Biology subjects

Hofmann, S. M.

Publications and source records attributed to Hofmann, S. M..

11 recordsLinked to original sources

bioRxiv2026

Expectation Shapes Neural Preparation for AI-generated and Real Image Processing: Evidence from EEG

AbstractAI-generated images, videos, and news have become an inseparable part of daily life, leading to increasing skepticism toward online information. Understanding how expectations about the presence of AI-generated content influence perception is crucial for elucidating the underlying neural mechanisms and facilitating the generation of naturalistic avatars. In this study, we analyzed an existing EEG dataset (N = 29) in which participants viewed emotional facial photographs of only real individuals while being informed that upcoming faces were either real ("REAL") or AI-generated ("FAKE"). We examined pre-stimulus oscillatory activities in the one-second EEG interval before stimulus onset and found significantly lower alpha power when participants expected "FAKE" compared to "REAL" faces. This effect was region-specific, particularly in right occipito-parietal and temporo-parietal regions, as identified by both sensor- and source- level analyses. In addition, the modulation effect between pre-stimulus alpha activity and post-stimulus event-related potentials (ERPs) was measured. A significant correlation between changes in late positive potential (LPP) amplitudes and pre-stimulus alpha power was observed exclusively for "FAKE" smiling faces, consistent with our previous findings. These results suggest that AI-related expectations modulate neural preparatory states, with lower alpha activity presumably reflecting increased attentional demands for stimuli believed to be artificially generated. This study demonstrates that top-down beliefs systematically shape both pre- and post-stimulus neural dynamics, providing new insights into how cognitive expectations bias perceptual processing, with implications for understanding human-AI interaction and improving the design and evaluation of AI- generated content in real-world contexts.

neuroscience↗

bioRxiv2025

Neural CXCR4 contributes to neuroimmune modulation of atherosclerosis in a cardio-metabolic Ldlr-/- mouse model

BackgroundAtherosclerosis is a chronic inflammatory disease characterized by metabolic and immune dysregulation. Emerging evidence suggests that specific central nervous system (CNS) regions modulate its progression via neuroimmune cardiovascular interfaces (NICIs). While the C-X-C motif chemokine receptor 4 (CXCR4) is known to participate in atherogenesis by regulating immune cell dynamics and vascular wall responses, the role of neural CXCR4 in atherosclerotic plaque formation remains unclear. MethodsWe generated a Nestin-Cre-mediated conditional Cxcr4 knockout mouse model on a low-density lipoprotein receptor-deficient (Ldlr-/-) background and fed these mice a western diet (WD) for up to 12 weeks to induce atherosclerosis. To evaluate the impact of neural CXCR4 function, we quantified atherosclerotic plaque burden, systemic metabolic parameters and circulating immune cell profiles, comparing neural Cxcr4-deficient mice with corresponding genetic controls. Spatial transcriptomics and RNAscope were employed to map Cxcr4 mRNA and its non-canonical ligand macrophage migration inhibitory factor (Mif) mRNA in neuroimmune-regulatory brain regions, and to assess diet-induced expression changes in relation to neuroinflammatory responses. ResultsNeural conditional deletion of Cxcr4 in Ldlr-/- mice significantly reduced atherosclerotic plaque formation in the aortic arch and aorta, without affecting body weight, lipid levels, glucose tolerance, or circulating immune cells. Cxcr4 gene expression was found to be uniformly low across hypothalamic subregions implicated in neuroimmune regulation of systemic inflammation and atherogenesis. Importantly, WD feeding did not modify this consistently low expression in male Ldlr-/- mice. In contrast, Mif mRNA expression was significantly upregulated in the PVN after 5-day WD feeding, but not after 8 weeks. Exploratory spatial transcriptomic analysis of PVN-containing coronal brain sections from male Ldlr-/- mice suggested that 5-day WD exposure is associated with MIF-CXCR4 signaling and downstream neuroinflammatory pathways in the PVN. ConclusionsThis study identifies neural CXCR4 as a component of neuroimmune modulation in atherosclerosis, exerting its effect independently of systemic metabolic or inflammatory changes. Short-term WD exposure activated gene expression of the CXCR4 ligand Mif in the PVN, pointing to a neuroimmune axis that may promote vascular inflammation and atherosclerotic plaque development. These findings establish a link between CNS CXCR4 and vascular disease and suggest that MIF-CXCR4-dependent neuroimmune pathways may play a role in cardiometabolic risk. Trial registrationNot applicable.

immunology↗

bioRxiv2025

EEG-decodability of facial expressions and their stereoscopic depth cues in immersive virtual reality

