The Computational Anatomy of Visual Neglect.

Area of Science:

• Cognitive Neuroscience
• Computational Neuropsychology
• Neuroscience

Background:

• Visual neglect is a significant neuropsychological deficit with clinical implications.
• It serves as a valuable model for studying lesion deficits in cognitive neuroscience.
• Understanding the underlying causes of visual neglect is crucial for diagnosis and treatment.

Purpose of the Study:

• To develop a computational model of visual neglect based on active inference.
• To establish a computational and neurophysiological process theory for visual neglect.
• To disambiguate the various causes of visual neglect through computational modeling.

Main Methods:

• Introduction of a Bayes optimal model utilizing Markov decision processes.
• Simulation of visual searches characteristic of the line cancellation task.
• Modeling of three distinct lesion types to replicate visual search deficits.

Main Results:

• The computational model successfully reproduces visual search patterns observed in the line cancellation task.
• Three simulated lesion levels correspond to known neuroanatomical pathways involved in saccadic eye movements.
• The model's pathologies align with systems implicated in visual neglect.

Conclusions:

• The active inference model provides a framework for understanding visual neglect.
• Simulated lesions offer insights into the neurophysiological underpinnings of visual search deficits.
• This computational approach aids in differentiating causes of visual neglect and its relation to eye movement systems.