Now is the time: operationalizing generative neurophenomenology through interpersonal methods.

Area of Science:

• Cognitive Science
• Neuroscience
• Phenomenology

Background:

• Neurophenomenology integrates first-person subjective experience with third-person neurobehavioral data.
• Lived experience is shaped by intersubjective, social, cultural, and historical factors.
• Existing neurophenomenology primarily focuses on individual experiences.

Purpose of the Study:

• To update neurophenomenology by emphasizing intersubjective and social dimensions.
• To propose a "generative neurophenomenology" approach suitable for the current scientific community.
• To clarify the meanings of 'generative' in phenomenology and modeling.

Main Methods:

• Transitioning from individual to multiple-person phenomenology methods to capture intersubjectivity.
• Expanding neuroscience to include multimodal interpersonal synchrony measures.
• Utilizing computational tools and diverse mathematical formalisms to integrate viewpoints.

Main Results:

• The proposed methods enrich the understanding of lived experience by incorporating social and intersubjective aspects.
• Computational modeling of neurophenomenology does not necessitate endorsing computationalism as a hypothesis of experience.
• Case studies in autism and family therapy demonstrate the clinical relevance and translational potential.

Conclusions:

• Generative neurophenomenology offers a robust framework for studying the complexities of lived experience.
• The updated approach has significant translational potential for clinical applications in psychiatry.
• Integrating intersubjectivity and social dynamics is crucial for a comprehensive understanding of human experience.