Biology subjects

Tuescher, O.

Publications and source records attributed to Tuescher, O..

11 recordsLinked to original sources

bioRxiv2026

Boredom and the representation of information content in the neocortex

Boredom - a pervasive mental state - promotes the pursuit of novel information by assigning negative value to monotonous conditions. Yet, how the brain extracts and represents the information content of ongoing sensory experience remains poorly understood. Here, we combine behavioral assays, neurophysiological recordings and computational modeling across humans and mice to investigate how sensory information shapes boredom-related behavior. In a cross-species choice task, both humans and mice robustly avoid monotonous sources of sensory stimulation. We formalize perceived monotony using empirical entropy as a measure of information content and show that monotony avoidance scales directly with low entropy and in humans correlates with boredom experience. Human electroencephalography and mesoscopic calcium imaging in mice reveal that the recruitment of neocortical activity tracks stimulus entropy. Two-photon calcium imaging in the auditory cortex of mice further uncovers a stimulus-invariant population code for entropy, supported by neurons tuned to information content. A recurrent network model reproduced this code through an interplay of afferent depression and recurrent facilitation. Together, we demonstrate how the information content of sensory experience is represented in cortical population activity, providing a basis for boredom-related avoidance behavior. Thus, our findings link synaptic and neuronal dynamics to boredom, acting as a safeguard mechanism to ensure high information input to the brain.

neuroscience↗

bioRxiv2026

16p11.2 Copy Number Variation Alters Genome Architecture and Transcriptional Regulation During Neurodevelopment

Microdeletions and microduplications in 16p11.2 are responsible for a spectrum of neurodevelopmental disorders (NDDs) with partially reciprocal and overlapping symptoms. However, the clinical variability in 16p11.2 microduplication patients is significantly greater than that in patients carrying a microdeletion. Here, we use iPSCs derived from members of a family carrying a 16p11.2 microduplication and model neurodevelopment through in vitro differentiation into neural progenitor cells (NPCs) and neurons. The analysis is complemented by reanalysis of publicly available data from 16p11.2 microdeletion patients. Transcriptome analysis revealed MAPK3-centered hubs of upregulated genes in the microduplication-carrying and downregulated in the microdeletion-carrying cells, indicating that MAPK3 is a central driver of 16p11.2 Copy Number Variation (CNV) pathology. While genes within the 16p11.2 region showed about a two-fold reduction in expression in cells carrying the microdeletion, their expression levels in microduplication-derived NPCs and neurons, but not in iPSCs, were elevated to a degree much higher than expected. This observation was accompanied by a substantial number of dysregulated genes unrelated to the genes in the critical region or their interaction networks. To further investigate whether altered chromatin organization may accompany these transcriptional changes, we generated Hi-C data from patient and control iPSCs and NPCs. This revealed increased chromatin contacts within the duplicated 16p11.2 region in patient-derived iPSCs, while genome-wide compartment analysis showed that increased compartments preferentially co-occurred with upregulated differentially expressed genes, particularly in NPCs. Together, these findings suggest that 16p11.2 microduplication may influence gene expression through both local dosage-dependent mechanisms and broader, differentiation-associated changes in chromatin organization. Our data support a model in which CNV-associated genome architecture changes may modulate transcriptional dysregulation and contribute to the variable neurodevelopmental phenotypes associated with 16p11.2 rearrangements.

pathology↗

bioRxiv2025

Network Adaptability Governs Resilience and Susceptibility to Social Defeat

Stress resilience is defined as the ability to maintain mental health after adversity. In humans, resilience is marked by threat-safety discrimination and extinction of fear, whereas susceptibility involves fear generalization and extinction resistance. Using a translational mouse model of chronic social defeat stress combined with preregistered multimodal brain imaging, we investigated structural and network-level markers of resilience, susceptibility, and threat learning. Resilience was characterized by preserved dentate gyrus integrity, greater microstructural complexity in prefrontal regions, and signatures consistent with enhanced inhibitory gating within amygdalar circuits. Susceptibility, in contrast, involved reduced dentate gyrus complexity and diminished microstructural flexibility, with a weaker but parallel pattern in the basolateral amygdala. Impaired threat learning was linked to compromised CA1/CA2 integrity and reduced pons connectivity, highlighting hippocampal-brainstem interactions in memory consolidation. Overall, these findings show that resilience emerges from adaptive network reorganization, whereas susceptibility and impaired learning reflect distinct dysfunctions, underscoring individual coping differences even among genetically identical animals.

