J. Pillow

发表

Dimensionality reduction in neural models: an information-theoretic generalization of spike-triggered average and covariance analysis.

Eero P. Simoncelli, Jonathan W. Pillow, J. Pillow, 2006, Journal of vision.

A Model-Based Spike Sorting Algorithm for Removing Correlation Artifacts in Multi-Neuron Recordings

Eero P. Simoncelli, Jonathan W. Pillow, J. Pillow, 2013, PloS one.

Spatio-temporal correlations and visual signalling in a complete neuronal population

Eero P. Simoncelli, Jonathan W. Pillow, L. Paninski, 2008, Nature.

To appear in: The New Cognitive Neurosciences, 3rd edition Editor: M. Gazzaniga. MIT Press, 2004. Characterization of Neural Responses with Stochastic Stimuli

Eero P. Simoncelli, Jonathan W. Pillow, L. Paninski, 2022 .

Discovering Event Structure in Continuous Narrative Perception and Memory

Jonathan W. Pillow, J. Pillow, K. Norman, 2016, Neuron.

Single-trial spike trains in parietal cortex reveal discrete steps during decision-making

Jonathan W. Pillow, Kenneth W. Latimer, Jacob L. Yates, 2015, Science.

Exploiting gradients and Hessians in Bayesian optimization and Bayesian quadrature.

Mikio C. Aoi, J. Pillow, Anqi Wu, 2017, 1704.00060.

Modeling the Impact of Common Noise Inputs on the Network Activity of Retinal Ganglion Cells Action Editor: Brent Doiron

Eero P. Simoncelli, Jonathon Shlens, Liam Paninski, 2022 .

Model-based decoding, information estimation, and change- point detection in multi-neuron spike trains

L. Paninski, J. Pillow, 2006 .

Spectral methods for neural characterization using generalized quadratic models

Jonathan W. Pillow, Il Park, Nicholas Priebe, 2013, NIPS.

Encoding and decoding in parietal cortex during sensorimotor decision-making

Il Memming Park, Jonathan W. Pillow, J. Pillow, 2014, Nature Neuroscience.

Dissociated functional significance of decision-related activity in the primate dorsal stream

Jonathan W. Pillow, Leor N. Katz, Jacob L. Yates, 2016, Nature.

Computational approaches to fMRI analysis

Kai Li, Theodore L. Willke, Uri Hasson, 2017, Nature Neuroscience.

Efficient Markov Chain Monte Carlo Methods for Decoding Neural Spike Trains

Liam Paninski, Jonathan W. Pillow, Yashar Ahmadian, 2011, Neural Computation.

Got a moment or two ? Neural models and linear dimensionality reduction

Il Memming Park, Evan Archer, J. Pillow, 2012 .

Combined Social and Spatial Coding in a Descending Projection from the Prefrontal Cortex

Jonathan W. Pillow, Ilana B. Witten, Nathan F. Parker, 2017, Cell.

Unsupervised identification of the internal states that shape natural behavior

Jonathan W. Pillow, Adam J. Calhoun, J. Pillow, 2019, Nature Neuroscience.

Unsupervised identification of the internal states that shape natural behavior

Adam J. Calhoun, J. Pillow, M. Murthy, 2019, Nature Neuroscience.

Combined social and spatial coding in a descending projection from the prefrontal cortex

J. Pillow, J. Taliaferro, I. Witten, 2017, bioRxiv.

Correcting motion induced fluorescence artifacts in two-channel neural imaging

Matthew S. Creamer, Jonathan W. Pillow, Andrew M Leifer, 2022, PLoS Comput. Biol..

Perceptual Completion across the Vertical Meridian and the Role of Early Visual Cortex

Nava Rubin, Jonathan W. Pillow, Jonathan Pillow, 2002, Neuron.

Volumetric Two-photon Imaging of Neurons Using Stereoscopy (vTwINS)

Adam S. Charles, Jonathan W. Pillow, David W. Tank, 2016, Nature Methods.

Volumetric Two-photon Imaging of Neurons Using Stereoscopy (vTwINS)

Adam S. Charles, D. Tank, J. Pillow, 2016 .

Majority of choice-related variability in perceptual decisions is present in early sensory cortex

Jonathan W. Pillow, Michael J. Morais, Eyal Seidemann, 2017, bioRxiv.

Dethroning the Fano Factor: a flexible, model-based approach to partitioning neural variability

Adam S. Charles, J. Pillow, G. Horwitz, 2017, bioRxiv.

