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Computational Vision

Neural Circuits and Algorithms

97 Publications

Spatial frequency selectivity in macaque LGN and V1

Paul Levy

Dissertation

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2023

Spatial frequency selectivity in macaque LGN and V1

@PHDTHESIS{Levy-phd,
     TITLE= "Spatial frequency selectivity in macaque {LGN} and {V1}",
     AUTHOR= "Paul Levy",
     ADVISOR= "J. Anthony Movshon and Eero P. Simoncelli",
     SCHOOL= "Center for Neural Science, New York University",
     ADDRESS= "New York, NY",
     YEAR= 2023,
     MONTH= "Apr",
     PDF-URL= "http://www.cns.nyu.edu/pub/lcv/levy-phd.pdf",
}

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Catalyzing next-generation Artificial Intelligence through NeuroAI

Anthony Zador, Sean Escola, Blake Richards, Bence Ölveczky, Yoshua Bengio, Kwabena Boahen, Matthew Botvinick, D. Chklovskii, Anne Churchland, Claudia Clopath, James DiCarlo, Surya Ganguli, Jeff Hawkins, Konrad Körding, Alexei Koulakov, Yann LeCun, Timothy Lillicrap, Adam Marblestone, Bruno Olshausen, Alexandre Pouget, Cristina Savin, Terrence Sejnowski, E. P. Simoncelli, Sara Solla, David Sussillo, Andreas S. Tolias, Doris Tsao

Nature Communications, 14:1597

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2023

Catalyzing next-generation Artificial Intelligence through NeuroAI

@ARTICLE{Zador23,
     TITLE= "Catalyzing next-generation Artificial Intelligence through NeuroAI",
     AUTHOR= "A Zador and S Escola and B Richards and B {O}lveczky and Y
     Bengio and K Boahen and M Botvinick and D Chklovskii and A
     Churchland and C Clopath and J DiCarlo and S Ganguli and
     J Hawkins and K K{oe}rding and A Koulakov and Y LeCun and T
     Lillicrap and A Marblestone and B Olshausen and A Pouget and C
     Savin and T Sejnowski and E P Simoncelli and S Solla and D
     Sussillo and AS Tolias and D Tsao",
     JOURNAL= "Nature Communications",
     VOLUME= 14,
     NUMBER= 1597,
     MONTH= "Mar",
     YEAR= 2023,
     DOI= "10.1038/s41467-023-37180-x",
     PDF-URL= "http://www.cns.nyu.edu/pub/lcv/zador23-reprint.pdf",
}

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Polar prediction of natural videos

P. Fiquet, E. P. Simoncelli

arXiv:2303.03432

2023

Coordinated drift of receptive fields in Hebbian/anti-Hebbian network models during noisy representation learning

Shanshan Qin, S. Farashahi, D. Lipshutz, A. Sengupta, D. Chklovskii, Cengiz Pehlevan

bioRxiv:2021.08.30.458264v1

Nature Neuroscience, 26 (2): 339--349

2023

Fine-tuning hierarchical circuits through learned stochastic co-modulation

Caroline Haimerl, E. P. Simoncelli, Cristina Savin

Advances in Neural Information Processing Systems, Vol. 35

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2022

Fine-tuning hierarchical circuits through learned stochastic co-modulation

@INPROCEEDINGS{Haimerl22b,
     TITLE= "Fine-tuning hierarchical circuits through learned stochastic co-modulation",
     AUTHOR= "C Haimerl and E P Simoncelli and C Savin ",
     BOOKTITLE= {Adv. Neural Information Processing Systems, Workshop on ''All Things Attention''},
     MONTH= "Dec",
     YEAR= 2022,
     URL= "https://openreview.net/forum?id=pmivD7VcBT",
     PDF-URL= "http://www.cns.nyu.edu/pub/lcv/haimerl22b.pdf",
}

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Maximum a posteriori natural scenes reconstruction from retinal ganglion cells with deep denoiser priors

Eric G. Wu, Nora Brackbill, Alexander Sher & Alan M. Litke, E. P. Simoncelli, E.J. Chichilnisky

Advances in Neural Information Processing Systems, Vol. 35

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2022

Maximum a posteriori natural scenes reconstruction from retinal ganglion cells with deep denoiser priors

@INPROCEEDINGS{Wu22,
     TITLE= "Maximum a posteriori natural scenes reconstruction from retinal ganglion cells
     with deep denoiser priors",
     AUTHOR= "E G Wu and N Brackbill and A Sher and A M Litke and E P
     Simoncelli and E J Chichilnisky",
     BOOKTITLE= {Adv. Neural Information Processing Systems (NeurIPS*22)},
     VOLUME= 35,
     MONTH= "Dec",
     YEAR= 2022,
     ADDRESS= "New Orleans",
     URL= "https://proceedings.neurips.cc/paper_files/paper/2022/hash/ae447e9dbfdd1189966e894b85bea062-Abstract-Conference.html",
     PDF-URL= "http://www.cns.nyu.edu/pub/lcv/wu22-reprint.pdf",
}

