Using goal-driven deep learning models to understand sensory cortex

Simple Learned Weighted Sums of Inferior Temporal Neuronal Firing Rates Accurately Predict Human Core Object Recognition Performance

(2015) N. J. Majaj et al.   JOURNAL OF NEUROSCIENCE

Deep Neural Networks Reveal a Gradient in the Complexity of Neural Representations across the Ventral Stream

(2015) U. Guclu et al.   JOURNAL OF NEUROSCIENCE

Human-level control through deep reinforcement learning

(2015) Volodymyr Mnih et al.   NATURE

Optogenetic and pharmacological suppression of spatial clusters of face neurons reveal their causal role in face gender discrimination

(2015) Arash Afraz et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Understanding Brains: Details, Intuition, and Big Data

(2015) Eve Marder   PLOS BIOLOGY

Neural Differentiation Tracks Improved Recall of Competing Memories Following Interleaved Study and Retrieval Practice

(2014) J. C. Hulbert et al.   CEREBRAL CORTEX

Performance-optimized hierarchical models predict neural responses in higher visual cortex

(2014) D. L. K. Yamins et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Deep Neural Networks Rival the Representation of Primate IT Cortex for Core Visual Object Recognition

(2014) Charles F. Cadieu et al.   PLoS Computational Biology

Deep Supervised, but Not Unsupervised, Models May Explain IT Cortical Representation

(2014) Seyed-Mahdi Khaligh-Razavi et al.   PLoS Computational Biology

Context-dependent computation by recurrent dynamics in prefrontal cortex

(2013) Valerio Mante et al.   NATURE

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

(2013) Marino Pagan et al.   NATURE NEUROSCIENCE

Trade-off between curvature tuning and position invariance in visual area V4

(2013) T. O. Sharpee et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Curvature Processing Dynamics in Macaque Area V4

(2012) Jeffrey M. Yau et al.   CEREBRAL CORTEX

Choice-specific sequences in parietal cortex during a virtual-navigation decision task

(2012) Christopher D. Harvey et al.   NATURE

How Does the Brain Solve Visual Object Recognition?

(2012) James J. DiCarlo et al.   NEURON

Metamers of the ventral stream

(2011) Jeremy Freeman et al.   NATURE NEUROSCIENCE

Selectivity and Tolerance ("Invariance") Both Increase as Visual Information Propagates from Cortical Area V4 to IT

(2010) N. C. Rust et al.   JOURNAL OF NEUROSCIENCE

Relating population-code representations between man, monkey, and computational models

(2010) Nikolaus Kriegeskorte   Frontiers in Neuroscience

The Unreasonable Effectiveness of Data

(2009) Alon Halevy et al.   IEEE INTELLIGENT SYSTEMS

A High-Throughput Screening Approach to Discovering Good Forms of Biologically Inspired Visual Representation

(2009) Nicolas Pinto et al.   PLoS Computational Biology

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

(2008) Jonathan W. Pillow et al.   NATURE

A neural code for three-dimensional object shape in macaque inferotemporal cortex

(2008) Yukako Yamane et al.   NATURE NEUROSCIENCE

Why is Real-World Visual Object Recognition Hard?

(2008) Nicolas Pinto et al.   PLoS Computational Biology