Reliability of fMRI time series: Similarity of neural processing during movie viewing

Schmälzle, Ralf; Imhof, Martin A.; Grall, Clare; Flaisch, Tobias; Schupp, Harald T.

doi:10.1101/158188

Cited by 11 publications

(11 citation statements)

References 57 publications

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“…A3 ) are roughly similar to those previously reported ( O’Connor et al, 2017 ). Specifically, high reliability in the visual network has been reported ( Schmäalzle et al, 2017 ). An exception is that reliability in the visual network does not differ much in our data between the resting state and video task ( Fig.…”

Section: Discussionmentioning

confidence: 99%

“…There is also a growing interest in FC evaluated not just during rest but during task performance, and in particular during viewing of natural stimuli such as video ( Elliott et al, 2019 ; O’Connor et al, 2017 ; Schmälzle et al, 2017 ; Vanderwal et al, 2017 ). Therefore we here combine data from resting state as well as viewing of videos.…”

Section: Introductionmentioning

confidence: 99%

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Functional connectivity of EEG is subject-specific, associated with phenotype, and different from fMRI

Nentwich

Madsen

et al. 2020

NeuroImage

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A variety of psychiatric, behavioral and cognitive phenotypes have been linked to brain “functional connectivity” – the pattern of correlation observed between different brain regions. Most commonly assessed using functional magnetic resonance imaging (fMRI), here, we investigate the connectivity-phenotype associations with functional connectivity measured with electroencephalography (EEG), using phase-coupling. We analyzed data from the publicly available Healthy Brain Network Biobank. This database compiles a growing sample of children and adolescents, currently encompassing 1657 individuals. Among a variety of assessment instruments we focus on ten phenotypic and additional demographic measures that capture most of the variance in this sample. The largest effect sizes are found for age and sex for both fMRI and EEG. We replicate previous findings of an association of Intelligence Quotient (IQ) and Attention Deficit Hyperactivity Disorder (ADHD) with the pattern of fMRI functional connectivity. We also find an association with socioeconomic status, anxiety and the Child Behavior Checklist Score. For EEG we find a significant connectivity-phenotype relationship with IQ. The actual spatial patterns of functional connectivity are quite different between fMRI and source-space EEG. However, within EEG we observe clusters of functional connectivity that are consistent across frequency bands. Additionally we analyzed reproducibility of functional connectivity. We compare connectivity obtained with different tasks, including resting state, a video and a visual flicker task. For both EEG and fMRI the variation between tasks was smaller than the variability observed between subjects. We also found an increase of reliability with increasing frequency of the EEG, and increased sampling duration. We conclude that, while the patterns of functional connectivity are distinct between fMRI and phase-coupling of EEG, they are nonetheless similar in their robustness to the task, and similar in that idiosyncratic patterns of connectivity predict individual phenotypes.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Functional connectivity of EEG is subject-specific, associated with phenotype, and different from fMRI

Nentwich

Madsen

et al. 2020

NeuroImage

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“…Consistent with the existence of such a rule, large individual differences occur in the situated activity associated with health behaviors (e.g., Barsalou, 2019;Dutriaux et al, 2019;Taylor Browne Luka, Dutriaux, Hendry, Stevenson, & Barsalou, 2019;Werner et al, 2019). Large individual differences also occur in neural activity as people perceive complex everyday events associated with situated action (e.g., Huth, de Heer, Griffiths, Theunissen, & Gallant, 2016;Huth, Nishimoto, Vu, & Gallant, 2012;Schmälzle, Imhof, Grall, Flaisch, & Schupp, 2017).…”

Section: Individual Differences In Grounded Cognitionmentioning

confidence: 99%

Challenges and Opportunities for Grounding Cognition

Barsalou

2020

Journal of Cognition

126

106

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According to the grounded perspective, cognition emerges from the interaction of classic cognitive processes with the modalities, the body, and the environment. Rather than being an autonomous impenetrable module, cognition incorporates these other domains intrinsically into its operation. The Situated Action Cycle offers one way of understanding how the modalities, the body, and the environment become integrated to ground cognition. Seven challenges and opportunities are raised for this perspective: (1) How does cognition emerge from the Situated Action Cycle and in turn support it? (2) How can we move beyond simply equating embodiment with action, additionally establishing how embodiment arises in the autonomic, neuroendocrine, immune, cardiovascular, respiratory, digestive, and integumentary systems? (3) How can we better understand the mechanisms underlying multimodal simulation, its functions across the Situated Action Cycle, and its integration with other representational systems? (4) How can we develop and assess theoretical accounts of symbolic processing from the grounded perspective (perhaps using the construct of simulators)? (5) How can we move beyond the simplistic distinction between concrete and abstract concepts, instead addressing how concepts about the external and internal worlds pattern to support the Situated Action Cycle? (6) How do individual differences emerge from different populations of situational memories as the Situated Action Cycle manifests itself differently across individuals? (7) How can constructs from grounded cognition provide insight into the replication and generalization crises, perhaps from a quantum perspective on mechanisms (as exemplified by simulators).

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“…EEG and fMRI data presented here were averaged across subjects before assessing the reliability of the task-related re-sponses they contain. This form of 'grand-averaging' is well established to analyze evoked potentials in EEG and has recently also been used in fMRI (Schmaelzle et al, 2017). We did not average across subjects in ECoG due to inconsistent electrode montages in each of the five subjects.…”

Section: Cohort Size and Impact Of Grand-averagingmentioning

confidence: 99%

Reliability and correlation of fMRI, ECoG and EEG during natural stimulus processing

Haufe

DeGuzman²,

Henin

et al. 2017

Preprint

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Human brain mapping relies heavily on fMRI, ECoG and EEG, which capture different physiological signals. Relationships between these signals have been established in the context of specific tasks or during resting state, often using spatially confined concurrent recordings in animals. But it is not certain whether these correlations generalize to other contexts relevant for human cognitive neuroscience. Here, we address the case of complex naturalistic stimuli and ask two basic questions. First, how reliable are the responses evoked by a naturalistic audio-visual stimulus in each of these imaging methods, and second, how similar are stimulus-related responses across methods? To this end, we investigated a wide range of brain regions and frequency bands. We presented the same movie clip twice to three different cohorts of subjects (N EEG = 45, N fMRI = 11, N ECoG = 5) and assessed stimulus-driven correlations across viewings and between imaging methods, thereby ruling out task-irrelevant confounds. All three imaging methods had similar repeat-reliability across viewings when fMRI and EEG data were averaged across subjects, highlighting the potential to achieve large signal-to-noise ratio by leveraging large sample sizes. The fMRI signal correlated positively with high-frequency ECoG power across multiple task-related cortical structures but positively with low-frequency EEG and ECoG power. In contrast to previous studies, these correlations were as strong for low-frequency as for high frequency ECoG. We also observed links between fMRI and infra-slow EEG voltage fluctuations. These results extend previous findings to the case of natural stimulus processing.

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Reliability of fMRI time series: Similarity of neural processing during movie viewing

Cited by 11 publications

References 57 publications

Functional connectivity of EEG is subject-specific, associated with phenotype, and different from fMRI

Functional connectivity of EEG is subject-specific, associated with phenotype, and different from fMRI

Challenges and Opportunities for Grounding Cognition

Reliability and correlation of fMRI, ECoG and EEG during natural stimulus processing

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