Face perception typically occurs in three-dimensional space, where stereoscopic depth cues enrich the perception of facial features. Yet, most neurophysiological research on face processing relies on two-dimensional displays, potentially overlooking the role of stereoscopic depth information. Here, we combine immersive virtual reality (VR), electroencephalography (EEG), and eye tracking to examine the neural representation of faces under controlled manipulations of stereoscopic depth. Thirty-four participants viewed computer-generated faces with neutral, happy, angry, and surprised expressions in frontal view under monoscopic and stereoscopic viewing conditions. Using time-resolved multivariate decoding, we show that EEG signals in immersive VR conditions can reliably differentiate facial expressions. Stereoscopic depth cues elicited a distinct and decodable neural signature, confirming the sensitivity of our approach to depth-related processing. Yet, expression decoding remained robust across depth conditions, indicating that under controlled frontal viewing, the neural representation of behaviorally distinguishable facial expressions is invariant to binocular depth cues. Eye tracking showed that expression-related gaze patterns contained comparable information but did not account for neural representations, while depth information was absent in gaze patterns--consistent with dissociable representational processes. Our findings demonstrate the feasibility of EEG-based neural decoding in fully immersive VR as a tool for investigating face perception in naturalistic settings and provide new evidence for the stability of expression representations across depth variations in three-dimensional viewing conditions.

neuroscience↗

bioRxiv2024

The utility of explainable A.I. for MRI analysis: Relating model predictions to neuroimaging features of the aging brain

IntroductionDeep learning models highly accurately predict brain-age from MRI but their explanatory capacity is limited. Explainable A.I. (XAI) methods can identify relevant voxels contributing to model estimates, yet, they do not reveal which biological features these voxels represent. In this study, we closed this gap by relating voxel-based contributions to brain-age estimates, extracted with XAI, to human-interpretable structural features of the aging brain. MethodsTo this end, we associated participant-level XAI-based relevance maps extracted from two ensembles of 3D-convolutional neural networks (3D-CNN) that were trained on T1-weighted and fluid attenuated inversion recovery images of 2016 participants (age range 18-82 years), respectively, with regional cortical and subcortical gray matter volume and thickness, perivascular spaces (PVS) and water diffusion-based fractional anisotropy of main white matter tracts. ResultsWe found that all neuroimaging markers of brain aging, except for PVS, were highly correlated with the XAI-based relevance maps. Overall, the strongest correlation was found between ventricular volume and relevance (r = 0.69), and by feature, temporal-parietal cortical thickness and volume, cerebellar gray matter volume and frontal-occipital white matter tracts showed the strongest correlations with XAI-based relevance. ConclusionOur ensembles of 3D-CNNs took into account a plethora of known aging processes in the brain to perform age prediction. Some age-associated features like PVS were not consistently considered by the models, and the cerebellum was more important than expected. Taken together, we highlight the ability of end-to-end deep learning models combined with XAI to reveal biologically relevant, multi-feature relationships in the brain.

neuroscience↗

bioRxiv2024

Pre-stimulus beta power encodes explicit and implicit perceptual biases in distinct cortical areas

Perception is biased by expectations and previous actions. Pre-stimulus brain oscillations are a potential candidate for implementing biases in the brain. In two EEG studies (43 and 39 participants) on somatosensory near-threshold detection, we investigated the pre-stimulus neural correlates of an (implicit) previous choice bias and an explicit bias. The explicit bias was introduced by informing participants about stimulus probability on a single-trial level (volatile context) or block-wise (stable context). Behavioural analysis confirmed adjustments in the decision criterion and confidence ratings according to the cued probabilities and previous choice-induced biases. Pre-stimulus beta power with distinct sources in sensory and higher-order cortical areas predicted explicit and implicit biases, respectively, on a single subject level and partially mediated the impact of previous choice and stimulus probability on the detection response. We suggest pre-stimulus beta oscillations in distinct brain areas as a neural correlate of explicit and implicit biases in somatosensory perception.

neuroscience↗

bioRxiv2024

Endothelial cannabinoid CB1 receptor deficiency reduces arterial inflammation and lipid uptake in response to atheroprone shear stress

