Refining mechanistic models of hallucinations for enhanced translatability

Area of Science:

• Cognitive Neuroscience
• Computational Neuroscience
• Neuroscience

Background:

• Foundational research has illuminated the cognitive and neural underpinnings of hallucinations over the past 20 years.
• Multiple theories propose distinct cognitive mechanisms for hallucinations, necessitating further investigation into their circuit-level implementations.

Purpose of the Study:

• To propose a general strategy for specifying and falsifying candidate mechanisms of (auditory) hallucinations.
• To advance the understanding of hallucination pathophysiology and guide the development of targeted therapeutics.

Main Methods:

• Articulating computational and biological details of theories to generate precise, testable predictions.
• Evaluating theories using experiments designed to falsify unique signatures.
• Utilizing theory-driven computational models constrained by findings from basic, preclinical, and clinical neuroscience.

Main Results:

• Demonstrated how computational models can prioritize falsifiable mechanistic theories of auditory hallucinations.
• Discussed how models can inform the development of behavioral paradigms and analytical approaches for direct theory comparison.

Conclusions:

• A principled strategy for specifying and falsifying mechanistic theories of hallucinations is crucial for refining understanding.
• This approach is essential for advancing the translational potential of hallucination research and therapeutic development.