Inferring synaptic inputs from spikes with a conductance-based neural encoding model

Jonathan W. Pillow, Fred Rieke, Kenneth W. Latimer, 2018, bioRxiv.

Running reduces firing but improves coding in rodent higher-order visual cortex

Jonathan W. Pillow, Amelia J. Christensen, J. Pillow, 2017, bioRxiv.

Improved numberical methods for computing likelihoods in the stochastic integrate-and-fire model

Liam Paninski, Jonathan W. Pillow, Christopher Williams, 2005 .

Editorial overview: Machine learning, big data, and neuroscience

M. Sahani, J. Pillow, 2019, Current Opinion in Neurobiology.

25th Annual Computational Neuroscience Meeting: CNS-2016

Morten L. Kringelbach, Majid Nili Ahmadabadi, Anders M. Dale, 2016, BMC Neuroscience.

Mice alternate between discrete strategies during perceptual decision-making

Nicholas A. Roy, Jonathan W. Pillow, Anne E. Urai, 2020, bioRxiv.

Discovering Event Structure in Continuous Narrative Perception and Memory

Kenneth A. Norman, Christopher Baldassano, Janice Chen, 2016, Neuron.

Adaptive stimulus selection for multi-alternative psychometric functions with lapses

Jonathan W Pillow, Jonathan W. Pillow, Ji Hyun Bak, 2018, bioRxiv.

Spatio-temporal correlations and visual signalling in a complete neuronal population

Eero P. Simoncelli, L. Paninski, J. Pillow, 2008, Nature.

Prediction and Decoding of Retinal Ganglion Cell Responses with a Probabilistic Spiking Model

E J Chichilnisky, Eero P. Simoncelli, Liam Paninski, 2005, The Journal of Neuroscience.

Statistical models for neural encoding, decoding, and optimal stimulus design.

Liam Paninski, Jonathan W. Pillow, Jonathan Pillow, 2007, Progress in brain research.

Model-Based Decoding, Information Estimation, and Change-Point Detection Techniques for Multineuron Spike Trains

Liam Paninski, Jonathan W. Pillow, Yashar Ahmadian, 2011, Neural Computation.

Modeling the impact of common noise inputs on the network activity of retinal ganglion cells

Eero P. Simoncelli, L. Paninski, J. Pillow, 2011, Journal of Computational Neuroscience.

Characterizing neural dependencies with copula models

Frank D. Wood, Jonathan W. Pillow, Pietro Berkes, 2008, NIPS.

Likelihood-based approaches to modeling the neural code

Jonathan W. Pillow, J. Pillow, 2007 .

A new theoretical framework jointly explains behavioral and neural variability across subjects performing flexible decision-making

Jonathan W. Pillow, Mikio C. Aoi, J. Pillow, 2022, bioRxiv.

Scalable variational inference for low-rank spatio-temporal receptive fields

Jonathan W. Pillow, J. Pillow, G. Field, 2022, bioRxiv.

Neural population dynamics underlying evidence accumulation in multiple rat brain regions

Jonathan W. Pillow, J. Pillow, C. Brody, 2021, bioRxiv.

Neural Latents Benchmark '21: Evaluating latent variable models of neural population activity pdf

Eva L. Dyer, Chethan Pandarinath, Lee E. Miller, 2021, NeurIPS Datasets and Benchmarks.

Efficient decoding of large-scale neural population responses with Gaussian-process multiclass regression

Jonathan W. Pillow, Jacob L. Yates, J. Pillow, 2021, bioRxiv.

Modeling statistical dependencies in multi-region spike train data

Jonathan W Pillow, Jonathan W. Pillow, Mikio C. Aoi, 2020, Current Opinion in Neurobiology.

A simple linear readout of MT supports motion direction-discrimination performance.

Jonathan W Pillow, Jonathan W. Pillow, Aaron J Levi, 2019, Journal of neurophysiology.

Poisson balanced spiking networks

Jonathan W. Pillow, Camille E. Rullán Buxó, J. Pillow, 2019, bioRxiv.

Scaling the Poisson GLM to massive neural datasets through polynomial approximations

Jonathan W. Pillow, David M. Zoltowski, J. Pillow, 2018, NeurIPS.

Functional dissection of signal and noise in MT and LIP during decision-making

Il Memming Park, Jonathan W Pillow, Jonathan W. Pillow, 2017, Nature Neuroscience.

