Long-range functional coupling predicts performance: Oscillatory EEG networks in multisensory processing

AbstractThe integration of sensory signals from different modalities requires flexible interaction of remote brain areas. One candidate mechanism to establish communication in the brain is transient synchronization of oscillatory neural signals. Although there is abundant evidence for the involvement of cortical oscillations in brain functions based on the analysis of local power, assessment of the phase dynamics among spatially distributed neuronal populations and their relevance for behavior is still sparse. In the present study, we investigated the interaction between remote brain areas by analyzing high-density electroencephalogram (EEG) data obtained from human participants engaged in a visuotactile pattern matching task. We deployed an approach for purely data-driven clustering of neuronal phase coupling in source space, which allowed imaging of large-scale functional networks in space, time and frequency without defining a priori constraints. Based on the phase coupling results, we further explored how brain areas interacted across frequencies by computing phase-amplitude coupling. Several networks of interacting sources were identified with our approach, synchronizing their activity within and across the theta (~5 Hz), alpha (~10 Hz), and beta (~ 20 Hz) frequency bands and involving multiple brain areas that have previously been associated with attention and motor control. We demonstrate the functional relevance of these networks by showing that phase delays – in contrast to spectral power – were predictive of task performance. The data-driven analysis approach employed in the current study allowed an unbiased examination of functional brain networks based on EEG source level connectivity data. Showcased for multisensory processing, our results provide evidence that large-scale neuronal coupling is vital to long-range communication in the human brain and relevant for the behavioral outcome in a cognitive task.

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Using Mutant Cycle Analysis to Elucidate Long-Range Functional Coupling in Allosteric Receptors

Methods in Molecular Biology - Allostery ◽

10.1007/978-1-61779-334-9_6 ◽

2011 ◽

pp. 97-113 ◽

Cited By ~ 3

Author(s):

Jai A. P. Shanata ◽

Shawnalea J. Frazier ◽

Henry A. Lester ◽

Dennis A. Dougherty

Keyword(s):

Long Range ◽

Functional Coupling

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Oscillatory EEG Signatures of Affective Processes during Interaction with Adaptive Computer Systems

Brain Sciences ◽

10.3390/brainsci11010035 ◽

2020 ◽

Vol 11 (1) ◽

pp. 35

Author(s):

Mathias Vukelić ◽

Katharina Lingelbach ◽

Kathrin Pollmann ◽

Matthias Peissner

Keyword(s):

Functional Connectivity ◽

Adaptive Systems ◽

Goal Achievement ◽

Basic Knowledge ◽

Functional Coupling ◽

System Behavior ◽

Affective Processes ◽

Oscillatory Eeg ◽

Novel Strategy ◽

Cortical System

Affect monitoring is being discussed as a novel strategy to make adaptive systems more user-oriented. Basic knowledge about oscillatory processes and functional connectivity underlying affect during naturalistic human–computer interactions (HCI) is, however, scarce. This study assessed local oscillatory power entrainment and distributed functional connectivity in a close-to-naturalistic HCI-paradigm. Sixteen participants interacted with a simulated assistance system which deliberately evoked positive (supporting goal-achievement) and negative (impeding goal-achievement) affective reactions. Electroencephalography (EEG) was used to examine the reactivity of the cortical system during the interaction by studying both event-related (de-)synchronization (ERD/ERS) and event-related functional coupling of cortical networks towards system-initiated assistance. Significantly higher α-band and β-band ERD in centro-parietal and parieto-occipital regions and β-band ERD in bi-lateral fronto-central regions were observed during impeding system behavior. Supportive system behavior activated significantly higher γ-band ERS in bi-hemispheric parietal-occipital regions. This was accompanied by functional coupling of remote β-band and γ-band activity in the medial frontal, left fronto-central and parietal regions, respectively. Our findings identify oscillatory signatures of positive and negative affective processes as reactions to system-initiated assistance. The findings contribute to the development of EEG-based neuroadaptive assistance loops by suggesting a non-obtrusive method for monitoring affect in HCI.

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Dynamic changes in large-scale functional connectivity predict performance in a multisensory task

10.1101/579938 ◽

2019 ◽

Author(s):

Karl J. Hollensteiner ◽

Edgar Galindo-Leon ◽

Florian Pieper ◽

Gerhard Engler ◽

Guido Nolte ◽

...

Keyword(s):

Functional Connectivity ◽

Long Range ◽

Large Scale ◽

Principal Component ◽

Stimulus Onset ◽

Functional Coupling ◽

Phase Coupling ◽

Network State ◽

Task Period ◽

Response Onset

AbstractComplex and variable behavior requires fast changes of functional connectivity in large-scale cortical networks. Here, we report on the cortical dynamics of functional coupling across visual, auditory and parietal areas during a lateralized detection task in the ferret. We hypothesized that fluctuations in coupling, indicative of dynamic variations in the network state, might predict the animals’ performance. While power for hit and miss trials showed significant differences only around stimulus and response onset, phase coupling already differed before stimulus onset. Principal component analysis of directed coupling at the single-trial level during this period revealed subnetworks that most strongly related to behavior. While higher global phase coupling of visual and auditory regions to parietal cortex was predictive of task performance, a second component showed that a reduction in coupling between subnetworks of sensory modalities was also necessary, probably to allow a better detection of the unimodal signals. Furthermore, we observed that long-range coupling became more predominant during the task period compared to the pre-stimulus baseline. Taken together, these results suggest that fluctuations in the network state, particular with respect to long-range connectivity, are key determinants of the animals’ behavior.

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