Biology subjects

Keeser, D.

Publications and source records attributed to Keeser, D..

6 recordsLinked to original sources

bioRxiv2025

Changing the Motivation for Mental Work with Temporal Interference Stimulation

Successful goal-directed behavior often requires the exertion of effortful control processes. The striatum is thought to play a key role in determining whether a goal is worth the required cognitive effort, but whether and how the striatum causally influences effort-based decisions in humans remains unclear. Here, we address this gap by employing transcranial temporal interference stimulation (tTIS), a novel non-invasive brain stimulation technique capable of targeting deeper brain regions. We applied striatum-targeted tTIS to healthy participants performing an effort-based decision task during functional MRI scanning. Supporting the idea that the striatum encodes both the benefits and costs of actions, we found that, on the behavioral level, striatum-targeted tTIS increased the sensitivity to both reward magnitudes and effort costs. At the neural level, this was mirrored by stronger representations of effort demands in the striatum under stimulation as well as by enhanced functional coupling between the striatum and the anterior cingulate cortex, a region at the intersection of motivation and cognition. Together, our findings provide insights into the causal contributions of the striatum to trading-off rewards against effort costs, informing neural accounts of motivated cognition and suggesting novel neural interventions for the treatment of amotivation.

neuroscience↗

bioRxiv2025

Modulating Brain Perfusion, Functional Connectivity, and Metabolite Patterns through Theta Burst Transcranial Focused Ultrasound Stimulation

BackgroundTranscranial ultrasonic stimulation (TUS) is an emerging non-invasive neuromodulation technique with the potential to target both cortical and subcortical brain regions. This study investigates the effects of theta-burst TUS (tb-TUS), a neuromodulatory pattern characterized by bursts of pulses repeated at a theta frequency, on cerebral blood flow, functional connectivity, and metabolite concentrations in the primary motor cortex (M1). The aim of this study is to take a first step towards the mechanistic and methodological feasibility of tb-TUS at the M1 using multimodal neuroimaging. MethodsSeventeen healthy participants underwent a double-blind, sham-controlled crossover design, receiving both active and sham tb-TUS to the left M1 over three days. Multimodal MRI, including pseudo-continuous arterial spin labeling (PCASL), resting-state functional MRI (rs-fMRI), and magnetic resonance spectroscopy (MRS), was conducted at baseline, pre-, and post-stimulation. Acoustic simulations and finger-tapping BOLD-peak signal guided individualized TUS targeting. ResultsActive tb-TUS significantly reduced cerebral blood flow (p < .001) and within-region functional connectivity (p < .001) in the M1 compared to sham stimulation. A non-significant trend towards decreased GABA was observed, with no significant session x condition interaction found for GABA, Glutamate, or Glx concentrations. ConclusionThis pilot study demonstrates that tb-TUS of the M1 induces reductions in cerebral blood flow and functional connectivity in healthy participants. Our findings indicate that tb-TUS may be mitigating neural hyperactivity patterns, but preliminary studies so far arrive at differing results, highlighting the need for further research to replicate our findings, elucidate the underlying mechanisms, and optimize stimulation protocols.

physiology↗

bioRxiv2025

Contralateral Prefrontal and Network Engagement during Left DLPFC 10 Hz rTMS: An Interleaved TMS-fMRI Study in Healthy Adults

BackgroundHigh-frequency repetitive transcranial magnetic stimulation (rTMS) over the left dorsolateral prefrontal cortex (DLPFC) serves as an effective treatment for major depression and other psychiatric disorders. Despite its growing clinical application, the neural mechanisms by which prefrontal rTMS exerts its therapeutic effects remain incompletely understood. To address this gap, we investigated the immediate blood-oxygen-level-dependent (BOLD) activity during 600 stimuli of left DLPFC 10 Hz rTMS in healthy individuals using interleaved TMS-fMRI. MethodsIn a crossover design, 17 healthy subjects received 10 Hz rTMS (60 trains with 9-second intertrain intervals) over the left DLPFC at 40% and 80% of their resting motor threshold (rMT) inside the MR scanner. Results10 Hz rTMS over the left DLPFC elicited BOLD responses in prefrontal regions, cingulate cortex, insula, striatum, thalamus, as well as auditory and somatosensory areas. Notably, our findings revealed that 10 Hz rTMS effects were lateralized towards the contralateral (right) DLPFC. Dose-response effects (40% vs. 80% rTMS) were exclusively observed in contralateral subcortical regions, whereas dose-responses within the DLPFC showed substantial inter-individual variability. ConclusionsThe 10 Hz rTMS protocol used in this study induced distinct target engagement and propagation patterns in the prefrontal cortex. These patterns differ from our previous interleaved TMS-fMRI findings using 600 stimuli of left DLPFC intermittent theta burst stimulation (iTBS) at the same intensities. Thus, interleaved TMS-fMRI emerges as a valuable method for comparing clinical prefrontal rTMS protocols regarding their immediate effect on brain circuits in order to differentiate their action mechanisms and to potentially inform clinical applications.

