Biology subjects

Maess, B.

Publications and source records attributed to Maess, B..

At least 19 recordsLinked to original sources

bioRxiv2026

Pitch motor areas contribute to the perception of prosodic categories in speech

Prosody is a fundamental aspect of speech characterized by suprasegmental features such as pitch. Prosodic pitch contours are used to convey speakers intentions, for example, to make a statement or ask a question. Understanding these intentions requires abstracting continuous, variable pitch information into discrete categories. Category perception has been proposed to recruit the motor system in an effector-specific manner, whereby cortical areas controlling motor effectors support speech sound recognition by identifying articulatory gestures. However, it remains unclear whether effectors involved in pitch production similarly contribute to prosodic category perception. To address this question, we collected magnetoencephalography data from 29 participants (15 females) while they first sang pitches arranged in five-tone melodies and then identified the prosody (Statement vs. Question) of single words varying in pitch contour along a five-level continuum. Using a region-restricted searchlight approach to decode singing from rest, we localized two premotor regions for pitch production, corresponding to the ventral and dorsal laryngeal motor cortex (LMC). A separate neural decoding analysis revealed that perceived prosodic categories were decodable in these regions, especially from the dorsal LMC that is more closely associated with pitch regulation. Importantly, decoding performance mirrored behavioral discriminability of prosodic categories across the continuum, suggesting that these regions are involved in perceptual decision-making. Finally, pitch motor areas exchanged category-related information with auditory regions, indicating these areas do not merely echo the processing in auditory regions. Together, these findings highlight effector-specific motor support for prosodic category perception, thereby broadening our understanding of motor involvement in speech perception. Significance StatementSpeech perception has been proposed to recruit the premotor cortex, with different subregions linking speech sounds to the articulatory gestures used to produce them. We investigated this idea through prosody--pitch changes in speech conveying meanings such as statements and questions. Using magnetoencephalography, we identified pitch motor areas during a singing task and tested whether they represent perceived prosodic categories. We found that prosodic categories were distinguishable in these regions and that this neural discriminability mirrored behavioral discriminability across clear and ambiguous prosody, suggesting involvement in perceptual decision-making. These findings are unlikely to reflect passive echoes from auditory regions, as pitch motor areas actively influenced them during categorical processing. Our results highlight effector-specific motor support for forming abstract prosodic representations.

neuroscience↗

bioRxiv2026

Inter- and intra-individual variability in structure-function coupling in human brain

Microstructure shapes functional brain dynamics. Yet this notion has remained largely untested for human brain signals measured with electroencephalography and magnetoencephalography (EEG/MEG). In this study, we related functional activity variance to microstructural variance across brain regions and across participants. Across regions, we used multiple independent datasets: EEG (n=209), MEG (n=507), high-resolution MRI (n=10), and the human post-mortem brain. Across participants, we used a multimodal dataset including MEG and high-resolution MRI (n=31). Between regions, alpha power correlated positively with layer IV thickness and with myelin and iron estimates at mid-cortical depth. By contrast, between participants, alpha power correlated negatively with mid-cortical myelin and iron estimates. Using computational modeling, we demonstrated that regional effects are consistent with excitatory changes, whereas inter-individual effects may be driven by inhibitory influence. This dissociation reveals distinct underlying mechanisms and indicates that different factors influence intra-versus inter-individual variations in alpha activity.

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bioRxiv2025

High-Resolution EEG Source Reconstruction from PCA-Corrected BEM-FMM Reciprocal Basis Funcions: A Study with Visual Evoked Potentials from Intermittent Photic Stimulation

Modern automated human head segmentations can generate high-resolution computational meshes involving many non-nested tissues. However, most source reconstruction software is limited to 3 -4 nested layers of low resolution and a small number of dipolar sources[~] 10, 000. Recently, we introduced modeling techniques for source reconstruction of magnetoencephalographic (MEG) signals using the reciprocal approach and the boundary element fast multipole method (BEM-FMM). The technique of BEM-FMM can process both nested and non-nested models with as many as 4 million surface elements. In this paper, we present an analogue technique for source reconstruction of electroencephalographic (EEG) signals based on cortical global basis functions. The present work uses Helmholtz reciprocity to relate the reciprocally-generated lead-field matrices to their direct counterpart, while resolving the issue of possible biases toward the reference electrode. Our methodology is tested with experimental EEG data collected from a cohort of 12, young and healthy, volunteers subjected to intermittent photic stimulation (IPS). Our novel high-resolution source reconstruction models can have impact on mental health screening as well as brain-computer inter-faces.