Bayesian latent structure discovery from multi-neuron recordings

Scott W. Linderman, Ryan P. Adams, Jonathan W. Pillow, 2016, NIPS.

Testing pseudo-linear models of responses to natural scenes in primate retina

Eero P. Simoncelli, Jonathan W. Pillow, Nora Brackbill, 2016, bioRxiv.

Capturing the Dynamical Repertoire of Single Neurons with Generalized Linear Models

Alison I. Weber, J. Pillow, 2016, Neural Computation.

Low-dimensional models of neural population activity in sensory cortical circuits

Jakob H. Macke, Jonathan W. Pillow, Urs Köster, 2014, NIPS.

Inferring synaptic conductances from spike trains with a biophysically inspired point process model

Jonathan W. Pillow, E. J. Chichilnisky, Kenneth W. Latimer, 2014, NIPS.

Bayesian inference for low rank spatiotemporal neural receptive fields

Mijung Park, Jonathan W. Pillow, J. Pillow, 2013, NIPS.

The Equivalence of Information-Theoretic and Likelihood-Based Methods for Neural Dimensionality Reduction

Jonathan W. Pillow, R. S. Williamson, M. Sahani, 2013, PLoS Comput. Biol..

Equating information-theoretic and likelihood-based methods for neural dimensionality reduction

Maneesh Sahani, Jonathan W. Pillow, R. S. Williamson, 2013, 1308.3542.

Receptive Field Inference with Localized Priors

Mijung Park, Jonathan W. Pillow, J. Pillow, 2011, PLoS Comput. Biol..

Heterogeneous response dynamics in retinal ganglion cells: the interplay of predictive coding and adaptation.

Sheila Nirenberg, Illya Bomash, Jonathan W Pillow, 2010, Journal of neurophysiology.

Time-rescaling methods for the estimation and assessment of non-Poisson neural encoding models

Jonathan W. Pillow, J. Pillow, 2009, NIPS.

Adaptive Bayesian Methods for Closed-Loop Neurophysiology

Mijung Park, Jonathan W. Pillow, J. Pillow, 2016 .

Neural characterization in partially observed populations of spiking neurons

J. Pillow, P. Latham, 2007, NIPS.

Brain kernel: A new spatial covariance function for fMRI data

Jonathan W. Pillow, Samuel A. Nastase, Christopher A. Baldassano, 2021, NeuroImage.

Prefrontal cortex exhibits multi-dimensional dynamic encoding during decision-making

Jonathan W. Pillow, Mikio C. Aoi, Valerio Mante, 2019, bioRxiv.

Bayesian Spike-Triggered Covariance Analysis

Il Memming Park, Jonathan W. Pillow, Il Park, 2011, NIPS.

Spike-triggered neural characterization.

Eero P. Simoncelli, Odelia Schwartz, Nicole C Rust, 2006, Journal of vision.

Brain-wide representations of prior information in mouse decision-making

Julia M. Huntenburg, Tatiana A. Engel, Jonathan W. Pillow, 2023, bioRxiv.

One-to-one mapping between deep network units and real neurons uncovers a visual population code for social behavior

Benjamin R. Cowley, Jonathan W. Pillow, Adam J. Calhoun, 2022, bioRxiv.

Lawful tracking of visual motion in humans, macaques, and marmosets in a naturalistic, continuous, and untrained behavioral context

Alexander C. Huk, Jonathan W. Pillow, Jonas Knöll, 2018, Proceedings of the National Academy of Sciences.

Biases in white noise analysis due to non-Poisson spike generation

Eero P. Simoncelli, J. Pillow, 2003, Neurocomputing.

Bayesian Efficient Coding

Il Memming Park, Jonathan W. Pillow, J. Pillow, 2017, bioRxiv.

No cause for pause: new analyses of ramping and stepping dynamics in LIP (Rebuttal to Response to Reply to Comment on Latimer et al 2015)

Alexander C. Huk, Jonathan W. Pillow, Kenneth W. Latimer, 2017, bioRxiv.

Fast shared response model for fMRI data

Jonathan W. Pillow, Ana Luísa Pinho, J. Pillow, 2019, ArXiv.

Continuous psychophysics: Target-tracking to measure visual sensitivity.

Johannes Burge, Jonathan W. Pillow, Kathryn Bonnen, 2015, Journal of vision.

Prefrontal cortex exhibits multidimensional dynamic encoding during decision-making

Jonathan W. Pillow, Mikio C. Aoi, J. Pillow, 2020, Nature Neuroscience.