Hung‐Yun Lu

Distinct roles of neuronal phenotypes during neurofeedback adaptation

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.

Long-term neuron tracking reveals balance of stability and plasticity in functional properties

This study tracks individual neurons over time to show that while spike waveforms remain stable, some functional properties like firing rates and tuning can change, indicating a balance between neural stability and plasticity.

Distinct tasks engage a shared neural subspace in human hippocampus and anterior cingulate cortex

The paper investigates how neural circuits in the human hippocampus and anterior cingulate cortex support multiple tasks, finding shared neural subspaces across distinct behaviors.

Population-level constraints on single neuron tuning changes during behavioral adaptation

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.

Volitional Regulation and Transferable Patterns of Midbrain Oscillations

This paper demonstrates neurofeedback using VTA LFP signals in non-human primates, showing transferable control strategies and potential for clinical applications.

Multiscale effective connectivity analysis of brain activity using neural ordinary differential equations

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

Neural population variance explains adaptation differences during learning

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.