Biology subjects

Weber, L. A.

Publications and source records attributed to Weber, L. A..

8 recordsLinked to original sources

bioRxiv2025

Environmental dynamics shape human learning: change points versus random walks

Adaptive learning requires interpreting prediction errors in light of environmental dynamics. However, environments may not only differ in terms of when changes occur, but also how they occur: some nonstationary processes in nature exhibit slow drifts over time, while others show more abrupt changes. This raises the question as to whether humans can adapt their learning to reflect the generative structure of their environment. Here, we compared how humans learn in two canonical nonstationary environments: abrupt change points versus gradual random walks. Using a predictive inference task and a unified Bayesian framework, we show across two behavioral experiments that humans adapt their learning normatively between these two environments. Notably, identical prediction errors were interpreted differently across them. Large prediction errors triggered sharp increases in learning rate under change-point but not random-walk dynamics, where small and large errors were more equally weighted. This matched the predictions of a normative Bayesian model, which itself adopted the appropriate generative model for each environment. In addition, we found that humans could dissociate two latent variables that needed to be jointly inferred: the mean and variance (or stochasticity). This was demonstrated by explicit uncertainty reports that closely tracked the current variance, and only showed sustained changes following change points in variance but not mean. Together, these results show that humans adapt their learning strategy to both how and what aspects of the environment are changing. They establish a unified computational account of adaptive learning across different environmental dynamics.

neuroscience↗

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

Low-intensity focused ultrasound to human amygdala reveals a causal role in ambiguous emotion processing and alters local and network-level activity

The amygdala is a core region changed in depression, a disorder characterized by compromised emotion, motivation and learning processes. However, lesion studies in humans examining amygdala function have largely focused on its role in processing fear. It currently remains unclear what causal role the human amygdala plays in more complex emotion, motivation and learning processes in daily life. This is because it has not been possible to reversibly modulate amygdala activity non-invasively in humans. Here, we used transcranial focused ultrasound stimulation (TUS) to bilaterally perturb neural activity in the basolateral amygdala (BLA). In separate sessions (n = 87), 29 healthy volunteers received offline-TUS to bilateral BLA, mid-insula or sham before playing a novel emotional learning task validated in an independent large cohort online (n = 210). 7T-resting-state and metabolite signals clearly demonstrated target engagement. BLA-TUS reduced the BLAs connectivity fingerprint and decreased its excitation/inhibition balance, suggesting an inhibitory effect of our TUS protocol on BLA activity. In behaviour, BLA-TUS caused a stimulation volume-dependent increase in the tendency to approach neutral, emotionally ambiguous faces, treating them more similarly to happy faces, and a slowing of reaction times for those two emotion categories. These effects were functionally and regionally specific and suggest a causal role for the amygdala in resolving emotional ambiguity. Our results provide important insights for future studies into mood disorders where ambiguous situations might be harder to resolve, which could contribute to existing emotional and learning biases.

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bioRxiv2022

Decision-making in dynamic, continuously evolving environments: quantifying the flexibility of human choice

During perceptual decision-making tasks, centroparietal EEG potentials report an evidence accumulation-to-bound process that is time locked to trial onset. However, decisions in real-world environments are rarely confined to discrete trials; they instead unfold continuously, with accumulation of time-varying evidence being recency-weighted towards its immediate past. The neural mechanisms supporting recency-weighted continuous decision making remain unclear. Here, we use a novel continuous task design to study how the Centroparietal Positivity (CPP) adapts to different environments that place different constraints on evidence accumulation. We show that adaptations in evidence weighting to these different environments are reflected in changes in the CPP. The CPP becomes more sensitive to fluctuations in sensory evidence when large shifts in evidence are less frequent, and the potential is primarily sensitive to fluctuations in decision-relevant (not decision-irrelevant) sensory input. A complementary triphasic component over occipito-parietal cortex encodes the sum of recently accumulated sensory evidence, and its magnitude covaries with parameters describing how different individuals integrate sensory evidence over time. A computational model based on leaky evidence accumulation suggests these findings can be accounted for by a shift in decision threshold between different environments, which is also reflected in the magnitude of pre-decision EEG activity. Our findings reveal how adaptations in EEG responses reflect flexibility in evidence accumulation to the statistics of dynamic sensory environments.

