Poster No:
1347
Submission Type:
Abstract Submission
Authors:
Duho Sihn1, Sung-Phil Kim1
Institutions:
1Ulsan National Institute of Science and Technology, Ulsan, Ulsan
First Author:
Duho Sihn
Ulsan National Institute of Science and Technology
Ulsan, Ulsan
Co-Author:
Sung-Phil Kim
Ulsan National Institute of Science and Technology
Ulsan, Ulsan
Introduction:
Behavioral regulation depends on brain functions that are distributed across different regions of the brain (Kaplan and Zimmer, 2020; Westlin et al., 2023). To achieve this distributed function, behavioral information must be transmitted efficiently throughout the brain. One mechanism underlying this process is the propagation of brain oscillations, also known as traveling waves. The strength of brain oscillations is often quantified by the oscillatory amplitude, which has been shown to affect behavioral information processing (Samaha et al., 2020). The oscillation propagation is also related to behavioral information transmission (Alamia et al., 2023), suggesting a possible interconnection between the oscillatory amplitude, oscillation propagation, and behavioral information transmission. However, this relationship remains insufficiently explored, particularly in humans.
Previous research has shown a correlation between a strength of oscillation propagation, defined by the spatial or temporal consistency of propagation directionality, and the oscillatory amplitude in several contexts, including non-human primate local field potentials (Denker et al., 2018), human electrocorticography (Das et al., 2022), and human electroencephalography (EEG) (Sihn and Kim, 2024). Despite these findings, how this relationship influences behavioral performance has yet to be clearly elucidated.
Methods:
To address this question, we analyzed a publicly available dataset (N = 17) (Cavanagh and Castellanos, 2021) comprising 63-channel scalp EEG recordings taken during video game play (Cavanagh and Castellanos, 2016). EEG signals were separated into four frequency bands: delta (1-3 Hz), theta (4-7 Hz), alpha (8-12 Hz), and beta (15-25 Hz). Oscillation propagation was quantified using the local phase gradient method, developed in our previous work (Sihn and Kim, 2024). We introduced two hypothetical oscillatory states based on oscillatory amplitude: high and low amplitude states. Brain-wide patterns of these oscillatory states, called brain-wide coactivity patterns in this study defined as a spatial distribution of two hypothetical oscillatory states, were calculated by the k-means clustering algorithm.
Results:
The oscillatory states reflected the strength of oscillation propagation, i.e., the temporal consistency of oscillation propagation directionality, such that the higher-amplitude state exhibited stronger temporal consistency. We found that both oscillatory states and oscillation propagation were associated with the likelihood of behavioral occurrence. The correlation between the oscillation amplitude and the oscillation propagation strength observed at the level of each EEG channel was replicated at the level of brain-wide coactivity patterns. Moreover, the likelihood of specific behavioral occurrence was significantly influenced by brain-wide coactivity patterns (the two-tailed Wilcoxon signed rank test, false-discovery-rate-corrected p < 0.05).
Conclusions:
Our results provide evidence for a two-state oscillatory model of behavioral information processing. In the high amplitude state, behavioral information is propagated across the brain because of the consistently propagated oscillation propagation, while in the low amplitude state, it is integrated within brain region because of the diverse oscillation propagation directionality. The brain-wide coactivity patterns associated with these oscillatory states appear to impact behavioral performance. Our findings suggest two key attributes of the brain oscillations, amplitude and propagation, to support brain-wide distributed functions.
Higher Cognitive Functions:
Higher Cognitive Functions Other
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural) 2
EEG/MEG Modeling and Analysis 1
Motor Behavior:
Motor Behavior Other
Novel Imaging Acquisition Methods:
EEG
Keywords:
Cognition
Computational Neuroscience
Cortex
Data analysis
Electroencephaolography (EEG)
Other - Traveling wave
1|2Indicates the priority used for review
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Please indicate below if your study was a "resting state" or "task-activation” study.
Task-activation
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Healthy subjects
Was this research conducted in the United States?
No
Were any human subjects research approved by the relevant Institutional Review Board or ethics panel?
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Were any animal research approved by the relevant IACUC or other animal research panel?
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Please indicate which methods were used in your research:
EEG/ERP
Behavior
Provide references using APA citation style.
1. Kaplan, H.S., Zimmer, M. (2020). Brain-wide representations of ongoing behavior: a universal principle? Current Opinion in Neurobiology, 64, 60-69.
2. Westlin, C., Theriault, J.E., Katsumi, Y., Nieto-Castanon, A., Kucyi, A., Ruf, S.F. et al. (2023). Improving the study of brain-behavior relationships by revisiting basic assumptions. Trends on Cognitive Sciences, 27(3), 246-257.
3. Samaha, J., Iemi, L., Haegens, S., Busch, N.A. (2020). Spontaneous brain oscillations and perceptual decision-making. Trends in Cognitive Sciences, 24(8), 639-653.
4. Alamia, A., Terral, L., D'ambra, M.R., VanRullen, R. (2023). Distinct roles of forward and backward alpha-band waves in spatial visual attention. eLife, 12, e85035.
5. Denker, M., Zehl, L., Kilavik, B.E., Diesmann, M., Brochier, T., Riehle, A. et al. (2018). LFP beta amplitude is linked to mesoscopic spatio-temporal phase patterns. Scientific Reports, 8(1), 5200.
6. Das, A., Myers, J., Mathura, R., Shofty, B., Metzger, B.A., Bijanki, K. et al. (2022). Spontaneous neuronal oscillations in the human insula are hierarchically organized traveling waves. eLife, 11, e76702.
7. Sihn, D., Kim, S.-P. (2024). Disruption of alpha oscillation propagation in patients with schizophrenia. Clinical Neurophysiology, 162, 262-270.
8. Cavanagh, J.F., Castellanos, J. (2021). EEG: Continuous gameplay of an 8-bit style video game. OpenNeuro, [Dataset] (Available from: https://openneuro.org/datasets/ds003517/versions/1.1.0).
9. Cavanagh, J.F., Castellanos, J. (2016). Identification of canonical neural events during continuous gameplay of an 8-bit style video game. NeuroImage, 133, 1-13.
No