Jack L. Gallant

发表

Nonlinear V1 responses to natural scenes revealed by neural network analysis

Ryan J. Prenger, Michael C.-K. Wu, Stephen V. David, 2004, Neural Networks.

The Berkeley Wavelet Transform: A Biologically Inspired Orthogonal Wavelet Transform

Ryan J. Prenger, Jack L. Gallant, Ben D. B. Willmore, 2008, Neural Computation.

Comparison of generic convolutional networks versus biologically inspired networks as models of V4 neurons

Michael Eickenberg, Jack L. Gallant, Michele Winter, 2020 .

Nonparametric sparse hierarchical models describe V1 fMRI responses to natural images

Pradeep Ravikumar, Jack L. Gallant, Bin Yu, 2008, NIPS.

Pycortex: an interactive surface visualizer for fMRI

Jack L. Gallant, James S. Gao, Alexander G. Huth, 2015, Front. Neuroinform..

Representation of object contour features in intermediate visual areas in the human brain

Jack L. Gallant, Shinji Nishimoto, Mark D. Lescroart, 2013 .

Evidence for perceptual saliency maps in area V4 during freeviewing visual search

Jack L. Gallant, James A. Mazer, 2010 .

Parametric reverse correlation reveals spatial linearity of retinotopic human V1 BOLD response

Stephen V. David, Jack L. Gallant, Kathleen A. Hansen, 2004, NeuroImage.

The DeepTune framework for modeling and characterizing neurons in visual cortex area V4

Jack L. Gallant, Adam Bloniarz, Michael Oliver, 2018, bioRxiv.

Natural Scene Statistics Account for the Representation of Scene Categories in Human Visual Cortex

Jack L. Gallant, Thomas Naselaris, Dustin E. Stansbury, 2013, Neuron.

Encoding and decoding in fMRI

Jack L. Gallant, Kendrick N. Kay, Thomas Naselaris, 2011, NeuroImage.

Pixels to Voxels: Modeling Visual Representation in the Human Brain pdf

Jitendra Malik, Jack L. Gallant, Pulkit Agrawal, 2014, ArXiv.

Estimation of voxel receptive fields in human visual cortex using natural images

Jack L. Gallant, Kendrick Kay, Thomas Naselaris, 2010 .

A Continuous Semantic Space Describes the Representation of Thousands of Object and Action Categories across the Human Brain

Jack L. Gallant, Shinji Nishimoto, Alexander G. Huth, 2012, Neuron.

Bayesian Reconstruction of Perceptual Experiences from Human Brain Activity

Ryan J. Prenger, Jack L. Gallant, Kendrick N. Kay, 2009, HCI.

Decoding human visual cortical activity evoked by continuous time-varying movies

Jack L. Gallant, Shinji Nishimoto, An Vu, 2010 .

LO represents motion and semantic categories in addition to object boundaries

Jack L. Gallant, Utkarsh Singhal, Mark D. Lescroart, 2019 .

STRFPAK (Version 5.3). Software for estimating Spatio-Temporal Receptive Fields of sensory neurons

Jack L. Gallant, Frédéric E. Theunissen, J. Zhang, 2003 .

Bayesian Reconstruction of Natural Images from Human Brain Activity

Ryan J. Prenger, Jack L. Gallant, Kendrick N. Kay, 2009, Neuron.

Modeling Complex Cells in an Awake Macaque during Natural Image Viewing

Jack L. Gallant, William E. Vinje, 1997, NIPS.

Category-based attention shifts tuning toward the target object category during natural visual search

Jack L. Gallant, Shinji Nishimoto, Alexander G. Huth, 2012 .

Visual cortex represents the statistical distributions of objects in natural scenes

Jack L. Gallant, Thomas Naselaris, Dustin E. Stansbury, 2010 .

Two-dimensional and three-dimensional texture processing in visual cortex of the macaque monkey

Jack L. Gallant, David C. Van Essen, H. Christoph Nothdurft, 1995 .

Voxelwise encoding models with non-spherical multivariate normal priors

Jack L. Gallant, Anwar Nunez-Elizalde, Alexander G. Huth, 2019, NeuroImage.

