Biology subjects

Petzschner, F. H.

Publications and source records attributed to Petzschner, F. H..

7 recordsLinked to original sources

bioRxiv2025

Differences in layer-specific activation of the insula during interoceptive vs. exteroceptive attention

Attention modulates the relative weighting of information and plays a critical role in modern theories of perception. While its role in exteroceptionthe perception of the external environmenthas been extensively studied, attentional processes in interoception, the perception of bodily states, are less well understood. In this study, we exploited high-field (7 Tesla) functional magnetic resonance imaging and concurrent field monitoring to investigate interoceptive attention at the level of cortical layers during a heartbeat attention task. Voxel-wise analyses reveal increased activity in the bilateral dorsal mid-insula during interoceptive attention (attending to ones heartbeat) compared to exteroceptive attention (attending to auditory white noise). Layer-specific analyses further demonstrate that this difference in activity is significantly higher in upper compared to lower cortical layers. This activation pattern persists after accounting for potential vascular artifacts through a deconvolution analysis with a physiological point spread function (PSF). To our knowledge, these findings represent the first empirical demonstration of layer-specific processes during interoceptive attention in human cortex. They may prove useful to inform and constrain theories of computational principles and physiological implementation of interoception.

neuroscience↗

bioRxiv2025

Altered Decision-Making Across Acute and Chronic Pain States: A Bias Towards Context-Dependent Valuations

Chronic pain is often characterized by the entrenchment of maladaptive behaviors -- avoidance, inactivity, and hypervigilance -- that outlast tissue damage. A central but mechanistically underspecified question is how behaviors acquired during acute pain become locked in as pain chronifies. Influential accounts, including the fear-avoidance model, suggest that behavioral patterns learned in a specific context -- such as avoidance during acute injury -- overgeneralize to situations where they are no longer advantageous. Whether this reflects altered learning or changes in how learned information guides decisions has remained unclear. To address this, we administered a probabilistic reinforcement learning task to 239 individuals with chronic pain, acute pain, or no pain, designed to dissociate two decision strategies: reliance on recent reinforcement history -- what was reinforced in a prior context -- versus global expected value -- the objective worth of an option regardless of context. Learning performance was comparable across all groups, confirming intact associative learning. However, groups differed significantly in decision-making: individuals with chronic pain favored options with stronger context-dependent reinforcement history over those with higher global expected value; however, those without pain showed no preference for one over the other, with the acute pain group showing an intermediate pattern. Computational modeling confirmed this, with chronic pain patients showing significantly reduced weighting toward global expected value. Critically, this shift tracked pain duration rather than intensity -- suggesting prolonged pain exposure gradually biases decisions away from global expected value towards a context-dependent history. These findings offer a computational explanation for behavioral persistence in chronic pain, and this duration-dependent shift, already evident in the acute pain group, may represent an early cognitive signature of chronification.

neuroscience↗

bioRxiv2025

Neurochemical markers of uncertainty processing in humans

How individuals process and respond to uncertainty has important implications for cognition and mental health. Here we use computational phenotyping to examine individualised "uncertainty fingerprints" in relation to neurometabolites and trait anxiety in humans. We introduce a novel categorical state-transition extension of the Hierarchical Gaussian Filter (HGF) to capture implicit learning in a four-choice probabilistic sensorimotor reversal learning task by tracking beliefs about stimulus transitions. Using 7-Tesla Magnetic Resonance Spectroscopy, we measured baseline neurotransmitter levels in the primary motor cortex (M1). Model-based results revealed dynamic belief updating in response to environmental changes. We further found region-specific relationships between M1 glutamate+ glutamine levels and prediction errors and volatility beliefs, revealing an important neural marker of probabilistic reversal learning in humans. High trait anxiety was associated with faster post-reversal responses. By integrating computational modelling with neurochemical assessments, this study provides novel insights into the neurocomputations that drive individual differences in processing uncertainty.

