Biology subjects

Mueller, H. J.

Publications and source records attributed to Mueller, H. J..

9 recordsLinked to original sources

bioRxiv2026

Dynamic Modulation of Distractor Suppression by Tonic and Trial-Level Alertness Fluctuations: A Pupillometric Study

Attentional control balances proactive suppression of predictable distractors with reactive suppression of unexpected ones. Yet, how internal states such as alertness shape this balance is unclear. Using pupillometry and eye tracking across two probability-cueing experiments (conducted in 2024) with varying distractor prevalence, we distinguished tonic (baseline pupil size across blocks) from trial-level pupil size fluctuations (trial-by-trial residual variability in pre-stimulus pupil size). With moderate prevalence, suppression of frequent-region distractors developed gradually, whereas high prevalence induced near-immediate suppression. Behavioral measures (e.g., reaction times) were closely linked to tonic and trial-level pupil size fluctuations. Critically, both alertness components jointly influenced control: during early learning, heightened trial-level pupil size increased distractor capture and reduced target fixations, whereas later on, suppression shifted to a proactive mode resilient to trial-level fluctuations. Under high prevalence, this shift occurred faster. Notably, higher trial-level pupil size generally accelerated first target selection. These findings show that tonic alertness and trial-level alertness fluctuations dynamically regulate reactive and proactive control during statistical learning. Impact StatementThis study shows that people become better at ignoring predictable distractions over time, but that this improvement depends not only on what they have learned about the task environment, but also on their current level of alertness. By combining eye tracking and pupil measures, we found that temporary increases in alertness can sometimes help people orient more quickly to relevant information, yet during earlier stages of learning they can also make attention more vulnerable to distracting events. These findings suggest that successful focus in complex environments depends on a dynamic interplay between learned expectations and moment-to-moment fluctuations in mental state, with implications for understanding sustained attention in settings such as monitoring, driving, and other tasks that require people to stay engaged while resisting distraction.

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bioRxiv2026

DMN Connectivity Predicts Location-Learning-Related Attentional Capture Vulnerability

Learned spatial regularities can reduce attentional capture by salient distractors, but observers vary in how strongly such regularities shape distractor interference. We asked whether this variability is associated with default mode network (DMN) functional connectivity, a network measure linked to individual differences in attention, internally guided cognition, and contextual memory. Using an existing fMRI visual-search dataset (N = 33), we tested whether task-run DMN connectivity was related to capture by distractors assigned to a learned spatial-probability history. Participants belonged to two training groups that differed in which distractor dimension carried the spatial bias: same-dimension distractors in one group and different-dimension distractors in the other. This design allowed us to ask whether the DMN association followed the design-defined biased dimension rather than general distractibility or a fixed physical distractor feature, while considering that the biased dimension also involved greater exposure. Higher within-DMN connectivity was associated with larger capture scores for the biased distractor dimension, whereas capture by the unbiased dimension showed little corresponding relation. This association remained positive after controls for inter-trial priming, head motion, nuisance signals, task-regressor residualization, global-signal regression, motion scrubbing, and trial-level exposure history. Exploratory edge-level analyses provided descriptive convergence, showing that capture-associated positive edges were concentrated around the DMN. These findings suggest that DMN connectivity may relate to individual differences in vulnerability to distractors embedded in learned spatial-probability histories.

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bioRxiv2026

Pre-stimulus Cortical State Modulates Dimension-Specific Attentional Capture

Suppressing visual distraction depends on observers goals and learning, but also on the brain state in which the next display arrives. We reanalyzed an fMRI visual-search dataset (N = 34) to ask whether pre-stimulus global signal (GS), a broad state-sensitive BOLD measure, predicts performance and attention-network engagement during learned distractor suppression. Participants searched for an orientation target while ignoring salient distractors defined in the same orientation dimension or a different color dimension; across groups, spatial regularities were assigned to same- or different-dimension distractors. Behavioral and fMRI contrasts reproduced the expected functional architecture: same-dimension distractors slowed responses and recruited a frontoparietal capture-related network, whereas different-dimension distractors produced little interference. Learned spatial suppression was clearest for same-dimension distractors, which produced larger costs and stronger visual and frontoparietal responses in the rare than frequent region. Within this architecture, GS predicted performance in opposite directions across learning contexts: higher GS preceded slower responses when same-dimension distractors carried the spatial regularity, but faster responses when different-dimension distractors did. Higher GS also preceded weaker same-dimension distractor-evoked frontoparietal activation, without a reliable group difference in that neural effect. Default-mode-network activity showed the same behavioral pattern as GS, whereas pupil size showed weaker group-level convergence and its RT slopes did not correlate with GS-RT slopes across participants. Learned distractor suppression therefore appears embedded in a broader state-performance mapping, linking pre-stimulus cortical state to how learned priority settings guide the next trial.

