Carlos Ponce

Carlos Ponce, MD, PhD

Assistant Professor of Neurobiology

The Neuroscience of Visual Recognition and Perception

Our main goal is to understand how the visual brain works in the natural world, when it is presented with rich and complex scenes, such as those we encounter in our daily lives. 

We focus our research on the brain of the rhesus macaque, employing electrophysiological techniques to record neuronal activity across the visual cortex hierarchy, including areas V1, V2, V4, inferotemporal cortex, and prefrontal cortex. Our approaches use leading-edge neural networks, both as tools for generating stimuli (e.g., generative adversarial networks) and as models for the visual system itself (e.g., convolutional neural networks, vision transformers). These powerful, machine-intelligence models enable us to manipulate images in complex ways, and to identify the types of visual information encoded by cortical neurons. We compare this information with that encoded by different neural network architectures, while also leveraging monkey behavior to gain insights into the origins and evolution of visual representations.

Behavioral tasks play a key role in our research. Thus, we are continually refining our animal training techniques, incorporating computer-based automation and tablet-based training directly within the animals' home cages. Our methodologies are grounded in ethological and ethical principles, allowing us to adjust the complexity of tasks to the animals' natural capabilities.

By bridging visual neuroscience and machine learning, we hope to advance automated visual recognition technologies in areas like medical imaging, security, and autonomous driving, and also shed light on the subjective experience of vision itself.

Publications View
Visual prototypes in the ventral stream are attuned to complexity and gaze behavior.
Authors: Authors: Rose O, Johnson J, Wang B, Ponce CR.
Nat Commun
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The neurons that mistook a hat for a face.
Authors: Authors: Arcaro MJ, Ponce C, Livingstone M.
Elife
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Evolving Images for Visual Neurons Using a Deep Generative Network Reveals Coding Principles and Neuronal Preferences.
Authors: Authors: Ponce CR, Xiao W, Schade PF, Hartmann TS, Kreiman G, Livingstone MS.
Cell
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Seeing faces is necessary for face-domain formation.
Authors: Authors: Arcaro MJ, Schade PF, Vincent JL, Ponce CR, Livingstone MS.
Nat Neurosci
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Posterior Inferotemporal Cortex Cells Use Multiple Input Pathways for Shape Encoding.
Authors: Authors: Ponce CR, Lomber SG, Livingstone MS.
J Neurosci
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End-Stopping Predicts Curvature Tuning along the Ventral Stream.
Authors: Authors: Ponce CR, Hartmann TS, Livingstone MS.
J Neurosci
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End-stopping predicts curvature tuning along the ventral stream.
Authors: Authors: Ponce CR, Hartmann TS, Livingstone MS.
J Neurosci
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Contributions of indirect pathways to visual response properties in macaque middle temporal area MT.
Authors: Authors: Ponce CR, Hunter JN, Pack CC, Lomber SG, Born RT.
J Neurosci
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Stereopsis.
Authors: Authors: Ponce CR, Born RT.
Curr Biol
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Integrating motion and depth via parallel pathways.
Authors: Authors: Ponce CR, Lomber SG, Born RT.
Nat Neurosci
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