Memetics and neural models of conspiracy theories

模因学和阴谋论的神经模型

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Abstract

Memetics has so far been developing in social sciences, but to fully understand memetic processes it should be linked to neuroscience models of learning, encoding, and retrieval of memories in the brain. Attractor neural networks show how incoming information is encoded in memory patterns, how it may become distorted, and how chunks of information may form patterns that are activated by many cues, forming the foundation of conspiracy theories. The rapid freezing of high neuroplasticity (RFHN) model is offered as one plausible mechanism of such processes. Illustrations of distorted memory formation based on simulations of competitive learning neural networks are presented as an example. Linking memes to attractors of neurodynamics should help to give memetics solid foundations, show why some information is easily encoded and propagated, and draw attention to the need to analyze neural mechanisms of learning and memory that lead to conspiracies.

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