The Neurophenomenology of Meditative States: Introducing Temporal Experience Tracing to Capture Subjective Experience States and their Neural Correlates

Abstract

A recurring problem for the study of the neural correlates of conscious experience states is the lack of continuous measures for first-person reports. In this thesis, I introduce Temporal Experience Tracing as a method for capturing continuous subjective experiences. This method requires participants to retrospectively graph the intensity of an experience along several phenomenological dimensions over time. I present the results from two groups practising three styles of mindfulness meditation in either a 3-day Retreat setting, or over several months in their own homes. The traces revealed common experience states with transition dynamics shared between the participant groups. We found both meditation style-specific experience states, as well as a cluster of difficulties experienced with the practice. From low-density portable EEG recordings, 98 neural features were computed, including spectral features, connectivity measures and information theoretic measures. These features enabled classification of the data-driven experience clusters in unseen meditation sessions from known participants in both meditation groups, while the meditation style could only be classified in the more experienced participant group, the Home meditation group. Finally, using univariate classifications, the neural features enabling correct binary classifications of experience states are studied. Supporting the idea of inter-individual phenomenological similarity, neural markers associated with high classification accuracies strongly overlapped between the two groups. Furthermore, we did not find an effect of mindfulness training on the classification accuracy of subjective experience states, suggesting that this method can capture aspects of the true underlying experiences even in untrained participants. This study is the first of its kind, combining a quantitative analysis of phenomenological structures in time with a data-driven approach to the study of neural correlates of mental states. Future applications of temporal experience tracing are discussed, including the study of temporal dynamics of continuous states of consciousness and the integration of the experience dynamics with neural dynamics.