Biology subjects

Ullsperger, M.

Publications and source records attributed to Ullsperger, M..

10 recordsLinked to original sources

bioRxiv2026

Transcranial ultrasound stimulation of the aMCC transiently improves performance, modulates N2 and conflict monitoring dynamics

Conflict monitoring and error processing are fundamental mechanisms underlying cognitive control and adaptive behavior and have been consistently associated with increased activity in the anterior midcingulate cortex (aMCC). Here, we used transcranial ultrasound stimulation (TUS), an emerging technique that enables non-invasive, deep, and focal neuromodulation, and EEG to investigate the causal role of the aMCC in cognitive control. Our findings demonstrate that TUS of aMCC improved performance, modulated the relationship between conflict monitoring and the stimulus-locked N2, and strengthened the suppression of distracting flankers as revealed by drift-diffusion model analyses. This suggests that TUS of aMCC enhances proactive control. Interestingly, TUS did not affect the error-related negativity as a measure of error monitoring. Finally, the TUS effects were observed during early compared with later task blocks corroborating previous findings which suggested that TUS effects are temporally dynamic and characterized by a limited post-stimulation window. HIGHLIGHTSO_LIaMCC-TUS and PCC-TUS both increase behavioral accuracy during the early stages of task performance. C_LIO_LIaMCC-TUS transiently reduces the effect of incongruence on the stimulus-locked N2 suggesting reduced response conflict. C_LIO_LIExploratory DDM analyses suggest that aMCC-TUS improves suppression of conflict- inducing distractors. C_LIO_LIaMCC thus selectively enhances proactive control, thereby reducing response conflict. C_LIO_LITUS effects show a transient temporal profile, peaking 17-27 minutes after stimulation and declining after [~]37 minutes. C_LI

neuroscience↗

bioRxiv2026

Sleep deprivation disrupts error awareness and subsequent behavioural regulation

Sleep deprivation is known to impair cognitive performance, yet its effects on error awareness and subsequent behavioral adjustments remain incompletely understood. Here, we investigated how sleep loss affects the use of subjective performance evaluation to guide post-error adaptations. Thirty healthy adults completed a novel, gamified error awareness multi-rule Simon task once while well rested and once after 24 h of total sleep deprivation. On each trial, participants reported both their task response and subjective evaluation of response accuracy. This design allowed us to dissociate objective performance from subjective error awareness and to examine their influence on subsequent behavior over time. Sleep deprivation slowed responses, reduced accuracy, increased missed responses, and decreased the proportion of consciously detected errors. These effects increased with time on task and were accompanied by greater instability in sustained attention. Critically, post-error adjustments were driven by subjective error awareness rather than factual error commission. Reaction times slowed most strongly after subjectively perceived errors, including instances in which the preceding response had been objectively correct. Accuracy showed post-error decreases that were most pronounced following unaware errors. Sleep deprivation further altered these awareness-dependent control processes, particularly in later task phases. Together, these findings indicate that sleep deprivation disrupts both error awareness and the effective use of awareness signals for behavioral regulation. Statement of significanceOne night of total sleep deprivation reduces behavioral error awareness and disrupts post-error adjustments in a time-dependent manner. Crucially, our findings show that adaptive cognitive control is strongly shaped by subjective error awareness--even when that awareness is inaccurate. By identifying conscious performance evaluation as a key mechanism linking sustained attention, sleep loss, and behavioral regulation, this work highlights the importance of considering subjective awareness when studying adaptive control under fatigue.

neuroscience↗

bioRxiv2025

The absent P3a. Performance monitoring ERPs differentiate trust in humans and autonomous systems.

To address suggestions that human brain responses to autonomous system errors may be used as brain-based measures of trust in automation, the present study asked participants to monitor the performance of either a virtual human or an autonomous system partner performing a novel, complex, real-world image classification task. We predicted visual feedback of partner errors would elicit the feedback-related negativity and P3 ERP components, and that these components would differ between the human and system groups. Behavioural results showed that while participants calibrated their trust in their partner according to our intended manipulation of error rates, no group differences were found. The ERP data, however, revealed FRN and P3 effects for both groups, modulated by accuracy and error rate. An unexpected finding was that the P3 topography differed between groups, with both a frontal P3a and posterior P3b component seen for the human condition, while for the system condition only the posterior P3b was observed and the P3a was completely absent. We suggest that this selective absence of the P3a may reflect reduced frontal attention during system monitoring in passive task conditions potentially resulting from reduced social and emotional processing for the system partner. This study demonstrates the potential for EEG-based measures of trust in automation to surpass the sensitivity of traditional measures of trust, while additionally uncovering a potential neural signature of automation complacency in the absent P3a. This identifies potential boundary conditions under which the application of human correlates of performance monitoring may not apply to the monitoring of an automated system.

neuroscience↗

bioRxiv2024

Methamphetamine-induced adaptation of learning rate dynamics depend on baseline performance.

