Publications and Recent Presentations

The integration of visual and target signals in V4 and IT during visual object search

Roth N, Rust NC (2018, submitted)

Inferotemporal cortex multiplexes behaviorally-relevant target match signals and visual representations in a manner that minimizes their interference

Roth N, Rust NC (2018)
PLoS ONE, in press; bioRxiv 152181; doi:

Single-exposure visual memory judgments are reflected in IT cortex

Meyer T, Rust NC (2018)
eLife 7:e32259. doi:

Do rats see like we see?

Rust NC (2017)
eLife e26401.

Single trial familiarity judgments are reflected in the IT population response.

Meyer T, Rust NC (2016)
Society for Neuroscience

Neural Quadratic Discriminant Analysis: Nonlinear decoding
with V1-like computation.

Pagan M, Simoncelli EP, Rust NC (2016)
Neural Computation. Volume 28: 2291-2319. October 2016.

Population representations: implicit, explicit, and invariant.

Rust NC
The Cognitive Neurosciences. 5th Edition. Eds. Gazzaniga and Mangun. MIT Press. 337-348. 2014

Quantifying the signals contained in heterogeneous neural
responses and determining their relationships with task

Pagan M, Rust NC
Journal of Neurophysiology. Volume 112: 1584-1598. September 2014

Dynamic target match signals in perirhinal cortex can be
explained by instantaneous computations that act
on dynamic input from inferotemporal cortex.

Pagan M, Rust NC (2014)
Journal of Neuroscience. Volume 34: 11067-11084. August 2014

Signals in inferotemporal and perirhinal cortex suggest
an “untangling” of visual target information.

Pagan M, Urban LS, Wohl MP, Rust NC
Nature Neuroscience. Volume 16: 1132-1139. August 2013

How does the brain solve visual object recognition?

DiCarlo JJ, Zoccolan D, Rust NC
Neuron. Volume 73: 415-434. February 2012

Balanced increases in selectivity and tolerance produce
constant sparseness along the ventral visual stream.

Rust NC, DiCarlo JJ
Journal of Neuroscience. Volume 32: 10170-10182. July 2012

Dissociation of neuronal and psychophysical responses
to local and global motion.

Hedges JH, Gartshteyn Y, Kohn A, Rust NC, Shadlen MN, Newsome WT, Movshon JA
Current Biology. Volume 21: 2023-2028. December 2011

Ambiguity and invariance: two fundamental challenges
for visual processing.

Rust NC, Stocker AA
Current Opinion in Neurobiology. Volume 20: 382-388. May 2010

Selectivity and tolerance (“invariance”) both increase as
visual information propagates from V4 to IT.

Rust NC, DiCarlo JJ
Journal of Neuroscience. Volume 30: 12978-12995. September 2010

How MT cells analyze the motion of visual patterns.

Rust NC, Mante V, Simoncelli EP, Movshon JA
Nature Neuroscience. Volume 11: 1421-1431. October 2006

Spike-triggered neural characterization.

Schwartz O, Pillow JP, Rust NC, Simoncelli EP
Journal of Vision. Volume 6: 484-507. July 2006

In praise of artifice.

Rust NC, Movshon JA
Nature Neuroscience. Volume 8:1647-1649. November 2005

Spatiotemporal elements of macaque V1 receptive fields.

Rust NC, Schwartz O, Movshon JA, Simoncelli EP
Neuron. Volume 46: 945-956. June 2005

Do we know what the early visual system does?

Carandini M, Demb JB, Mante V, Tolhurst DJ, Dan Y, Olshausen BA, Gallant JL, Rust NC
Journal of Neuroscience. Volume 25: 10577-10597. November 2005

Analyzing neural responses to natural signals: Maximally
informative dimensions.

Sharpee T, Rust NC, Bialek W
Neural Computation. Volume 16: 223-250. February 2004

A reciprocal relationship between reliability and responsiveness
in developing cortical neurons.

Rust NC, Schultz SR, Movshon JA
Journal of Neuroscience. Volume 15: 10519-10523. December 2002