Modulation of retinal ganglion cell responses by the endocannabinoid system and the involvement of TRPV1 channels

The endocannabinoid (eCB) system was found to modulate synaptic transmission in the central nervous system (CNS). The retina carries out complex neural computations that involve several physiological mechanisms, including short and long-term plasticity phenomena. The mechanisms responsible for modifying the strength of retinal synaptic transmission, however, are not fully understood. Previous studies in the Vision Lab showed that bath application of a drug that elevates the concentration of endocannabinoids reduced the peak amplitude of visual-evoked postsynaptic potentials (vePSP) in retinal ganglion cells (RGCs) but paradoxically increased their spiking output. In addition, the rise in endocannabinoid concentration shifted the voltage dependence of the sodium current to the left. The reduction in vePSP amplitude is consistent with the known presynaptic effects of eCBs on synaptic transmission whilst it was postulated that the increase in spiking output could be mediated by TRPV1 receptors, which are nonselective ligand gated cation channel sensitive to eCBs and a broad range of other stimuli. This study investigated the potential role of TRPV1 channels in the modulation of RGCs excitability by recording their electrical activity in wild-type and TRPV1 knock-out mice using whole cell patch clamping techniques. We found that the endocannabinoid anandamide acts on TRPV1 channels to increase cell excitability. Increasing the levels of anandamide in the absence of TRPV1 channels, however, led to the activation of RGCs at more hyperpolarised potentials, suggesting that other targets of anandamide are involved in RGC modulation. Moreover, the TRPV1 agonist and antagonist capsaicin and capsazepine are likely to have non-specific effects as application of capsazepine was able to reduce cell excitability in the TRPV knockout mice (TRPV1-/-)

Inner and Inter Label Propagation: Salient Object Detection in the Wild

In this paper, we propose a novel label propagation based method for saliency detection. A key observation is that saliency in an image can be estimated by propagating the labels extracted from the most certain background and object regions. For most natural images, some boundary superpixels serve as the background labels and the saliency of other superpixels are determined by ranking their similarities to the boundary labels based on an inner propagation scheme. For images of complex scenes, we further deploy a 3-cue-center-biased objectness measure to pick out and propagate foreground labels. A co-transduction algorithm is devised to fuse both boundary and objectness labels based on an inter propagation scheme. The compactness criterion decides whether the incorporation of objectness labels is necessary, thus greatly enhancing computational efficiency. Results on five benchmark datasets with pixel-wise accurate annotations show that the proposed method achieves superior performance compared with the newest state-of-the-arts in terms of different evaluation metrics.Comment: The full version of the TIP 2015 publicatio