Neuronal orientation selectivity has been shown in animal models to require corticocortical network cooperation and to be dependent on the presence of GABAergic inhibition. However, it is not known whether variability in these fundamental neurophysiological parameters leads to variability in behavioral performance. Here, using a combination of magnetic resonance spectroscopy, magnetoencephalography, and visual psychophysics, we show that individual performance on a visual orientation discrimination task is correlated with both the resting concentration of GABA and the frequency of stimulus-induced gamma oscillations in human visual cortex. Behaviorally, a strong oblique effect was found, with the mean angular threshold for oblique discrimination being five times higher than that for vertically oriented stimuli. Similarly, we found an oblique effect for the dependency of performance on neurophysiological parameters. Orientation detection thresholds were significantly negatively correlated with visual cortex GABA concentration for obliquely oriented patterns (r ϭ Ϫ0.65, p Ͻ 0.015) but did not reach significance for vertically oriented stimuli (r ϭ Ϫ0.39, p ϭ 0.2). Similarly, thresholds for obliquely oriented stimuli were negatively correlated with gamma oscillation frequency (r ϭ Ϫ0.65, p Ͻ 0.017), but thresholds for vertical orientations were not (r ϭ Ϫ0.02, p ϭ 0.9). Gamma oscillation frequency was positively correlated with GABA concentration in primary visual cortex (r ϭ 0.67, p Ͻ 0.013). These results confirm the importance of GABAergic inhibition in orientation selectivity and demonstrate, for the first time, that interindividual performance on a simple visual task is linked to neurotransmitter concentration. The results also suggest a key role for GABAergic gamma oscillations in visual discrimination tasks.

Sheep are a key source of meat, milk and fibre for the global livestock sector, and an important biomedical model. Global analysis of gene expression across multiple tissues has aided genome annotation and supported functional annotation of mammalian genes. We present a large-scale RNA-Seq dataset representing all the major organ systems from adult sheep and from several juvenile, neonatal and prenatal developmental time points. The Ovis aries reference genome (Oar v3.1) includes 27,504 genes (20,921 protein coding), of which 25,350 (19,921 protein coding) had detectable expression in at least one tissue in the sheep gene expression atlas dataset. Network-based cluster analysis of this dataset grouped genes according to their expression pattern. The principle of ‘guilt by association’ was used to infer the function of uncharacterised genes from their co-expression with genes of known function. We describe the overall transcriptional signatures present in the sheep gene expression atlas and assign those signatures, where possible, to specific cell populations or pathways. The findings are related to innate immunity by focusing on clusters with an immune signature, and to the advantages of cross-breeding by examining the patterns of genes exhibiting the greatest expression differences between purebred and crossbred animals. This high-resolution gene expression atlas for sheep is, to our knowledge, the largest transcriptomic dataset from any livestock species to date. It provides a resource to improve the annotation of the current reference genome for sheep, presenting a model transcriptome for ruminants and insight into gene, cell and tissue function at multiple developmental stages.

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SummaryDuring smooth pursuit eye movement, observers often misperceive velocity. Pursued stimuli appear slower (Aubert-Fleishl phenomenon [1, 2]), stationary objects appear to move (Filehne illusion [3]), the perceived direction of moving objects is distorted (trajectory misperception [4]), and self-motion veers away from its true path (e.g., the slalom illusion [5]). Each illusion demonstrates that eye speed is underestimated with respect to image speed, a finding that has been taken as evidence of early sensory signals that differ in accuracy [4, 6–11]. Here we present an alternative Bayesian account, based on the idea that perceptual estimates are increasingly influenced by prior expectations as signals become more uncertain [12–15]. We show that the speeds of pursued stimuli are more difficult to discriminate than fixated stimuli. Observers are therefore less certain about motion signals encoding the speed of pursued stimuli, a finding we use to quantify the Aubert-Fleischl phenomenon based on the assumption that the prior for motion is centered on zero [16–20]. In doing so, we reveal an important property currently overlooked by Bayesian models of motion perception. Two Bayes estimates are needed at a relatively early stage in processing, one for pursued targets and one for image motion.