neuroscience↗

bioRxiv2025

A ventral striatal learning signal reflecting individual differences in the success of fear extinction

Individual differences in fear extinction learning are centrally involved in anxiety vulnerability. We here investigate individual extinction differences using a model-free, data-driven approach, by applying Latent Class Growth Modeling (LCGM) to four in-house data sets from altogether N=234 healthy male participants. This revealed two distinct trajectory classes: fast extinguishers and slow extinguishers. This pattern was replicated in two independent public data sets (total N=275, female and male). In a subset of the in-house samples with functional magnetic resonance imaging (fMRI) data (n=122 males), we investigated the neural correlates of class membership, focusing on the ventral striatum (VS), a key area previously implicated in encoding extinction prediction errors (EPE). We found that fast extinguishers exhibited VS activity at the time of unconditioned stimulus omission early in extinction, consistent with an EPE signal, whereas this signal only appeared late in extinction in slow extinguishers. These findings suggest that extinction success is shaped by how the VS learns safety.

neuroscience↗

bioRxiv2023

A mathematical model of the Alzheimer's Disease biomarker cascade demonstrates statistical pitfalls in identifying neurobiological surrogates of cognitive reserve

IntroductionIn order to investigate neurobiological surrogates of cognitive reserve, statistical interaction analyses have been put forward and used by several studies. However, as these neurobiological surrogates are potentially affected by neurodegeneration as part of the amyloid cascade, which is characterized by chronological time-moderated associations between biomarkers, cross sectional sampling in combination with the disregard of time as a confounder could introduce interaction effects that may be misinterpretabed as cognitive reserve in statistical analyses. MethodsWe modeled the amyloid cascade with a minimal set of three biomarkers amyloid load, corticospinal fluid tau, hippocampal volume and cognitive outcome using a differential equation system, whose parameters were estimated from empirical data from the ADNI. Interaction effects between pathology markers amyloid and tau with hippocampal volume as potential marker of cognitive reserve were estimated on two simulated data samples. Both samples were calculated from varying amyloid, tau and hippocampal volume for the initial configuration of individual trajectories. For Sample 1, data points were sampled at a fixed time after baseline. For Sample 2, data points were sampled at random time points. ResultsRegression analyses on Sample 1 yielded estimates for interaction effects of 0. For Sample 2, estimates were -.1692 and -.0807 for amyloid and tau with hippocampal volume, respectively. The interaction effect estimates for Sample 2 decreased several orders of magnitude when taking into account the timepoint of sampling. ConclusionStudies aiming to investigate neurobiological surrogates of cognitive reserve that are affected by Alzheimers Disease-related neurodegenerative processes need to consider inter-individually varying sampling time points in the data to avoid misinterpreting interaction effects.

neuroscience↗

bioRxiv2023

Understanding the neural mechanisms of emotion-cognition interaction via high resolution mapping in space, time, frequency, and information transfer

Interactions between emotional and cognitive processing play a critical role in determining human behavior. The ability to efficiently control these interactions is essential for goal-directed behavior. Previous research on emotion-cognition interaction in humans has primarily focused on its neural topography using techniques with either low temporal resolution (fMRI) or low spatial resolution (ERP), leaving the underlying neuronal mechanisms and their behavioral implications poorly understood. Here, we used EEG recordings from a large cohort of human participants (N=121) and employed source-reconstruction with finite-element head modeling during an emotional Flanker task. Our findings reveal a neural interaction between emotional interference and cognitive control within the pars triangularis of the right inferior frontal gyrus (rIFG). These results align spatially and conceptually with meta-analytic evidence from fMRI studies on interference inhibition processes, supporting the idea that the rIFG is crucial for interference inhibition, regardless of the interfering information type. Notably, the neural interaction between emotion and cognition in the rIFG was transient, peaking during the transition from emotional to cognitive processing, and was most pronounced in the beta-frequency band. Furthermore, conditional Granger-causality analysis of information flow indicated that the pars triangularis of the rIFG communicated with other functional subdivisions of the rIFG and parieto-occipital areas (such as the Precuneus and V2) in a frequency-specific manner. This information flow predicted individual emotional and cognitive interference effects on behavior. Overall, our findings highlight the functional and temporal segregation and integration of emotion, cognition, and their interaction in the rIFG. Furthermore, rIFGs top-down modulation of visuo-attentional areas, ultimately shaping behavioral performance, underscores the importance of stimulus interference inhibition for emotion-cognition interaction. Author summaryUnderstanding the interplay between emotion and cognition is crucial for understanding human behavior. Our study investigates the role of transient oscillatory activity using source-localized EEG in a large cohort. We identify a spatial overlap of the interaction of emotion and cognition processing in the rIFGs pars triangularis, aligning closely with localizations indicated by meta-analytic fMRI evidence. This interaction, primarily in the beta-frequency (around 20Hz) band, is transient, peaking during the shift from emotional to cognitive processing. Granger-causality analysis reveals frequency-specific communication patterns within the rIFG and parieto-occipital areas, predicting individual emotional and cognitive interference effects. Our findings elucidate the functional and temporal dynamics of emotion-cognition interaction within the rIFG, providing insights into the nuanced neural processes shaping human behavior.

