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The history of neural activity determines the synaptic plasticity mechanisms employed in the brain. Previous studies report a rapid reduction in the strength of excitatory synapses onto layer 2/3 (L2/3) pyramidal neurons of the primary visual cortex (V1) following two days of dark exposure and subsequent re-exposure to light. The abrupt increase in visually driven activity is predicted to drive homeostatic plasticity, however, the parameters of neural activity that trigger these changes are unknown. To determine this, we first recorded spike trains in vivo from V1 layer 4 (L4) of dark exposed (DE) mice of both sexes that were re-exposed to light through homogeneous or patterned visual stimulation. We found that delivering the spike patterns recorded in vivo to L4 of V1 slices was sufficient to reduce the amplitude of miniature excitatory postsynaptic currents (mEPSCs) of V1 L2/3 neurons in DE mice, but not in slices obtained from normal reared (NR) controls. Unexpectedly, the same stimulation pattern produced an up-regulation of mEPSC amplitudes in V1 L2/3 neurons from mice that received 2 h of light re-exposure (LE). A Poisson spike train exhibiting the same average frequency as the patterns recorded in vivo was equally effective at depressing mEPSC amplitudes in L2/3 neurons in V1 slices prepared from DE mice. Collectively, our results suggest that the history of visual experience modifies the responses of V1 neurons to stimulation and that rapid homeostatic depression of excitatory synapses can be driven by non-patterned input activity.

The activity of a border ownership selective (BOS) neuron indicates where a foreground object is located relative to its (classical) receptive field (RF). A population of BOS neurons thus provides an important component of perceptual grouping, the organization of the visual scene into objects. In previous theoretical work, it has been suggested that this grouping mechanism is implemented by a population of dedicated grouping ("G") cells that integrate the activity of the distributed feature cells representing an object and, by feedback, modulate the same cells, thus making them border ownership selective. The feedback modulation by G cells is thought to also provide the mechanism for object-based attention. A recent modeling study showed that modulatory common feedback, implemented by synapses with N-methyl-D-aspartate (NMDA)-type glutamate receptors, accounts for the experimentally observed synchrony in spike trains of BOS neurons and the shape of cross-correlations between them, including its dependence on the attentional state. However, that study was limited to pairs of BOS neurons with consistent border ownership preferences, defined as two neurons tuned to respond to the same visual object, in which attention decreases synchrony. But attention has also been shown to increase synchrony in neurons with inconsistent border ownership selectivity. Here we extend the computational model from the previous study to fully understand these effects of attention. We postulate the existence of a second type of G-cell that represents spatial attention by modulating the activity of all BOS cells in a spatially defined area. Simulations of this model show that a combination of spatial and object-based mechanisms fully accounts for the observed pattern of synchrony between BOS neurons. Our results suggest that modulatory feedback from G-cells may underlie both spatial and object-based attention.

The amount of visual information projected from the retina to the brain exceeds the information processing capacity of the latter. Attention, therefore, functions as a filter to highlight important information at multiple stages of the visual pathway that requires further and more detailed analysis. Among other functions, this determines where to fixate since only the fovea allows for high resolution imaging. Visual saliency modeling, i.e. understanding how the brain selects important information to analyze further and to determine where to fixate next, is an important research topic in computational neuroscience and computer vision. Most existing bottom-up saliency models use low-level features such as intensity and color, while some models employ high-level features, like faces. However, little consideration has been given to mid-level features, such as texture, for visual saliency models. In this paper, we extend a biologically plausible proto-object based saliency model by adding simple texture channels which employ nonlinear operations that mimic the processing performed by primate visual cortex. The extended model shows statistically significant improved performance in predicting human fixations compared to the previous model. Comparing the performance of our model with others on publicly available benchmarking datasets, we find that our biologically plausible model matches the performance of other models, even though those were designed entirely for maximal performance with little regard to biological realism.

Objective: CAD/CAM systems require scan spray for chairside sampling of tooth surfaces. However, this leads to alterations of the sprayed preparation and may affect marginal and internal adaption of the restoration. The aim of this study was to define the effect of scan spray on preparation form by evaluating the morphologies and the thicknesses of three different scan sprays. Materials and Methods: The surface morphology of the coatings of different scan sprays (A, B, C) was evaluated by use of a confocal laser scanning microscope. The thicknesses of spray coatings were measured on a glass plate as well as under simulated clinical conditions using a profilometer and a surface digitalisation device. The data were analysed by a 1-way ANOVA (α = .05). Results: The confocal laser scanning microscopy showed rough and irregular formed coating surfaces of all sprays, whereas an increasing numbers of small spray particles were seen from spray A over spray B to spray C. Mean coating thicknesses on the glass plate were: spray A 25.3 Mm, spray B 18.9 Mm and spray C 19.2 Mm. Significant differences were detected between spray A and B (P = .017). Under simulated clinical conditions median coating thicknesses were: spray A 15.5 Mm, spray B 15.0 Mm and spray C 13.3 Mm. A statistically significant difference could be detected only between spray A and C (P = .033). Conclusions: The coatings of the used scan spray systems showed different surface morphologies and exhibited different thicknesses. Consequently, the application of scan sprays affects the precision of the final CAD/CAM restorations. However, the scan sprays under investigation showed acceptable coating thicknesses for clinical use. [ABSTRACT FROM AUTHOR]