Non-Linear Neuronal Responses as an Emergent Property of Afferent Networks: A Case Study of the Locust Lobula Giant Movement Detector

In principle it appears advantageous for single neurons to perform non-linear operations. Indeed it has been reported that some neurons show signatures of such operations in their electrophysiological response. A particular case in point is the Lobula Giant Movement Detector (LGMD) neuron of the locust, which is reported to locally perform a functional multiplication. Given the wide ramifications of this suggestion with respect to our understanding of neuronal computations, it is essential that this interpretation of the LGMD as a local multiplication unit is thoroughly tested. Here we evaluate an alternative model that tests the hypothesis that the non-linear responses of the LGMD neuron emerge from the interactions of many neurons in the opto-motor processing structure of the locust. We show, by exposing our model to standard LGMD stimulation protocols, that the properties of the LGMD that were seen as a hallmark of local non-linear operations can be explained as emerging from the dynamics of the pre-synaptic network. Moreover, we demonstrate that these properties strongly depend on the details of the synaptic projections from the medulla to the LGMD. From these observations we deduce a number of testable predictions. To assess the real-time properties of our model we applied it to a high-speed robot. These robot results show that our model of the locust opto-motor system is able to reliably stabilize the movement trajectory of the robot and can robustly support collision avoidance. In addition, these behavioural experiments suggest that the emergent non-linear responses of the LGMD neuron enhance the system's collision detection acuity. We show how all reported properties of this neuron are consistently reproduced by this alternative model, and how they emerge from the overall opto-motor processing structure of the locust. Hence, our results propose an alternative view on neuronal computation that emphasizes the network properties as opposed to the local transformations that can be performed by single neurons

Основы творческой деятельности веб-журналиста. Учебная программа учреждения высшего образования по учебной дисциплине для специальности: 1-23 01 08 Журналистика (по направлениям) направления специальности 1-23 01 08-03 Журналистика (веб-журналистика)

Wildfires pose a serious threat to life in many countries. For police, fire and emergency services authorities in most jurisdictions in North America and Australia evacuation is now the option that is preferred overwhelmingly. Wildfire evacuation modeling can assist authorities in planning evacuation responses to future threats. Understanding residents' behavior under wildfire threat may assist in wildfire evacuation modeling. This paper reviews North American and Australian research into wildfire evacuation behavior published between January 2005 and June 2017. Wildfire evacuation policies differ across the two regions: in North America mandatory evacuations are favored, in Australia most are advisory. Research from both regions indicates that following a wildfire evacuation warning some threatened residents will wish to remain on their property in order to protect it, many will delay evacuating, and some residents who are not on their property when an evacuation warning is issued may seek to return. Mandatory evacuation is likely to result in greater compliance, enforcement policies are also likely to be influential. Self-delayed evacuation is likely if warnings are not sufficiently informative: residents are likely to engage in information search rather than initiating evacuation actions. The wildfire warning and threat histories of a location may influence residents' decisions and actions. The complexities of behavioral factors influencing residents' actions following an evacuation warning pose challenges for wildfire evacuation modeling. Suggestions are offered for ways in which authorities might reduce the numbers of residents who delay evacuating following a wildfire warning. © 2018 Springer Science+Business Media, LLC, part of Springer Natur