%0 Journal Article %J Proceedings of the National Academy of Sciences %D 2009 %T A rodent model for the study of invariant visual object recognition %A Zoccolan, D. %A Oertelt, N. %A DiCarlo, J. J. %A Cox, D. D. %X

The human visual system is able to recognize objects despite tremendous variation in their appearance on the retina resulting from variation in view, size, lighting, etc. This ability–known as "invariant" object recognition–is central to visual perception, yet its computational underpinnings are poorly understood. Traditionally, nonhuman primates have been the animal model-of-choice for investigating the neuronal substrates of invariant recognition, because their visual systems closely mirror our own. Meanwhile, simpler and more accessible animal models such as rodents have been largely overlooked as possible models of higher-level visual functions, because their brains are often assumed to lack advanced visual processing machinery. As a result, little is known about rodents' ability to process complex visual stimuli in the face of real-world image variation. In the present work, we show that rats possess more advanced visual abilities than previously appreciated. Specifically, we trained pigmented rats to perform a visual task that required them to recognize objects despite substantial variation in their appearance, due to changes in size, view, and lighting. Critically, rats were able to spontaneously generalize to previously unseen transformations of learned objects. These results provide the first systematic evidence for invariant object recognition in rats and argue for an increased focus on rodents as models for studying high-level visual processing.

%B Proceedings of the National Academy of Sciences %V 106 %P 8748 - 8753 %8 05/2009 %G eng %U http://www.pnas.org/cgi/doi/10.1073/pnas.0811583106 %N 21 %! Proceedings of the National Academy of Sciences %R 10.1073/pnas.0811583106 %0 Journal Article %J Journal of Neuroscience %D 2007 %T Trade-Off between Object Selectivity and Tolerance in Monkey Inferotemporal Cortex %A Zoccolan, D. %A Kouh, M. %A Poggio, T. %A DiCarlo, J. J. %X

Object recognition requires both selectivity among different objects and tolerance to vastly different retinal images of the same object, resulting from natural variation in (e.g.) position, size, illumination, and clutter. Thus, discovering neuronal responses that have object selectivity and tolerance to identity-preserving transformations is fundamental to understanding object recognition. Although selectivity and tolerance are found at the highest level of the primate ventral visual stream [the inferotemporal cortex {(IT)],} both properties are highly varied and poorly understood. If an {IT} neuron has very sharp selectivity for a unique combination of object features ("diagnostic features"), this might automatically endow it with high tolerance. However, this relationship cannot be taken as given; although some {IT} neurons are highly object selective and some are highly tolerant, the empirical connection of these key properties is unknown. In this study, we systematically measured both object selectivity and tolerance to different identity-preserving image transformations in the spiking responses of a population of monkey {IT} neurons. We found that {IT} neurons with high object selectivity typically have low tolerance (and vice versa), regardless of how object selectivity was quantified and the type of tolerance examined. The discovery of this trade-off illuminates object selectivity and tolerance in {IT} and unifies a range of previous, seemingly disparate results. This finding also argues against the idea that diagnostic conjunctions of features guarantee tolerance. Instead, it is naturally explained by object recognition models in which object selectivity is built through {AND-like} tuning mechanisms.

%B Journal of Neuroscience %V 27 %P 12292 - 12307 %8 07/2007 %G eng %U http://www.jneurosci.org/cgi/doi/10.1523/JNEUROSCI.1897-07.2007 %N 45 %! Journal of Neuroscience %R 10.1523/JNEUROSCI.1897-07.2007 %0 Journal Article %J Journal of Neuroscience %D 2005 %T Multiple Object Response Normalization in Monkey Inferotemporal Cortex %A Zoccolan, D. %A Cox, David D. %A DiCarlo, James J. %K Animals %K Brain Mapping %K Macaca mulatta %K Male %K Photic Stimulation %K Posture %K Psychology %K Recognition %K Temporal Lobe %K Visual Pathways %K Visual Perception %X

The highest stages of the visual ventral pathway are commonly assumed to provide robust representation of object identity by disregarding confounding factors such as object position, size, illumination, and the presence of other objects (clutter). However, whereas neuronal responses in monkey inferotemporal cortex (IT) can show robust tolerance to position and size changes, previous work shows that responses to preferred objects are usually reduced by the presence of nonpreferred objects. More broadly, we do not yet understand multiple object representation in IT. In this study, we systematically examined IT responses to pairs and triplets of objects in three passively viewing monkeys across a broad range of object effectiveness. We found that, at least under these limited clutter conditions, a large fraction of the response of each IT neuron to multiple objects is reliably predicted as the average of its responses to the constituent objects in isolation. That is, multiple object responses depend primarily on the relative effectiveness of the constituent objects, regardless of object identity. This average effect becomes virtually perfect when populations of IT neurons are pooled. Furthermore, the average effect cannot simply be explained by attentional shifts but behaves as a primarily feedforward response property. Together, our observations are most consistent with mechanistic models in which IT neuronal outputs are normalized by summed synaptic drive into IT or spiking activity within IT and suggest that normalization mechanisms previously revealed at earlier visual areas are operating throughout the ventral visual stream.

%B Journal of Neuroscience %V 25 %P 8150 - 8164 %8 07/2005 %G eng %U http://www.jneurosci.org/cgi/doi/10.1523/JNEUROSCI.2058-05.2005 %N 36 %! Journal of Neuroscience %R 10.1523/JNEUROSCI.2058-05.2005