Possible significance of spatial heterogeneities of local visual features for face perception

Second-order visual filters are the mechanisms which preattentively combine the rectified outputs of first-order filters (the linear striate neurons). This allows them to select the image areas which are characterized by spatial heterogeneity of the local visual features. The aim of our research is to determine whether information from these areas may be sufficient to detect unfamiliar faces and to distinguish their gender. In our experiments we used digital photos of real living things or artificial objects and faces. All these images were adjusted to an average luminance, contrast and size (7 angle degree) and were processed to extract the areas which differ the most in contrast, orientation, and spatial frequency in each of the six spatial frequencies (0.5, 1, 2, 4, 8, and 16 cpd). The other image parts were adjusted to the background. The obtained pictures were presented in a random sequence. The observer had to say what he/she saw after each presentation. When a face was presented the observer’s answer could be assigned to one of the categories: ‘it is not clear’, ‘head’, ‘human face’, ‘male / female’. We found that the information contained in the image areas with a spatial heterogeneity of the local features is sufficient not only for detecting a face, but also for distinguishing its gender. The best results were obtained at a carrier frequency of 2 cpd. The results were a little bit worse at 0.5 and 1 cpd. However, the information extracted from the high-frequency half of the spectrum was significantly less useful. The obtained results allow us to suggest that the information transmitted by the second-order visual filters may be used for pattern recognition.

Heterogeneity in the Responses of Adjacent Neurons to Natural Stimuli in Cat Striate Cortex

When presented with simple stimuli like bars and gratings, adjacent neurons in striate cortex exhibit shared selectivity for multiple stimulus dimensions, such as orientation, direction, and spatial frequency. This has led to the idea that local averaging of neuronal responses provides a more reliable representation of stimulus properties. However, when stimulated with complex, time-varying natural scenes (i.e., movies), striate neurons exhibit highly sparse responses. This raises the question of how much response heterogeneity the local population exhibits when stimulated with movies, and how it varies with separation distance between cells. We investigated this question by simultaneously recording the responses of groups of neurons in cat striate cortex to the repeated presentation of movies using silicon probes in a multi-tetrode configuration. We found, first, that the responses of striate neurons to movies are brief (tens of milliseconds), decorrelated, and exhibit high population sparseness. Second, we found that adjacent neurons differed significantly in their peak firing rates even when they responded to the same frames of a movie. Third, pairs of adjacent neurons recorded on the same tetrodes exhibited as much heterogeneity in their responses as pairs recorded by different tetrodes. These findings demonstrate that complex natural scenes evoke highly heterogeneous responses within local populations, suggesting that response redundancy in a cortical column is substantially lower than previously thought.