BackgroundPeripherally restricted cannabinoid CB1 receptor antagonists without central side effects hold promise for treating metabolic disorders including diabetes and obesity. In atherosclerosis, the specific effects of peripheral CB1 signaling in vascular endothelial cells (ECs) remain incompletely understood. Methods and resultsEndothelial expression of the CB1 encoding gene CNR1 was detectable in human plaque single-cell RNA sequencing data. In situ hybridization of Cnr1 in murine aortas revealed a significantly increased endothelial expression within atheroprone compared to atheroresistant regions. In vitro, CNR1 was upregulated by oscillatory shear stress (OSS) in human aortic endothelial cells (HAoECs). Endothelial CB1 deficiency (Cnr1EC-KO) in female mice on atherogenic background resulted in pronounced endothelial phenotypic changes, with reduced vascular inflammation and permeability. This resulted in attenuated plaque development with reduced lipid content in female mice, while reduced white and brown adipose tissue mass and liver steatosis were observed in both males and females. Ex vivo imaging of carotid arteries via two-photon microscopy revealed less labeled low density lipoprotein (Dil-LDL) uptake in Cnr1EC-KO. This was accompanied by a significant reduction of aortic endothelial caveolin-1 (CAV1) expression, a key structural protein involved in lipid transcytosis, in female Cnr1EC-KO mice. In vitro, pharmacological blocking with CB1 antagonist AM281 reproduced the inhibition of CAV1 expression and Dil-LDL uptake in response to atheroprone OSS in HAoECs, which was dependent on cAMP-mediated PKA activation. Conversely, the CB1 agonist ACEA increased Dil-LDL uptake and CAV1 expression in HAoECs. Finally, treatment of atherosclerotic mice with the peripheral CB1 antagonist JD-5037 reduced plaque progression, CAV1 and endothelial adhesion molecule expression in female mice. ConclusionsThese results confirm an essential role of endothelial CB1 to the pathogenesis of atherosclerosis. Peripheral CB1 antagonists may hold promise as an effective therapeutic strategy for treating atherosclerosis and related metabolic disorders. NOVELTY AND SIGNIFICANCEWhat is known? O_LIEnhanced endocannabinoid-cannabinoid CB1 receptor signaling has been implicated in metabolic disorders, atherosclerosis, and hypertension, but the cell-specific role of endothelial CB1 in atherosclerosis is not well understood. C_LIO_LIGlobal CB1 antagonists improve metabolic function and inhibit atherosclerotic plaque development in mouse models, but have failed in the clinic due to centrally mediated psychiatric side effects. C_LI What is new? O_LIBased on human single-cell RNA sequencing data, CB1 is expressed in human plaque ECs. C_LIO_LIUsing transgenic mouse models and human primary aortic endothelial cells, we provide evidence for a key role of CB1 in endothelial shear stress response, inflammatory gene expression, and LDL uptake. C_LIO_LIThe underlying signaling pathway of CB1-induced endothelial LDL uptake involves a cAMP-PKA-dependent regulation of caveolin 1 (CAV1) expression, a structural protein of the shear stress sensitive signaling domains of the plasma membrane. C_LIO_LIBy limiting endothelial CAV1 and VCAM1 expression, peripherally restricted CB1 antagonists confer atheroprotection in mice. C_LI Our findings reveal that endothelial CB1 expression is induced by atheroprone shear stress responses and contributes to impaired vascular barrier function, inflammation, and lipid uptake, thereby promoting atherosclerotic lesion formation and progression. By elucidating the transcriptomic pathways regulated by endothelial CB1 and its broad influence on lipid uptake and metabolism in arteries, liver, and brown and white adipose tissue, our study provides insights into novel pathways and potential interventions for the treatment of atherosclerosis and metabolic disorders. The use of peripherally restricted CB1 antagonists that specifically target vascular inflammation and tissue lipid storage could be a complementary and safe therapeutic avenue to treat cardiovascular and metabolic disease comorbidities without altering CB1 signaling in the brain.

immunology↗

bioRxiv2024

Linking brain-heart interactions to emotional arousal in immersive virtual reality

The subjective experience of emotions is linked to the contextualized perception and appraisal of changes in bodily (e.g., heart) activity. Increased emotional arousal has been related to attenuated high-frequency heart rate variability (HF-HRV), lower EEG parieto-occipital alpha power, and higher heartbeat-evoked potential (HEP) amplitudes. We studied emotional arousal-related brain- heart interactions using immersive virtual reality (VR) for naturalistic yet controlled emotion induction. 29 healthy adults (13 women, age: 26{+/-}3) completed a VR experience that included rollercoasters while EEG and ECG were recorded. Continuous emotional arousal ratings were collected during a video replay immediately after. We analyzed emotional arousal-related changes in HF-HRV as well as in BHIs using HEPs. Additionally, we used the oscillatory information in the ECG and the EEG to model the directional information flows between the brain and heart activity. We found that higher emotional arousal was associated with lower HEP amplitudes in a left fronto- central electrode cluster. While parasympathetic modulation of the heart (HF-HRV) and parieto- occipital EEG alpha power were reduced during higher emotional arousal, there was no evidence for the hypothesized emotional arousal-related changes in bidirectional information flow between them. Whole-brain exploratory analyses in additional EEG (delta, theta, alpha, beta and gamma) and HRV (low-frequency, LF, and HF) frequency bands revealed a temporo-occipital cluster, in which higher emotional arousal was linked to decreased brain-to-heart (i.e., gamma[->]HF-HRV) and increased heart-to-brain (i.e., LF-HRV[->]gamma) information flow. Our results confirm previous findings from less naturalistic experiments and suggest a link between emotional arousal and brain-heart interactions in temporo-occipital gamma power.

