Confabulation (neural networks)
A confabulation, also known as a false, degraded, or corrupted memory, is a stable pattern of activation in an artificial neural network or neural assembly that does not correspond to any previously learned patterns. The same term is also applied to the (nonartificial) neural mistake-making process leading to a false memory (confabulation). Cognitive science In cognitive science, the generation of confabulatory patterns is symptomatic of some forms of brain trauma. In this, confabulations relate to pathologically induced neural activation patterns depart from direct experience and learned relationships. In computational modeling of such damage, related brain pathologies such as dyslexia and hallucination result from simulated lesioning and neuron death. Forms of confabulation in which missing or incomplete information is incorrectly filled in by the brain are generally modelled by the well known neural network process called pattern completion. Neural networks Confabulation is central to a theory of cognition and consciousness by S. L. Thaler in which thoughts and ideas originate in both biological and synthetic neural networks as false or degraded memories nucleate upon various forms of neuronal and synaptic fluctuations and damage. Such novel patterns of neural activation are promoted to ideas as other neural nets perceive utility or value