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Efficient and direct estimation of a neural subunit model for sensory coding

Brett Vintch, Andrew D Zaharia, J Anthony Movshon, Eero P Simoncelli
2012 Advances in Neural Information Processing Systems  
Subspace methods such as spike-triggered covariance (STC) can recover multiple filters, but require substantial amounts of data, and recover an orthogonal basis for the subspace in which the filters reside  ...  We present a method for directly fitting this model to spike data, and apply it to both simulated and real neuronal data from primate V1.  ...  Figure 1 : 1 Spike-triggered covariance analysis of a simulated V1 complex cell.  ... 
pmid:26273181 pmcid:PMC4532270 fatcat:iq6kvd47yjeq5fp2g3qqp5sgie

Inferring hidden structure in multilayered neural circuits

Niru Maheswaranathan, David B. Kastner, Stephen A. Baccus, Surya Ganguli, Peter E. Latham
2018 PLoS Computational Biology  
triggered average (STA) and covariance (STC) for high dimensional stimuli.  ...  Our models demonstrate a 53% improvement in predicting ganglion cell spikes over classical linear-nonlinear (LN) models.  ...  Acknowledgments The authors would like to thank Ben Naecker, Ben Poole, and Lane McIntosh for discussions as well as Stéphane Deny, Tim Gollisch, Ben Naecker, and Alex Williams for comments on the manuscript  ... 
doi:10.1371/journal.pcbi.1006291 pmid:30138312 fatcat:5yn5oedl3ffsbmoyvwesbtr5ty

Inferring hidden structure in multilayered neural circuits [article]

Niru Maheswaranathan, David B. Kastner, Stephen A. Baccus, Surya Ganguli
2017 bioRxiv   pre-print
triggered average (STA) and covariance (STC) for high dimensional stimuli.  ...  Subunits had consistently high thresholds, leading to sparse activity patterns in which only one subunit drives ganglion cell spiking at any time.  ...  Acknowledgments The authors would like to thank Ben Naecker, Ben Poole, and Lane McIntosh for discussions as well as Stéphane Deny, Ben Naecker, and Alex Williams for comments on the manuscript.  ... 
doi:10.1101/120956 fatcat:xpd2ixu7dnh3tiv4etmroqz5pm

A Convolutional Subunit Model for Neuronal Responses in Macaque V1

B. Vintch, J. A. Movshon, E. P. Simoncelli
2015 Journal of Neuroscience  
Subspace methods like spike-triggered covariance can recover multiple filters but require substantial amounts of data, and recover an orthogonal basis for the subspace in which the filters reside, rather  ...  These filters cannot be estimated using standard methods, such as spike-triggered averaging.  ...  The results show that the fitted model outperforms previously published functional models (specifically, the LN, energy, and spike-triggered covariance [STC]-based models) for all cells, in addition to  ... 
doi:10.1523/jneurosci.2815-13.2015 pmid:26538653 pmcid:PMC4635132 fatcat:ih7k7lhowbayzbknct6wky75i4

Inference of Nonlinear Spatial Subunits by Spike-Triggered Clustering in Primate Retina [article]

Nishal P Shah, Nora Brackbill, Colleen E. Rhoades, Alexandra Kling, Georges Goetz, Alan Litke, Alexander Sher, Eero P Simoncelli, E.J. Chichilnisky
2018 bioRxiv   pre-print
We present a novel method for maximum likelihood estimation of nonlinear subunits by soft-clustering spike-triggered stimuli.  ...  Joint clustering with multiple RGCs revealed shared subunits in neighboring cells, producing a parsimonious population model.  ...  Acknowledgements Author contributions NS, NB, CR, AK, GG collected the MEA data, NS, EJC, ES conceived and designed the experiments, NS implemented the subunit model and analyzed data, AS and AL developed  ... 
doi:10.1101/496422 fatcat:fgypfzfx6zhzxnivfxjlsojyqa