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bioRxiv2023

Electrophysiological signatures of temporal context in the bisection task

Despite relatively accurate time judgment, subjective time is susceptible to various contexts, such as sample spacing and frequency. Several electroencephalographic (EEG) components have been linked to timing, including the contingent negative variation (CNV), offset P2, and late positive component of timing (LPCt). However, the specific role of these components in the contextual modulation of perceived time remains unclear. In this study, we conducted two temporal bisection experiments, where participants had to judge if a test duration was close to a short or long standard. Unbeknownst to participants, the sample spacing (Experiment 1) and frequency (Experiment 2) were altered to create short and long contexts while keeping the test range and standards the same in different sessions. The results showed that the bisection threshold shifted toward the ensemble mean and that CNV and LPCt were sensitive to context modulation. Compared to the long context, the CNV climbing rate increased in the short context, and the amplitude and latency of the LPCt were reduced. These findings suggest the CNV represents an expectancy wave for upcoming decision-making, while LPCt reflects the decision-making process, both influenced by the temporal context.

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bioRxiv2022

Subjective cognitive decline predicts lower cingulo-opercular network functional connectivity in individuals with lower neurite density in the forceps minor

Cognitive complaints of attention/concentration problems are highly frequent in older adults with subjective cognitive decline (SCD). Functional connectivity in the cingulo-opercular network (CON-FC) supports cognitive control, tonic alertness, and visual processing speed. Thus, those complaints in SCD may reflect a decrease in CON-FC. Frontal white-matter tracts such as the forceps minor exhibit age- and SCD-related alterations and, therefore, might influence the CON-FC decrease in SCD. Here, we aimed to determine whether SCD predicts an impairment in CON-FC and whether neurite density in the forceps minor modulates that effect. To do so, we integrated cross-sectional and longitudinal analyses of multimodal data in a latent growth curve modeling approach. Sixty-nine healthy older adults (13 males; 68.33 {+/-} 7.95 years old) underwent resting-state functional and diffusion-weighted magnetic resonance imaging, and the degree of SCD was assessed at baseline with the memory functioning questionnaire (greater score indicating more SCD). Forty-nine of the participants were further enrolled in two follow-ups, each about 18 months apart. Baseline SCD did not predict CON-FC after three years or its rate of change (p-values > 0.092). Notably, however, the forceps minor neurite density did modulate the relation between SCD and CON-FC (intercept; b = 0.21, 95% confidence interval, CI, [0.03, 0.39], p = 0.021), so that SCD predicted a greater CON-FC decrease in older adults with relatively lower neurite density in the forceps minor. The neurite density of the forceps minor, in turn, negatively correlated with age. These results suggest that CON-FC alterations in SCD are dependent upon the forceps minor neurite density. Accordingly, these results imply modifiable age-related factors that could help delay or mitigate both age and SCD-related effects on brain connectivity.

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bioRxiv2022

Predictive coding in ASD: inflexible weighting of prediction errors when switching from stable to volatile environments

The nature of predictive-processing differences between individuals with autism spectrum disorder (ASD) and typically developing (TD) individuals is widely debated. Some studies suggest impairments in predictive processing in ASD, while others report intact processes, albeit with atypical learning dynamics. Here, we assessed duration reproduction tasks in high- and low-volatility settings to examine the updating dynamics of prior beliefs and sensory estimates. Employing a two-state Bayesian model, we differentiated how individuals with ASD and TD controls update their priors and perceptual estimates, and how these updates affect long-term prediction and behavior. Our findings indicate that individuals with ASD use prior knowledge and sensory input similarly to TD controls in perceptual estimates. However, they place a greater weight on sensory inputs specifically for iteratively updating their priors. This distinct approach to prior updating led to slower adaptation across trials; individuals with ASD relied less on their priors in perceptual estimates during the first half of sessions but achieved comparable integration weights as TD controls by the end of the session. By differentiating these aspects, our study highlights the importance of considering inter-trial updating dynamics to reconcile diverse findings of predictive processing in ASD. In consequence to the current findings, we suggest the distinct iterative updating account of predictive processing in ASD. Significance StatementResearch on predictive processing in Autism Spectrum Disorder (ASD) remains controversial. The current study employed a two-state Bayesian model in varied volatility settings to explore inter-trial updating dynamics in ASD compared to typically developing (TD) peers. We found that individuals with ASD, while utilizing prior knowledge similarly to TD controls, place a disproportionate emphasis on sensory inputs when updating their priors. This unique pattern of slower adaptation during iterative updating leads to significant behavioral differences in the first half of trials between the two groups, but comparable levels by the end of the session. These findings not only highlight the importance of considering different timescales and dynamic updating processes in ASD, but also suggest that the predictive processing framework in ASD involves unique prior updating mechanisms that is likely associated with increased sensory reliance.

