The Phenomenology of Anesthesia: A Neurodivergent Auto-Observational Analysis of Cognitive Suspension and Restoration
Gustavo Chittolina Pettan
Zenodo (CERN European Organization for Nuclear Research) April 30, 2026 preprint DOI: 10.5281/zenodo.19904022 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Autoethnographic first-person phenomenological case study Qualitative Case report |
|---|---|
| Sample size | 1 |
| Population | The author, a Twice-Exceptional (2E) individual with Autism Spectrum Disorder (ASD Level 2) undergoing a 10.5-hour surgical procedure under general anesthesia |
| Duration | 10.5-hour surgical procedure |
| Topics | Philosophy of mind |
| Key findings | Argues that neurodivergent-based phenomenological auto-observation, drawing on the author's hypersystematization and pattern recognition, can document the lived experience of general anesthesia that traditional neurotypical clinical frameworks miss. The first-person account describes cognitive suspension, sensory reintegration, and "cognitive rebooting" after a 10.5-hour surgery, which the author proposes as qualitative data for developing the "Adaptive Synergy Model." |
Abstract
The subjective experience of general anesthesia remains largely a "black box" within neurobiology and psychoanalysis. Traditional clinical observations rely on external neurotypical frameworks, often failing to capture the nuanced phenomenological transition between consciousness and medically induced unconsciousness. This paper introduces a novel methodological approach: neurodivergent-based phenomenological auto-observation. Utilizing the inherent hypersystematization and heightened pattern recognition of a Twice-Exceptional (2E) and Autism Spectrum Disorder (ASD Level 2) cognitive profile, this study documents the first-person lived experience of cognitive suspension and subsequent neurological restoration following a complex, prolonged (10.5-hour) surgical procedure. The findings provide qualitative data on sensory reintegration and cognitive rebooting, offering vital insights for the development of the Adaptive Synergy Model.
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