neuroscience↗

bioRxiv2022

GIP receptor agonism improves dyslipidemia and atherosclerosis independently of body weight in obese mice

Agonism at the receptors for the glucose-dependent insulinotropic polypeptide (GIPR) is a key component of the novel unimolecular co-agonists which are among the most promising drugs in clinical development for the treatment of obesity and diabetes. The therapeutic effect of chronic GIPR agonism to treat dyslipidemia, and thus to reduce the cardiovascular disease risk, has not been explored yet. Herein we found that treatment with a long-acting acylated GIP analog (Acyl-GIP) reduced dyslipidemia and atherogenesis in male LDL receptor knockout mice. Acyl-GIP administration resulted in smaller adipocytes within the inguinal fat depot and RNAseq analysis of the latter revealed that Acyl-GIP may improve dyslipidemia by directly modulating lipid metabolism in this fat depot. This study identified an unanticipated efficacy of chronic GIPR agonist administration to improve dyslipidemia and cardiovascular disease.

pharmacology and toxicology↗

bioRxiv2021

Towards the Interpretability of Deep Learning Models for Human Neuroimaging

Brain-age (BA) estimates based on deep learning are increasingly used as neuroimaging biomarker for brain health; however, the underlying neural features have remained unclear. We combined ensembles of convolutional neural networks with Layer-wise Relevance Propagation (LRP) to detect which brain features contribute to BA. Trained on magnetic resonance imaging (MRI) data of a population-based study (n=2637, 18-82 years), our models estimated age accurately based on single and multiple modalities, regionally restricted and whole-brain images (mean absolute errors 3.37-3.86 years). We find that BA estimates capture aging at both small and large-scale changes, revealing gross enlargements of ventricles and subarachnoid spaces, as well as white matter lesions, and atrophies that appear throughout the brain. Divergence from expected aging reflected cardiovascular risk factors and accelerated aging was more pronounced in the frontal lobe. Applying LRP, our study demonstrates how superior deep learning models detect brain-aging in healthy and at-risk individuals throughout adulthood.

neuroscience↗

bioRxiv2020

Decoding subjective emotional arousal from EEG during an immersive Virtual Reality experience

Immersive virtual reality (VR) enables naturalistic neuroscientific studies while maintaining experimental control, but dynamic and interactive stimuli pose methodological challenges. We here probed the link between emotional arousal, a fundamental property of affective experience, and parieto-occipital alpha power under naturalistic stimulation: 37 young healthy adults completed an immersive VR experience, which included rollercoaster rides, while their EEG was recorded. They then continuously rated their subjective emotional arousal while viewing a replay of their experience. The association between emotional arousal and parieto-occipital alpha power was tested and confirmed by (1) decomposing the continuous EEG signal while maximizing the comodulation between alpha power and arousal ratings and by (2) decoding periods of high and low arousal with discriminative common spatial patterns and a Long Short-Term Memory recurrent neural network. We successfully combine EEG and a naturalistic immersive VR experience to extend previous findings on the neurophysiology of emotional arousal towards real-world neuroscience.

neuroscience↗

bioRxiv2020

Relationship between Regional White Matter Hyperintensities and Alpha Oscillations in Older Adults

Aging is associated with increased white matter hyperintensities (WMHs) and with the alterations of alpha oscillations (7-13 Hz). However, a crucial question remains, whether changes in alpha oscillations relate to aging per se or whether this relationship is mediated by age-related neuropathology like WMHs. Using a large cohort of cognitively healthy older adults (N=907, 60-80 years), we assessed relative alpha power, alpha peak frequency, and long-range temporal correlations (LRTC) from resting-state EEG. We further associated these parameters with voxel-wise WMHs from 3T MRI. We found that a higher prevalence of WMHs in the superior and posterior corona radiata as well as in the thalamic radiation was related to elevated alpha power, with the strongest association in the bilateral occipital cortex. In contrast, we observed no significant relation of the WMHs probability with alpha peak frequency and LRTC. Finally, higher age was associated with elevated alpha power via total WMH volume. Although an increase in alpha oscillations due to WMH can have a compensatory nature, we rather suggest that an elevated alpha power is a consequence of WMH affecting a spatial organization of alpha sources.

neuroscience↗