neuroscience↗

bioRxiv2025

Improved Source Localization of Auditory Evoked Fields using Reciprocal BEM-FMM

The precise localization of auditory evoked fields (AEFs) from magnetoencephalography (MEG) data is very important for the functional understanding of the auditory cortex in medicine and cognitive neuroscience. The numerical solution of the field equations in the human head using the boundary element method (BEM) is a powerful tool for achieving this. We hypothesized that the spatial resolution of the BEM is crucial for the achievable accuracy. However, in classical BEM (as implemented, e.g., in MNE-Python), very high resolutions are impractical due to the associated prohibitive computational effort. In contrast, our recently introduced reciprocal boundary element fast multipole method (reciprocal BEM-FMM) allows for hitherto unprecedented spatial resolution. In this work, we apply our reciprocal BEM-FMM technique for source estimation to localize AEFs, and we compare our results with the source estimates produced using a 3-layer BEM model (standard BEM) via MNE-Python. We first validate our methodology through comparison of source estimates of simulated N1m components of AEFs using a receiver operating characteristic (ROC) measure. While we obtain ROC measures of about 80% for the standard BEM, reciprocal BEM-FMM reaches about 90%, a significant statistical improvement. We then apply this methodology to analyze the source estimates of experimental data obtained from a cohort of 7 participants subjected to binaural auditory stimulation. Using a dispersion measurement to quantify the focality of localized sources, we find improvements upwards of 30% using reciprocal BEM-FMM over the standard BEM. Analyses from both simulated and experimental data show localization of AEFs using high-resolution reciprocal BEM-FMM is significantly better in terms of accuracy and focality than those estimates of the low-resolution standard BEM. We therefore recommend using the high-resolution reciprocal BEM-FMM to utilize high spatial anatomical precision for the modeling of neural activity.

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bioRxiv2025

High-Definition MEG Source Estimation using the Reciprocal Boundary Element Fast Multipole Method

Magnetoencephalographic (MEG) source estimation relies on the computation of the gain (lead-field) matrix, which embodies the linear relationship between the amplitudes of the sources and the recorded signals. However, with a realistic forward model, the calculation of the gain matrix in a "direct" fashion is a computationally expensive task because the number of dipolar sources in standard MEG pipelines is often limited to [~]10,000. We propose a fast approach based on the reciprocal relationship between MEG and transcranial magnetic stimulation (TMS). This approach couples naturally with the charge-based boundary element fast multipole method (BEM-FMM), which allows us to efficiently generate gain matrices for high-resolution multi-layer non-nested meshes involving source spaces of up to a [~]1 million dipoles. We evaluate our approach by performing MEG source reconstruction against simulated data (at varying noise levels) obtained from the direct computation of MEG readings from 2000 different dipole positions over the cortical surface of 5 healthy subjects. Additionally, we test our methods with real MEG data from evoked somatosensory fields by right-hand median nerve stimulation in these same 5 subjects. We compare our experimental source reconstruction results against the standard MNE-Python source reconstruction pipeline.

neuroscience↗

bioRxiv2025

Shared and distinct representational dynamics of phonemes and prosody in ventral and dorsal speech streams

Phonemes and prosodic contours are fundamental elements of speech used to convey complementary meanings. Perceiving these elements requires mapping variable acoustic cues onto discrete categories along ventral and dorsal speech streams. While traditional models make clear predictions, exactly where and when this acoustic-to-categorical mapping occurs remains unclear. Using magnetoencephalography and behavioural psychophysics, combined with time-resolved representational similarity and multivariate transfer entropy analyses, we show how phonemes and prosody propagate along the dual streams and how their categorical representations are gradually formed. Contrary to theoretical predictions, acoustic and categorical representations occur in parallel, rather than serially, across time and space for both elements. Moreover, prosody categories extend further along both streams than phoneme categories, with differently weighted contributions of posterior temporal areas. These results highlight a shared principle of parallel acoustic and categorical processing, yet partially distinct abstraction mechanisms for phonemes and prosody, key to access the multilayered meaning of speech.