Towards the Next Generation of Retinal Neuroprosthesis: Visual Computation with Spikes [article]

Zhaofei Yu and Jian K. Liu and Shanshan Jia and Yichen Zhang and Yajing Zheng and Yonghong Tian and Tiejun Huang
2020 arXiv   pre-print
Here we review some of the recent progress about visual computation models that use spikes for analyzing natural scenes, including static images and dynamic movies.  ...  The retina computes visual scenes and then sends its output as neuronal spikes to the cortex for further computation. Therefore, the neuronal signal of interest for retinal neuroprosthesis is spike.  ...  the assumption that the input of the neuron is correlated; spike-triggered covariance model [72, 73, 66] , where covariance of spike-triggered ensemble is analyzed with eigenvector analysis to obtain  ... 
arXiv:2001.04064v1 fatcat:sqralx5q2zca3k6nvamur46wbe

Toward the Next Generation of Retinal Neuroprosthesis: Visual Computation with Spikes

Zhaofei Yu, Jian K. Liu, Shanshan Jia, Yichen Zhang, Yajing Zheng, Yonghong Tian, Tiejun Huang
2020 Engineering  
This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version  ...  An extension of the STA to covariance analysis, which is known as spike-triggered covariance, serves as a powerful tool for analyzing the second-order dynamics of the retinal neurons [63, 64] .  ...  filters are included with the assumption that the inputs of the neuron are correlated; the spike-triggered covariance model [64, 70, 71] , in which the covariance of the spike-triggered ensemble is analyzed  ... 
doi:10.1016/j.eng.2020.02.004 fatcat:33rqlxpyefdd7luo3pkm4wumqq

An in silico deep learning approach to multi-epitope vaccine design: a SARS-CoV-2 case study

Zikun Yang, Paul Bogdan, Shahin Nazarian
2021 Scientific Reports  
By combining the in silico immunoinformatics and deep neural network strategies, the DeepVacPred computational framework directly predicts 26 potential vaccine subunits from the available SARS-CoV-2 spike  ...  11 of them to construct a multi-epitope vaccine for SARS-CoV-2 virus.  ...  The code used for data generation and/or analysis in the study are available on github.com (https ://githu b.com/ zikun yang/DCVST ).  ... 
doi:10.1038/s41598-021-81749-9 pmid:33547334 fatcat:shy5z5wi6zc5ri2peycjsb6beq

Cross-orientation suppression in visual area V2

Ryan J. Rowekamp, Tatyana O. Sharpee
2017 Nature Communications  
Previous work has found multiple types of V2 neurons, with neurons of each type selective for multi-edge features.  ...  First, the relevant edges for V2 neurons can be grouped into quadrature pairs, indicating invariance to local translation.  ...  Acknowledgements We thank Margot Larroche and Sebastien Tawa for help with preliminary analyses of this data set and Lawrence Sincich for discussions.  ... 
doi:10.1038/ncomms15739 pmid:28593941 pmcid:PMC5472723 fatcat:elmxbnq3qbholirwee6ebep5te

Spatiotemporal Elements of Macaque V1 Receptive Fields

Nicole C. Rust, Odelia Schwartz, J. Anthony Movshon, Eero P. Simoncelli
2005 Neuron  
But an analysis with spikes. This analysis reveals an unsuspected of the spike-triggered covariance (STC) can resolve richness of neuronal computation within V1.  ...  LNP Functional Models for V1 Neurons, and Their Characterization Using Spike-Triggered Analyses (A) A standard simple cell model, based on a single space-time oriented filter.  ...  functional model estimated with spike-triggered techniques.  ... 
doi:10.1016/j.neuron.2005.05.021 pmid:15953422 fatcat:bwqllw7lwnb3tfdp3tghtzzeim

Individual variability of neural computations in the primate retina [article]