The ability to calibrate learning according to new information is a fundamental component of an organisms ability to adapt to changing conditions. Yet, the exact neural mechanisms guiding dynamic learning rate adjustments remain unclear. Catecholamines appear to play a critical role in adjusting the degree to which we use new information over time, but individuals vary widely in the manner in which they adjust to changes. Here, we studied the effects of a low dose of methamphetamine (MA), and individual differences in these effects, on probabilistic reversal learning dynamics in a within-subject, double-blind, randomized design. Participants first completed a reversal learning task during a drug-free baseline session to provide a measure of baseline performance. Then they completed the task during two sessions, one with MA (20 mg oral) and one with placebo (PL). First, we showed that, relative to PL, MA modulates the ability to dynamically adjust learning from prediction errors. Second, this effect was more pronounced in participants who performed moderately low at baseline. These results present novel evidence for the involvement of catecholaminergic transmission on learning flexibility and highlights that baseline performance modulates the effect of the drug.

neuroscience↗

bioRxiv2023

Cholinergic modulation of motor sequence learning

The cholinergic system plays a key role in motor function, but whether pharmacological modulation of cholinergic activity affects motor sequence learning is unknown. The acetylcholine receptor antagonist biperiden, an established treatment in movement disorders, reduces attentional modulation, but whether it influences motor sequence learning is not clear. Using a randomized, double-blind placebo-controlled crossover design, we tested thirty healthy young participants and show that biperiden impairs production of sequential finger movements following a fixed but not a random sequence. A similar interaction was observed in widespread oscillatory broadband power changes (4-25 Hz) in the motor sequence learning network after receiving biperiden, with greater power in the theta, alpha, and beta bands over ipsilateral motor and bilateral parietal-occipital areas. The reduced theta power during a fixed compared to random sequence, likely reflecting disengagement of top-down attention to sensory processes, was disrupted by biperiden. The alpha synchronization during learned sequences, reflecting sensory gating and lower visuospatial attention requirements for the learned, compared with visuomotor responses to a random sequence, was greater after biperiden, potentially reflecting excessive visuospatial attention reduction following biperiden, also affecting visuomotor responding required to enable sequence learning. Beta oscillations facilitate sequence learning by integrating visual and somatosensory inputs, stabilizing learned sequences, and promoting prediction of the next stimulus. The beta synchronization after biperiden fits with a disruption of the selective visuospatial attention enhancement associated with initial sequence learning. These findings highlight the role of cholinergic processes in motor sequence learning.

neuroscience↗

bioRxiv2023

Success versus failure in cognitive control: meta-analytic evidence from neuroimaging studies on error processing

Brain mechanisms of error processing have often been investigated using response interference tasks and focusing on the posterior medial frontal cortex, which is also implicated in resolving response conflict in general. Thereby, the role other brain regions may play has remained undervalued. Here, activation likelihood estimation meta-analyses were used to synthesize the neuroimaging literature on brain activity related to committing errors versus responding successfully in interference tasks and to test for commonalities and differences. The salience network and the temporoparietal junction were commonly recruited irrespective of whether responses were correct or incorrect, pointing towards a general involvement in coping with situations that call for increased cognitive control. The dorsal posterior cingulate cortex, posterior thalamus, and left superior frontal gyrus showed error-specific convergence, which underscores their consistent involvement when performance goals are not met. In contrast, successful responding revealed stronger convergence in the dorsal attention network and lateral prefrontal regions. Underrecruiting these regions in error trials may reflect failures in activating the task-appropriate stimulus-response contingencies necessary for successful response execution.

neuroscience↗

bioRxiv2023

A thin line between conflict and reaction time effectson EEG and fMRI brain signals

