Author pages are created from data sourced from our academic publisher partnerships and public sources.
Performance-optimized hierarchical models predict neural responses in higher visual cortex
- Daniel Yamins, H. Hong, C. Cadieu, E. Solomon, Darren Seibert, J. DiCarlo
- Computer Science, Medicine
- Proceedings of the National Academy of Sciences
- 8 May 2014
Significance Humans and monkeys easily recognize objects in scenes. This ability is known to be supported by a network of hierarchically interconnected brain areas. However, understanding neurons in… Expand
Fast Readout of Object Identity from Macaque Inferior Temporal Cortex
Understanding the brain computations leading to object recognition requires quantitative characterization of the information represented in inferior temporal (IT) cortex. We used a biologically… Expand
How Does the Brain Solve Visual Object Recognition?
Mounting evidence suggests that 'core object recognition,' the ability to rapidly recognize objects despite substantial appearance variation, is solved in the brain via a cascade of reflexive,… Expand
Using goal-driven deep learning models to understand sensory cortex
Fueled by innovation in the computer vision and artificial intelligence communities, recent developments in computational neuroscience have used goal-driven hierarchical convolutional neural networks… Expand
Untangling invariant object recognition
Despite tremendous variation in the appearance of visual objects, primates can recognize a multitude of objects, each in a fraction of a second, with no apparent effort. However, the brain mechanisms… Expand
Why is Real-World Visual Object Recognition Hard?
Progress in understanding the brain mechanisms underlying vision requires the construction of computational models that not only emulate the brain's anatomy and physiology, but ultimately match its… Expand
Selectivity and Tolerance (“Invariance”) Both Increase as Visual Information Propagates from Cortical Area V4 to IT
Our ability to recognize objects despite large changes in position, size, and context is achieved through computations that are thought to increase both the shape selectivity and the tolerance… Expand
Object Selectivity of Local Field Potentials and Spikes in the Macaque Inferior Temporal Cortex
- G. Kreiman, C. Hung, A. Kraskov, R. Quiroga, T. Poggio, J. DiCarlo
- Biology, Medicine
- 2 February 2006
Local field potentials (LFPs) arise largely from dendritic activity over large brain regions and thus provide a measure of the input to and local processing within an area. We characterized LFPs and… Expand
Anterior inferotemporal neurons of monkeys engaged in object recognition can be highly sensitive to object retinal position.
Visual object recognition is computationally difficult because changes in an object's position, distance, pose, or setting may cause it to produce a different retinal image on each encounter. To… Expand
Structure of Receptive Fields in Area 3b of Primary Somatosensory Cortex in the Alert Monkey
We investigated the two-dimensional structure of area 3b neuronal receptive fields (RFs) in three alert monkeys. Three hundred thirty neurons with RFs on the distal fingerpads were studied with… Expand