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bioRxiv2025

The effects of task similarity during representation learning in brains and neural networks

The complexity of our environment poses significant challenges for adaptive behavior. Recognizing shared structures across tasks can theoretically improve learning through generalization. However, how such shared representations emerge and influence performance remains poorly understood. Contrary to expectations, our findings revealed that individuals trained on tasks with similar low-dimensional structures performed worse than those trained on dissimilar tasks. Magnetoencephalography revealed correlated neural representations in the samestructure group and anticorrelated ones in the different-structure group. Crucially, practice reduced this performance gap and shifted the neural representations of the tasks in the samestructure group towards anticorrelation, like those in the different-structure group. A neural network model trained on similar tasks replicated these findings: tasks with similar structures require more iterations to orthogonalize their representations. These results highlight a complex interplay between task similarity, neural dynamics, and behavior, challenging traditional assumptions about learning and generalization.

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bioRxiv2024

Evaluating noise correction approaches for non-invasive electrophysiology of the human spinal cord

The spinal cord is a vital component of the central nervous system for the processing of sensorimotor information transmitted between the body and the brain. Electrospinography (ESG) is the most accessible non-invasive technique for recording spinal signals in humans, but the vast and detrimental impact of physiological noise (mostly of cardiac nature) has prevented widespread adoption. Here, we aim to address this issue by examining various denoising algorithms for cardiac artefact reduction - including principal component analysis-based techniques (PCA), independent component analysis-based approaches (ICA) and signal space projection (SSP). We observed that in situations where large numbers of spinal electrodes are used, SSP offers the best results in terms of balancing the removal of harmful noise and preserving neural information of interest. In cases where only a small number of electrodes are available, an approach based on PCA is deemed helpful. Approaches based on ICA were found to be unsuitable for cardiac artefact removal in ESG, due to a suboptimal balance of artefact removal and signal preservation. Finally, we also approached this issue from a signal-enhancement perspective and observed that in cases where extensive electrode arrays are used in the context of task-based designs, a spatial filtering technique based on canonical correlation analysis (CCA) reveals clear evoked spinal potentials even with single-trial resolution. Taken together, there are several appropriate algorithms for physiological noise removal in ESG, rendering this an accessible and easy-to-use technique for non-invasive assessments of human spinal cord function.

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bioRxiv2024

Fast and Accurate EEG/MEG BEM-Based Forward Problem Solution for High-Resolution Head Models

A BEM (boundary element method) based approach is developed to accurately solve an EEG/MEG forward problem for a modern high-resolution head model in approximately 60 seconds using a common workstation. The method utilizes a charge-based BEM with fast multipole acceleration (BEM-FMM) and a "smart" mesh pre-refinement (called b-refinement) close to the singular source(s). No costly matrix-filling or direct solution steps typical for the standard BEM are required; the method generates on-skin voltages as well as MEG magnetic fields for high-resolution head models in approximately 60 seconds after initial model assembly. The method is verified both theoretically and experimentally.

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bioRxiv2024

Accuracy of dipole source reconstruction in the 3-layerBEM model against the 5-layer BEM-FMM model

ObjectiveTo compare cortical dipole fitting spatial accuracy between the widely used yet highly simplified 3-layer and modern more realistic 5-layer BEM-FMM models with and without adaptive mesh refinement (AMR) methods. MethodsWe generate simulated noiseless 256-channel EEG data from 5-layer (7-compartment) meshes of 15 subjects from the Connectome Young Adult dataset. For each subject, we test four dipole positions, three sets of conductivity values, and two types of head segmentation. We use the boundary element method (BEM) with fast multipole method (FMM) acceleration, with or without (AMR), for forward modeling. Dipole fitting is carried out with the FieldTrip MATLAB toolbox. ResultsThe average position error (across all tested dipoles, subjects, and models) is [~]4 mm, with a standard deviation of [~]2 mm. The orientation error is [~]20{degrees} on average, with a standard deviation of [~]15{degrees}. Without AMR, the numerical inaccuracies produce a larger disagreement between the 3- and 5-layer models, with an average position error of [~]8 mm (6 mm standard deviation), and an orientation error of 28{degrees} (28{degrees} standard deviation). ConclusionsThe low-resolution 3-layer models provide excellent accuracy in dipole localization. On the other hand, dipole orientation is retrieved less accurately. Therefore, certain applications may require more realistic models for practical source reconstruction. AMR is a critical component for improving the accuracy of forward EEG computations using a high-resolution 5-layer volume conduction model. SignificanceImproving EEG source reconstruction accuracy is important for several clinical applications, including epilepsy and other seizure-inducing conditions.