The last two decades of electrophysiological and neuroimaging research converged that the activity in the medial frontal cortex plays a pivotal role in cognitive control processes. Notably, the midfrontal theta (MFT) oscillatory EEG power, as well as activity in the anterior midcingulate cortex (aMCC) or pre-supplementary motor area (preSMA), were consistently proclaimed as markers of conflict processing. However, these brain signals are strongly correlated with response time (RT) variability in various non-conflict tasks, which overshadows the true nature of their involvement. Our previous study (Beldzik et al., 2022) successfully identified these brain signals during a simultaneous EEG-fMRI experiment implementing Stroop and Simon tasks. Based on the assumption that overcoming the habitual prepotent response during high interference trials require additional neural resources beyond simple decision variable represented in RTs, here we aim to verify if these markers exhibit a congruency effect beyond RT variations. Furthermore, we explored if these brain signals represent either proactive or reactive cognitive control mechanisms by investigating two widely known behavioral phenomena observed in conflict tasks: proportion congruency and congruency sequence effects. The results revealed partially null findings for MFT activity, yet a distinct cognitive control specialization between aMCC and preSMA. Our study provides novel evidence that the former is involved in proactive control mechanisms, possibly contingency learning, whereas the latter reflects reactive control mechanisms by exhibiting a strong congruency effect regardless of RT variation and responding to adaptive behavior.

neuroscience↗

bioRxiv2023

Cortical beta power reflects a neural implementation of decision boundary collapse in a speeded flanker task

A prominent account of decision-making assumes that information is accumulated until a fixed response threshold is crossed. However, many decisions require weighting of information appropriately against time. Collapsing response thresholds are a mathematically optimal solution to this decision problem. However, our understanding of the neurocomputational mechanisms that underly dynamic response thresholds remains very incomplete. To investigate this issue, we used a multistage drift diffusion model (DDM) and also analysed EEG beta power lateralization (BPL). The latter served as a neural proxy for decision signals. We analysed a large dataset (n=863) from a speeded flanker task and data from an independent confirmation sample (n=119). We show that a DDM with collapsing decision thresholds, a process where the decision boundary reduces over time, captured participants time-dependent decision policy better than a model with fixed thresholds. Previous research suggests that BPL over motor cortices reflects features of a decision signal and that its peak may serve as a neural proxy for the decision threshold. Our findings offer compelling evidence for the existence of collapsing decision thresholds in decision-making processes.

neuroscience↗

bioRxiv2022

Conflict- and error-related theta activities are coupled to BOLD signals in different brain regions

Both conflict and error processing have been linked to the midfrontal theta power (4-8 Hz) increase as indicated by EEG studies and greater hemodynamic activity in the anterior midcingulate cortex (aMCC) as indicated by fMRI studies. Conveniently, the source of the midfrontal theta power was estimated in or nearby aMCC. However, previous studies using concurrent EEG and fMRI recordings in resting-state or other cognitive tasks observed only a negative relationship between theta power and BOLD signal in the brain regions typically showing task-related deactivations. In this study, we used a simultaneous EEG-fMRI technique to investigate a trial-by-trial coupling between theta power and hemodynamic activity during the performance of two conflict tasks. Independent component analysis (ICA) was applied to denoise the EEG signal and select individual midfrontal EEG components, whereas group ICA was applied to fMRI data to obtain a functional parcellation of the frontal cortex. Using a linear mixed- effect model, theta power was coupled with the peak of hemodynamic responses from various frontal, cingulate, and insular cortical sites to unravel the potential brain sources that contribute to conflict- and error-related theta variability. Although several brain regions exhibited conflict-related increases in hemodynamic activity, the conflict pre-response theta showed only a negative correlation to BOLD signal in the midline area 9 (MA9), a region exhibiting conflict-sensitive deactivation. Conversely, and more expectedly, error-related theta showed a positive relationship to activity in the aMCC. Our results provide novel evidence suggesting that the amplitude of pre-response theta reflects the process of active inhibition that suppresses the MA9 activity. This process is affected independently by the stimulus congruency, reaction times variance, and is susceptible to the time-on-task effect. Finally, it predicts the commitment of an omission error. Together, our findings highlight that conflict- and error-related theta oscillations represent fundamentally different processes.

neuroscience↗

bioRxiv2021

Feedback-related EEG dynamics separately reflect decision parameters, biases, and future choices

Optimal decision making in complex environments requires dynamic learning from unexpected events. To speed up learning, we should heavily weight information that indicates state-action-outcome contingency changes and ignore uninformative fluctuations in the environment. Often, however, unrelated information is hard to ignore and can potentially bias our learning. Here we used computational modelling and EEG to investigate learning behaviour in a modified probabilistic choice task that introduced two types of unexpected events that were irrelevant for optimal task performance, but nevertheless could potentially bias learning: pay-out magnitudes were varied randomly and, occasionally, feedback presentation was enhanced by visual surprise. We found that participants overall good learning performance was biased by distinct effects of these non-normative factors. On the neural level, these parameters are represented in a dynamic and spatiotemporally dissociable sequence of EEG activity. Later in feedback processing the different streams converged on a central to centroparietal positivity reflecting a final pathway of adaptation that governs future behaviour.

neuroscience↗