neuroscience↗

bioRxiv2022

Arousal defines the conditions for facilitation by L-DOPA of extinction consolidation and associated prefrontal activity

Even after successful extinction, conditioned fear can return. Strengthening the consolidation of the fear-inhibitory safety memory formed during extinction is one way to counteract return of fear. In this preregistered direct replication study in male participants, we confirm that spontaneous post-extinction reactivations of a neural activation pattern evoked in the ventromedial prefrontal cortex (vmPFC) during extinction predict extinction memory retrieval 24 h later. We do not confirm that L-DOPA administration after extinction enhances retrieval and that this is mediated by enhancement of the number of vmPFC reactivations. However, additional non-preregistered analyses reveal a beneficial effect of L-DOPA on extinction retrieval when controlling for the trait-like stable baseline levels of salivary alpha-amylase enzymatic activity (trait sAA) levels that participants show on the three experimental days. Further, trait sAA negatively predicts retrieval, and this effect is rescued by L-DOPA treatment. Our results suggest that individuals with high basal levels of sympathetic nervous system (SNS) activity may have poor extinction and that L-DOPA may be selectively beneficial for these individuals, which holds potential for clinical applications.

neuroscience↗

bioRxiv2020

Measuring spectrally-resolved information transfer for sender- and receiver-specific frequencies

Information transfer, measured by transfer entropy, is a key component of distributed computation. It is therefore important to understand the pattern of information transfer in order to unravel the distributed computational algorithms of a system. Since in many natural systems distributed computation is thought to rely on rhythmic processes a frequency resolved measure of information transfer is highly desirable. Here, we present a novel algorithm, and its efficient implementation, to identify separately frequencies sending and receiving information in a network. Our approach relies on the invertible maximum overlap discrete wavelet transform (MODWT) for the creation of surrogate data in the computation of transfer entropy and entirely avoids filtering of the original signals. The approach thereby avoids well-known problems due to phase shifts or the ineffectiveness of filtering in the information theoretic setting. We also show that measuring frequency-resolved information transfer is a partial information decomposition problem that cannot be fully resolved to date and discuss the implications of this issue. Last, we evaluate the performance of our algorithm on simulated data and apply it to human magnetoencephalography (MEG) recordings and to local field potential recordings in the ferret. In human MEG we demonstrate top-down information flow in temporal cortex from very high frequencies (above 100Hz) to both similarly high frequencies and to frequencies around 20Hz, i.e. a complex spectral configuration of cortical information transmission that has not been described before. In the ferret we show that the prefrontal cortex sends information at low frequencies (4-8 Hz) to early visual cortex (V1), while V1 receives the information at high frequencies (> 125 Hz). Author SummarySystems in nature that perform computations typically consist of a large number of relatively simple but interacting parts. In human brains, for example, billions of neurons work together to enable our cognitive abilities. This well-orchestrated teamwork requires information to be exchanged very frequently. In many cases this exchange happens rhythmically and, therefore, it seems beneficial for our understanding of physical systems if we could link the information exchange to specific rhythms. We here present a method to determine which rhythms send, and which rhythms receive information. Since many rhythms can interact at both sender and receiver side, we show that the interpretation of results always needs to consider that the above problem is tightly linked to partial information decomposition - an intriguing problem from information theory only solved recently, and only partly. We applied our novel method to information transfer in the human inferior temporal cortex, a brain region relevant for object perception, and unexpectedly found information transfer originating at very high frequencies at 100Hz and then forking to be received at both similarly high but also much lower frequencies around 20Hz. These results overturn the current standard assumption that low frequencies send information to high frequencies.

