Carlos Ramon Ponce
Harvard University, MA·Neuroscience·Early-career
How does the primate brain make sense of the messy, varied visual world, and decide what is worth looking at? Most of what we know about visual neurons comes from tests with simple shapes or small sets of tidy photos, and models built that way often fail on random natural images.
- Fields
Neuroscience
Computer Science
Psychology
- Topics
visual neuroscience
primate vision
macaque
- Grants
- 4 known grants, through May 2030
What they work on
- Compare competing ways of predicting how inferotemporal cortex neurons respond to natural images, such as hand-designed features, distance from a neuron's most activating image, and fitted neural networks, in a 'tournament' using chronic microelectrode arrays in macaques.
- Explain why generative networks paired with neuron-guided search produce highly activating 'prototype' images, by analyzing the geometry of the generator's input space and how search algorithms exploit it.
- Build perceptual distance functions that predict neuron responses to natural images from their similarity to prototypes, and extend image synthesis to recover information from whole populations of neurons.
- Test whether monkeys' preferential viewing is guided by local image features rather than whole-object recognition, using synthesized and modified images while recording from V4, IT and the pulvinar.
- Train deep-learning models that reproduce both macaque gaze behavior and neuronal responses, and test whether they generalize to social and natural scenes.
- Determine how MDMA and methamphetamine change social viewing and responses of neurons in visual cortex, pulvinar and ventral striatum, using chronic arrays over repeated doses and the ATHENA-N modeling codebase.
More about the research
The lab's projects attack this gap in macaque monkeys. They record from many visual neurons with implanted electrode arrays. They also pair those recordings with deep-learning models that generate images, so that the neurons themselves help choose what images to test. The projects ask what visual neurons encode, how that guides eye movements, and how drugs and social context change it.
Why it matters
Understanding how the brain recognizes and prioritizes visual information could point to mechanisms behind sensory processing disorders such as cortical visual impairment and inform efficient visual recognition systems for medical imaging and prosthetics for people with vision loss. The work may also inform tools for detecting social processing differences in autism, help guide therapies and treatment durations for MDMA and methamphetamine use, and improve biologically inspired machine vision.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
The Mechanistic Role of Visual Areas at the Interaction of Social Behavior and Drug Effects in Nonhuman Primates
NIH · Sep 2025 – May 2030
CRCNS: Neural and computational mechanisms underlying natural viewing behavior
NIH · Sep 2025 – Jan 2029
CAREER: Defining how the primate visual system works under naturalistic conditions
NSF · Oct 2022 – Sep 2027
Closest labs
Pavan Turaga
Arizona State University Campus Immersion, AZ·Computer Science
Test whether replacing the fixed input distribution of a generative adversarial network with tunable non-parametric distributions reduces distribution mismatch when generated samples are mixed.
Michael Stryker
University of California-San Francisco, CA·Neuroscience
Record large populations of neurons with multi-electrode arrays in the retina and visual cortex of awake, behaving mice while they view naturalistic visual flow and simpler artificial patterns.
Yan Yan
University of Illinois Chicago, IL·Computer Science
Develop unsupervised learning models for re-identifying and tracking people and vehicles across a network of city cameras, processing video in real time across edge devices and the cloud.
The school
Harvard University: 42 labs on PI Pages, $1.5B a year on research, 712 research doctorates a year.
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