Publications | Penn Visual Memory Lab

Publications and Recent Presentations

A call for more clarity around causality in neuroscience

Barack DL, Miller EK, Moore CI, Packer AM, Pessoa L, Ross LN, Rust NC (2022)

Trends in Neurosciences

Identifying objects and remembering images: Insights from deep neural networks

Rust NC, Jannuzi BGL (2022)

Current Directions in Psychological Science

Ritalin as a causal perturbation

Hacker CM, Rust NC (2021)

Trends in cognitive sciences

Remembering the past to see the future

Rust NC, Palmer SE (2021)

Annual Review of Vision Science

Pinpointing the neural signatures of single-exposure visual recognition memory

Mehrpour V, Meyer T, Simoncelli EP, Rust NC (2021)

PNAS

Understanding image memorability

Rust NC, Mehrpour V (2020)

Trends In Cognitive Sciences

The Citation Diversity Statement: A practice of transparency, a way of life

Zurn P, Bassett DS, Rust NC (2020)

Trends In Cognitive Sciences

Population response magnitude variation in inferotemporal cortex predicts image memorability

Jaegle A, Mehrpour V, Mohsenzadeh Y, Meyer T, Oliva A, Rust NC (2019)

eLife

Visual novelty, curiosity, and intrinsic reward in machine learning and the brain

Jaegle A, Mehrpour V, Rust NC (2019)

Current Opinion in Neurobiology

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

Roth N, Rust NC (2019)

Journal of Neurophysiology

Rethinking assumptions about how trial and nuisance variability impact neural task performance in a fast-processing regime

Roth N, Rust NC (2019)

Journal of Neurophysiology

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

Single-exposure visual memory judgments are reflected in IT cortex

Meyer T, Rust NC (2018)

eLife

Do rats see like we see?

Rust NC (2017)

eLife

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

Pagan M, Simoncelli EP, Rust NC (2016)

Neural Computation

Population representations: implicit, explicit, and invariant

Rust NC

The Cognitive Neurosciences

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

Pagan M, Rust NC

Journal of Neurophysiology

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

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

Pagan M, Urban LS, Wohl MP, Rust NC

Nature Neuroscience

How does the brain solve visual object recognition?

DiCarlo JJ, Zoccolan D, Rust NC

Neuron

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

Rust NC, DiCarlo JJ

Journal of Neuroscience

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

Ambiguity and invariance: two fundamental challenges
for visual processing

Rust NC, Stocker AA

Current Opinion in Neurobiology

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

Rust NC, DiCarlo JJ

Journal of Neuroscience

How MT cells analyze the motion of visual patterns

Rust NC, Mante V, Simoncelli EP, Movshon JA

Nature Neuroscience

Spike-triggered neural characterization

Schwartz O, Pillow JP, Rust NC, Simoncelli EP

Journal of Vision

In praise of artifice

Rust NC, Movshon JA

Nature Neuroscience

Spatiotemporal elements of macaque V1 receptive fields

Rust NC, Schwartz O, Movshon JA, Simoncelli EP

Neuron

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

Analyzing neural responses to natural signals: Maximally
informative dimensions

Sharpee T, Rust NC, Bialek W

Neural Computation

A reciprocal relationship between reliability and responsiveness
in developing cortical neurons

Rust NC, Schultz SR, Movshon JA

Journal of Neuroscience

Publications and Recent Presentations

A call for more clarity around causality in neuroscience

Identifying objects and remembering images: Insights from deep neural networks

Ritalin as a causal perturbation

Remembering the past to see the future

Pinpointing the neural signatures of single-exposure visual recognition memory

Understanding image memorability

The Citation Diversity Statement: A practice of transparency, a way of life

Population response magnitude variation in inferotemporal cortex predicts image memorability

Visual novelty, curiosity, and intrinsic reward in machine learning and the brain

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

Rethinking assumptions about how trial and nuisance variability impact neural task performance in a fast-processing regime

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

Single-exposure visual memory judgments are reflected in IT cortex

Do rats see like we see?

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

Population representations: implicit, explicit, and invariant

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

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

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

How does the brain solve visual object recognition?

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

Dissociation of neuronal and psychophysical responses to local and global motion

Ambiguity and invariance: two fundamental challenges for visual processing

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

How MT cells analyze the motion of visual patterns

Spike-triggered neural characterization

In praise of artifice

Spatiotemporal elements of macaque V1 receptive fields

Do we know what the early visual system does?

Analyzing neural responses to natural signals: Maximally informative dimensions

A reciprocal relationship between reliability and responsiveness in developing cortical neurons

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

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

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

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

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

Dissociation of neuronal and psychophysical responses
to local and global motion

Ambiguity and invariance: two fundamental challenges
for visual processing

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

Analyzing neural responses to natural signals: Maximally
informative dimensions

A reciprocal relationship between reliability and responsiveness
in developing cortical neurons