bioinformatics↗

bioRxiv2024

Characterizing directional dynamics of semantic prediction based on inter-regional temporal generalization

The event-related potential/field component N400(m) has been widely used as a neural index for semantic prediction. It has long been hypothesized that feedback information from inferior frontal areas plays a critical role in generating the N400. However, due to limitations in causal connectivity estimation, direct testing of this hypothesis has remained difficult. Here, magnetoencephalography (MEG) data was obtained during a classic N400 paradigm where the semantic predictability of a fixed target noun was manipulated in simple German sentences. To estimate causality, we implemented a novel approach based on machine learning and temporal generalization to estimate the effect of inferior frontal gyrus (IFG) on temporal areas. In this method, a support vector machine (SVM) classifier is trained on each time point of the neural activity in IFG to classify less predicted (LP) and highly predicted (HP) nouns and then tested on all time points of superior/middle temporal sub- regions activity (and vice versa, to establish spatio-temporal evidence for or against causality). The decoding accuracy was significantly above chance level when the classifier was trained on IFG activity and tested on future activity in superior and middle temporal gyrus (STG/MTG). The results present new evidence for a model predictive speech comprehension where predictive IFG activity is fed back to shape subsequent activity in STG/MTG, implying a feedback mechanism in N400 generation. In combination with the also observed strong feedforward effect from left STG/MTG to IFG, our findings provide evidence of dynamic feedback and feedforward influences between IFG and temporal areas during N400 generation.

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bioRxiv2023

Evoked Responses to Localized Sounds Suggest Linear Representation of Elevation in Human Auditory Cortex

The auditory system computes the position of a sound along each of the three spatial axes, azimuth, elevation and distance, from very different acoustical cues. The extraction of sound azimuth from binaural cues (differences in arrival time and intensity between the ears) is well understood, as is the representation of these binaural cues in the auditory cortex of different species. Sound elevation is computed from monaural spectral cues arising from direction-dependent filtering of the pinnae, head, and upper body. The cortical representation of these cues in humans is still debated. We have shown that the fMRI blood-oxigen level-dependent activity in small parts of auditory cortex relates monotonically to perceived sound elevation and tracks listeners internal adaptation to new spectral cues. Here we confirm the previously suggested cortical code with a different method that reflects neural activity rather than blood oxigenation (electroencephalography), show that elevation is represented relatively late in the cortex, with related activity peaking at about 400 ms after sound onset, and show that differences in sound elevation can be decoded from the electroencephalogram of listeners, particularely from those who can distinguish elevations well. We used an adaptation design to isolate elevation-specific brain responses from those to other features of the stimuli. These responses gradually increased with decreasing sound elevation, consistent with our previous fMRI findings and population rate code for sound elevation. The long latency as well as the topographical distribution of the elevation-specific brain response indicates the involvement of higher-level cognitive processes not present for binaural cue representation. The differences between brain responses to sounds at different elevations predicted the listeners sound localization accuracy, suggesting that these responses reflect perceived elevation. This is, to our knowledge, the first study that demonstrates the cortical encoding of sound elevation in humans with high-temporal resolution. Our results agree with previous findings from functional magnetic resonance imaging, providing strong support for the hypothesis that elevation is represented in a population-rate code. This represents a critical advance in our understanding of spatial auditory processing along a dimension that is still poorly understood.

