Adaptation in the visual system: Networked fatigue or suppressed prediction error signalling?

Area of Science:

• Neuroscience
• Cognitive Science
• Visual Perception

Background:

• The brain continuously adapts to visual environment changes.
• Neural adaptation impacts sensory neuron activity and perception.
• There is ongoing debate on the mechanisms of visual adaptation.

Purpose of the Study:

• To review neuroimaging and psychophysical evidence on neural adaptation.
• To evaluate the validity of predictive coding models for visual adaptation.
• To compare networked fatigue models against predictive coding models.

Main Methods:

• Review of existing neuroimaging studies.
• Analysis of psychophysical evidence.
• Comparative evaluation of theoretical models (networked fatigue vs. predictive coding).

Main Results:

• Predictive coding models face fundamental challenges from empirical evidence.
• Observations show distinct repetition and expectation effects.
• Predictive coding accounts inaccurately predict repulsive adaptation aftereffects.

Conclusions:

• Networked fatigue models offer a more parsimonious explanation for visual adaptation.
• Stimulus expectations may interact with fatigue-based adaptation.
• Proposes novel hypotheses on fatigue adaptation and predictive processes.