Abstract
In recent years, a number of studies have explored the possible use of rats as models of high-level visual functions. One central question at the root of such an investigation is to understand whether rat object vision relies on the processing of visual shape features or, rather, on lower-order image properties (e.g., overall brightness). In a recent study, we have shown that rats are capable of extracting multiple features of an object that are diagnostic of its identity, at least when those features are, structure-wise, distinct enough to be parsed by the rat visual system. In the present study, we have assessed the impact of object structure on rat perceptual strategy. We trained rats to discriminate between two structurally similar objects, and compared their recognition strategies with those reported in our previous study. We found that, under conditions of lower stimulus discriminability, rat visual discrimination strategy becomes more view-dependent and subject-dependent. Rats were still able to recognize the target objects, in a way that was largely tolerant (i.e., invariant) to object transformation; however, the larger structural and pixel-wise similarity affected the way objects were processed. Compared to the findings of our previous study, the patterns of diagnostic features were: (i) smaller and more scattered; (ii) only partially preserved across object views; and (iii) only partially reproducible across rats. On the other hand, rats were still found to adopt a multi-featural processing strategy and to make use of part of the optimal discriminatory information afforded by the two objects. Our findings suggest that, as in humans, rat invariant recognition can flexibly rely on either view-invariant representations of distinctive object features or view-specific object representations, acquired through learning.
Highlights
The results presented in this study suggest that, to what observed for humans, for rats, transformation-tolerant recognition can flexibly rely on either view-invariant representations of distinctive object features or view-specific object representations
Given the extraordinary potential of the rat as a model to dissect neuronal functions at the molecular, synaptic, and circuitry levels (Margrie et al, 2002; Ohki et al, 2005; Lee et al, 2006; Greenberg et al, 2008; Deisseroth, 2011; Fenno et al, 2011; Egger et al, 2012; Tye and Deisseroth, 2012; Meyer et al, 2013), our findings suggest that rat studies could significantly advance our understanding of the formation and maintenance of transformation-tolerant object representations in the visual cortex
As a follow-up to one of our recent studies (Alemi-Neissi et al, 2013), we exploited the same classification image method used there, known as the Bubbles, which has been previously applied to human (Gosselin and Schyns, 2001; Nielsen et al, 2008), monkey (Nielsen et al, 2008), pigeon (Gibson et al, 2005) and, recently, rat vision studies (Vermaercke and Op de Beeck, 2012; Alemi-Neissi et al, 2013)
Summary
Over the past few years, rat vision has become the subject of intensive investigation (Zoccolan et al, 2009, 2010; Meier et al, 2011; Tafazoli et al, 2012; Vermaercke and Op de Beeck, 2012; Alemi-Neissi et al, 2013; Brooks et al, 2013; Meier and Reinagel, 2013; Reinagel, 2013a,b; Wallace et al, 2013; Vermaercke et al, 2014; Vinken et al, 2014), because of the experimental advantages that rodent species might offer as models to study visual functions (see Zoccolan, 2015 for a review). Object similarity affects rat recognition studies have found that rats are capable of invariant (a.k.a. transformation-tolerant) recognition, i.e., they can recognize visual objects in spite of substantial variation in their appearance (Zoccolan et al, 2009) This ability has been found to rely on the spontaneously perceived similarity between novel and previously learned views of an object, as well as on the gradual, explicit learning of each newly encountered view (Tafazoli et al, 2012). This suggests that rats achieve invariant object recognition by combining the automatic tolerance afforded by partially invariant representations of distinctive object features with the more complete invariance acquired by learning and storing multiple, view-specific object representations. Several studies suggest that the same argument applies to the recognition strategies of other species, e.g., monkeys (Logothetis et al, 1994; Logothetis and Pauls, 1995; Wang et al, 2005; Nielsen et al, 2008; Yamashita et al, 2010) and pigeons (Wasserman et al, 1996; Spetch et al, 2001; Spetch and Friedman, 2003; Gibson et al, 2007), a number of differences with human recognition (in addition to commonalities) has been found (e.g., see Soto and Wasserman, 2014 for a review)
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