Alpha oscillations encode Bayesian belief updating underlying attentional allocation in dynamic environments.

In a dynamic environment, expectations of the future constantly change based on updated evidence and affect the dynamic allocation of attention. To further investigate the neural mechanisms underlying attentional expectancies, we employed a modified Central Cue Posner Paradigm in which the probability of cues being valid (that is, accurately indicated the upcoming target location) was manipulated. Attentional deployment to the cued location (α), which was governed by precision of predictions on previous trials, was estimated using a hierarchical Bayesian model and was included as a regressor in the analyses of electrophysiological (EEG) data.

The neural substrates of how model-based learning affects risk taking: Functional coupling between right cerebellum and left caudate.

Higher executive control capacity allows people to appropriately evaluate risk and avoid both excessive risk aversion and excessive risk-taking. The neural mechanisms underlying this relationship between executive function and risk taking are still unknown. We used voxel-based morphometry (VBM) analysis combined with resting-state functional connectivity (rs-FC) to evaluate how one component of executive function, model-based learning, relates to risk taking.

Frontostriatal Functional Connectivity Underlies the Association between Punishment Sensitivity and Procrastination.

Procrastination is defined as putting off an intended course of action voluntarily despite the harmful consequences. Previous studies have suggested that procrastination is associated with punishment sensitivity in that high punishment sensitivity results in increased negative utility for task performance. We hypothesized the effects of punishment sensitivity on procrastination would be mediated by a network connecting the caudate nucleus and prefrontal cortex, both of which have been previously associated with self-control and emotional control during procrastination.

Modulating hierarchical learning by high-definition transcranial alternating current stimulation at theta frequency.

Considerable evidence highlights the dorsolateral prefrontal cortex (DLPFC) as a key region for hierarchical (i.e. multilevel) learning.

Electrophysiological Signatures of Hierarchical Learning.

Human perception and learning is thought to rely on a hierarchical generative model that is continuously updated via precision-weighted prediction errors (pwPEs). However, the neural basis of such cognitive process and how it unfolds during decision-making remain poorly understood. To investigate this question, we combined a hierarchical Bayesian model (i.

Dynamic integration and segregation of amygdala subregional functional circuits linking to physiological arousal.

The dynamical organization of brain networks is essential to support human cognition and emotion for rapid adaption to ever-changing environment. As the core nodes of emotion-related brain circuitry, the basolateral amygdala (BLA) and centromedial amygdala (CMA) as two major amygdalar nuclei, are recognized to play distinct roles in affective functions and internal states, via their unique connections with cortical and subcortical structures in rodents. However, little is known how the dynamical organization of emotion-related brain circuitry reflects internal autonomic responses in humans.

The Neural Mechanism of Number Line Bisection: A fMRI study.

The neural networks involved in number line bisection are poorly understood. We used functional magnetic resonance imaging (fMRI) to investigate these. fMRI was analyzed from 28 healthy volunteers who performed number and physical line bisection tasks (and their respective baselines).

The metaphoric nature of the ordinal position effect.

Serial orders are thought to be spatially represented in working memory: The beginning items in the memorised sequence are associated with the left side of space and the ending items are associated with the right side of space. However, the origin of this ordinal position effect has remained unclear. It was suggested that the direction of serial order-space interaction is related to the reading/writing experience.

Addition and Subtraction but Not Multiplication and Division Cause Shifts of Spatial Attention.

Many studies have shown that solving addition and subtraction problems can induce overt shifts of spatial attention. In particular, right-side targets are detected faster than left-side targets when preceded by an addition operation, while left-side targets are detected faster than right-side targets when preceded by a subtraction operation. However, the interaction between space and arithmetic in multiplication or division is hardly studied and remains controversial.