Investigating Multiple Streams of Consciousness: Using Descriptive Experience Sampling to Explore Internally and Externally Directed Streams of Thought.

Charles Fernyhough,Ben Alderson-Day,Russell T Hurlburt,Simone Kühn

doi:10.3389/fnhum.2018.00494

Abstract

Research into resting-state cognition has often struggled with the challenge of assessing inner experience in the resting state. We employed Descriptive Experience Sampling (DES), a method aimed at generating detailed and high-fidelity descriptions of experience, to investigate how experience in the resting state can vary between internal, external, and multiple simultaneous streams. Using a large body of experiential and brain activation data acquired from five DES participants, independent raters classified sampled moments of experience according to whether they were internally directed, externally directed, or contained elements of both at the same time. In line with existing models, comparison of internal with external experience samples identified a network of regions associated with the default mode network. Regions of interest resulting from the whole-brain contrasts successfully predicted independent raters’ forced-choice categorizations of samples for which experience had a simultaneous internal and external focus. The present study is distinctive in tying neural activations in the resting state to detailed descriptions of specific phenomenology, and in demonstrating how the DES method enables a particularly nuanced analysis of moments of experience, especially their ability simultaneously to incorporate both an internal and an external focus. The study represents an integration of rich phenomenology and characterizations of brain activity, tracing interpretive paths from phenomenology to neural activation and vice versa.

Highlights

There has been a significant growth of interest in studying the brain when participants are not engaged in any particular task
In order to predict these composite scores, we applied k-means clustering to the subject-demeaned percent signal changes extracted from each of the four region of interest (ROI) identified in our original whole-brain analysis
The model was significant, F(1, 4.54) = 8.656, p = 0.036, indicating that the ROIs derived from those samples where internality/externality could be identified with confidence were useful in using fMRI data to predict a continuous internality/externality rating in those other samples where our raters were less confident in their internality/externality classification

Summary

Introduction

There has been a significant growth of interest in studying the brain when participants are not engaged in any particular task (so-called resting-state measurements). The consistency with which activity in these brain regions decreases during tasks and increases during rest has led to the notion of a so-called “default mode” network (DMN) of the brain (Buckner et al, 2008). This growth of interest in the brain’s resting-state networks has been paralleled by an increase of interest in cognitive processes that are not stimulated by any particular external stimuli, commonly referred to as mind-wandering (Callard et al, 2013). Efforts to link such “stimulus-independent” cognitions to their underlying neural states have been hampered by the difficulty of capturing descriptions of ongoing cognitive states in sufficient fidelity, richness, and detail

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