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bioRxiv2019

Human subsystems of medial temporal lobes extend locally to amygdala nuclei and globally to an allostatic-interoceptive system

In mammals, the hippocampus, entorhinal, perirhinal, and parahippocampal cortices (i.e., core regions of the human medial temporal lobes, MTL) are locally interlaced with the adjacent amygdala nuclei at the structural and functional levels. At the global brain level, the human MTL has been described as part of the default mode network whereas amygdala nuclei as parts of the salience network, with both networks forming collectively a large-scale brain system supporting allostatic-interoceptive functions. We hypothesized (i) that intrinsic functional connectivity of slow activity fluctuations would reveal human MTL subsystems locally extending to the amygdala; and (ii) that these extended local subsystems would be globally embedded in large-scale brain systems supporting allostatic-interoceptive functions. From the resting-state fMRI data of three independent samples of cognitively healthy adults (one main and two replication samples: Ns = 101, 61, and 29, respectively), we analyzed the functional connectivity of fluctuating ongoing BOLD-activity within and outside the amygdala-MTL in a data-driven way using masked independent component and dual-regression analyses. We found that at the local level MTL subsystems extend to the amygdala and are functionally organized along the longitudinal amygdala-MTL axis. These subsystems were characterized by a consistent involvement of amygdala, hippocampus, and entorhinal cortex, but a variable participation of perirhinal and parahippocampal regions. At the global level, amygdala-MTL subsystems selectively connected to salience, thalamic-brainstem, and default mode networks - the major cortical and subcortical parts of the allostatic-interoceptive system. These results provide evidence for integrated amygdala-MTL subsystems in humans, which are embedded within a larger allostatic-interoceptive system.

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bioRxiv2019

Predictability of salient distractor increases top-down control in healthy younger and older adults

Younger adults are able to shield attentional selection against distractors when they have preknowledge about the upcoming distractor location. For older adults, who suffer from an overall decrease in attentional capacity and who are, in addition, particularly prone to attentional capture, such an adaptive shielding ability would be of particular importance. However, it is an open question whether healthy older adults can utilise the predictability of distractor locations to improve top-down controlled selection to the same degree as younger adults. The theory of visual attention (TVA) framework provides a systematic way to measure an individuals efficiency of top-down control. The present study combined a TVA-based partial-report paradigm with abrupt-onset cues rendering the indicated location highly salient in a bottom-up fashion. Experiment 1, in which (on cued trials) the cue was invariably followed by a distractor at the cued location, showed that the cueing increased the weight of the distractor in the competition for selection compared to uncued distractors (on trials without a cue). In Experiment 2, the probability with which the abrupt-onset cue indicated the upcoming distractor location (1/3 vs. 2/3 of trials) was manipulated between experimental blocks. Participants were able to learn these statistical contingencies and exert top-down control more efficiently in blocks with highly valid distractor location cues, as compared to low-validity blocks. This finding suggests that, even though abrupt-onset spatial cues increase the attentional weights of distractors, participants can acquire and use pre-knowledge about the likelihood that a distractor will appear at an indicated location to down-weight the bottom-up attentional-capture signal. This ability turned out to be comparable across age groups, suggesting that efficient use of predictive information to shield against distracting information is preserved in normal ageing.

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bioRxiv2019

Age Differences in Hemispheric Lateralization in Spatial and Verbal Visual Working Memory

Due to hemispheric specialization of the human brain, neural signatures of visual working memory (WM) performance are expected to differ between tasks involving verbal versus spatial memoranda. Theories of cognitive aging suggest a reduction of hemispheric specialization in older adults. Using behavioral and neural WM capacity markers, we assessed hemispheric lateralization in younger and older adults performing a spatial or verbal visual WM task. Participants encoded information presented in the left or right hemifield. We observed behavioral advantages for spatial stimuli processed in the right hemisphere and for verbal stimuli processed in the left hemisphere. While younger adults showed lateralization in both tasks, older adults showed lateralization only in the verbal task. Lateralization was assessed by the contralateral delay activity (CDA) on the neural level. CDA amplitudes displayed hemispheric lateralization for verbal versus spatial material, but this effect was age-invariant. While our findings support right-hemispheric specialization for spatial information maintenance, and left-hemispheric specialization for verbal information maintenance, we could not confirm a generalized reduction in hemispheric lateralization at older ages.

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