Contribution of large scale biases in decoding of direction-of-motion from high-resolution fMRI data in human early visual cortex.

Previous studies have demonstrated that the perceived direction of motion of a visual stimulus can be decoded from the pattern of functional magnetic resonance imaging (fMRI) responses in occipital cortex using multivariate analysis methods (Kamitani and Tong, 2006). One possible mechanism for this is a difference in the sampling of direction selective cortical columns between voxels, implying that information at a level smaller than the voxel size might be accessible with fMRI. Alternatively, multivariate analysis methods might be driven by the organization of neurons into clusters or even orderly maps at a much larger scale. To assess the possible sources of the direction selectivity observed in fMRI data, we tested how classification accuracy varied across different visual areas and subsets of voxels for classification of motion-direction. To enable high spatial resolution functional MRI measurements (1.5mm isotropic voxels), data were collected at 7T. To test whether information about the direction of motion is represented at the scale of retinotopic maps, we looked at classification performance after combining data across different voxels within visual areas (V1-3 and MT+/V5) before training the multivariate classifier. A recent study has shown that orientation biases in V1 are both necessary and sufficient to explain classification of stimulus orientation (Freeman et al., 2011). Here, we combined voxels with similar visual field preference as determined in separate retinotopy measurements and observed that classification accuracy was preserved when averaging in this 'retinotopically restricted' way, compared to random averaging of voxels. This insensitivity to averaging of voxels (with similar visual angle preference) across substantial distances in cortical space suggests that there are large-scale biases at the level of retinotopic maps underlying our ability to classify direction of motion.

Selective mechanisms for complex visual patterns revealed by adaptation.

A great deal is known about the initial steps of visual processing. We know that humans have neural mechanisms selectively tuned to simple patterns of particular spatial frequencies and orientations. We also know that much later in the visual pathway, in inferotemporal cortex, cells respond to extremely complex visual patterns such as images of faces. Very little is known about intermediate levels of visual processing, where early visual signals are presumably combined to represent increasingly complex visual features. Here we show the existence of visual mechanisms in humans, tuned and selective to particular combinations of simple sinusoidal patterns, using a novel method of compound adaptation.

Sheep don't forget a face.

The human brain has evolved specialized neural mechanisms for visual recognition of faces, which afford us a remarkable ability to discriminate between, remember and think about many hundreds of different individuals. Sheep also recognize and are attracted to individual sheep and humans by their faces, as they possess similar specialized neural systems in the temporal and frontal lobes for assisting in this important social task, including a greater involvement of the right brain hemisphere. Here we show that individual sheep can remember 50 other different sheep faces for over 2 years, and that the specialized neural circuits involved maintain selective encoding of individual sheep and human faces even after long periods of separation.

Human face recognition in sheep: lack of configurational coding and right hemisphere advantage.

Face recognition in sheep is qualitatively similar to that in humans in terms of its left visual field bias, and the effects of expertise and configural coding. The current study was designed to determine whether such effects are species specific by investigating the case of sheep recognising humans. It was found that the sheep could identify human faces and while they showed a small inversion-induced decline in discriminatory performance, this was significantly less than seen with sheep faces. In other aspects, there were qualitative differences with human face recognition compared with conspecific recognition. In contrast with sheep faces there was no left visual field advantage in the recognition of human faces and the internal features were not used at all as visual cues. The data suggest that these sheep, whilst being extensively exposed to interactions with humans, were unable to identify them with all the same 'expert' methods as were used to discriminate other sheep. This suggests that different neural systems may, to some extent, be used for recognition of sheep as opposed to human faces. The relative contribution to differential neural processing of the faces of the different species and the role of expertise are discussed.

Configurational coding, familiarity and the right hemisphere advantage for face recognition in sheep.

This study examined characteristics of visual recognition of familiar and unfamiliar faces in sheep using a 2-way discrimination task. Of particular interest were effects of lateralisation and the differential use of internal (configurational) vs external features of the stimuli. Animals were trained in a Y-maze to identify target faces from pairs, both of which were familiar (same flock as the subjects) or both of which were unfamiliar (different flock). Having been trained to identify the rewarded face a series of stimuli were presented to the sheep, designed to test for the use of each visual hemifield in the discriminations and the use of internal and external facial cues. The first experiment showed that there was a left visual hemifield (LVF) advantage in the identification of 'hemifaces', and 'mirrored hemifaces' and 'chimeric' faces and that this effect was strongest with familiar faces. This represents the first evidence for visual field bias outside the primate literature. Results from the second experiment showed that, whilst both familiar and unfamiliar faces could be identified by the external features alone, only the familiar faces could be recognised by the internal features alone. Overall the results suggest separate recognition methods for socially familiar and unfamiliar faces, with the former being coded more by internal, configurational cues and showing a lateral bias to the left visual field.