Biology subjects

Tusche, A.

Publications and source records attributed to Tusche, A..

5 recordsLinked to original sources

bioRxiv2025

Subliminal beauty engages the brain's valuation circuits

Neuroeconomic models propose that the anterior ventral striatum (aVS) and ventromedial prefrontal cortex (vmPFC) are key regions for computing subjective value (SV) signals that guide choice. However, the role of conscious awareness in this process remains debated. Here we examined whether SV can be automatically computed in these regions without conscious awareness. In an fMRI experiment, participants viewed faces that varied in attractiveness under three conditions: (i) suppressed from awareness via continuous flash suppression (CFS), (ii) clearly visible without suppression, or (iii) absent (background only) with CFS. Participants reported trial-wise facial identity (objective) and visibility (subjective) measures of facial awareness. In a post-fMRI session, they rated the attractiveness of each face as a measure of SV. When faces were seen, task performance (d) exceeded chance and responses were faster than in absent trials. When faces were unseen, performance was at chance but responses were slower than absent trials. Neurally, seen and unseen faces elicited greater neural signal than absent trials and showed similar neural patterns in the fusiform face area (FFA). Critically, neural signal in vmPFC correlated with SV for both seen and unseen faces, with similar neural patterns. In aVS, SV-related signal was only observed for unseen faces. Furthermore, mean face-related signal in FFA correlated with SV-related signals in aVS and vmPFC for unseen faces. These findings demonstrate that SV can be automatically computed in aVS and vmPFC without conscious awareness, suggesting a neural pathway by which subliminal information can influence value-based choice.

neuroscience↗

bioRxiv2025

Emotion Regulation in the Gradient Framework: Large-Scale Brain Organization Shapes Individual Differences in Reappraisal Success

Emotion regulation is essential for well-being and mental health, yet individuals vary widely in their emotion regulation success. Why? Traditional neuroimaging studies of emotion regulation often focus on localized neural activity or isolated networks, overlooking how large-scale brain organization may shape the integration of distributed systems and sub-processes supporting regulatory success. Here, we applied a novel system-level framework based on spatial gradients of macroscale brain organization to study variance in emotion regulation success. Using two large fMRI datasets (n=358, n=263), we projected global activation patterns from a laboratory emotion regulation task onto principal gradients derived from independent resting-state fMRI data from the Human Connectome Project. These gradients capture low-dimensional patterns of neural variation, providing a topographical framework within which complex mental phenomena, such as emotion regulation, emerge. In both datasets, individual differences in regulation success were predicted by systematic reconfiguration along Gradient 1--a principal axis differentiating unimodal and heteromodal brain areas. This gradient-based neural reconfiguration also predicted lower negative affect in daily life, as measured via smartphone-based experience sampling in a subset of participants (n=55). Meta-analytic decoding via Neurosynth revealed that Gradient 1 and regulation success align with multiple psychological processes, including social cognition, memory, attention, and negative emotion, suggesting this gradient reflects diverse, integrative demands during effective emotion regulation. These findings advance a network-level account of regulatory success, offering a biologically grounded, ecologically valid framework for understanding adaptive emotional functioning. Such gradient-based dynamics may serve as predictive biomarkers of regulatory success and inform targeted interventions in clinical populations. Significance StatementWhy are some people better than others at regulating their emotional experiences? This study employs a novel systems neuroscience framework to demonstrate that successful emotion regulation relies not only on localized brain activity, but also on how large-scale neural activation patterns systematically shift along principal axes of the brains intrinsic, large-scale spatial architecture. We demonstrate that variance in emotion regulation success--both in the laboratory (assessed using an established emotion regulation task) and in daily life (captured using phone-based experience sampling)--is associated with dynamic transitions along a principal neural gradient from sensory to transmodal association regions in the brain. This insight may lead to the development of new brain-based markers for predicting emotional resilience and tailoring mental health interventions.

neuroscience↗

bioRxiv2024

Brain Charts for the Rhesus Macaque Lifespan

Recent efforts to chart human brain growth across the lifespan using large-scale MRI data have provided reference standards for human brain development. However, similar models for nonhuman primate (NHP) growth are lacking. The rhesus macaque, a widely used NHP in translational neuroscience due to its similarities in brain anatomy, phylogenetics, cognitive, and social behaviors to humans, serves as an ideal NHP model. This study aimed to create normative growth charts for brain structure across the macaque lifespan, enhancing our understanding of neurodevelopment and aging, and facilitating cross-species translational research. Leveraging data from the PRIMatE Data Exchange (PRIME-DE) and other sources, we aggregated 1,522 MRI scans from 1,024 rhesus macaques. We mapped non-linear developmental trajectories for global and regional brain structural changes in volume, cortical thickness, and surface area over the lifespan. Our findings provided normative charts with centile scores for macaque brain structures and revealed key developmental milestones from prenatal stages to aging, highlighting both species-specific and comparable brain maturation patterns between macaques and humans. The charts offer a valuable resource for future NHP studies, particularly those with small sample sizes. Furthermore, the interactive open resource (https://interspeciesmap.childmind.org) supports cross-species comparisons to advance translational neuroscience research.

neuroscience↗

bioRxiv2023

A neurocomputational account of the link between social perception and social action

People selectively help others based on perceptions of their merit or need. Here, we develop a neurocomputational account of how these social perceptions translate into social choice. Using a novel fMRI social perception task, we show that both merit and need perceptions recruited the brains social inference network. A behavioral computational model identified two non-exclusive mechanisms underlying variance in social perceptions: a consistent tendency to perceive others as meritorious/needy (bias) and a propensity to sample and integrate normative evidence distinguishing high from low merit/need in other people (sensitivity). Variance in peoples merit (but not need) bias and sensitivity independently predicted distinct aspects of altruism in a social choice task completed months later. An individuals merit bias predicted context-independent variance in peoples overall other-regard during altruistic choice, biasing people towards prosocial actions. An individuals merit sensitivity predicted context-sensitive discrimination in generosity towards high and low merit recipients by influencing other-regard and self-regard during altruistic decision-making. This context-sensitive perception-action link was associated with activation in the right temporoparietal junction. Together, these findings point towards stable, biologically based individual differences in perceptual processes related to abstract social concepts like merit, and suggest that these differences may have important behavioral implications for an individuals tendency toward favoritism or discrimination in social settings.

neuroscience↗

bioRxiv2020

Evidence accumulation, not "self-control,"explains why the dlPFC activates during normative choice

What role do cognitive control regions like the dorsolateral prefrontal cortex (dlPFC) play in normative behavior (e.g., generosity, healthy eating)? Some models suggest that dlPFC activation during normative choice reflects the use of control to overcome default hedonistic preferences. Here, we develop an alternative account, showing that an attribute-based neural drift diffusion model (anDDM) predicts trial-by-trial variation in dlPFC response across three fMRI studies and two self-control contexts (altruistic sacrifice and healthy eating). Using the anDDM to simulate a variety of self-control dilemmas generated a novel prediction: although dlPFC activity might typically increase for norm-consistent choices, deliberate self-regulation focused on normative goals should decrease or even reverse this pattern (i.e., greater dlPFC response for hedonic, self-interested choices). We confirmed these predictions in both altruistic and dietary choice contexts. Our results suggest that dlPFC response during normative choice may depend more on value-based evidence accumulation than inhibition of our baser instincts.

neuroscience↗