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Original Research ARTICLE

Neural representations that support invariant object recognition

Robbe L. T. Goris and Hans P. Op de Beeck^*

Laboratory of Experimental Psychology, University of Leuven, Leuven, Belgium

Neural mechanisms underlying invariant behaviour such as object recognition are not well understood. For brain regions critical for object recognition, such as inferior temporal cortex (ITC), there is now ample evidence indicating that single cells code for many stimulus aspects, implying that only a moderate degree of invariance is present. However, recent theoretical and empirical work seems to suggest that integrating responses of multiple non-invariant units may produce invariant representations at population level. We provide an explicit test for the hypothesis that a linear read-out mechanism of a pool of units resembling ITC neurons may achieve invariant performance in an identification task. A linear classifier was trained to decode a particular value in a 2-D stimulus space using as input the response pattern across a population of units. Only one dimension was relevant for the task, and the stimulus location on the irrelevant dimension (ID) was kept constant during training. In a series of identification tests, the stimulus location on the relevant dimension (RD) and ID was manipulated, yielding estimates for both the level of sensitivity and tolerance reached by the network. We studied the effects of several single-cell characteristics as well as population characteristics typically considered in the literature, but found little support for the hypothesis. While the classifier averages out effects of idiosyncratic tuning properties and inter-unit variability, its invariance is very much determined by the (hypothetical) ‘average’ neuron. Consequently, even at population level there exists a fundamental trade-off between selectivity and tolerance, and invariant behaviour does not emerge spontaneously.

Keywords:

object recognition, inferior temporal cortex, population coding, multidimensional tuning

Citation:

Goris RLT and Op de Beeck HP (2009). Neural representations that support invariant object recognition. Front. Comput. Neurosci. 3:3. doi: 10.3389/neuro.10.003.2009

Received:

11 July 2008;

Paper pending published:

09 September 2008;

Accepted:

04 February 2009;

Published online:

17 February 2009.

Edited by:

Hava T. Siegelmann, University of Massachusetts Amherst, USA

Reviewed by:

Yasser Roudi, NORDITA, Sweden
Bartlett W. Mel, University of Southern California, USA

© 2009 Goris and Op de Beeck. This is an open-access article subject to an exclusive license agreement between the authors and the Frontiers Research Foundation, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are credited.

*Correspondence:

Hans P. Op de Beeck, Laboratory of Experimental Psychology, University of Leuven, Tiensestraat 102, 3000 Leuven, Belgium. e-mail: Hans.opdebeeck@psy.kuleuven.be