neuroscience↗

bioRxiv2021

Auditory mismatch responses are differentially sensitive to changes in muscarinic acetylcholine versus dopamine receptor function

The auditory mismatch negativity (MMN) has been proposed as a biomarker of NMDA receptor (NMDAR) dysfunction in schizophrenia. Pathophysiological theories suggest that such dysfunction might be partially caused by aberrant interactions of different modulatory neurotransmitters with NMDARs, which could explain heterogeneity among patients with schizophrenia and their treatment response. Understanding the differential impact of different neuromodulators on readouts of NMDAR function is therefore of high clinical relevance. Here, we report results from two studies (N=81 each) which systematically tested whether the MMN is sensitive to diminishing and enhancing cholinergic vs. dopaminergic function. Both studies used a double-blind, placebo-controlled between-subject design and monitored individual drug plasma levels. Using a novel variant of the auditory oddball paradigm, we contrasted phases with stable versus volatile probabilities of tone switches. In the first study, we found that the muscarinic acetylcholine receptor antagonist biperiden reduced and/or delayed mismatch responses, particularly during stable phases of the experiment, whereas this effect was absent for amisulpride, a dopamine D2/D3 receptor antagonist. The direct comparison between biperiden and amisulpride indicated a significant drug x mismatch interaction. In the second study, neither elevating acetylcholine nor dopamine levels via administration of galantamine and levodopa, respectively, exerted significant effects on MMN. Overall, our results indicate differential sensitivity of the MMN to changes in cholinergic (muscarinic) versus dopaminergic receptor function. This finding may prove useful for developments of future tools for predicting individual treatment responses in disorders that show abnormal MMN, such as schizophrenia.

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.

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bioRxiv2019

State anxiety biases estimates of uncertainty during reward learning in volatile environments

Previous research established that clinical anxiety impairs decision making and that high trait anxiety interferes with learning rates. Less understood are the effects of temporary anxious states on learning and decision making in healthy populations. Here we follow proposals that anxious states in healthy individuals elicit a pattern of aberrant behavioural, neural, and physiological responses comparable with those found in anxiety disorders, particularly when processing uncertainty in unstable environments. In our study, both a state anxious and a control group learned probabilistic stimulus-outcome mappings in a volatile task environment while we recorded their electrophysiological (EEG) signals. By using a hierarchical Bayesian model, we assessed the effect of state anxiety on Bayesian belief updating with a focus on uncertainty estimates. State anxiety was associated with an underestimation of environmental and informational uncertainty, and an increase in uncertainty about volatility estimates. Anxious individuals deemed their beliefs about reward contingencies to be more precise and to require less updating, ultimately leading to impaired reward-based learning. We interpret this pattern as evidence that state anxious individuals are less tolerant to informational uncertainty about the contingencies governing their environment and more uncertain about the level of stability of the world itself. Further, we tracked the neural representation of belief update signals in the trial-by-trial EEG amplitudes. In control participants, both lower-level precision-weighted prediction errors (pwPEs) about the reward outcomes and higher-level volatility-pwPEs were represented in the ERP signals with an anterior distribution. A different pattern emerged under state anxiety, where a neural representation of pwPEs was only found for updates about volatility. Expanding previous computational work on trait anxiety, our findings establish that temporary anxious states in healthy individuals impair reward-based learning in volatile environments, primarily through changes in uncertainty estimates and potentially a degradation of the neuronal representation of hierarchically-related pwPEs, considered to play a central role in current Bayesian accounts of perceptual inference and learning.

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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↗