2021
U-Net with hierarchical bottleneck attention for landmark detection in fundus images of the degenerated retina
We propose HBA-U-Net: a U-Net backbone with hierarchical bottleneck attention to highlight retinal abnormalities that may be important for fovea and optic disc segmentation in the degenerated retina.
A computational model of phosphene appearance for epiretinal prostheses
We present a phenomenological model that predicts phosphene appearance as a function of stimulus amplitude, frequency, and pulse duration.
Explainable AI for retinal prostheses: Predicting electrode deactivation from routine clinical measures
We present an explainable artificiall intelligence (XAI) model fit on a large longitudinal dataset that can predict electrode deactivation in Argus II.
Towards immersive virtual reality simulations of bionic vision
We propose to embed biologically realistic models of simulated prosthetic vision in immersive virtual reality so that sighted subjects can act as ‘virtual patients’ in real-world tasks.
Deep learning-based scene simplification for bionic vision
We combined deep learning-based scene simplification strategies with a psychophysically validated computational model of the retina to generate realistic predictions of simulated prosthetic vision.
2019
Model-based recommendations for optimal surgical placement of epiretinal implants
We systematically explored the space of possible implant configurations to make recommendations for optimal intraocular positioning of Argus II.
Data-driven models in human neuroscience and neuroengineering
In this review, we provide an accessible primer to modern modeling approaches and highlight recent data-driven discoveries in the domains of neuroimaging, single-neuron and neuronal population responses, and device neuroengineering.
Neural correlates of sparse coding and dimensionality reduction
Brains face the fundamental challenge of extracting relevant information from high-dimensional external stimuli in order to form the neural basis that can guide an organism’s behavior and its interaction with the world. One potential approach …
A model of ganglion axon pathways accounts for percepts elicited by retinal implants
We show that the perceptual experience of retinal implant users can be accurately predicted using a computational model that simulates each individual patient’s retinal ganglion axon pathways.
Biophysical model of axonal stimulation in epiretinal visual prostheses
To investigate the effect of axonal stimulation on the retinal response, we developed a computational model of a small population of morphologically and biophysically detailed retinal ganglion cells, and simulated their response to epiretinal …
Commentary: Detailed visual cortical responses generated by retinal sheet transplants in rats with severe retinal degeneration
A Commentary on: Detailed Visual Cortical Responses Generated by Retinal Sheet Transplants in Rats with Severe Retinal Degeneration by Foik, A. T., Lean, G. A., Scholl, L. R., McLelland, B. T., Mathur, A., Aramant, R. B., et al. (2018). J. Neurosci. …
2018
CARLsim 4: An open source library for large scale, biologically detailed spiking neural network simulation using heterogeneous clusters
We have developed CARLsim 4, a user-friendly SNN library written in C++ that can simulate large biologically detailed neural networks. Improving on the efficiency and scalability of earlier releases, the present release allows for the simulation …
2017
Learning to see again: Biological constraints on cortical plasticity and the implications for sight restoration technologies
The goal of this review is to summarize the vast basic science literature on developmental and adult cortical plasticity with an emphasis on how this literature might relate to the field of prosthetic vision.
2016
3D visual response properties of MSTd emerge from an efficient, sparse population code
Using a dimensionality reduction technique known as non-negative matrix factorization, we found that a variety of medial superior temporal (MSTd) neural response properties could be derived from MT-like input features. The responses that emerge from …
2015
A GPU-accelerated cortical neural network model for visually guided robot navigation
We present a cortical neural network model for visually guided navigation that has been embodied on a physical robot exploring a real-world environment. The model includes a rate based motion energy model for area V1, and a spiking neural network …
CARLsim 3: A user-friendly and highly optimized library for the creation of neurobiologically detailed spiking neural networks
We have developed CARLsim 3, a user-friendly, GPU-accelerated SNN library written in C/C++ that is capable of simulating biologically detailed neural models. The present release of CARLsim provides a number of improvements over our prior SNN library …
2014
Vision-based robust road lane detection in urban environments
This paper presents an integrative approach to ego-lane detection that aims to be as simple as possible to enable real-time computation while being able to adapt to a variety of urban and rural traffic scenarios. The approach at hand combines and …
Efficient spiking neural network model of pattern motion selectivity in visual cortex
We present a two-stage model of visual area MT that we believe to be the first large-scale spiking network to demonstrate pattern direction selectivity. In this model, component-direction-selective (CDS) cells in MT linearly combine inputs from V1 …
GPGPU accelerated simulation and parameter tuning for neuromorphic applications
We describe a simulation environment that can be used to design, construct, and run spiking neural networks (SNNs) quickly and efficiently using graphics processing units (GPUs). We then explain how the design of the simulation environment utilizes …
2013
Categorization and decision-making in a neurobiologically plausible spiking network using a STDP-like plasticity rule
We present a large-scale model of a hierarchical spiking neural network (SNN) that integrates a low-level memory encoding mechanism with a higher-level decision process to perform a visual classification task in real-time. The model consists of …
2010
Exploring olfactory sensory networks: Simulations and hardware emulation
Olfactory stimuli are represented in a high-dimensional space by neural networks of the olfactory system. While a number of studies have illustrated the importance of inhibitory networks within the olfactory bulb or the antennal lobe for the shaping …