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In our earlier work, we found that feature space induced by tactile receptive fields (TRFs) are better than that by visual receptive fields (VRFs) in texture boundary detection tasks. This suggests that TRFs could be intimately associated with texture-like input. In this paper, we investigate how TRFs can develop in a cortical learning context. Our main hypothesis is that TRFs can be self-organized using the same cortical development mechanism found in the visual cortex, simply by exposing it to texture-like inputs (as opposed to natural-scene-like inputs). To test our hypothesis, we used the LISSOM model of visual cortical development. Our main results show that texture-like inputs lead to the self-organization of TRFs while natural-scene-like inputs lead to VRFs. These results suggest that TRFs can better represent texture than VRFs. We further analyzed the effectiveness of TRFs in representing texture, using kernel Fisher discriminant (KFD) and the results, along with texture classification performance, confirm that this is indeed the case. We expect these results to help us better understand the nature of texture, as a fundamentally tactile property.