Yin-Jui Chang

The paper investigates single-neuron dynamics during neurofeedback adaptation in rhesus macaques, finding that inhibitory interneurons are more active and engaged in learning compared to excitatory pyramidal neurons.

This paper introduces a fluorescence-lifetime-based multiplexed detection strategy using fluorogenic aptamers to distinguish viral RNA targets with minimal cross-reactivity and spectral overlap.

This study examines how individual neurons adapt during behavioral training and finds that neurons with strong population co-variation and prior behavioral contribution are less likely to change their activity.

This paper introduces a deep learning model to analyze multiscale brain activity dynamics and demonstrates its effectiveness in capturing causal interactions across scales.

The paper investigates how neural spiking variability affects adaptation during a brain-computer interface task in rhesus macaques, finding that population variance metrics differ between easy and hard adaptation conditions.

This paper introduces a model to infer brain communication across scales and shows it outperforms existing methods in accuracy and predictive power.