A Computational Model of Visual Anisotropy

Visual anisotropy has been demonstrated in multiple tasks where performance differs between vertical, horizontal, and oblique orientations of the stimuli. We explain some principles of visual anisotropy by anisotropic smoothing, which is based on a variation on Koenderink's approach in [1]. We tested the theory by presenting Gaussian elongated luminance profiles and measuring the perceived orientations by means of an adjustment task. Our framework is based on the smoothing of the image with elliptical Gaussian kernels and it correctly predicted an illusory orientation bias towards the vertical axis. We discuss the scope of the theory in the context of other anisotropies in perception

Heterogeneity of hypothalamic pro-opiomelanocortin-expressing neurons revealed by single-cell RNA sequencing

$\textbf{Objective}$ Arcuate proopiomelanocortin (POMC) neurons are critical nodes in the control of body weight. Often characterized simply as direct targets for leptin, recent data suggest a more complex architecture. $\textbf{Methods}$ Using single cell RNA sequencing, we have generated an atlas of gene expression in murine POMC neurons. $\textbf{Results}$ Of 163 neurons, 118 expressed high levels of $\textit{Pomc}$ with little/no Agrp expression and were considered “canonical” POMC neurons (P$^{+}$). The other 45/163 expressed low levels of $\textit{Pomc}$ and high levels of $\textit{Agrp}$ (A$^{+}$P$_{+}$). Unbiased clustering analysis of P$^{+}$ neurons revealed four different classes, each with distinct cell surface receptor gene expression profiles. Further, only 12% (14/118) of P$^{+}$ neurons expressed the leptin receptor ($\textit{Lepr}$) compared with 58% (26/45) of A$^{+}$P$_{+}$ neurons. In contrast, the insulin receptor ($\textit{Insr}$) was expressed at similar frequency on P$^{+}$ and A$^{+}$P$_{+}$ neurons (64% and 55%, respectively). $\textbf{Conclusion}$ These data reveal arcuate POMC neurons to be a highly heterogeneous population. Accession Numbers: GSE92707.This work was supported by the UK Medical Research Council (MRC) Metabolic Disease Unit (MRC_MC_UU_12012/1 & MRC_MC_UU_12012/5), a Wellcome Trust Strategic Award (100574/Z/12/Z), and the Helmholtz Alliance ICEMED

Heterogeneity of hypothalamic pro-opiomelanocortin-expressing neurons revealed by single-cell RNA sequencing

$\textbf{Objective}$ Arcuate proopiomelanocortin (POMC) neurons are critical nodes in the control of body weight. Often characterized simply as direct targets for leptin, recent data suggest a more complex architecture. $\textbf{Methods}$ Using single cell RNA sequencing, we have generated an atlas of gene expression in murine POMC neurons. $\textbf{Results}$ Of 163 neurons, 118 expressed high levels of $\textit{Pomc}$ with little/no Agrp expression and were considered “canonical” POMC neurons (P$^{+}$). The other 45/163 expressed low levels of $\textit{Pomc}$ and high levels of $\textit{Agrp}$ (A$^{+}$P$_{+}$). Unbiased clustering analysis of P$^{+}$ neurons revealed four different classes, each with distinct cell surface receptor gene expression profiles. Further, only 12% (14/118) of P$^{+}$ neurons expressed the leptin receptor ($\textit{Lepr}$) compared with 58% (26/45) of A$^{+}$P$_{+}$ neurons. In contrast, the insulin receptor ($\textit{Insr}$) was expressed at similar frequency on P$^{+}$ and A$^{+}$P$_{+}$ neurons (64% and 55%, respectively). $\textbf{Conclusion}$ These data reveal arcuate POMC neurons to be a highly heterogeneous population. Accession Numbers: GSE92707.This work was supported by the UK Medical Research Council (MRC) Metabolic Disease Unit (MRC_MC_UU_12012/1 & MRC_MC_UU_12012/5), a Wellcome Trust Strategic Award (100574/Z/12/Z), and the Helmholtz Alliance ICEMED

Integration across time determines path deviation discrimination for moving objects.

YesBackground: Human vision is vital in determining our interaction with the outside world. In this study we characterize our ability to judge changes in the direction of motion of objects-a common task which can allow us either to intercept moving objects, or else avoid them if they pose a threat. Methodology/Principal Findings: Observers were presented with objects which moved across a computer monitor on a linear path until the midline, at which point they changed their direction of motion, and observers were required to judge the direction of change. In keeping with the variety of objects we encounter in the real world, we varied characteristics of the moving stimuli such as velocity, extent of motion path and the object size. Furthermore, we compared performance for moving objects with the ability of observers to detect a deviation in a line which formed the static trace of the motion path, since it has been suggested that a form of static memory trace may form the basis for these types of judgment. The static line judgments were well described by a 'scale invariant' model in which any two stimuli which possess the same two-dimensional geometry (length/width) result in the same level of performance. Performance for the moving objects was entirely different. Irrespective of the path length, object size or velocity of motion, path deviation thresholds depended simply upon the duration of the motion path in seconds. Conclusions/Significance: Human vision has long been known to integrate information across space in order to solve spatial tasks such as judgment of orientation or position. Here we demonstrate an intriguing mechanism which integrates direction information across time in order to optimize the judgment of path deviation for moving objects.Wellcome Trust, Leverhulme Trust, NI