Department of Neuroscience

Research Abstract

The goal of our lab is to define how neurons from different cortical areas interact to realize our perception of shape and motion. We study this question in the brain of the rhesus macaque, recording action potentials from neurons that span the entire cortico-visual hierarchy, from V1, V2, V4, MT and inferotemporal cortex (IT). We believe that the best explanation for visual processing is mathematical – thus we work to ensure that all of our results can be implemented in computational models like deep neural networks. read more

Selected Publications

• Wang B and Ponce CR, A Geometric Analysis of Deep Generative Image Models and Its Applications. In Proc. International Conference on Learning Representations, 2021.
• Arcaro MJ, Ponce CR, Livingstone M. The neurons that mistook a hat for a face. Elife. 2020; 9:e53798. Published 2020 Jun 10.
• Ponce CR, Xiao W, Schade PF, Hartmann TS, Kreiman G, and Livingstone MS (2019) Evolving images for visual neurons using a deep generative network reveals coding principles and neuronal preferences, Cell. 2019 May 2;177(4):999-1009.
• Hartmann TS, Livingstone MS and Ponce CR. Feature maps as a common signature for theories of visual recognition. In preparation.
• Ponce CR, Lomber SG, Livingstone MS. (2017) Posterior inferotemporal cortex cells use multiple visual pathways for shape encoding. J. Neurosci. May 10;37(19):5019-5034.
• Ponce CR, Hartmann T, Livingstone MS. (2017) Curvature and end-stopping as organizing principles for ventral stream organization. J. Neurosci. December; 2507-16.
• Ponce CR, Genecin MP, Perez-Melara G and Livingstone, MS. (2016) Automated chair-training of rhesus macaques. J Neurosci Methods, Apr 1; 263:75-80.
• Ponce CR, Lomber SG, Born RT. (2008) Integrating motion and depth via parallel pathways. Nat Neurosci. Feb; 11(2):216-23.

For a complete list of Dr. Ponce’s publications, click here.