Alan M Litke

This study uses electrical stimulation to replicate natural spiking activity in primate retinal neurons, achieving lower variability than visual stimuli.

This study develops a framework for cellular-resolution electrical stimulation of neurons using current steering and biophysical models, demonstrating its effectiveness in targeting retinal ganglion cells.

The paper develops a population decoding model to predict sound source location using mouse superior colliculus neurons, showing that mutual information weighted models perform best with RF neurons.

The paper examines how different primate retinal ganglion cell types respond to natural scenes, finding stereotyped response kinetics and distinct firing pattern repertoires across cell types.

The paper decomposes retinal ganglion cell electrical images to infer cell types and functional properties using a novel optimization-based algorithm.

The paper characterizes auditory responsive neurons in the mouse superior colliculus using naturalistic sounds and identifies four distinct subtypes with specific spatial preferences.

The paper develops a biophysical model to study retinal ganglion cell responses to multi-electrode stimulation and validates it with experimental data from macaque retinas.

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 study shows fixational eye movements improve retinal signal precision by enhancing spike timing and cell interactions in macaque retinas.

This paper introduces a dynamically optimized electrical stimulation method to enhance neural activity control in retinal implants, showing improved visual stimulus reconstruction compared to static methods.

The paper trains a convolutional neural network to predict retinal ganglion cell responses to natural images in macaques and humans, finding it more accurate than a linear-nonlinear model.

The paper infers light responses of primate retinal ganglion cells using electrical features, achieving moderate correlation with measured firing rates.

The paper infers electrical stimulation sensitivity of primate retinal ganglion cells from their recorded activity, showing that electrode features and cell compartmental differences affect stimulation thresholds.

This study evaluates the effectiveness of focal electrical stimulation in the central macaque retina to reproduce visual signals, finding higher expected image quality compared to the peripheral retina.

This study demonstrates that high-fidelity electrical stimulation of human retinal ganglion cells is achievable with extracellular stimulation, validated through ex vivo experiments and comparison to macaque retina results.

The paper develops a method to reconstruct natural images from retinal ganglion cell activity using deep denoiser priors, achieving high perceptual similarity with fewer parameters than previous approaches.

The paper examines individual variability in neural computations of the primate retina using machine learning and finds sex-based differences in firing rates and temporal integration.

The paper investigates nonlinear visuoauditory integration in the mouse superior colliculus, finding that integration depends on auditory stimulus properties and reveals conditions consistent with existing models.

This study shows that C57BL/6 mice lack high-frequency hearing and a topographic map of auditory space due to a genetic mutation, and this can be rescued by introducing wild-type Cdh23.

The paper reconstructs natural images from primate retinal ganglion cell responses, showing that optimal filters reflect image statistics and include contributions from nearby cells.

The paper compares functional properties of major retinal ganglion cell types between humans and macaques using similar experimental methods, finding close parallels in their responses and organization.

The paper introduces a method to infer nonlinear spatial subunits in primate retina using spike-triggered clustering, showing improved response prediction with subunit models in both natural and controlled stimuli.

The paper shows that spectral cues are necessary for encoding frontal auditory space in the mouse superior colliculus, while lateral fields rely on ILDs.

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.

The paper evaluates local return stimulation to improve selective activation of retinal ganglion cells at cellular resolution in isolated primate retina.

The paper develops a Gaussian Process model to cancel electrical stimulation artifacts and detect neural spikes in multi-electrode recordings, achieving low error rates and real-time compatibility.

The paper investigates visual response properties of neurons in the mouse superior colliculus, finding that deep SC neurons are suppressed by specific visual stimuli and exhibit complex-cell-like properties.

Generalized linear models fit macaque parasol ganglion cells under white noise but fail on naturalistic stimuli, even when fitted on them, and added scalar nonlinearities do not rescue them.