Biology subjects

Krause, F.

Publications and source records attributed to Krause, F..

12 recordsLinked to original sources

bioRxiv2025

The Neural Architecture of Dream Recall Frequency: Insights from Interindividual Variations in Brain Structure and Function

Dreaming represents a complex and universal aspect of human sleep, yet it remains an intriguing phenomenon, with the neural mechanisms underlying dream experiences and their frequency not fully understood. This study employs a multimodal neuroimaging approach, integrating quantitative multi-parameter mapping, diffusion tensor imaging, and resting-state functional MRI, to investigate the neural correlates of dream recall frequency (DRF) in a large cohort of 258 healthy individuals. By employing Linked Independent Component Analysis (LICA), we were able to discern distinctive patterns of brain structure and function that correlated with variations in DRF. Our findings elucidate a complex relationship between dream recall and brain microstructure integrity, particularly in white matter regions of the orbitofrontal cortex, parahippocampal gyrus, superior parietal lobule, and occipital cortex. Higher DRF was related to increased white matter microstructure integrity in these regions and decreased gray matter volume in occipital and temporal areas. In terms of functional measures, higher DRF was associated with reduced connectivity across a range of resting-state networks, including the default mode, visual, and dorsal attention networks. This was particularly evident in the right precuneus and posterior cingulate cortex. These results suggest that enhanced dream recall may be related to the organization of higher-order visual and cognitive processing areas, supporting a top-down model of dreaming. This study contributes to a more comprehensive understanding of the neural substrates underlying individual differences in dream recall, offering a foundation for future investigations into the neurobiology and causal relationships of dreaming.

neuroscience↗

bioRxiv2025

Schistosoma mansoni-induced host immunopathology is gut microbiota dependent

Despite progress in schistosomiasis control during recent decades in endemic areas, this parasitic blood-fluke infection continues to pose a substantial public health burden. In depth understanding of the mechanisms behind the complex immunopathology and drivers of morbidity in schistosomiasis is urgently needed. Chronic infection with the parasitic blood fluke Schistosoma mansoni manifests the most severe pathology in relation to egg-induced host immune responses and fibrosis development. Host immune homeostasis is influenced by the commensal gut microbiota, which may therefore also affect systemic immunopathology induced by S. mansoni. Both humans and experimental animal models show metabolomic changes related to gut microbial and liver metabolism during S. mansoni infection, further supporting a link between gut microbiota and regulation of S. mansoni pathology. To investigate whether a radically changed gut microbiota composition would result in changed S. mansoni egg-induced pathology, a mouse model combining antibiotic treatment and infection was established. In the model, the commensal gut microbial composition of female C57BL/6-NTac mice was altered by oral administration of a broad-spectrum ampicillin-vancomycin cocktail prior to infection with S. mansoni and throughout the experiment. An ecosystem view of the host immune milieu was collated by measuring a wide range of parameters: gut microbiome characterisation, immune profiling on the transcriptional level (ileum and liver) supported by flow cytometry of cells (spleen and mesenteric lymph nodes) and bead-based measurements of immune parameters in sera, short-chain fatty acid measurements in sera and caecal content, intestinal permeability assessment, liver enzyme levels in sera, and histology and stereology to characterise immunopathology (ileum and liver). The application of stereological principles to address the non-spherical nature of egg-induced liver granulomas and ileum inflammation supported by liver enzyme levels, collagen deposition, and immune parameters, enabled demonstration of significantly less granuloma formation in livers from antibiotics treated mice compared to controls. The observed difference in the degree of egg-induced inflammatory response in livers from infected mice mediated by antibiotics treatment, was not observed in ileum tissue and could not be explained by infection burden. Our mouse model results demonstrate a role for the gut microbiota and intestinal immune milieu in regulation of systemic S. mansoni infection-driven liver pathology and, hence, potential morbidity. In translational context, these findings warrant that drivers of gut microbial changes and intestinal immune milieu must be considered when pursuing novel holistic interventions for treatment or alleviation of persistent schistosomiasis.

immunology↗

bioRxiv2024

Neural Mechanisms of Feedback Processing and Behavioral Adaptation during Neurofeedback Training