neuroscience↗

bioRxiv2023

Serotonin Reduces Belief Stickiness

Serotonin fosters cognitive flexibility, but how, exactly, remains unclear. We show that serotonin reduces belief stickiness: the tendency to get "stuck" in a belief about the state of the world despite incoming contradicting evidence. Participants performed a task assessing belief stickiness in a randomized, double-blind, placebo-controlled study using a single dose of the selective serotonin reuptake inhibitor (SSRI) escitalopram. In the escitalopram group, higher escitalopram plasma levels reduced belief stickiness more, resulting in better inference about the state of the world. Moreover, participants with sufficiently high escitalopram plasma levels had less belief stickiness, and therefore better state inference, than participants on placebo. Exaggerated belief stickiness is exemplified by obsessions: "sticky" thoughts that persist despite contradicting evidence. Indeed, participants with more obsessions had greater belief stickiness, and therefore worse state inference. The opposite relations of escitalopram and obsessions with belief stickiness may explain the therapeutic effect of SSRIs in obsessive-compulsive disorder.

neuroscience↗

bioRxiv2021

Interoception of breathing and its relationship with anxiety

Interoception, the perception of internal bodily states, is thought to be inextricably linked to affective qualities such as anxiety. While interoception spans sensory to metacognitive processing, it is not clear whether anxiety is differentially related to these processing levels. Here we investigated this question in the domain of breathing, using computational modelling and high-field (7 Tesla) fMRI to assess brain activity relating to dynamic changes in inspiratory resistance of varying predictability. Notably, the anterior insula was associated with both breathing-related prediction certainty and prediction errors, suggesting an important role in representing and updating models of the body. Individuals with low vs. moderate anxiety traits showed differential anterior insula activity for prediction certainty. Multimodal analyses of data from fMRI, computational assessments of breathing-related metacognition, and questionnaires demonstrated that anxiety-interoception links span all levels from perceptual sensitivity to metacognition, with strong effects seen at higher levels of interoceptive processes.

neuroscience↗

bioRxiv2021

TAPAS: an open-source software package for Translational Neuromodeling and Computational Psychiatry

Psychiatry faces fundamental challenges with regard to mechanistically guided differential diagnosis, as well as prediction of clinical trajectories and treatment response of individual patients. This has motivated the genesis of two closely intertwined fields: (i) Translational Neuromodeling (TN), which develops "computational assays" for inferring patient-specific disease processes from neuroimaging, electrophysiological, and behavioral data; and (ii) Computational Psychiatry (CP), with the goal of incorporating computational assays into clinical decision making in everyday practice. In order to serve as objective and reliable tools for clinical routine, computational assays require end-to-end pipelines from raw data (input) to clinically useful information (output). While these are yet to be established in clinical practice, individual components of this general end-to-end pipeline are being developed and made openly available for community use. In this paper, we present the Translational Algorithms for Psychiatry-Advancing Science (TAPAS) software package, an open-source collection of building blocks for computational assays in psychiatry. Collectively, the tools in TAPAS presently cover several important aspects of the desired end-to-end pipeline, including: (i) tailored experimental designs and optimization of measurement strategy prior to data acquisition, (ii) quality control during data acquisition, and (iii) artifact correction, statistical inference, and clinical application after data acquisition. Here, we review the different tools within TAPAS and illustrate how these may help provide a deeper understanding of neural and cognitive mechanisms of disease, with the ultimate goal of establishing automatized pipelines for predictions about individual patients. We hope that the openly available tools in TAPAS will contribute to the further development of TN/CP and facilitate the translation of advances in computational neuroscience into clinically relevant computational assays.

neuroscience↗

bioRxiv2018

Focus of attention modulates the heartbeat evoked potential

Theoretical frameworks such as predictive coding suggest that the perception of the body and world - interoception and exteroception - involve intertwined processes of inference, learning, and prediction. In this framework, attention is thought to gate the influence of sensory information on perception. In contrast to exteroception, there is limited evidence for purely attentional effects on interoception. Here, we empirically tested if attentional focus modulates cortical processing of single heartbeats, using a newly-developed experimental paradigm to probe purely attentional differences between exteroceptive and interoceptive conditions in the heartbeat evoked potential (HEP). We found that the HEP is significantly higher during interoceptive compared to exteroceptive attention, in a time window of 520-580ms after the R-peak. Furthermore, this effect predicted self-report measures of autonomic system reactivity. This study thus provides direct evidence that the HEP is modulated by attention and supports recent interpretations of the HEP as a neural correlate of interoceptive prediction errors.

neuroscience↗