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Neural Networks for Efficient Bayesian Decoding of Natural Images from Retinal Neurons
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Towards the Reconstruction of Moving Images by Populations of Retinal Ganglion Cells
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Perceptual Losses for Real-Time Style Transfer and Super-Resolution
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Reconstructing Visual Experiences from Brain Activity Evoked by Natural Movies
inferredcites →https://doi.org/10.1016/j.neuron.2009.09.006openalex-snapshot
Bayesian Reconstruction of Natural Images from Human Brain Activity
inferredcites →https://doi.org/10.1038/ncomms13749openalex-snapshot
Making brain–machine interfaces robust to future neural variability
inferredcites →https://doi.org/10.1038/nn1444openalex-snapshot
Decoding the visual and subjective contents of the human brain
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Bayesian model of dynamic image stabilization in the visual system
inferredcites →https://doi.org/10.1073/pnas.1207035109openalex-snapshot
Retinal prosthetic strategy with the capacity to restore normal vision
inferredcites →https://doi.org/10.1073/pnas.1403112111openalex-snapshot
Performance-optimized hierarchical models predict neural responses in higher visual cortex
inferredcites →https://doi.org/10.1080/713663221openalex-snapshot
A simple white noise analysis of neuronal light responses
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Neural Encoding and Decoding with Deep Learning for Dynamic Natural Vision
inferredcites →https://doi.org/10.1101/045336openalex-snapshot
Testing pseudo-linear models of responses to natural scenes in primate retina
inferredcites →https://doi.org/10.1109/acssc.2016.7869110openalex-snapshot
A neural model of high-acuity vision in the presence of fixational eye movements
inferredcites →https://doi.org/10.1109/cvprw.2009.5206848openalex-snapshot
ImageNet: A large-scale hierarchical image database
inferredcites →https://doi.org/10.1109/cvprw.2015.7301266openalex-snapshot
Self-tuned deep super resolution
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Deep Learning Face Attributes in the Wild
inferredcites →https://doi.org/10.1109/icdmw.2016.0041openalex-snapshot
Medical Image Denoising Using Convolutional Denoising Autoencoders
inferredcites →https://doi.org/10.1109/iembs.2011.6091044openalex-snapshot
Comparisons between linear and nonlinear methods for decoding motor cortical activities of monkey
inferredcites →https://doi.org/10.1109/tip.2003.819861openalex-snapshot
Image quality assessment: from error visibility to structural similarity
inferredcites →https://doi.org/10.1145/3065386openalex-snapshot
ImageNet classification with deep convolutional neural networks
inferredcites →https://doi.org/10.1152/jn.01175.2004openalex-snapshot
Fidelity of the Ensemble Code for Visual Motion in Primate Retina
inferredcites →https://doi.org/10.1152/jn.1997.78.5.2336openalex-snapshot
Decoding Visual Information From a Population of Retinal Ganglion Cells
inferredcites →https://doi.org/10.1167/11.1.14openalex-snapshot
Seeing grating-textured surface begins at the border
inferredcites →https://doi.org/10.1198/jasa.2009.tm08326openalex-snapshot
Approximate Methods for State-Space Models
inferredcites →https://doi.org/10.1364/josaa.26.000b25openalex-snapshot
The relationship between optimal and biologically plausible decoding of stimulus velocity in the retina
inferredcites →https://doi.org/10.1364/josaa.34.001511openalex-snapshot
Perceptually optimized image rendering
inferredcites →https://doi.org/10.1371/journal.pbio.1001251openalex-snapshot
Reconstructing Speech from Human Auditory Cortex
inferredcites →https://doi.org/10.1371/journal.pcbi.1004304openalex-snapshot
High Accuracy Decoding of Dynamical Motion from a Large Retinal Population
inferredcites →https://doi.org/10.1523/jneurosci.18-18-07411.1998openalex-snapshot
A Statistical Paradigm for Neural Spike Train Decoding Applied to Position Prediction from Ensemble Firing Patterns of Rat Hippocampal Place Cells
inferredcites →https://doi.org/10.1523/jneurosci.19-18-08036.1999openalex-snapshot
Reconstruction of Natural Scenes from Ensemble Responses in the Lateral Geniculate Nucleus
inferredcites →https://doi.org/10.1523/jneurosci.3256-10.2011openalex-snapshot
Incorporating Naturalistic Correlation Structure Improves Spectrogram Reconstruction from Neuronal Activity in the Songbird Auditory Midbrain
inferredcites →https://doi.org/10.1523/jneurosci.3577-09.2009openalex-snapshot
Decoding and Reconstructing Color from Responses in Human Visual Cortex
inferredcites →https://doi.org/10.17863/cam.51996openalex-snapshot
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
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Adam: A Method for Stochastic Optimization
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Loss Functions for Neural Networks for Image Processing
inferredcites →https://doi.org/10.48550/arxiv.1606.08921openalex-snapshot
Image Restoration Using Convolutional Auto-encoders with Symmetric Skip Connections
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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An Adaptive Convolution Auto-encoder Based on Spiking Neurons
inferred← citeshttps://doi.org/10.1007/s10489-022-03402-wopenalex-snapshot
Fusion of ANNs as decoder of retinal spike trains for scene reconstruction
inferred← citeshttps://doi.org/10.1007/s11633-022-1335-2openalex-snapshot
Neural Decoding of Visual Information Across Different Neural Recording Modalities and Approaches
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Neural data science: accelerating the experiment-analysis-theory cycle in large-scale neuroscience
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Toward the Next Generation of Retinal Neuroprosthesis: Visual Computation with Spikes
