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Lecture

Neuronal Dynamics of Cognition: Decision Models

Description

This lecture covers the neuronal dynamics of decision making, focusing on competitive dynamics and decision models. Topics include perceptual decision making, theory of decision dynamics, solutions for symmetric and biased cases, simulations, experiments, and the problem of free will.

In MOOC

Neuronal Dynamics 2- Computational Neuroscience: Neuronal Dynamics of Cognition

Official source

Related concepts (31)

Simulation

A simulation is the imitation of the operation of a real-world process or system over time. Simulations require the use of models; the model represents the key characteristics or behaviors of the selected system or process, whereas the simulation represents the evolution of the model over time. Often, computers are used to execute the simulation. Simulation is used in many contexts, such as simulation of technology for performance tuning or optimizing, safety engineering, testing, training, education, and video games.

Competition

Competition is a rivalry where two or more parties strive for a common goal which cannot be shared: where one's gain is the other's loss (an example of which is a zero-sum game). Competition can arise between entities such as organisms, individuals, economic and social groups, etc. The rivalry can be over attainment of any exclusive goal, including recognition. Competition occurs in nature, between living organisms which co-exist in the same environment. Animals compete over water supplies, food, mates, and other biological resources.

Decision-making

In psychology, decision-making (also spelled decision making and decisionmaking) is regarded as the cognitive process resulting in the selection of a belief or a course of action among several possible alternative options. It could be either rational or irrational. The decision-making process is a reasoning process based on assumptions of values, preferences and beliefs of the decision-maker. Every decision-making process produces a final choice, which may or may not prompt action.

Recurrent neural network

A recurrent neural network (RNN) is one of the two broad types of artificial neural network, characterized by direction of the flow of information between its layers. In contrast to uni-directional feedforward neural network, it is a bi-directional artificial neural network, meaning that it allows the output from some nodes to affect subsequent input to the same nodes. Their ability to use internal state (memory) to process arbitrary sequences of inputs makes them applicable to tasks such as unsegmented, connected handwriting recognition or speech recognition.

Competition law

Competition law is the field of law that promotes or seeks to maintain market competition by regulating anti-competitive conduct by companies. Competition law is implemented through public and private enforcement. It is also known as antitrust law (or just antitrust), anti-monopoly law, and trade practices law; the act of pushing for antitrust measures or attacking monopolistic companies (known as trusts) is commonly known as trust busting. The history of competition law reaches back to the Roman Empire.

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