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Normative theories of synaptic plasticity for representation and perceptual discrimination

Colin Bredenberg

Dissertation

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2022

Normative theories of synaptic plasticity for representation and perceptual discrimination

@PHDTHESIS{Bredenberg-phd,
     TITLE= "Normative theories of synaptic plasticity for representation
     and perceptual discrimination",
     AUTHOR= "Colin Bredenberg",
     ADVISOR= "Cristina Savin and Eero P. Simoncelli",
     SCHOOL= "Center for Neural Science, New York University",
     ADDRESS= "New York, NY",
     YEAR= 2022,
     MONTH= "Sep",
     PDF-URL= "http://www.cns.nyu.edu/pub/lcv/bredenberg-phd.pdf",
}

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Neural Circuits for Dynamics-Based Segmentation of Time Serie

T. Tesileanu, S. Golkar, Samaneh Nasiri, A. Sengupta, D. Chklovskii

Neural Computation, 34 (4): 891–938

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2022

Neural Circuits for Dynamics-Based Segmentation of Time Serie

@article{10.1162/neco_a_01476,
    author = {Teşileanu, Tiberiu and Golkar, Siavash and Nasiri, Samaneh and Sengupta, Anirvan M. and Chklovskii, Dmitri B.},
    title = "{Neural Circuits for Dynamics-Based Segmentation of Time Series}",
    journal = {Neural Computation},
    volume = {34},
    number = {4},
    pages = {891-938},
    year = {2022},
    month = {03},
    abstract = "{The brain must extract behaviorally relevant latent variables from the signals streamed by the sensory organs. Such latent variables are often encoded in the dynamics that generated the signal rather than in the specific realization of the waveform. Therefore, one problem faced by the brain is to segment time series based on underlying dynamics. We present two algorithms for performing this segmentation task that are biologically plausible, which we define as acting in a streaming setting and all learning rules being local. One algorithm is model based and can be derived from an optimization problem involving a mixture of autoregressive processes. This algorithm relies on feedback in the form of a prediction error and can also be used for forecasting future samples. In some brain regions, such as the retina, the feedback connections necessary to use the prediction error for learning are absent. For this case, we propose a second, model-free algorithm that uses a running estimate of the autocorrelation structure of the signal to perform the segmentation. We show that both algorithms do well when tasked with segmenting signals drawn from autoregressive models with piecewise-constant parameters. In particular, the segmentation accuracy is similar to that obtained from oracle-like methods in which the ground-truth parameters of the autoregressive models are known. We also test our methods on data sets generated by alternating snippets of voice recordings. We provide implementations of our algorithms at https://github.com/ttesileanu/bio-time-series.}",
    issn = {0899-7667},
    doi = {10.1162/neco_a_01476},
    url = {https://doi.org/10.1162/neco\_a\_01476},
    eprint = {https://direct.mit.edu/neco/article-pdf/34/4/891/2003154/neco\_a\_01476.pdf},
}

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Deep denoising for scientific discovery: A case study in electron microscopy

S. Mohan, Ramon Manzorro, Joshua L. Vincent, Binh Tang, Dev Y. Sheth, E. P. Simoncelli, David S. Matteson, Peter A. Crozier, Carlos Fernandez-Granda

IEEE Transactions on Computational Imaging, 8:585-597

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2022

Deep denoising for scientific discovery: A case study in electron microscopy

@ARTICLE{Mohan22,
     TITLE= "Deep denoising for scientific discovery: A case study in electron microscopy",
     AUTHOR= "S Mohan and R Manzorro and J L Vincent and B Tang and D Y
     Sheth and E P Simoncelli and D S Matteson and P A Crozier and
     C Fernandez-Granda",
     JOURNAL= "IEEE Trans. Computational Imaging",
     MONTH= "Jul",
     VOLUME= 8,
     PAGES= "585--597",
     YEAR= 2022,
     DOI= "10.1109/TCI.2022.3176536",
     PDF-URL= "http://www.cns.nyu.edu/pub/lcv/mohan22-reprint.pdf",
}

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Effects of foveation on early visual representations

B. Broderick

Dissertation

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2022

Effects of foveation on early visual representations

@PHDTHESIS{Broderick-phd,
     TITLE= "Effects of foveation on early visual representations",
     AUTHOR= "William F. Broderick",
     ADVISOR= "Eero P. Simoncelli and Jonathan Winawer",
     SCHOOL= "Center for Neural Science, New York University",
     ADDRESS= "New York, NY",
     YEAR= 2022,
     MONTH= "May",
     PDF-URL= "http://www.cns.nyu.edu/pub/lcv/broderick-phd.pdf",
}

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