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bioRxiv2022

Laminar Neural Dynamics of Auditory Evoked Responses: Computational Modeling of Local Field Potentials in Auditory Cortex of Non-Human Primates

Evoked neural responses to sensory stimuli have been extensively investigated in humans and animal models both to enhance our understanding of brain function and to aid in clinical diagnosis of neurological and neuropsychiatric conditions. Recording and imaging techniques such as electroencephalography (EEG), magnetoencephalography (MEG), local field potentials (LFPs), and calcium imaging provide complementary information about different aspects of brain activity at different spatial and temporal scales. Modeling and simulations provide a way to integrate these different types of information to clarify underlying neural mechanisms. In this study, we aimed to shed light on the neural dynamics underlying auditory evoked responses by fitting a rate-based model to LFPs recorded via multi-contact electrodes which simultaneously sampled neural activity across cortical laminae. Recordings included neural population responses to best-frequency (BF) and non-BF tones at four representative sites in primary auditory cortex (A1) of awake monkeys. The model considered major neural populations of excitatory, parvalbumin-expressing (PV), and somatostatin-expressing (SOM) neurons across layers 2/3, 4, and 5/6. Unknown parameters, including the connection strength between the populations, were fitted to the data. Our results revealed similar population dynamics, fitted model parameters, predicted equivalent current dipoles (ECD), tuning curves, and lateral inhibition profiles across recording sites and animals, in spite of quite different extracellular current distributions. We found that PV firing rates were higher in BF than in non-BF responses, mainly due to different strengths of tonotopic thalamic input, whereas SOM firing rates were higher in non-BF than in BF responses due to lateral inhibition. In conclusion, we demonstrate the feasibility of the model-fitting approach in identifying the contributions of cell-type specific population activity to stimulus-evoked LFPs across cortical laminae, providing a foundation for further investigations into the dynamics of neural circuits underlying cortical sensory processing.

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bioRxiv2022

Non-invasive multi-channel electrophysiology of the human spinal cord - assessing somatosensory processing from periphery to cortex

The spinal cord is of fundamental importance for integrative processing in brain-body communication, yet routine non-invasive recordings in humans are hindered by vast methodological challenges. Here we overcome these challenges by developing an easy-to-use electrophysiological approach based on high-density multi-channel spinal recordings combined with multivariate spatial-filtering analyses. These advances enable a spatiotemporal characterization of spinal cord responses and demonstrate a sensitivity that permits assessing even single-trial responses. To furthermore enable the study of integrative processing along the neural processing hierarchy in somatosensation, we expand this approach by simultaneous peripheral, spinal and cortical recordings and provide direct evidence that bottom-up integrative processing occurs already within the spinal cord and thus after the first synaptic relay in the central nervous system. Finally, we demonstrate the versatility of this approach by providing non-invasive recordings of nociceptive spinal cord responses during heat-pain stimulation. Beyond establishing a new window on human spinal cord function at millisecond timescale, this work provides the foundation to study brain-body communication in its entirety in health and disease.

neuroscience↗

bioRxiv2022

High-Resolution EEG Source Reconstruction with Boundary Element Fast Multipole Method Using Reciprocity Principle and TES Forward Model Matrix

BackgroundAccurate high-resolution EEG source reconstruction (localization) is important for several tasks, including rigorous and rapid mental health screening. ObjectiveThe present study has developed, validated, and applied a new source localization algorithm utilizing a charge-based boundary element fast multipole method (BEM-FMM) coupled with the Helmholtz reciprocity principle and the transcranial electrical stimulation (TES) forward solution. MethodsThe unknown cortical dipole density is reconstructed over the entire cortical surface by expanding into global basis functions in the form of cortical fields of active TES electrode pairs. These pairs are constructed from the reading electrodes. An analog of the minimum norm estimation (MNE) equation is obtained after substituting this expansion into the reciprocity principle written in terms of measured electrode voltages. Delaunay (geometrically balanced) triangulation of the electrode cap is introduced first. Basis functions for all electrode pairs connected by the edges of a triangular mesh are precomputed and stored in memory. A smaller set of independent basis functions is then selected and employed at every time instant. This set is based on the highest voltage differences measured. ResultsThe method is validated against the classic, yet challenging problem of median nerve stimulation and the tangential cortical sources located at the posterior wall of the central sulcus for an N20/P20 peak (2 scanned subjects). The method is further applied to perform source reconstruction of synthesized tangential cortical sources located at the posterior wall of the central sulcus (12 different subjects). In the second case, an average source reconstruction error of 7 mm is reported for the best possible noiseless scenario. ConclusionsOnce static preprocessing with TES electrodes has been done (the basis functions have been computed), our method requires fractions of a second to complete the accurate high-resolution source localization.