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Electroencephalography-driven three-dimensional object decoding with multi-view perception diffusion
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High - quality decoding of RGB images from the neuronal signals of the pigeon optic tectum
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Reconstruction of natural visual scenes from neural spikes with deep neural networks
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Understanding the circuit basis of cognitive functions using mouse models
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Generative adversarial networks for reconstructing natural images from brain activity
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Neuroscience Cloud Analysis As a Service: An open-source platform for scalable, reproducible data analysis
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Simulation of visual perception and learning with a retinal prosthesis
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Firing-rate-modulated spike detection and neural decoding co-design
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Deep learning approaches for neural decoding across architectures and recording modalities
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A latent variable approach to decoding neural population activity
inferred← citeshttps://doi.org/10.1101/2020.03.18.997924openalex-snapshot
YASS: Yet Another Spike Sorter applied to large-scale multi-electrode array recordings in primate retina
inferred← citeshttps://doi.org/10.1101/2022.01.23.477422openalex-snapshot
Rapid Selectivity to Natural Images Across Layers of Primate V1
inferred← citeshttps://doi.org/10.1101/2022.05.19.492737openalex-snapshot
Maximum a posteriori natural scene reconstruction from retinal ganglion cells with deep denoiser priors
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Reconstruction of visual images from mouse retinal ganglion cell spiking activity using convolutional neural networks
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A thin-film optogenetic visual prosthesis
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Modeling responses of macaque and human retinal ganglion cells to natural images using a convolutional neural network
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Scalable approximate Bayesian inference for particle tracking data
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Visual reconstruction from 2-photon calcium imaging suggests linear readout properties of neurons in mouse primary visual cortex
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Neural Sampling Strategies for Visual Stimulus Reconstruction fromTwo-photon Imaging of Mouse Primary Visual Cortex
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Seeing Beyond the Brain: Conditional Diffusion Model with Sparse Masked Modeling for Vision Decoding
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Psychometry: An Omnifit Model for Image Reconstruction from Human Brain Activity
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Neural Ganglion Sensors: Learning Task-specific Event Cameras Inspired by the Neural Circuit of the Human Retina
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Simultaneous Neural Spike Encoding and Decoding Based on Cross-modal Dual Deep Generative Model
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Reconstructing Retinal Visual Images from 3T fMRI Data Enhanced by Unsupervised Learning
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Neural Sampling Strategies for Visual Stimulus Reconstruction from Two-photon Imaging of Mouse Primary Visual Cortex
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Sparse Coding Enables the Reconstruction of High-Fidelity Images and Video from Retinal Spike Trains
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BrainRAM: Cross-Modality Retrieval-Augmented Image Reconstruction from Human Brain Activity
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Nonlinear Decoding of Natural Images From Large-Scale Primate Retinal Ganglion Recordings
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Decoding dynamic visual scenes across the brain hierarchy
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High-Fidelity Reproduction of Visual Signals by Electrical Stimulation in the Central Primate Retina
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Hacia una neuroprótesis visual basada en IA: desarrollo e implementación en humanos de una interfaz neuronal deep learning
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Attention maps reveal stimulus-dependent retinal population codes
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Interpreting Encoding and Decoding Models
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Neural Clustering Processes
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Towards the Next Generation of Retinal Neuroprosthesis: Visual Computation with Spikes
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Deep learning approaches for neural decoding: from CNNs to LSTMs and spikes to fMRI
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High-contrast "gaudy" images improve the training of deep neural network models of visual cortex
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Variational framework for partially-measured physical system control: examples of vision neuroscience and optical random media
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How nonlinear processing shapes natural stimulus encoding in the retina
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Reconstruction of natural images from responses of primate retinal ganglion cells
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Fast deep neural correspondence for tracking and identifying neurons in C. elegans using semi-synthetic training
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Precise control of neural activity using dynamically optimized electrical stimulation
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