Banks as the Actors of a Modern Monetary Policy in Russia: Effects of Exposure on the Econom

The article's relevance is determined by the fact that in the conditions of a bank-oriented financial system the "signals" from the central bank regarding decisions about the monetary policy go to the economy via banks, through which the main channels of the transmission mechanism of the monetary policy are implemented. The analysis of the effects of banks as the actors of the monetary policy is therefore relevant. The article, based on a study of the elements of investment potential for their impact on GDP, contains conclusions about the possibility of achieving economic growth as one of the strategic goals the monetary policy through the main channels of the transmission mechanism using its standard tools. The article is to identify and quantify the factors that have significant effects on economic growth through the impact on investment potential. The change in the Bank of Russia's key interest affects only some of the investment potential elements such as deposits of legal entities in rubles. Such impact can slightly improve GDP. The use of monetary policy tools will enable the influence on the change of the nominal interest rate and, therefore, the adjustment of real rates, and it may also affect aggregate demand (consumption and investment potential)

One system for learning and remembering episodes and rules

Humans can learn individual episodes and generalizable rules and also successfully retain both kinds of acquired knowledge over time. In the cognitive science literature, (1) learning individual episodes and rules and (2) learning and remembering are often both conceptualized as competing processes that necessitate separate, complementary learning systems. Inspired by recent research in statistical learning, we challenge these trade-offs, hypothesizing that they arise from capacity limitations rather than from the inherent incompatibility of the underlying cognitive processes. Using an associative learning task, we show that one system with excess representational capacity can learn and remember both episodes and rules

How do brain maps affect neuroscientific investigation? A study with novices

This study explores how scientific conceptualizations, such as partitioning of the brain into distinct regions, shape investigation. One hundred fifty-six undergraduate psychology students (novices) completed a science learning task in which they explored the behavioral functions of a fictional brain segment by conducting simplified neuroimaging and lesioning experiments on it. We investigated how the partitioning of the segment into regions influenced participants' experimental choices and learning outcomes by randomly seeding the brain regions for each participant. The participants exhibited conceptual influences on their experimentation: they preferred to explore the boundaries and prototypical--or "skeletal"--locations of the delineated regions. These conceptual biases significantly shaped learning outcomes; for example, participants were more successful at identifying signals near region boundaries. Additionally, participants demonstrated conceptual expectations that led them to associate a discovered signal with locations within one region rather than locations that straddled region boundaries. This research contributes to our understanding of how the scientific concepts affect scientific investigation

The Influences of Category Learning on Perceptual Reconstructions

We explore different ways in which the human visual system can adapt for perceiving and categorizing the environment. There are various accounts of supervised (categorical) and unsupervised perceptual learning, and different perspectives on the functional relationship between perception and categorization. We suggest that common experimental designs are insufficient to differentiate between hypothesised perceptual learning mechanisms and reveal their possible interplay. We propose a relatively underutilized way of studying potential categorical effects on perception, and test the predictions of different perceptual learning models using a two-dimensional, interleaved categorization-plus-reconstruction task. We find evidence that human visual encodings adapt to the feature structure of the environment, allocate encoding resources with respect to categorization utility, and adapt to prevent miscategorizations