Invariance of visual operations at the level of receptive fields

Receptive field profiles registered by cell recordings have shown that mammalian vision has developed receptive fields tuned to different sizes and orientations in the image domain as well as to different image velocities in space-time. This article presents a theoretical model by which families of idealized receptive field profiles can be derived mathematically from a small set of basic assumptions that correspond to structural properties of the environment. The article also presents a theory for how basic invariance properties to variations in scale, viewing direction and relative motion can be obtained from the output of such receptive fields, using complementary selection mechanisms that operate over the output of families of receptive fields tuned to different parameters. Thereby, the theory shows how basic invariance properties of a visual system can be obtained already at the level of receptive fields, and we can explain the different shapes of receptive field profiles found in biological vision from a requirement that the visual system should be invariant to the natural types of image transformations that occur in its environment.Comment: 40 pages, 17 figure

Thinking about seeing: Perceptual sources of knowledge are encoded in the theory of mind brain regions of sighted and blind adults

Blind people's inferences about how other people see provide a window into fundamental questions about the human capacity to think about one another's thoughts. By working with blind individuals, we can ask both what kinds of representations people form about others' minds, and how much these representations depend on the observer having had similar mental states themselves. Thinking about others' mental states depends on a specific group of brain regions, including the right temporo-parietal junction (RTPJ). We investigated the representations of others' mental states in these brain regions, using multivoxel pattern analyses (MVPA). We found that, first, in the RTPJ of sighted adults, the pattern of neural response distinguished the source of the mental state (did the protagonist see or hear something?) but not the valence (did the protagonist feel good or bad?). Second, these neural representations were preserved in congenitally blind adults. These results suggest that the temporo-parietal junction contains explicit, abstract representations of features of others' mental states, including the perceptual source. The persistence of these representations in congenitally blind adults, who have no first-person experience with sight, provides evidence that these representations emerge even in the absence of relevant first-person perceptual experiences.National Science Foundation (U.S.) (Award 0645960)National Science Foundation (U.S.) (Award 095518)National Institutes of Health (U.S.) (Grant 1R01 MH096914-01A1

Neural representations that support invariant object recognition

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.status: publishe