Training a spiking neuronal network model of visual-motor cortex to play a virtual racket-ball game using reinforcement learning.

Recent models of spiking neuronal networks have been trained to perform behaviors in static environments using a variety of learning rules, with varying degrees of biological realism. Most of these models have not been tested in dynamic visual environments where models must make predictions on future states and adjust their behavior accordingly. The models using these learning rules are often treated as black boxes, with little analysis on circuit architectures and learning mechanisms supporting optimal performance. Here we developed visual/motor spiking neuronal network models and trained them to play a virtual racket-ball game using several reinforcement learning algorithms inspired by the dopaminergic reward system. We systematically investigated how different architectures and circuit-motifs (feed-forward, recurrent, feedback) contributed to learning and performance. We also developed a new biologically-inspired learning rule that significantly enhanced performance, while reducing training time. Our models included visual areas encoding game inputs and relaying the information to motor areas, which used this information to learn to move the racket to hit the ball. Neurons in the early visual area relayed information encoding object location and motion direction across the network. Neuronal association areas encoded spatial relationships between objects in the visual scene. Motor populations received inputs from visual and association areas representing the dorsal pathway. Two populations of motor neurons generated commands to move the racket up or down. Model-generated actions updated the environment and triggered reward or punishment signals that adjusted synaptic weights so that the models could learn which actions led to reward. Here we demonstrate that our biologically-plausible learning rules were effective in training spiking neuronal network models to solve problems in dynamic environments. We used our models to dissect the circuit architectures and learning rules most effective for learning. Our model shows that learning mechanisms involving different neural circuits produce similar performance in sensory-motor tasks. In biological networks, all learning mechanisms may complement one another, accelerating the learning capabilities of animals. Furthermore, this also highlights the resilience and redundancy in biological systems.VoRSUNY DownstatePhysiology and PharmacologyNathan Kline Institute for Psychiatric ResearchN/

The management of patients with primary chronic anal fissure: a position paper

Anal fissure is one of the most common and painful proctologic diseases. Its treatment has long been discussed and several different therapeutic options have been proposed. In the last decades, the understanding of its pathophysiology has led to a progressive reduction of invasive and potentially invalidating treatments in favor of conservative treatment based on anal sphincter muscle relaxation. Despite some systematic reviews and an American position statement, there is ongoing debate about the best treatment for anal fissure. This review is aimed at identifying the best treatment option drawing on evidence-based medicine and on the expert advice of 6 colorectal surgeons with extensive experience in this field in order to produce an Italian position statement for anal fissures. While there is little chance of a cure with conservative behavioral therapy, medical treatment with calcium channel blockers, diltiazem and nifepidine or glyceryl trinitrate, had a considerable success rate ranging from 50 to 90%. Use of 0.4% glyceryl trinitrate in standardized fashion seems to have the best results despite a higher percentage of headache, while the use of botulinum toxin had inconsistent results. Nonresponding patients should undergo lateral internal sphincterotomy. The risk of incontinence after this procedure seems to have been overemphasized in the past. Only a carefully selected group of patients, without anal hypertonia, could benefit from anoplasty

Economic Impacts of Climate Change on Vegetative Agriculture Markets in Israel

We integrate the combined agricultural production effects of forecasted changes in CO2, temperature and precipitation into a multi-regional, country-wide partial equilibrium positive mathematical programming model. By conducting a meta-analysis of 2103 experimental observations from 259 agronomic studies we estimate production functions relating yields to CO2 concentration and temperature for 55 crops. We apply the model to simulate climate change in Israel based on 15 agricultural production regions. Downscaled projections for CO2 concentration, temperature and precipitation were derived from three general circulation models and four representative concentration pathways, showing temperature increase and precipitation decline throughout most of the county during the future periods 2041–2060 and 2061–2080. Given the constrained regional freshwater and non-freshwater quotas, farmers will adapt by partial abandonment of agriculture lands, increasing focus on crops grown in controlled environments at the expense of open-field and rain-fed crops. Both agricultural production and prices decline, leading to reduced agricultural revenues; nevertheless, production costs reduce at a larger extent such that farming profits increase. As total consumer surplus also augments, overall social welfare rises. We find that this outcome is reversed if the positive fertilization effects of increased CO2 concentrations are overlooked

Unemployment: The Silent Epidemic

This paper examines two key aspects of unemployment-its propagation mechanism and socioeconomic costs. It identifies a key feature of this macroeconomic phenomenon: it behaves like a disease. A detailed assessment of the transmission mechanism and the existing pecuniary and nonpecuniary costs of unemployment suggests a fundamental shift in the policy responses to tackling joblessness. To stem the contagion effect and its outsized social and economic impact, fiscal policy can be designed around two criteria for successful disease intervention-preparedness and prevention. The paper examines how a job guarantee proposal uniquely meets those two requirements. It is a policy response whose merits include much more than its macroeconomic stabilization features, as discussed in the literature. It is, in a sense, a method of inoculation against the vile effects of unemployment. The paper discusses several preventative features of the program