The acquisition of new skills is facilitated by providing individuals with feedback that reflects their performance. This process creates a closed loop that involves feedback processing and regulation recalibration to promote effective training. Functional magnetic resonance imaging (fMRI)-based neurofeedback is unique in applying this principle by delivering direct feedback on the self-regulation of brain activity. Understanding how feedback-driven learning occurs requires examining how feedback is evaluated and how regulation adjusts in response to feedback signals. In this pre-registered mega-analysis, we re-analyzed data from eight intermittent fMRI neurofeedback studies (N = 153 individuals) to investigate brain regions where activity and connectivity are linked to feedback processing and regulation recalibration (i.e., regulation after feedback) during training. We harmonized feedback scores presented during training in these studies and computed their linear associations with brain activity and connectivity using parametric general linear model analyses. We observed that, during feedback processing, feedback scores were positively associated with (1) activity in the reward system, dorsal attention network, default mode network, and cerebellum; and with (2) reward system-related connectivity within the salience network. During regulation recalibration, no significant associations were observed between feedback scores and either activity or associative learning-related connectivity. Our results suggest that neurofeedback is processed in the reward system, supporting the theory that reinforcement learning shapes this form of brain training. In addition, the involvement of large-scale networks in feedback processing, continuously transitioning between evaluating external feedback and internally assessing the adopted cognitive state, suggests that higher-level processing is integral to this type of learning. Our findings highlight the pivotal role of performance-related feedback as a driving force in learning, potentially extending beyond neurofeedback training to other feedback-based processes. Key PointsWe conducted a pre-registered mega-analysis integrating data from eight fMRI neurofeedback studies to examine feedback processing and regulation recalibration during neurofeedback training. During feedback processing, feedback was associated with activity in the reward system, dorsal attention network, default mode network, and cerebellum; as well as with reward system-related connectivity within the salience network. We found no positive results during regulation blocks; however, additional analyses suggest that recalibration may have already occurred during feedback presentation.

neuroscience↗

bioRxiv2024

A non-catalytic function of a disintegrin and metalloprotease 10 determines hepatic progenitor cell fate

During chronic liver disease, hepatocytes may undergo proliferative arrest, leading to the activation, expansion and differentiation of hepatic progenitor cells (HPCs). Here we observe that expression of A Disintegrin And Metalloprotease (ADAM) 10 is increased in human and murine chronic liver disease correlating with HPC expansion. We report that proteolytic processing of ADAM10 by ADAM9 and generation of an ADAM10 intracellular domain that translocates to the nucleus, rather than ADAM10 enzymatic activity is essential for the regulation of HPC gene expression and differentiation. Genetic loss of ADAM10 in vitro and in vivo enhances stemness gene expression, increases the accumulation of undifferentiated HPCs and promotes the formation of liver fibrosis. Taken together, we demonstrate that a non-catalytic function of ADAM10 is an essential regulator of HPC fate and HPC-driven regeneration. Our data ascribe a non-proteolytic function to ADAM proteases which may be a general concept in adult tissue stem cells.

cell biology↗

bioRxiv2024

ADAM17 regulates hepatic DNA damage repair and tumour formation

BackgroundHepatocellular carcinoma (HCC) is one of the leading causes of cancer deaths worldwide. Still, therapy options for this tumour entity are limited and novel therapeutic options are highly sought after. Genomic instability of hepatocytes promotes oncogenic transformation and underlies the regulation of micro-environmental signalling cues. The membrane-bound a disintegrin and metalloprotease (ADAM) 17 is a major regulator of micro-environmental signals through the proteolytic release of paracrine factors. However, its role in hepatic DNA damage repair and its contribution to hepatic tumourigenesis is still unclear. MethodsWe investigated the effect of ADAM17 on diethylnitrosamine (DEN)-induced acute DNA damage and subsequent DNA damage repair by utilizing mice with ubiquitous or myeloid-specific genetic deficiency in ADAM17. DNA double strand breaks and inflammation were investigated by immunofluorescence of liver tissue sections. tumourigenesis in mice with myeloid-specific ADAM17-deficiency was investigated in a chemically induced hepatocarcinogenesis model. ResultsADAM17 on myeloid cells, in particular Kupffer cells is essentially involved in the non-cell autonomous regulation of DNA damage repair in hepatocytes. Parenchymal ADAM17 regulates hepatocyte fate and recruitment of infiltrating myeloid cells. Furthermore, myeloid ADAM17 promotes hepatic tumour initiation and correlates with poor prognosis in human HCC. ConclusionsWe identified ADAM17, in particular on myeloid cells as an essential driver of hepatic tumourigenesis and as a potential novel drug target for the treatment of hepatic malignancies.

cancer biology↗

bioRxiv2024

Neural correlates of nightmares revisited: findings from large-scale fMRI cohorts

