Mechanisms of species divergence through visual adaptation and sexual selection:Perspectives from a cichlid model system

The theory of ecological speciation suggests that assortative mating evolves most easily when mating preferences aredirectly linked to ecological traits that are subject to divergent selection. Sensory adaptation can play a major role in this process,because selective mating is often mediated by sexual signals: bright colours, complex song, pheromone blends and so on. Whendivergent sensory adaptation affects the perception of such signals, mating patterns may change as an immediate consequence.Alternatively, mating preferences can diverge as a result of indirect effects: assortative mating may be promoted by selectionagainst intermediate phenotypes that are maladapted to their (sensory) environment. For Lake Victoria cichlids, the visual environmentconstitutes an important selective force that is heterogeneous across geographical and water depth gradients. We investigatethe direct and indirect effects of this heterogeneity on the evolution of female preferences for alternative male nuptial colours(red and blue) in the genus Pundamilia. Here, we review the current evidence for divergent sensory drive in this system, extractgeneral principles, and discuss future perspectives [Current Zoology 56 (3): 285-299, 2010].

Adaptation to visual stimulation modifies the burst firing property of V1 neurons

The mean firing rate of visual cortical neurons is reduced after prolonged visual stimulation, but the underlying process by which this occurs as well as the biological significance of this phenomenon remains unknown. Computational neuroscience studies indicate that high-frequency bursts in stimulus-driven responses can be transmitted across synapses more reliably than isolated spikes, and thus may carry accurate stimulus-related information. Our research examined whether or not adaptation affects the burst firing property of visual cortical neurons by examining changes in the burst firing changes of V1 neurons during adaptation to the preferred visual stimulus. The results show that adaptation to prolonged visual stimulation significantly decreased burst frequency （bursts/s） and burst length （spikes/burst）, but increased burst duration and the interspike interval within bursts. These results suggest that the adaptation of V1 neurons to visual stimulation may result in a decrease of feedforward response gain but an increase of functional activities from lateral and/or feedback connections, which could lead to a reduction in the effectiveness of adapted neurons in transmitting information to its driven neurons.

Adaptation to visual stimulation modifies the burst firing property of V1 neurons

The mean firing rate of visual cortical neurons is reduced after prolonged visual stimulation,but the underlying process by which this occurs as well as the biological significance of this phenomenon remains unknown.Computational neuroscience studies indicate that high-frequency bursts in stimulus-driven responses can be transmitted across synapses more reliably than isolated spikes,and thus may carry accurate stimulus-related information.Our research examined whether or not adaptation affects the burst firing property of visual cortical neurons by examining changes in the burst firing changes of V1 neurons during adaptation to the preferred visual stimulus.The results show that adaptation to prolonged visual stimulation significantly decreased burst frequency(bursts/s)and burst length(spikes/burst),but increased burst duration and the interspike interval within bursts.These results suggest that the adaptation of V1 neurons to visual stimulation may result in a decrease of feedforward response gain but an increase of functional activities from lateral and/or feedback connections,which could lead to a reduction in the effectiveness of adapted neurons in transmitting information to its driven neurons.

Moving target detection based on improved ghost suppression and adaptive visual background extraction

Visual background extraction algorithm(ViBe)uses the first frame image to initialize the background model,which can easily introduce the“ghost”.Because ViBe uses the fixed segmentation threshold to achieve the foreground and background segmentation,the detection results in many false detections for the highly dynamic background.To solve these problems,an improved ghost suppression and adaptive Visual Background Extraction algorithm is proposed in this paper.Firstly,with the pixel’s temporal and spatial information,the historical pixels of a certain combination are used to initialize the background model in the odd frames of the video sequence.Secondly,the background sample set combined with the neighborhood pixels are used to determine a complex degree of the background,to acquire the adaptive segmentation threshold.Thirdly,the update rate is adjusted based on the complexity of the background.Finally,the detected result goes through a post-processing to achieve better detection results.The experimental results show that the improved algorithm will not only quickly suppress the“ghost”,but also have a better detection in a complex dynamic background.

Web-based visualization of spatial objects in 3DGIS

Adaptive rendering large and complex spatial data has become an important research issue in a 3DGIS application. In order to transmit the data to the client efficiently, this paper proposes a node-layer data model to manage the 3D scene. Because the large spatial data and limited network bandwidth are the main bottlenecks of web-based 3DGIS, a client/server architecture including progressive transmission methods and multiresolution representations, together with the spatial index, are developed to improve the performance. All this makes the application quite scalable. Experimental results reveal that the application works appropriately.

Objective visual performance evaluation with visual evoked potential measurements based on an adaptive optics system

An objective visual performance evaluation with visual evoked potential （VEP） measurements was first inte- grated into an adaptive optics （AO） system. The optical and neural limits to vision can be bypassed through this system. Visual performance can be measured electrophysiologically with VEP, which reflects the objective func- tion from the retina to the primary visual cortex. The VEP ts without and with AO correction were preliminarily carried out using this system, demonstrating the great potential of this system in the objective visual performance evaluation. The new system will provide the necessary technique and equipment support for the further study of human visual function.

A virtual globe-based time-critical adaptive visualization method for 3D city models

3D city models,which are important items of content on the virtual globe,are characterized by complicated structures and large amounts of data.These factors make the visualization of 3D city models highly dependent upon the performance of computer hardware.Thus,achieving the efficient rendering of 3D city models using different hardware performance levels represents one of the key problems currently facing researchers.This paper proposes a time-critical adaptive visualization method that first estimates the possible rendering time for each model according to the data structure of the model in addition to the CPU/GPU performance of the computer.It then dynamically adjusts the rendering level for each model based on the results of an estimation of the rendering time to ensure that the final scene can be completed within a given time.To verify the effectiveness and flexibility of this method,it is applied using different computers.The results show that the adaptive visualization method presented in this paper not only can adapt to computers with different levels of performances but also demonstrates an obvious improvement in the time estimation precision,visual effects,and optimization speed relative to existing adaptive visualization methods.