Individual differences in functional connectivity during naturalistic viewing conditions

Abstract

Naturalistic viewing paradigms such as movies have been shown to reduce participant head motion and improve arousal during fMRI scanning relative to task-free rest, and have been used to study both functional connectivity and stimulus-evoked BOLD-signal changes. These task-based hemodynamic changes are synchronized across subjects and involve large areas of the cortex, and it is unclear whether individual differences in functional connectivity are enhanced or diminished under such naturalistic conditions. This work first aims to characterize variability in BOLD-signal based functional connectivity (FC) across 2 distinct movie conditions and eyes-open rest (n=31 healthy adults, 2 scan sessions each). We found that movies have higher within- and between-subject correlations in cluster-wise FC relative to rest. The anatomical distribution of inter-individual variability was similar across conditions, with higher variability occurring at the lateral prefrontal lobes and temporoparietal junctions. Second, we used an unsupervised test-retest matching algorithm that identifies individual subjects from within a group based on FC patterns, quantifying the accuracy of the algorithm across the three conditions. The movies and resting state all enabled identification of individual subjects based on FC matrices, with accuracies between 61% and 100%. Overall, pairings involving movies outperformed rest, and the social, faster-paced movie attained 100% accuracy. When the parcellation resolution, scan duration, and number of edges used were increased, accuracies improved across conditions, and the pattern of movies>rest was preserved. These results suggest that using dynamic stimuli such as movies enhances the detection of FC patterns that are unique at the individual level.

Delineating the Macroscale Areal Organization of the Macaque Cortex In Vivo

“…Within the same condition (awake-awake, anesthesia-anesthesia), the within-individual spatial correlations of gradient and edge density maps are explicitly higher than between-individual correlations. Consistent with prior work in humans (Miranda-Domínguez et al, 2014; Finn et al, 2015; O’Connor et al, 2017; Vanderwal et al, 2017), the functional brain organization is similar across different awake conditions (i.e., movie and rest), though some decrements in similarities for FC, gradients, and edge maps were noted. Importantly, the ability to identify individuals using data collected with anesthesia was notably decreased when attempting to match the same subject across the awake and anesthetized states.…”

“…Over the past decade, numerous studies have demonstrated the ability to extract highly similar intrinsic FC networks, regardless of whether imaging is carried out during an active task state or rest (Cole et al, 2014; Fair et al, 2007; Vanderwal et al, 2017). Recent work has increasingly highlighted the potential value of using non-rest states, particularly naturalistic viewing, for assessing FC, as head motion appears to be lower and tolerability higher.…”

“…Recent work has increasingly highlighted the potential value of using non-rest states, particularly naturalistic viewing, for assessing FC, as head motion appears to be lower and tolerability higher. While systematic differences in connectivity patterns are undoubtedly present across states, as revealed by within-subject comparisons, differences in connectivity patterns across individuals can be similar, at least for static FC patterns (Finn et al, 2015; O’Connor et al., 2017; Vanderwal et al, 2017; Wang et al, 2017). Given the various behavioral demands of awake imaging for NHP, we have found that naturalistic viewing conditions can be particularly valuable, at least for full-brain parcellations.…”

Are Measures of Transfer Effects Missing the Target?

“…Already, studies have shown that analyzing brain activity during the full length of watching a movie allows for a more accurate prediction of academic performance (Valkanova et al 2014;Cantlon and Li 2013) as well as increased accuracy in detecting individual patterns of functional connectivity (Vanderwal et al 2017) compared to measuring brain activity during rest or an experimental task. Artificial intelligence, facial expression and eye tracking, portable head scans, virtual reality, and filming behavior are just examples of methods that will allow studying and analyzing participants in more naturalistic settings, minimizing confounding factors and enabling a richer signal.…”

Stability and similarity of the pediatric connectome as developmental measures

“…Matching algorithms can be run using data collected under a variety of acquisition states, most commonly resting state and conventional task conditions. In 2017, Vanderwal et al showed that using movies as an acquisition state for FC measures yielded matching accuracies up to 100% in a small sample of adults (Vanderwal et al, 2017). Movies were shown to preserve and possibly enhance the identification of individually distinct patterns of FC in a sample of healthy adults when compared to task-free rest.…”