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Seth argues the brain uses Bayesian inference and predictive modelling [fn 3] to produce a "controlled hallucination" which is a subjective rendering of the inside and outside world. The brain makes predictions, sensory signals keep the predictions tied to their causes, and subjective experiences are created via "top-down" predictions rather ...
Anil Kumar Seth (born 11 June 1972) is a British neuroscientist and professor of Cognitive and Computational Neuroscience at the University of Sussex. A proponent of materialist explanations of consciousness , [ 1 ] he is currently amongst the most cited scholars on the topics of neuroscience and cognitive science globally.
Anil Seth defines such models as those that relate brain phenomena such as fast irregular electrical activity and widespread brain activation to properties of consciousness such as qualia. Seth allows for different types of models including mathematical, logical, verbal and conceptual models.
Neuroscientist Anil Seth and philosopher Peter Godfrey-Smith, for example, have argued that consciousness requires biological conditions present in human and animal brains but unlikely to be ...
Predictive coding was initially developed as a model of the sensory system, where the brain solves the problem of modelling distal causes of sensory input through a version of Bayesian inference. It assumes that the brain maintains an active internal representations of the distal causes, which enable it to predict the sensory inputs. [5]
However, neuroscientist Anil Seth argued that emphasis on the so-called hard problem is a distraction from what he calls the "real problem": understanding the neurobiology underlying consciousness, namely the neural correlates of various conscious processes. [22] This more modest goal is the focus of most scientists working on consciousness. [133]
Fixing that problem has proven difficult, in part because new systems produce such plausible looking text. Scientists might have found a way to overcome ‘hallucinations’ that plague AI systems ...
A fundamental principle of control theory is that a good controller should incorporate an internal model. Thus the brain's controller of attention should incorporate an internal model of attention – a set of information that is continuously updated and that reflects the dynamics and the changing state of attention.