Michael B. Manookin

The paper identifies and characterizes a long-range inhibitory circuit in primate retina involving A1 amacrine cells and recursive bistratified ganglion cells, revealing their network organization and spike dynamics.

The paper introduces a computational framework to design stimuli that selectively manipulate specific retinal ganglion cell types with minimal impact on others.

This paper introduces a high-throughput method for studying retinal ganglion cell projections, physiology, and morphology across species without relying on genetically modified animals.

This study shows that ASCL1 can reprogram adult and infant macaque Müller glia into retinal ganglion cell-like neurons using a modified vector cassette.

The paper identifies functional diversity in primate retinal ganglion cells (RGCs) through multi-electrode recordings, revealing non-classical receptive field structures and specialized roles beyond spatial filtering.

This paper develops a deep learning model of the retina with photoreceptor adaptation mechanisms, improving prediction of primate and rat retinal ganglion cell responses to dynamic stimuli.

The paper identifies features of predictive computations in the primate retina that may generalize across sensory systems.

This study identifies four primate retinal pathways that encode predictive motion information, nearly optimally representing future object trajectories.

This study shows that neural sensitization in the primate retina maintains neuronal sensitivity during light intensity fluctuations, improving sensory encoding accuracy.

The paper investigates the unique physiological properties of ON and OFF smooth monostratified ganglion cells in primate retinas, revealing nonlinear subunit properties and dendritic contributions to their receptive field structure.