Jian K. Liu

Magnetoencephalography during memory-guided finger sequences shows preparation and execution occupy distinct, partly overlapping subspaces; execution patterns appear first in hippocampus and last in M1, 160 ms before the first press.

This paper decodes natural scenes from optogenetic responses in mouse visual cortex and shows that patterned stimulation can reproduce visual representations with high fidelity.

NeuroSort improves spike sorting by modeling neural dynamics, enabling efficient isolation of thousands of neurons across various recording conditions.

This study uses deep learning to decode dynamic natural visual scenes from neural activity across brain regions, revealing distinct encoding patterns in visual cortex and subcortical nuclei compared to hippocampus.

This paper develops a computational model of retinal gap junctions (G-filter) that improves deep neural networks' performance in blind denoising tasks.

The paper introduces a simple model that improves predictions of retinal ganglion cell responses to natural images by incorporating spatial variance in addition to average light intensity.

The paper introduces a method for multi-area two-photon imaging in awake mice, enabling simultaneous single-cell resolution imaging across different brain regions.

This study uses CNNs to reveal structural components of retinal circuits by analyzing neural responses to white noise images.