ArticleNeuroscience of consciousness2026
Phenomenology of the stream of thought: dissociable dynamic dimensions revealed through experience sampling.
Article in Neuroscience of consciousness, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
The pursuit of a scientific theory of consciousness has gained momentum in neuroscience over the past 25 years. While much research has centered on perceptual consciousness, the dynamic experience of the stream of thought, proposed by William James over a century ago, has remained relatively underexplored. The Dynamic Framework of Thought (DFT) introduced a taxonomy of thought dynamics, emphasizing their role in shaping conscious experiences. The present study explores the introspective accessibility and distinctiveness of two dynamic dimensions of thought, freely moving and deliberately directed, derived from the taxonomy of the DFT. To investigate these dynamics, four experiments were conducted, including laboratory-based and online experiments as well as an fMRI-based experiment, to assess the consistency of the relationship between these thought dynamics across various experimental contexts. In all experiments, participants reported the dynamics of their thoughts during a probed resting period in which they sat quietly with eyes open, viewing a blank screen. Using a mixed-methods approach combining qualitative and quantitative assessments, this study suggests that individuals can have some introspective access to their thought dynamics. Freely moving and deliberately directed thoughts were distinguishable and negatively correlated but not anticorrelated across participants and experimental contexts. These findings suggest that the stream of thought can be characterized by at least two distinct dynamic dimensions-freely moving and deliberately directed-offering valuable insights for future neurophenomenological research aimed at bridging first-person reports of thought dynamics with third-person data on brain processes.
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