimuli. However, the directionality of this effect was reversed compared to what was expected, namely a larger N1 amplitude for high probability items, possibly indicating a perceptual bias toward the more predictable item. We further observed an effect of syllable stress on the P2 amplitude, with greater amplitudes in response to first syllable stress items. The current results suggest that phonotactic probability plays an important role in processing self-generated speech, supporting feedforward models involved in speech production.

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bioRxiv2021

The P3b differentiates parallel physical and rule-based updating of a sensory model

The capacity to form and update mental representations of the type and timing of sensory events is a central tenet of adaptive behavior in a dynamically changing environment. An internal model of stimulus contingencies provides a means to optimize behavior through predictive adjustments based on past to future events. To this end, neural and cognitive processes rely on systematic relations between events and use these rules to optimize information processing. The P3 complex of the event-related potential of the electroencephalogram (ERP/EEG) is a well-established and extensively tested index of such mechanisms. Here we investigated the P3b sensitivity to auditory stimulus deviations associated with two updating operations: physical change (switching stimulus pitches) and rule change (switching additive and subtractive target stimulus counting). Participants listened to a variant of the classical oddball sequence consisting of frequent standard (600 Hz) and two equally probable less frequent deviant tones (660 Hz, 540 Hz), keeping count of the deviant tones and switching between addition and subtraction with a pitch change. The results indicate specific amplitude modulations, confirming the P3b as a context-sensitive marker of physical and cognitive components of an internal model. This suggests that the P3b can be used as a differential marker of predictive coding mechanisms.

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bioRxiv2021

Delayed auditory encoding and variable representation of stimulus regularity in cerebellar lesion patients

The dynamic and fleeting nature of sound necessitates the rapid encoding and use of information distributed over time. Here we investigated cerebellar contributions to these abilities. We measured EEG from cerebellar patients and healthy controls while they listened to "oddball" sound sequences consisting of infrequent pitch-deviant and frequent standard tones. Inter-stimulus-intervals were temporally regular (600 ms) or irregular (200-1000 ms). This allowed probing early event-related potentials (ERP; P50, N100) that reflect repetitive and changing stimulus characteristics in temporally regular or less (irregular) predictable sequences. Further, time-frequency data provided an index of temporal processing variability at the stimulation frequencies. We expected that cerebellar lesions lead to aberrant encoding and use of auditory information, reflected in the ERP morphology of peak amplitudes, latencies and typical suppression effects linked to stimulus predictability. Results confirm longer P50 peak latencies in patients and variable processing at stimulation frequencies covarying with the location of cerebellar damage. These findings further support the idea that the cerebellum might play a generalizable role in the encoding of auditory stimulation over time.

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bioRxiv2021

Temporo-cerebellar connectivity underlies timing constraints in audition

The flexible and efficient adaptation to dynamic, rapid changes in the auditory environment likely involves generating and updating of internal models. Such models arguably exploit connections between the neocortex and the cerebellum, supporting proactive adaptation. Here we test the functional mechanisms associated with temporo-cerebellar connectivity, verifying these mechanisms for speech sounds. First, we identify lesion-specific deficits for the encoding of short timescale spectro-temporal non-speech and speech properties in patients with left posterior temporal cortex stroke. Second, using lesion-guided probabilistic tractography in healthy participants, we reveal bidirectional temporo-cerebellar connectivity with cerebellar dentate nuclei and crura I/II. These findings imply that the encoding and modeling of rapidly modulated auditory spectro-temporal properties engage a temporo-cerebellar interface. The data further support the conjecture that proactive adaptation to a dynamic environment via internal models is a generalizable principle. Significance StatementAsymmetric sampling in time, the principle of duration-sensitive hemispheric specialization of the cerebral cortex in the sensory decomposition of sound, is a widely tested hypothesis in auditory neuroscience. This functional organization is mirrored in the cerebellar cortex, implicated in the internal forward-modeling of sensory feedback that arises from motor actions. The potential structural and functional integration of these systems is not well understood. Using a unique combination of causal lesion-symptom mapping in persons with temporal lobe damage and diffusion-weighted magnetic resonance neuroimaging in healthy persons, we identify one key missing link and provide evidence for cross-lateral temporo-cerebellar connectivity using probabilistic white matter fiber tractography. These cerebellar-pontine-temporal cortex connections not only support asymmetric sampling in time but also establish the basis for a generalizable role of cerebellar forward-modeling in sensation beyond the monitoring of sensory feedback in the motor domain.