neuroscience↗

bioRxiv2020

Cortical network mechanisms of response inhibition

Both the right inferior frontal gyrus (rIFG) and the pre-supplementary motor area (pre-SMA) are crucial for successful response inhibition. However, the particular functional roles of those two regions have been controversially debated for more than a decade now. It is unclear whether the rIFG directly initiates stopping or serves an attentional function, whereas the stopping is triggered by the pre-SMA. The current multimodal MEG/fMRI study sought to clarify the role and temporal activation order of both regions in response inhibition using a selective stopping task. This task dissociates inhibitory from attentional processes. Our results reliably reveal a temporal precedence of rIFG over pre-SMA. Moreover, connectivity during response inhibition is directed from rIFG to pre-SMA and predicts stopping performance. Response inhibition is implemented via beta-band oscillations. Our findings support the hypothesis that response inhibition is initiated by the rIFG as a form of attention-independent top-down control.

neuroscience↗

bioRxiv2019

Community driven dynamics of oscillatory network responses to threat

Physiological responses to threat stimuli involve neural synchronized oscillations in cerebral networks with distinct organization properties. Community architecture within these networks and its dynamic adaptation could play a critical role in achieving optimal physiological responses.\n\nHere we applied dynamic network analyses to address the early phases of threat processing at the millisecond level, describing multi-frequency (theta and alpha) integration and basic reorganization properties (flexibility and clustering) that drive physiological responses. We quantified cortical and subcortical network interactions and captured illustrative reconfigurations using community allegiance as essential fingerprints of large-scale adaptation.\n\nA theta band driven community reorganization of key anatomical regions forming the threat network (TN) along with transitions of nodes from the dorsal attention (DAN) and salience (SN) circuits predict the optimal physiological response to threat. We show that increase flexibility of the community network architecture drives the physiological responses during instructed threat processing. Nodal switches modulate the directionality of information flows in the involved circuits.\n\nThese results provide a captivating perspective of flexible network responses to threat and shed new light on basic physiological principles relevant for the development of stress- and threat-related mental disorders.

neuroscience↗

bioRxiv2018

Excitability regulation in the dorsomedial prefrontal cortex during sustained instructed fear responses: a TMS-EEG study

BackgroundThreat detection is essential for protecting individuals from precarious situations. Early studies suggested a network of amygdala, limbic regions and dorsomedial prefrontal cortex (dmPFC) involved in fear processing. Excitability regulation in the dmPFC might be crucial for physiological fear processing, while an abnormal excitability pattern could lead to mental illness. Non-invasive paradigms to measure excitability regulation during fear processing in humans are missing.\n\nMethodsWe adapted an experimental approach of excitability characterization using electroencephalography (EEG) recordings and transcranial magnetic stimulation (TMS) over the dmPFC during an instructed fear paradigm to dynamically dissect its role in fear processing. Event-related (ERP) and TMS-evoked potentials (TEP) were analyzed to trace dmPFC excitability in healthy young volunteers (n = 40, age = 27.6 {+/-} 5.7 years, 22 females). Moreover, we linked the excitability regulation patterns to individual structural MRI-derived properties of gray matter microstructural integrity of the fear network.\n\nResultsAn increased cortical excitability was demonstrated in the threat (T) condition in comparison to no-threat (NT) as showed by increased amplitude of evoked potentials. Furthermore, TMS over the dmPFC induced markedly increased evoked responses during T condition in relation to NT. Moreover, we found that the structural integrity of the dmPFC and the amygdala predict excitability regulation patterns as measured by ERP and TEP during fear processing.\n\nConclusionsWe describe the dynamic range of excitability regulation in dmPFC during fear processing. The applied paradigm can be used to non-invasively track response abnormalities to threat stimuli in healthy subjects or patients with mental disorders.

neuroscience↗