Neuroscience and Neurobiology Commons^™

Toward A Manifold Encoding Neural Responses, Luciano Dyballa, Andra M. Rudzite, Mahmood S. Hoseini, Mishek Thapa, Michael P. Stryker, Greg D. Field, Steven W. Zucker

MODVIS Workshop

Understanding circuit properties from physiological data presents two challenges: (i) recordings do not reveal connectivity, and (ii) stimuli only exercise circuits to a limited extent. We address these challenges for the mouse visual system with a novel neural manifold obtained using unsupervised algorithms. Each point in our manifold is a neuron; nearby neurons respond similarly in time to similar parts of a stimulus ensemble. This ensemble includes drifting gratings and flows, i.e., patterns resembling what a mouse would “see” running through fields.

Regarding (i), our manifold differs from the standard practice in computational neuroscience: embedding trials in neural coordinates. Topology …

Virtual Eye: A Spatial-Temporal Bottom-Up Eye Sensitivity Model, Todd Goodall

MODVIS Workshop

Video quality and compression models use the

spatial contrast sensitivity function (CSF), which is solved

based on a linear system approximation. This function measures

the eye’s sensitivity to sinusoid gratings, ignoring the subtle

connectivity and inhomogeniety of cell density across the

visual field. Non-linear aspects of the eye, such as the change

in frequency sensitivity with changing illumination, are not

captured by this simple approximation. We propose Virtual

Eye, a bottom-up approach that models the spatio-temporal

dynamics of the eye across the visual field. Each functional

retinal cell layer in the eye is modeled using non-uniform spatial

cell responses, which …

Modeling Emmetropization In An Incessantly Moving Eye, Michele Rucci, Jonathan D. Victor

MODVIS Workshop

Many questions remain unanswered regarding the specific cues and mechanisms for emmetropization, the process by which, during development, the eye adjusts itself so that distant objects are in focus. Research has so far primarily focused on the spatial cues present in the image on the retina, such as the degree of blur. However, eye movements incessantly transform a mostly static scene into temporal modulations, so that the input to the retina is not an image, but a spatiotemporal flow of luminance. Models of retinal input signals indicate that this space-time reformatting caused by eye movements yields additional cues to the …