Study ObjectivesNightmares are linked to daytime distress and psychiatric and neurological disorders. However, knowledge about the brain regions involved in nightmare production is sparse. This study aimed to examine the relationship between nightmare frequency and the functional connectivity of the amygdala with the prefrontal cortex, which is central to emotional regulation. Additionally, the study sought to replicate previous findings on the neural correlates of nightmares using two large cohorts. Methods464 participants underwent functional and structural MRI recordings and answered questions assessing nightmare and dream recall frequency. A general linear model assessed the voxelwise correlation between the amygdala-prefrontal cortex connectivity with nightmare frequency. Additionally, regional homogeneity (ReHo) maps were calculated, high and low nightmare frequency and the entire nightmare frequency spectrum contrasts were determined while controlling for age, sex, and dream recall frequency. ResultsThe study did not find a significant correlation between nightmare frequency and amygdala-prefrontal cortex connectivity. Previous ReHo findings of group differences between high and low nightmare frequency could not be replicated. However, parametric analysis revealed an association between nightmare frequency and ReHo differences in the cerebellum. ConclusionsThis failure to confirm hypothesized and previously reported results, especially with a larger sample size, suggests a need to reevaluate the existing knowledge of the neural correlates of nightmares and consider individual differences such as personality, trauma history, and cognitive processes. Overall, our findings highlight the complexities of interpreting neuroimaging data in sleep research.

neuroscience↗

bioRxiv2023

Changes in large-scale neural networks under stress are linked to affective reactivity to stress in real life

Controlled laboratory stress induction procedures are very effective in inducing physiological and subjective stress. However, whether such stress responses are representative for stress reactivity in real life is not clear. Using a combined within-subject functional MRI laboratory stress and ecological momentary assessment stress paradigm, we investigated dynamic shifts in large-scale neural network configurations under stress and how these relate to affective reactivity to stress in real life. Laboratory stress induction resulted in significantly increased cortisol levels, and shifts in task-driven neural activity including increased salience network (SN) activation in an oddball task and decreased default mode network activity in a memory retrieval task. Crucially, individuals showing increased SN reactivity specifically in the early phase of the acute stress response also expressed increased affective reactivity in real life. Our findings provide (correlational) evidence that real-life affective stress reactivity is driven primarily by vigilant attentional reorienting mechanisms associated with SN.

neuroscience↗

bioRxiv2023

A Comparison of fMRI Data-Derived and Physiological Data-Derived Methods for Physiological Noise Correction

Physiological noise substantially affects fMRI data quality, particularly in areas near fluid-filled cavities and arteries such as the brainstem. Peripheral physiological signals can be recorded alongside fMRI and incorporated into general linear models to remove variance associated with cardiac and respiratory cycles using methods such as Retrospective Image Correction (RETROICOR). In contrast, data-driven noise reduction methods such as anatomical component correction (aCompCor) and independent component analysis based automatic removal of motion artifacts (ICA-AROMA) do not rely on additional peripheral physiological recordings. These methods have shown efficacy in correcting for motion, scanner as well as physiological artifacts. This raises the question of whether logistically demanding peripheral recordings offer added value. We therefore used nuisance regression methods based on peripherally recorded physiology (RETROICOR, heart rate, respiratory volume) as well as fMRI data itself (ICA-AROMA, aCompCor) to account for noise in a resting-state data set. Subsequently, we compared variance explained by the respective methods and improvements in temporal signal-to-noise ratio throughout different regions of interest in the brain. Consistent with prior research, RETROICOR, heart rate and respiratory volume explain significant variance throughout the brain with peaks around areas of strong cardiac pulsations. ICA-AROMA and aCompCor account for a substantial proportion of the variance explained by the methods using peripheral physiology. Nonetheless, the methods based on peripheral physiological recordings retain unique explanatory power. Analysis revealed a pattern of unreliability of ICA-AROMA to consistently identify and remove physiological noise across recordings in each participant, which is compensated by RETROICOR, heart rate and respiratory volume. This unreliability partially results from misclassifications in the noise selection models of ICA-AROMA. Our results suggest that it is advisable to additionally apply cleaning based on peripheral physiological recordings, especially when assessing inter-individual differences and areas with regionally high levels of physiological noise.

neuroscience↗

bioRxiv2021

Using wearable biosensors and ecological momentary assessments for the detection of prolonged stress in real life