neuroscience↗

bioRxiv2022

Age-related changes in neural synchronization and the sustained response to amplitude and frequency modulation of sound

Perception of speech requires sensitivity to features, such as amplitude and frequency modulations, that are often temporally regular. Previous work suggests age-related changes in neural responses to temporally regular features, but little work has focused on age differences for different types of modulations. We recorded magnetoencephalography in younger (21-33 years) and older adults (53-73 years) to investigate age differences in neural responses to slow (2-6 Hz sinusoidal and non-sinusoidal) modulations in amplitude, frequency, or combined amplitude and frequency. Audiometric pure-tone average thresholds were elevated in older compared to younger adults, indicating subclinical hearing impairment in the recruited older-adult sample. Neural responses to sound onset (independent of temporal modulations) were increased in magnitude in older compared to younger adults, suggesting hyperresponsivity and a loss of inhibition in the aged auditory system. Analyses of neural activity to modulations revealed greater neural synchronization with amplitude, frequency, and combined amplitude-frequency modulations for older compared to younger adults. This potentiated response generalized across different degrees of temporal regularity (sinusoidal and non-sinusoidal), although neural synchronization was generally lower for non-sinusoidal modulation. Despite greater synchronization, sustained neural activity was reduced in older compared to younger adults for sounds modulated both sinusoidally and non-sinusoidally in frequency. Our results suggest age differences in the sensitivity of the auditory system to features present in speech and other natural sounds.

neuroscience↗

bioRxiv2022

Age-related changes in the neural mechanics of dynamic auditory attention in time

Listening in everyday life requires attention to be deployed dynamically - when listening is expected to be difficult and when relevant information is expected to occur - to conserve mental resources. Conserving mental resources may be particularly important for older adults who often experience difficulties understanding speech. In the current study, we use electro- and magnetoencephalography to investigate the neural and behavioral mechanics of attention regulation during listening and the effects that aging has on these. We show that neural alpha oscillatory activity indicates when in time attention is deployed (Experiment 1) and that deployment depends on listening difficulty (Experiment 2). Older adults (54-72 years) also show successful attention regulation but appear to utilize timing information differently compared to younger adults (20-33 years). We further show a notable age-group dissociation in recruited brain regions. In younger adults, superior parietal cortex underlies alpha power during attention regulation, whereas, in older adults, alpha power emerges from more ventro-lateral areas (posterior temporal cortex; Experiment 3). This difference in the sources of alpha activity between age groups only occurred during task performance and was absent during rest (Experiment S1). In sum, our study suggests that older adults employ different neural control strategies compared to younger adults to regulate attention in time under listening challenges.

neuroscience↗

bioRxiv2021

Individual alpha power predicts language comprehension

Alpha power attenuation during cognitive task performing has been suggested to reflect a process of release of inhibition, increase of excitability, and thereby benefit the improvement of performance. Here, we hypothesized that changes in individual alpha power during the execution of a complex language comprehension task may correlate with the individual performance in that task. We tested this using magnetoencephalography (MEG) recorded during comprehension of German sentences of different syntactic complexity. Results showed that neither the frequency nor the power of the spontaneous oscillatory activity at rest were associated with the individual performance. However, during the execution of a sentences processing task, the individual alpha power attenuation did correlate with individual language comprehension performance. Source reconstruction localized effects in temporal-parietal regions of both hemispheres. While the effect of increased task difficulty is localized in the right hemisphere, the difference in power attenuation between tasks of different complexity exhibiting a correlation with performance was localized in left temporal-parietal brain regions known to be associated with language processing. From our results, we conclude that in-task attenuation of individual alpha power is related to the essential mechanisms of the underlying cognitive processes, rather than merely to general phenomena like attention or vigilance. HighlightsO_LIComprehension of structurally complexed embedded sentences is correlated with individual alpha power attenuation during task but not with alpha power at rest. C_LIO_LIThese effects were localized in temporal-parietal brain regions known to be associated with language processing. C_LI Data availability statementAnonymized raw data will be made available upon request via email to the corresponding author provided the requesting researchers sign a formal data sharing agreement and cite this paper as origin of the data.

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