Mediation Analysis for High-Dimensional Mediators and Outcomes with an Application to Multimodal Imaging Data.

Multimodal neuroimaging data have attracted increasing attention for brain research. An integrated analysis of multimodal neuroimaging data and behavioral or clinical measurements provides a promising approach for comprehensively and systematically investigating the underlying neural mechanisms of different phenotypes. However, such an integrated data analysis is intrinsically challenging due to the complex interactive relationships between the multimodal multivariate imaging variables.

The neural basis of perceived unfairness in economic exchanges.

Human decision making in situations of inequity has long been regarded as a competition between the sense of fairness and self-interest, primarily based on behavioral and neuroimaging studies of inequity that disfavor the actor while favoring others. Here, we use functional magnetic resonance imaging experiments to study refusals and protests using both favoring and disfavoring inequity in three economic exchange games with undercompensating, nearly equal, and overcompensating offers. Refusals of undercompensating offers recruited a heightened activity in the right dorsolateral prefrontal cortex (dlPFC).

Temporal-order judgment of audiovisual events involves network activity between parietal and prefrontal cortices.

Our perception of the temporal order of everyday external events depends on the integrated sensory information in the brain. Our understanding of the brain mechanism for temporal-order judgment (TOJ) of unisensory events, particularly in the visual domain, is advanced. In case of multisensory events, however, there are unanswered questions.

Amygdala mediated connectivity in perceptual decision-making of emotional facial expressions.

Recognizing emotional facial expressions is a part of perceptual decision-making processes in the brain. Arriving at a decision for the brain becomes more difficult when available sensory information is limited or ambiguous. We used clear and noisy pictures with happy and angry emotional expressions and asked 32 participants to categorize these pictures based on emotions.

Higher frequency network activity flow predicts lower frequency node activity in intrinsic low-frequency BOLD fluctuations.

The brain remains electrically and metabolically active during resting conditions. The low-frequency oscillations (LFO) of the blood oxygen level-dependent (BOLD) signal of functional magnetic resonance imaging (fMRI) coherent across distributed brain regions are known to exhibit features of this activity. However, these intrinsic oscillations may undergo dynamic changes in time scales of seconds to minutes during resting conditions.

Time-delay-induced phase-transition to synchrony in coupled bursting neurons.

Signal transmission time delays in a network of nonlinear oscillators are known to be responsible for a variety of interesting dynamic behaviors including phase-flip transitions leading to synchrony or out of synchrony. Here, we uncover that phase-flip transitions are general phenomena and can occur in a network of coupled bursting neurons with a variety of coupling types. The transitions are marked by nonlinear changes in both temporal and phase-space characteristics of the coupled system.

Targeted control of amplitude dynamics in coupled nonlinear oscillators.

We propose a general strategy for designing coupling functions in order to achieve a desired amplitude dynamics in coupled nonlinear oscillators. The target dynamics achieved by the proposed control schemes is a fixed-point motion at a desired amplitude level or a periodic motion at a desired frequency. The control schemes are illustrated with Rössler and Hindmarsh-Rose oscillators.

Amplitude death in nonlinear oscillators with nonlinear coupling.

Amplitude death is the cessation of oscillations that occurs in coupled nonlinear systems when fixed points are stabilized as a consequence of the interaction. We show here that this phenomenon is very general: it occurs in nonlinearly coupled systems in the absence of parameter mismatch or time delay although time-delayed interactions can enhance the effect. Application is made to synaptically coupled model neurons, nonlinearly coupled Rössler oscillators, as well as to networks of nonlinear oscillators with nonlinear coupling.