Spontaneous cognitive processes and the behavioral validation of time-varying brain connectivity

• Authors: Aaron Kucyi, Stanford University; Arielle Tambini, University of California Berkeley; Sepideh Sadaghiani, University of Illinois; Shella Keilholz, Emory University; Jessica R. Cohen, University of North Carolina
• Journal Title: NETWORK NEUROSCIENCE
• Volume: Volume 2, Number 4
• Publisher: MIT PRESS | 2018-01-01, Pages 397-417
• Type of Work: Article | Final Publisher PDF
• Publisher DOI: http://doi.org/10.1162/netn_a_00037
• Subjects: Biology, Neuroscience; Health Sciences, Radiology
• Keywords: Science & Technology; Life Sciences & Biomedicine; Neurosciences; Neurosciences & Neurology; Dynamic functional connectivity; Default mode network; Resting state; Spontaneous cognition; Mind wandering; Arousal; DYNAMIC FUNCTIONAL CONNECTIVITY; RESTING-STATE FMRI; DEFAULT MODE NETWORK; ONGOING ACTIVITY FLUCTUATIONS; SLOW EEG FLUCTUATIONS; VISUAL-CORTEX; LONG-TERM; MEMORY CONSOLIDATION; SPONTANEOUS THOUGHT; AWAKE REACTIVATION

Abstract

In cognitive neuroscience, focus is commonly placed on associating brain function with changes in objectively measured external stimuli or with actively generated cognitive processes. In everyday life, however, many forms of cognitive processes are initiated spontaneously, without an individual’s active effort and without explicit manipulation of behavioral state. Recently, there has been increased emphasis, especially in functional neuroimaging research, on spontaneous correlated activity among spatially segregated brain regions (intrinsic functional connectivity) and, more specifically, on intraindividual fluctuations of such correlated activity on various time scales (time-varying functional connectivity). In this Perspective, we propose that certain subtypes of spontaneous cognitive processes are detectable in time-varying functional connectivity measurements. We define these subtypes of spontaneous cognitive processes and review evidence of their representations in time-varying functional connectivity from studies of attentional fluctuations, memory reactivation, and effects of baseline states on subsequent perception. Moreover, we describe how these studies are critical to validating the use of neuroimaging tools (e.g., fMRI) for assessing ongoing brain network dynamics. We conclude that continued investigation of the behavioral relevance of time-varying functional connectivity will be beneficial both in the development of comprehensive neural models of cognition, and in informing on best practices for studying brain network dynamics.