Nishal Shah, Nora Brackbill, Ryan Samarakoon, Colleen Rhoades, Alexandra Kling, Alexander Sher, Alan Litke, Yoram Singer, Jonathon Shlens, E.J. Chichilnisky
2021 bioRxiv   pre-print
Simulations indicated that combining a vast dataset of healthy macaque recordings with behavioral feedback could be used to identify the neural code and improve retinal implants for treating blindness.  ...  AbstractVariation in the neural code between individuals contributes to making each person unique.  ...  describing variation in spatial nonlinearities, subunit models were fitted using spike triggered 5 clustering d 7 .  ... 
doi:10.1101/2021.02.14.431169 fatcat:dtcz7wrzo5eqhmiabu3xduxlrm

Inferring Nonlinear Neuronal Computation Based on Physiologically Plausible Inputs

James M. McFarland, Yuwei Cui, Daniel A. Butts, Matthias Bethge
2013 PLoS Computational Biology  
We thus present a modeling framework that can capture a broad range of nonlinear response functions while providing physiologically interpretable descriptions of neural computation.  ...  Here we present an approach for modeling sensory processing, termed the Nonlinear Input Model (NIM), which is based on the hypothesis that the dominant nonlinearities imposed by physiological mechanisms  ...  Alonso for contributing the LGN data, the Theunissen lab and CRCNS database for providing the songbird auditory midbrain data, N. Rust and T. Movshon for contributing the macaque V1 data, and T.  ... 
doi:10.1371/journal.pcbi.1003143 pmid:23874185 pmcid:PMC3715434 fatcat:tvs2jswpvnhfdingo6cbzqkywi

Features and functions of nonlinear spatial integration by retinal ganglion cells

Tim Gollisch
2013 Journal of Physiology - Paris  
covariance, extensions of generalized linear models).  ...  Models of neural responses to stimuli with complex spatiotemporal correlation structure often assume that neurons are only selective for a small number of linear projections of a potentially high-dimensional  ...  Acknowledgements The author would like to thank Vidhyasankar Krishnamoorthy for contributing the data for Fig. 1 .  ... 
doi:10.1016/j.jphysparis.2012.12.001 pmid:23262113 fatcat:npxp5drrafgmzmkg34cefcsom4

Deep convolutional models improve predictions of macaque V1 responses to natural images

Santiago A. Cadena, George H. Denfield, Edgar Y. Walker, Leon A. Gatys, Andreas S. Tolias, Matthias Bethge, Alexander S. Ecker, Wolfgang Einhäuser
2019 PLoS Computational Biology  
In conclusion, multi-layer convolutional neural networks (CNNs) set the new state of the art for predicting neural responses to natural images in primate V1 and deep features learned for object recognition  ...  Recently, two approaches based on deep learning have emerged for modeling these nonlinear computations: transfer learning from artificial neural networks trained on object recognition and data-driven convolutional  ...  We thank Tori Shinn for help with animal training and neural recordings.  ... 
doi:10.1371/journal.pcbi.1006897 pmid:31013278 pmcid:PMC6499433 fatcat:rvmjfntj7zfhdclzvge2e623vi

Hidden Complexity of Synaptic Receptive Fields in Cat V1

J. Fournier, C. Monier, M. Levy, O. Marre, K. Sari, Z. F. Kisvarday, Y. Fregnac
2014 Journal of Neuroscience  
We further show that the diversity of Complex-like contributions recovered at the subthreshold level is expressed in the cell spiking output.  ...  intracellular membrane potential recordings in cat V1 with 2D dense noise stimulation to decompose the Simple-like and Complex-like components of the subthreshold RF into a parallel set of functionally distinct subunits  ...  We thus searched for a more efficient and parsimonious representation of the secondorder kernel and opted for a decomposition method similar to the principal component analysis of the spike-triggered covariance  ... 
doi:10.1523/jneurosci.0474-13.2014 pmid:24741042 pmcid:PMC6608221 fatcat:wylxdhus5negtcv3wa3ekpe4gu
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