neuroscience↗

bioRxiv2024

How to measure functional connectivity using resting-state fMRI? A comprehensive empirical exploration of different connectivity metrics

BackgroundFunctional connectivity in the context of functional magnetic resonance imaging is typically quantified by Pearso[n]s or partial correlation between regional time series of the blood oxygenation level dependent signal. However, a recent interdisciplinary methodological work proposes more than 230 different metrics to measure similarity between different types of time series. ObjectiveHence, we systematically evaluated how the results of typical research approaches in functional neuroimaging vary depending on the functional connectivity metric of choice. We further explored which metrics most accurately detect neural decline induced by age and malignant brain tumors, aiming to initiate a debate on how best assessing brain connectivity in functional neuroimaging research. MethodsWe addressed both research questions using four independent neuroimaging datasets, comprising multimodal data from a total of 1187 individuals. We analyzed resting-state functional sequences to calculate functional connectivity using 20 representative metrics from four distinct mathematical domains. We further used T1- and T2-weighted images to compute regional brain volumes, diffusion-weighted imaging data to build structural connectomes, and pseudo-continuous arterial spin labeling to measure regional brain perfusion. ResultsFirst, our results demonstrate that the results of typical functional neuroimaging approaches differ fundamentally depending on the functional connectivity metric of choice. Second, we show that correlational and distance metrics are most appropriate to cover neural decline induced by age. In this context, partial correlation performs worse than other correlational metrics. Third, our findings suggest that the FC metric of choice depends on the utilized scanning parameters, the regions of interest, and the individual investigated. Lastly, beyond the major objective of this study, we provide evidence in favor of brain perfusion measured via pseudo-continuous arterial spin labeling as a robust neural entity mirroring age-related neural and cognitive decline. ConclusionOur empirical evaluation supports a recent theoretical functional connectivity framework. Future functional imaging studies need to comprehensively define the study-specific theoretical property of interest, the methodological property to assess the theoretical property, and the confounding property that may bias the conclusions.

neuroscience↗

bioRxiv2023

Neural Mechanisms of Sequential Dependence in Time Perception: The Impact of Prior Task and Memory Processing

Our perception and decision-making are susceptible to prior context. Such sequential dependence has been extensively studied in the visual domain, but less is known about its impact on time perception. Moreover, there are ongoing debates about whether these sequential biases occur at the perceptual stage or during subsequent post-perceptual processing. Using functional Magnetic Resonance Imaging (fMRI), we investigated neural mechanisms underlying temporal sequential dependence and the role of action in time judgments across trials. Participants performed a timing task where they had to remember the duration of green coherent motion and were cued to either actively reproduce its duration or simply view it passively. We found that sequential biases in time perception were only evident when the preceding task involved active duration reproduction. Merely encoding a prior duration without reproduction failed to induce such biases. Neurally, we observed activation in networks associated with timing, such as striato-thalamo-cortical circuits, and performance monitoring networks, particularly when a "Response" trial was anticipated. Importantly, the hippocampus showed sensitivity to these sequential biases, and its activation negatively correlated with the individuals sequential bias following active reproduction trials. These findings highlight the significant role of memory networks in shaping time-related sequential biases at the post-perceptual stages. Significance StatementOur study explores the neural mechanisms of sequential dependence in time perception and reveals that active reproduction of time duration in the previous trial can bias subsequent estimates, resulting in a sequential dependence effect. In contrast, passive viewing of a stimulus without reproducing its duration does not produce this effect. At the neural level, we observed increased activity in memory regions like the hippocampus when sequential biases were reduced. Furthermore, we found a negative correlation between hippocampal activation and sequential bias following active reproduction trials, suggesting that the involvement of memory networks mediates how we are influenced by past experiences when judging time.

neuroscience↗

bioRxiv2021

Intrinsic Network Activity Reflects the Ongoing Experience of Chronic Pain

Analyses of intrinsic network activity have been instrumental in revealing cortical processes that are altered in chronic pain patients. However, such studies have not accounted for variable time courses of network activity and subjective pain experience. In a novel approach, we aimed to elucidate how intrinsic functional networks evolve in regard to the fluctuating intensity of the experience of chronic pain. In a longitudinal study with 156 fMRI sessions, 20 chronic back pain patients and 20 chronic migraine patients were asked to continuously rate the intensity of their endogenous pain. Using group independent component analysis and dual-regression, we extracted the time courses of 100 independent components separately for chronic back pain and chronic migraine. We investigated the relationship between the fluctuation of intrinsic network activity with the time course of subjective pain ratings. For chronic back pain, we found increased cortical network activity for the salience network and a local pontine network, as well as decreased network activity in the anterior and posterior default mode network for higher pain intensities. Higher pain intensities in chronic migraine were accompanied with lower activity in a prefrontal cortical network. By taking the perspective of the individual, we focused on the processes that matter for each patient, which are phases of relatively low pain and more straining phases of relatively high pain. The present design of ongoing assessment of the endogenous pain can be a powerful and promising tool to assess the signature of a patients endogenous pain encoding over weeks and months.

neuroscience↗