The Bayesian brain: phantom percepts resolve sensory uncertainty.

Area of Science:

• Neuroscience
• Cognitive Science
• Computational Neuroscience

Background:

• Sensory deafferentation, the loss of sensory input, commonly leads to phantom perceptions across various sensory domains.
• The underlying mechanisms driving these 'phantom' sensations in the absence of external stimuli remain a key question in neuroscience.

Purpose of the Study:

• To explain the generation of phantom perceptions using a Bayesian brain model and the free-energy principle.
• To elucidate how the brain reduces environmental uncertainty and prediction errors in sensory deafferentation.

Main Methods:

• Conceptual modeling based on Bayesian inference and the free-energy principle.
• Analysis of neuroanatomical correlates, including sensory cortex activity, anterior cingulate, and insula involvement.

Main Results:

• Phantom perceptions are interpreted as a mechanism to reduce topographically restricted uncertainty caused by deafferentation.
• Sensory cortex hyperactivity, decreased inhibition, and map plasticity contribute to the generation of false sensory information.
• Activation of areas involved in salience and stress (anterior cingulate, insula) supports stimulus detection and uncertainty reduction.

Conclusions:

• The Bayesian brain model, driven by the free-energy principle, explains phantom percepts as a strategy to minimize uncertainty.
• Phantom perceptions serve an adaptive function by attempting to make sense of the environment despite sensory loss.
• This framework highlights the brain's predictive processing and active inference mechanisms in maintaining environmental awareness.