Spectro-temporal receptive fields and high-order stimulus-response functions: Methods, validation and physiological mechanisms

Stephen V. David, Jack L. Gallant, Frédéric E. Theunissen, 2014 .

Computational methods for functional characterization of visual neurons

Jack L. Gallant, Michael Chinkuo Wu, 2008 .

Pyrcca: Regularized Kernel Canonical Correlation Analysis in Python and Its Applications to Neuroimaging

Jack L. Gallant, Natalia Y. Bilenko, J. Gallant, 2015, Front. Neuroinform..

Fourier power, subjective distance, and object categories all provide plausible models of BOLD responses in scene-selective visual areas

Jack L. Gallant, Mark D. Lescroart, Dustin Stansbury, 2015, Front. Comput. Neurosci..

BOLD predictions: automated simulation of fMRI experiments

James Gao, Jack L. Gallant, Leila Wehbe, 2018 .

Supplementary Information for Natural Speech Reveals the Semantic Maps That Tile Human Cerebral Cortex

Thomas L. Griffiths, Jack L. Gallant, Alexander G. Huth, 2022 .

A deep convolutional energy model of V4 responses to natural movies

Jack L. Gallant, Michael Oliver, J. Gallant, 2016 .

Intermediate human visual areas represent the locations of silhouette edges in natural movies

Jack L. Gallant, Shinji Nishimoto, Mark D. Lescroart, 2014 .

Human Scene-Selective Areas Represent 3D Configurations of Surfaces

Jack L. Gallant, Mark D. Lescroart, J. Gallant, 2019, Neuron.

Decoding the Semantic Content of Natural Movies from Human Brain Activity

Jack L. Gallant, Shinji Nishimoto, Alexander G. Huth, 2016, Frontiers in systems neuroscience.

Both convolutional neural networks and voxel-wise encoding models of brain activity derived from ConvNets represent boundary-and surface-related features

Jack L. Gallant, Pulkit Agrawal, Mark D. Lescroart, 2016 .

Principles of neural shape coding in area V2

Ryan J. Prenger, Jack L. Gallant, Ben Willmore, 2005 .

A New Age of Computing and the Brain pdf

Polina Golland, Hanspeter Pfister, Jack L. Gallant, 2020, ArXiv.

Design of Complex Experiments Using Mixed Integer Linear Programming.

Jack L. Gallant, Storm Slivkoff, J. Gallant, 2020, 2012.02361.

A voxel-wise encoding model for early visual areas decodes mental images of remembered scenes

Jack L. Gallant, Kamil Ugurbil, Thomas Naselaris, 2015, NeuroImage.

A Statistical Modeling Framework for Investigating Visual Scene Processing in the Human Brain

Jack L. Gallant, Dustin E. Stansbury, J. Gallant, 2014 .

Working Memory and Decision Processes in Visual Area V4

Jack L. Gallant, Benjamin Y. Hayden, J. Gallant, 2013, Front. Neurosci..

Eye movement-invariant representations in the human visual system

Jack L. Gallant, Shinji Nishimoto, Alexander G. Huth, 2017, Journal of vision.

Shape Perception: Complex Contour Representation in Visual Area V4

Jack L. Gallant, J. Gallant, Kate Gustavsen, 2003, Current Biology.

Using a novel source-localized phase regressor technique for evaluation of the vascular contribution to semantic category area localization in BOLD fMRI

Jack L. Gallant, An T. Vu, J. Gallant, 2015, Front. Neurosci..

Human visual areas invariant to eye movements during natural vision

Jack L. Gallant, Shinji Nishimoto, Alexander G. Huth, 2013 .

Object recognition: Seeing us seeing shapes

Jack L. Gallant, James A. Mazer, J. Gallant, 2000, Current Biology.

Voxelwise encoding models with non-spherical multivariate normal priors

Jack L. Gallant, Alexander G. Huth, J. Gallant, 2018, NeuroImage.

Erratum: Neural activity in areas V1 ... (NeuroReport 9:7 (1673-1678))

Jack L. Gallant, Charles Edward Connor, David C. Van Essen, 1998 .

The Representation of Semantic Information Across Human Cerebral Cortex During Listening Versus Reading Is Invariant to Stimulus Modality

Jack L. Gallant, Alexander G. Huth, Fatma Deniz, 2019, The Journal of Neuroscience.