The locus coeruleus as a global model failure system.

Area of Science:

• Neuroscience
• Computational Neuroscience
• Cognitive Science

Background:

• Predictive processing models suggest brains predict sensory input.
• Prediction errors drive plasticity and learning.
• The locus coeruleus (LC) is implicated in signaling prediction errors.

Purpose of the Study:

• To explore the role of the locus coeruleus (LC) in signaling global model failures.
• To examine the utility of LC signals in cortical learning rate control.
• To understand how the LC circuit computes these signals and its implications for neurodivergence.

Main Methods:

• Literature review and theoretical synthesis.
• Analysis of recent findings on LC function.
• Exploration of computational models of prediction error signaling.

Main Results:

• Evidence supports the LC signaling global prediction errors, particularly when sensory input strongly violates internal models.
• The LC's role in modulating cortical plasticity via learning rate control is discussed.
• Potential mechanisms for LC signal computation are explored.

Conclusions:

• The LC may provide a crucial signal for updating internal models of the world when faced with significant prediction errors.
• This perspective offers insights into learning, neuroplasticity, and neurodivergent conditions.