@article {58,
	title = {A rodent model for the study of invariant visual object recognition},
	journal = {Proceedings of the National Academy of Sciences},
	volume = {106},
	year = {2009},
	month = {05/2009},
	pages = {8748 - 8753},
	abstract = {<p>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\&ndash;known as \&quot;invariant\&quot; object recognition\&ndash;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\&$\#$39; 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.</p>
},
	issn = {0027-8424},
	doi = {10.1073/pnas.0811583106},
	url = {http://www.pnas.org/cgi/doi/10.1073/pnas.0811583106},
	author = {Zoccolan, D. and Oertelt, N. and DiCarlo, J. J. and Cox, D. D.}
}
@article {68,
	title = {Does Learned Shape Selectivity in Inferior Temporal Cortex Automatically Generalize Across Retinal Position?},
	journal = {Journal of Neuroscience},
	volume = {28},
	year = {2008},
	month = {01/2008},
	pages = {10045 - 10055},
	abstract = {<p>Biological visual systems have the remarkable ability to recognize objects despite confounding factors such as object position, size, pose, and lighting. In primates, this ability likely results from neuronal responses at the highest stage of the ventral visual stream [inferior temporal cortex {(IT)]} that signal object identity while tolerating these factors. However, for even the apparently simplest {IT} tolerance (\&quot;invariance\&quot;), tolerance to object position on the retina, little is known about how this feat is achieved. One possibility is that {IT} position tolerance is innate in that discriminatory power for newly learned objects automatically generalizes across position. Alternatively, visual experience plays a role in developing position tolerance. To test these ideas, we trained adult monkeys in a difficult object discrimination task in which their visual experience with novel objects was restricted to a single retinal position. After training, we recorded the spiking activity of an unbiased population of {IT} neurons and found that it contained significantly greater selectivity among the newly learned objects at the experienced position compared with a carefully matched, non-experienced position. Interleaved testing with other objects shows that this difference cannot be attributed to a bias in spatial attention or neuronal sampling. We conclude from these results that, at least under some conditions, full transfer of {IT} neuronal selectivity across retinal position is not automatic. This finding raises the possibility that visual experience plays a role in building neuronal tolerance in the ventral visual stream and the recognition abilities it supports.</p>
},
	issn = {0270-6474},
	doi = {10.1523/JNEUROSCI.2142-08.2008},
	url = {http://www.jneurosci.org/cgi/doi/10.1523/JNEUROSCI.2142-08.2008},
	author = {Cox, D. D. and DiCarlo, J. J.}
}
