Biology subjects

Walther, S.

Publications and source records attributed to Walther, S..

4 recordsLinked to original sources

bioRxiv2025

Continuous theta-burst stimulation of the ventromedial prefrontal cortex reduces Pavlovian go-invigoration and enhances thalamo-striatal reward prediction error signals

The ventromedial prefrontal cortex (vmPFC) represents value, i.e. whether environmental cues are good or bad. Rewarding cue value is aligned with a tendency to act or to inhibit in case of potential punishment, a so-called Pavlovian Bias. Value-related vmPFC activation may therefore impact Pavlovian bias. However, it remains unknown how the activity in the vmPFC modulates the Pavlovian bias. Thus, we applied continuous theta-burst stimulation (cTBS), a non-invasive protocol that transiently reduces cortical excitability, over the vmPFC in a single-blinded, between-subject study. 90 healthy adults performed a motivational Go/NoGo learning task during fMRI after receiving cTBS (n=45) or sham (n=45) stimulation. Behaviourally, cTBS reduced overall Go response rates and slowed reaction times. Computational modelling showed a decrease in the learning rate, selectively for rewarding outcomes. Computational fMRI analysis showed stronger reward prediction error (RPE) signals in the vmPFC, mediodorsal thalamus, and left dorsal striatum after cTBS, without changes in neural signals at cue onset. These findings provide causal evidence that the vmPFC drives the action-invigoration component of the Pavlovian bias. Significance statementWe causally link ventromedial prefrontal cortex (vmPFC) function to motivated action in humans. In a single-blind cTBS-fMRI study (n=90), transient vmPFC inhibition reduced Go responding, slowed reaction times, and selectively lowered the positive learning rate early in learning. At the same time, reward-prediction-error signals increased in mediodorsal thalamus, dorsal striatum, and vmPFC, while cue-onset value/choice signals were unchanged. Together, the results indicate that vmPFC normally speeds value updating and invigorates actions; when inhibited, control shifts toward slower, subcortically supported learning under higher uncertainty.

neuroscience↗

bioRxiv2024

The FAIR-Device - a non-lethal and generalist semi-automatic Malaise trap for insect biodiversity monitoring: Proof of concept

Field monitoring plays a crucial role in understanding insect dynamics within ecosystems. It facilitates pest distribution assessment, control measure evaluation, and prediction of pest outbreaks. Additionally, it provides important information on bioindicators with which the state of biodiversity and ecological integrity in specific habitats and ecosystems can be accurately assessed. However, traditional monitoring systems can present various difficulties, leading to a limited temporal and spatial resolution of the obtained information. Despite recent advancements in automatic insect monitoring traps, also called e-traps, most of these systems focus exclusively on studying agricultural pests, rendering them unsuitable for monitoring diverse insect populations. To address this issue, we introduce the Field Automatic Insect Recognition (FAIR)-Device, a novel non-lethal field tool that relies on semi-automatic image capture and species identification using artificial intelligence via the iNaturalist platform. Our objective was to develop an automatic, cost-effective, and non-specific monitoring solution capable of providing high-resolution data for assessing insect diversity. During a 26-day proof-of-concept evaluation, the FAIR-Device recorded 24.8 GB of video, identifying 431 individuals from 9 orders, 50 families, and 69 genera. While improvements are possible, our device demonstrated potential as a cost-effective, non-lethal tool for monitoring insect biodiversity. Looking ahead, we envision new monitoring systems such as e-traps as valuable tools for real-time insect monitoring, offering unprecedented insights for ecological research and agricultural practices.

zoology↗

bioRxiv2020

Exploring the limits of ComBat method for multi-site diffusion MRI harmonization

The findings from diffusion-weighted magnetic resonance imaging (dMRI) studies often show inconsistent and sometimes contradictory results due to small sample sizes as well as differences in acquisition parameters and pre-/post-processing methods. To address these challenges, collaborative multi-site initiatives have provided an opportunity to collect larger and more diverse groups of subjects, including those with neuropsychiatric disorders, leading to increased power and findings that may be more representative at the group and individual level. With the availability of these datasets openly, the ability of joint analysis of multi-site dMRI data has become more important than ever. However, intrinsic- or acquisition-related variability in scanner models, acquisition protocols, and reconstruction settings hinder pooling multi-site dMRI directly. One powerful and fast statistical harmonization method called ComBat (https://github.com/Jfortin1/ComBatHarmonization) was developed to mitigate the "batch effect" in gene expression microarray data and was adapted for multi-site dMRI harmonization to reduce scanner/site effect. Our goal is to evaluate this commonly used harmonization approach using a large diffusion MRI dataset involving 542 individuals from 5 sites. We investigated two important aspects of using ComBat for harmonization of fractional anisotropy (FA) across sites: First, we assessed how well ComBat preserves the inter-subject biological variability (measured by the effect sizes of between-group FA differences) after harmonization. Second, we evaluated the effect of minor differences in pre-processing on ComBats performance. While the majority of effect sizes are mostly preserved in some sites after harmonization, they are not well-preserved at other sites where non-linear scanner contributions exist. Further, even minor differences in pre-processing can yield unwanted effects during ComBat harmonization. Thus, our findings suggest paying careful attention to the data being harmonized as well as using the same processing pipeline while using ComBat for data harmonization.

neuroscience↗

bioRxiv2020

Altered central pain processing in fibromyalgia - a multimodal neuroimaging case-control study using arterial spin labelling

Fibromyalgia is characterized by chronic pain and a striking discrepancy between objective signs of tissue damage and severity of pain. Function and structural alterations in brain areas involved in pain processing may explain this feature. Previous case-control studies in fibromyalgia focused on acute pain processing using experimentally-evoked pain paradigms. Yet, these studies do not allow conclusions about chronic, stimulus-independent pain. Resting-state cerebral blood flow (rsCBF) acquired by arterial spin labelling (ASL) may be a more accurate marker for chronic pain. The objective was to integrate four different functional and structural neuroimaging markers to evaluate the neural correlate of chronic, stimulus-independent pain using a resting-state paradigm. In line with the pathophysiological concept of enhanced central pain processing we hypothesized that rsCBF is increased in fibromyalgia in areas involved in processing of acute pain. We performed an age matched case-control study of 32 female fibromyalgia patients and 32 pain-free controls and calculated group-differences in rsCBF, resting state functional connectivity, grey matter density and cortical thickness using whole-brain and region of interest analyses. We adjusted all analyses for depression and anxiety. As centrally acting drugs are likely to interfere with neuroimaging markers, we performed a subgroup analysis limited to patients not taking such drugs. We found no differences between cases and control in rsCBF of the thalamus, the basal ganglia, the insula, the somatosensory cortex, the prefrontal cortex, the anterior cingulum and supplementary motor area as brain previously identified to be involved in acute processing in fibromyalgia. The results remained robust across all four neuroimaging markers and when limiting the study population to patients not taking centrally acting drugs and matched controls. In conclusion, we found no evidence for functional or structural alterations in brain areas involved in pain processing in fibromyalgia that could reflect neural correlates of chronic stimulus-independent pain.

neuroscience↗