It is widely assumed that distributed bell-shaped tuning (e.g. Radial Basis functions) characterizes the shape selectivity of macaque inferior temporal (IT) neurons, analogous to the orientation or spatial frequency tuning found in early visual cortex. Demonstrating such tuning properties requires testing the responses of neurons for different values along dimensions of shape. We recorded the responses of single macaque IT neurons to variations of a rectangle and a triangle along simple shape dimensions, such as taper and axis curvature. The neurons showed systematic response modulation along these dimensions, with the greatest response, on average, to the highest values on the dimensions, e.g. to the most curved shapes. Within the range of values tested, the response functions were monotonic rather than bell-shaped. Multi-dimensional scaling of the neural responses showed that these simple shape dimensions were coded orthogonally by IT neurons: the degree and direction of responses modulation (i.e. the increase or decrease of responses along a dimension) was independent for the different dimensions. Furthermore, for combinations of curvature-related and other simple shape dimensions, the joint tuning was separable, that is well predicted by the product of the tuning for each of the dimensions. The independence of dimensional tuning may provide the neural basis for the independence of psychophysical judgements of multidimensional stimuli.

Neurons in the inferior temporal cortex (IT) of the macaque fire more strongly to some shapes than others, but little is known about how to characterize this shape tuning more generally, because most previous studies have used somewhat arbitrary variations in the stimuli with unspecified magnitudes of the changes. The present investigation studied the modulation of IT cells to nonaccidental property (NAP, i.e., invariant to orientations in depth) and metric property (MP, i.e., depth dependent) variations of dimensions of generalized cones (a general formalism for characterizing shapes hypothesized to mediate object recognition). Changes in an NAP resulted in greater neuronal modulation than equally large pixel-wise changes in an MP (including those consisting of a rotation in depth). There was also precise and highly systematic neuronal tuning to the quantitative variations of MPs along specific dimensions to which a neuron was sensitive. The NAP advantage was independent of whether the object was composed of only a single part or had two parts. These findings indicate that qualitative shape changes such as NAPs help explain the surplus amount of IT shape sensitivity that cannot be accounted for on the basis of metric or pixel-based changes alone. This NAP advantage may provide the neural basis for the greater detectability of NAP compared with MP changes in human psychophysics.

We determined the degree to which the response modulation of macaque inferior temporal (IT) neurons corresponds to perceptual versus physical shape similarities. IT neurons were tested with four groups of shapes. One group consisted of variations of simple, symmetrical (i.e. regular) shapes that differed in nonaccidental properties (NAPs, i.e. viewpoint-invariant), such as curved versus straight contours. The second and third groups were composed of, respectively, simple and complex asymmetrical (i.e. irregular) shapes, all with curved contours. A fourth group consisted of simple, asymmetrical shapes, but with straight (corners) instead of curved contours. The neural modulations were greater for the shapes differing in NAPs than for the shapes differing in the configuration of the convexities and concavities. Multidimensional scaling showed that a population code of the neural activity could readily distinguish the four shape groups. This pattern of neural modulation was strongly manifested in the results of a sorting task by human subjects but could not be predicted using current image-based models (i.e. pixel energies, V1-like Gabor-jet filtering and HMAX). The representation of shape in IT thus exceeds a mere faithful representation of physical reality, by emphasizing perceptually salient features relevant for essential categorizations.

Repetition of a stimulus results in decreased responses in many cortical areas. This so-called adaptation or repetition suppression has been used in several human functional magnetic resonance imaging studies to deduce the stimulus selectivity of neuronal populations. We tested in macaque monkeys whether the degree of neural adaptation depends on the similarity between the adapter and test stimulus. To manipulate similarity, we varied stimulus size. We recorded the responses of single neurons to different-sized shapes in inferior temporal (IT) and prefrontal cortical (PFC) areas while the animals were engaged in a size or shape discrimination task. The degree of response adaptation in IT decreased with increasing size differences between the adapter and the test stimuli in both tasks, but the dependence of adaptation on the degree of similarity between the adapter and test stimuli was limited mainly to the early phase of the neural response in IT. PFC neurons showed only weak size-contingent repetition effects, despite strong size selectivity observed with the same stimuli. Thus, based on the repetition effects in PFC, one would have erroneously concluded that PFC shows weak or no size selectivity in such tasks. These findings are relevant for the interpretation of functional magnetic resonance adaptation data: they support the conjecture that the degree of adaptation scales with the similarity between adapter and test stimuli. However, they also show that the temporal evolution of adaptation during the course of the response, and differences in the way individual regions react to stimulus repetition, may complicate the inference of neuronal tuning from functional magnetic resonance adaptation.

The aim of this study was to evaluate the influence of complexity and symmetry on shape recognition, by measuring the recognition of unfamiliar shapes (created using Fourier Boundary Descriptors, FBDs) through a delayed matching task. Between complexity levels the shapes differed in the frequency of the FBDs and within complexity levels in their phase. Shapes were calibrated to be physically equally similar for the different complexity levels. Matching two sequentially presented shapes was slower and less accurate when complexity increased and for asymmetrical compared to symmetrical versions of the shapes. Thus, we show that simplicity in general and symmetry in particular enhance the short-term recognition of unfamiliar shapes.