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bioRxiv2020

Left frontal motor delta oscillations reflect the temporal integration of multimodal speech

During multimodal speech perception, slow delta oscillations (~1 - 3 Hz) in the listeners brain synchronize with speech signal, likely reflecting signal decomposition at the service of comprehension. In particular, fluctuations imposed onto the speech amplitude envelope by a speakers prosody seem to temporally align with articulatory and body gestures, thus providing two complementary sensations to the speech signals temporal structure. Further, endogenous delta oscillations in the left motor cortex align with speech and music beat, suggesting a role in the temporal integration of (quasi)-rhythmic stimulations. We propose that delta activity facilitates the temporal alignment of a listeners oscillatory activity with the prosodic fluctuations in a speakers speech during multimodal speech perception. We recorded EEG responses in an audiovisual synchrony detection task while participants watched videos of a speaker. To test the temporal alignment of visual and auditory prosodic features, we filtered the speech signal to remove verbal content. Results confirm (i) that participants accurately detected audiovisual synchrony, and (ii) greater delta power in left frontal motor regions in response to audiovisual asynchrony. The latter effect correlated with behavioural performance, and (iii) decreased delta-beta coupling in the left frontal motor regions when listeners could not accurately integrate visual and auditory prosodies. Together, these findings suggest that endogenous delta oscillations align fluctuating prosodic information conveyed by distinct sensory modalities onto a common temporal organisation in multimodal speech perception.

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bioRxiv2020

Expectancy changes the self-monitoring of voice identity

Self-voice attribution can become difficult when voice characteristics are ambiguous, and functional magnetic resonance imagines (fMRI) investigations of such ambiguity are sparse. We utilized voice-morphing (self-other) to manipulate (un-)certainty in self-voice attribution in a button-press paradigm. This allowed investigating how levels of self-voice certainty alter brain activation in regions monitoring voice identity areas and unexpected changes in voice playback quality. FMRI results confirm a self-voice suppression effect in the right anterior superior temporal gyrus (aSTG) when self-voice attribution was unambiguous. Although the right inferior frontal gyrus (IFG) was more active during self-generated voice compared to when passively-heard, the putative role of this region in detecting unexpected self-voice changes was not confirmed. Further research on the link between right aSTG and IFG is required and may establish a threshold monitoring voice identity in action. The current results have implications for a better understanding of an altered experience of self-voice feedback leading to auditory verbal hallucinations.

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bioRxiv2019

Auditory predictions and prediction errors in response to self-initiated vowels

It has been suggested that speech production is accomplished by an internal forward model, reducing processing activity directed to self-produced speech in the auditory cortex. The current study uses an established N1-suppression paradigm comparing self- and externally-initiated natural speech sounds to answer two questions:\n\nO_LIAre forward predictions generated to process complex speech sounds, such as vowels, initiated via a button press?\nC_LIO_LIAre prediction errors regarding self-initiated deviant vowels reflected in the corresponding ERP components?\nC_LI\n\nResults confirm an N1-suppression in response to self-initiated speech sounds. Furthermore, our results suggest that predictions leading to the N1-suppression effect are specific, as self-initiated deviant vowels do not elicit an N1-suppression effect. Rather, self-initiated deviant vowels elicit an enhanced N2b and P3a compared to externally-generated deviants, externally-generated standard, or self-initiated standards, again confirming prediction specificity.\n\nResults show that prediction errors are salient in self-initiated auditory speech sounds, which may lead to more efficient error correction in speech production.

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