Ganglion Cells in Primate Retina Use Fuzzy Logic to Encode Complex Visual Receptive Fields

Synaptic Origins of the Complex Receptive Field Structure in Primate Smooth Monostratified Retinal Ganglion Cells

Considerable progress has been made in studying the receptive fields of the most common primate retinal ganglion cell (RGC) types, such as parasol RGCs. Much less is known about the rarer primate RGC types and the circuitry that gives rise to noncanonical receptive field structures. The goal of this study was to analyze synaptic inputs to smooth monostratified RGCs to determine the origins of their complex spatial receptive fields, which contain isolated regions of high sensitivity called "hotspots." Interestingly, smooth monostratified RGCs co-stratify with the well-studied parasol RGCs and are thus constrained to receiving input from bipolar and amacrine cells with processes sharing the same layer, raising the question of how their functional differences originate. Through 3D reconstructions of circuitry and synapses onto ON smooth monostratified and ON parasol RGCs from central macaque retina, we identified four distinct sampling strategies employed by smooth and parasol RGCs to extract diverse response properties from co-stratifying bipolar and amacrine cells. The two RGC types differed in the proportion of amacrine cell input, relative contributions of co-stratifying bipolar cell types, amount of synaptic input per bipolar cell, and spatial distribution of bipolar cell synapses. Our results indicate that the smooth RGC's complex receptive field structure arises through spatial asymmetries in excitatory bipolar cell input which formed several discrete clusters comparable with physiologically measured hotspots. Taken together, our results demonstrate how the striking differences between ON parasol and ON smooth monostratified RGCs arise from distinct strategies for sampling a common set of synaptic inputs.

Using Fuzzy Logic Method to Investigate the Effect of Economic Sanctions on Business Cycles in the Islamic Republic of Iran

One of the main economic issues in Iran is the issue of economic sanctions. These sanctions have been imposed by various institutions and countries around the world in various forms since 1979 against Iran. Economic sanctions have affected large sections of Iran’s economy. Meanwhile, economic sanctions against Iran have had far-reaching effects on trade cycles in Iran. The purpose of this article is to investigate the impact of economic sanctions on the structure of business cycles in Iran. The sanction index is a tool for studying quantitative sanctions. The opinions of 15 experts in sanctions economics were collected using fuzzy questionnaires. And the sanction index was obtained. The fuzzy logic method in the MATLAB software space calculated the economic sanction index for 1979–2019. The self-regression calculated the effect of economic sanctions on business cycles. There are two scenarios in this article. In scenario 1, sanctions increased inflation, reduced production, and reduced investment. Also, during the embargo period, the recessions are longer. The second scenario of the research shows the economy without sanctions. The results showed that, in these conditions, inflation has less effect on production and investment. And the economy will experience a long period of prosperity without sanctions.