General object-based features account for letter perception

Brain-like functional specialization emerges spontaneously in deep neural networks

(2022) Katharina Dobs et al.   Science Advances

Limits to visual representational correspondence between convolutional neural networks and the human brain

(2021) Yaoda Xu et al.   Nature Communications

Qualitative similarities and differences in visual object representations between brains and deep networks

(2021) Georgin Jacob et al.   Nature Communications

Local features and global shape information in object classification by deep convolutional neural networks

(2020) Nicholas Baker et al.   VISION RESEARCH

The inferior temporal cortex is a potential cortical precursor of orthographic processing in untrained monkeys

(2020) Rishi Rajalingham et al.   Nature Communications

White matter fascicles and cortical microstructure predict reading-related responses in human ventral temporal cortex

(2020) Mareike Grotheer et al.   NEUROIMAGE

Deep neural network models of sensory systems: windows onto the role of task constraints

(2019) Alexander JE Kell et al.   CURRENT OPINION IN NEUROBIOLOGY

Number detectors spontaneously emerge in a deep neural network designed for visual object recognition

(2019) Khaled Nasr et al.   Science Advances

Perceptual dissociations among views of objects, scenes, and reachable spaces.

(2019) Emilie L. Josephs et al.   JOURNAL OF EXPERIMENTAL PSYCHOLOGY-HUMAN PERCEPTION AND PERFORMANCE

Similarity judgments and cortical visual responses reflect different properties of object and scene categories in naturalistic images

(2019) Marcie L. King et al.   NEUROIMAGE

Deep Learning: The Good, the Bad, and the Ugly

(2019) Thomas Serre   Annual Review of Vision Science

The temporal evolution of conceptual object representations revealed through models of behavior, semantics and deep neural networks

(2018) B.B. Bankson et al.   NEUROIMAGE

A Task-Optimized Neural Network Replicates Human Auditory Behavior, Predicts Brain Responses, and Reveals a Cortical Processing Hierarchy

(2018) Alexander J.E. Kell et al.   NEURON

Mid-level visual features underlie the high-level categorical organization of the ventral stream

(2018) Bria Long et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Visual search for object categories is predicted by the representational architecture of high-level visual cortex

(2017) Michael A. Cohen et al.   JOURNAL OF NEUROPHYSIOLOGY

Mid-level perceptual features contain early cues to animacy

(2017) Bria Long et al.   JOURNAL OF VISION

The effects of alphabet and expertise on letter perception.

(2016) Robert W. Wiley et al.   JOURNAL OF EXPERIMENTAL PSYCHOLOGY-HUMAN PERCEPTION AND PERFORMANCE

Using goal-driven deep learning models to understand sensory cortex

(2016) Daniel L K Yamins et al.   NATURE NEUROSCIENCE

Connectivity precedes function in the development of the visual word form area

(2016) Zeynep M Saygin et al.   NATURE NEUROSCIENCE

Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence

(2016) Radoslaw Martin Cichy et al.   Scientific Reports

ImageNet Large Scale Visual Recognition Challenge

(2015) Olga Russakovsky et al.   INTERNATIONAL JOURNAL OF COMPUTER VISION

Visual Awareness Is Limited by the Representational Architecture of the Visual System

(2015) Michael A. Cohen et al.   JOURNAL OF COGNITIVE 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 concept learning through probabilistic program induction

(2015) B. M. Lake et al.   SCIENCE

Origins of the specialization for letters and numbers in ventral occipitotemporal cortex

(2015) Thomas Hannagan et al.   TRENDS IN COGNITIVE SCIENCES

Processing multiple visual objects is limited by overlap in neural channels

(2014) M. A. Cohen et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

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

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

Alexia due to ischemic stroke of the visual word form area

(2013) Peter E. Turkeltaub et al.   NEUROCASE

Distributed circuits, not circumscribed centers, mediate visual recognition

(2013) Marlene Behrmann et al.   TRENDS IN COGNITIVE SCIENCES

Representational geometry: integrating cognition, computation, and the brain

(2013) Nikolaus Kriegeskorte et al.   TRENDS IN COGNITIVE SCIENCES

Anatomy of the visual word form area: Adjacent cortical circuits and long-range white matter connections

(2012) Jason D. Yeatman et al.   BRAIN AND LANGUAGE

Turning visual search time on its head

(2012) S.P. Arun   VISION RESEARCH

Learning to See Words

(2011) Brian A. Wandell et al.   Annual Review of Psychology

Specialization for written words over objects in the visual cortex

(2011) Marcin Szwed et al.   NEUROIMAGE

The unique role of the visual word form area in reading

(2011) Stanislas Dehaene et al.   TRENDS IN COGNITIVE SCIENCES

Functional specificity in the human brain: A window into the functional architecture of the mind

(2010) N. Kanwisher   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Situating visual search

(2010) Ken Nakayama et al.   VISION RESEARCH

The role of invariant line junctions in object and visual word recognition

(2009) Marcin Szwed et al.   VISION RESEARCH

Letter perception: from pixels to pandemonium

(2008) Jonathan Grainger et al.   TRENDS IN COGNITIVE SCIENCES