BackgroundIncreasing efforts toward prevention of stress-related mental disorders have created a need for unobtrusive real-life monitoring of stress-related symptoms. Wearable devices have emerged as a possible solution to aid in this process, but their use in real-life stress detection has not been systematically investigated. MethodsUsing ecological momentary assessments (EMA) combined with wearable biosensors for ecological physiological assessments (EPA), we investigated the impact of an ecological stressor (i.e., an exam week) on physiological arousal and affect. With this paradigm we investigated whether we could use wearable devices to detect stress states using machine learning models. ResultsDuring stressful high-stake exam (versus control) weeks, participants reported increased negative affect and decreased positive affect. Intriguingly, physiological arousal was decreased on average during the exam week. Time-resolved analyses revealed peaks in physiological arousal associated with both self-reported stress and self-reported positive affect, while the overall decrease in physiological arousal was mediated by lower positive affect during the stress period. We then used machine learning to show that a combination of EMA and physiology yields optimal identification of stress states. ConclusionsOur findings highlight the potential of wearable biosensors in stress-related mental-health monitoring, but critically show that psychological context is essential for interpreting physiological arousal detected using these devices.

physiology↗

bioRxiv2021

Self-regulation of stress-related large-scale brain network balance using real-time fMRI Neurofeedback

It has recently been shown that acute stress affects the allocation of neural resources between large-scale brain networks, and the balance between the executive control network and the salience network in particular. Maladaptation of this dynamic resource reallocation process is thought to play a major role in stress-related psychopathology, suggesting that stress resilience may be determined by the retained ability to adaptively reallocate neural resources between these two networks. Actively training this ability could hence be a potentially promising way to increase resilience in individuals at risk for developing stress-related symptomatology. Using real-time functional Magnetic Resonance Imaging, the current study investigated whether individuals can learn to self-regulate stress-related large-scale network balance. Participants were engaged in a bidirectional and implicit real-time fMRI neurofeedback paradigm in which they were intermittently provided with a visual representation of the difference signal between the average activation of the salience and executive control networks, and tasked with attempting to self-regulate this signal. Our results show that, given feedback about their performance over three training sessions, participants were able to (1) learn strategies to differentially control the balance between SN and ECN activation on demand, as well as (2) successfully transfer this newly learned skill to a situation where they (a) did not receive any feedback anymore, and (b) were exposed to an acute stressor in form of the prospect of a mild electric stimulation. The current study hence constitutes an important first successful demonstration of neurofeedback training based on stress-related large-scale network balance - a novel approach that has the potential to train control over the central response to stressors in real-life and could build the foundation for future clinical interventions that aim at increasing resilience. HighlightsO_LIAcute stress affects the allocation of neural resources between large-scale brain networks C_LIO_LIWe provide a first successful demonstration of neurofeedback training based on stress-related large-scale brain networks C_LIO_LINovel approach has the potential to train control over central response to stressors in real-life C_LIO_LICould build foundation for future clinical interventions to increase resilience C_LI

neuroscience↗

bioRxiv2019

Active head motion reduction in Magnetic Resonance Imaging using tactile feedback

Head motion is a common problem in clinical as well as empirical (functional) Magnetic Resonance Imaging applications, as it can lead to severe artefacts that reduce image quality. The scanned individuals themselves, however, are often not aware of their head motion. The current study explored whether providing subjects with this information using tactile feedback would reduce their head motion and consequently improve image quality. In a single session that included six runs, 24 participants performed three different cognitive tasks: (1) passive viewing, (2) mental imagery, and (3) speeded responses. These tasks occurred in two different conditions: (a) with a strip of medical tape applied from one side of the MR head-coil, via the participants forehead, to the other side, and (b) without the medical tape being applied. Results revealed that application of medical tape to the forehead of subjects to provide tactile feedback significantly reduced both translational as well as rotational head motion. While this effect did not differ between the three cognitive tasks, there was a negative quadratic relationship between head motion with and without feedback. That is, the more head motion a subject produced without feedback, the stronger the motion reduction given the feedback. In conclusion, the here tested method provides a simple and cost-efficient way to reduce subjects head motion, and might be especially beneficial when extensive head motion is expected a priori.

neuroscience↗

bioRxiv2019

The microbiota regulates inflammatory responses to toxin-induced CNS demyelination but has minimal impact on remyelination

The microbiota is now recognised as a key influence on the host immune response in the central nervous system (CNS). As such, there has been some progress towards therapies that modulate the microbiota with the aim of limiting immune-mediated demyelination, as occurs in multiple sclerosis. However, remyelination - the regeneration of myelin sheaths - also depends upon an immune response, and the effects that such interventions might have on remyelination have not yet been explored. Here, we show that the inflammatory response during CNS remyelination in mice is modulated by antibiotic or probiotic treatment, as well as in germ-free mice. We also explore the effect of these changes on oligodendrocyte progenitor cell differentiation, which is inhibited by antibiotics but unaffected by our other interventions. These results reveal that high combined doses of oral antibiotics negatively influence remyelination and further our understanding of how mammalian regeneration relates to the microbiota.

neuroscience↗