Document Type

Article

Publication Date

12-6-2018

Publication Title

Frontiers in Human Neuroscience

Volume

12

First page number:

1

Last page number:

11

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.

Keywords

Resting state; fMRI; Default mode network; Frontal-parietal network; Dorsal attention network; Stimulus-independent thought; Mind-wandering

Disciplines

Neuroscience and Neurobiology

File Format

PDF

File Size

567 Kb

Language

English

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

Download

UNLV article access

Search your library

Share

COinS