Dongping Yang

Dissociating the intensity and phase origins of sleepiness through a threshold-distance model of sleep-wake dynamics

The paper resolves the ambiguity in sleepiness prediction by decomposing it into intensity and phase axes using a threshold-distance model, linking sleepiness to both homeostatic pressure and circadian modulation.

Circadian-Modulated Thresholds for Sleep Patterns in Aging and Narcolepsy

This paper derives circadian-modulated sleep thresholds from a biophysical model, showing aging and narcolepsy as opposite deformations along the orexinergic axis.

Circadian-Modulated Thresholds as a Mechanistic Basis for Sleep-Wake Transitions, Recovery, and Sleepiness

This paper develops a computational model that explains sleep-wake transitions and sleepiness through circadian-modulated thresholds, showing how circadian and homeostatic drives interact dynamically.

Representation Transfer via Invariant Input-driven Neural Manifolds for Brain-inspired Computations

The paper introduces a brain-inspired framework for domain adaptation in AI, using recurrent neural networks to create transferable representations that enable rapid few-shot adaptation with fewer parameters.

Mechanistic Modeling of Sleep-Wake Transitions via Circadian-Modulated Threshold Dynamics

This study updates a computational model of sleep-wake regulation by introducing circadian-modulated thresholds, capturing key sleep phenomena and offering insights into circadian misalignment effects.

Neural Heterogeneity Enhances Reliable Neural information Processing: Local Sensitivity and Globally Input-slaved Transient Dynamics

This paper identifies a mechanism for reliable neural information processing through neural heterogeneity, showing it disrupts spatiotemporal patterns and aligns network activity with inputs.

Bridging Scales: Spectral Theory Reveals How Local Connectivity Rules Sculpt Global Neural Dynamics in Spatially Extended Networks

This paper develops a spatially extended neural network model with spectral theory to show how local connectivity parameters determine global neural dynamics and explains cortical dynamics shifts in mice.

Synfire Chain Dynamics Unravelling Theta-nested Gamma Oscillations for Balancing Prediction and Dodge in Navigation

This study investigates theta-nested gamma oscillations in navigation, showing they balance prediction and alertness by linking theta frequency to motion velocity.

Evolutionary learning in the brain by heterosynaptic plasticity

This paper proposes an evolutionary algorithm model of brain learning using non-local rules and demonstrates its effectiveness in training neural networks with biologically plausible weights.

Unified Analysis of Global and Focal Aspects of Absence Epilepsy via Neural Field Theory of the Corticothalamic System

The paper unifies global and focal aspects of absence epilepsy using a corticothalamic model, showing how seizure localization and generalization relate to observed dynamics in humans and rats.