Cross-Brain Neurofeedback: Scientific Concept and Experimental Platform

Duan, Lian; Liu, Weijie; Dai, Rui-Na; Li, Rui; Lu, Chunming; Huang, Yuxia; Zhu, Chaozhe

doi:10.1371/journal.pone.0064590

Cited by 52 publications

(63 citation statements)

References 16 publications

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“…The interbrain synchronisation, which is often observed during social communications [31, 32, 38, 39], is also expected in the analysed spoken communication experiment; in the present context, it is embedded in the structure of the entire multi-brain network. Here, we perform a formal analysis of the multi-brain graph to describe the social impact on the brain activity of each participant.…”

Section: Resultssupporting

confidence: 61%

“…In this respect, the research of the social impact on the processes in the brain [27–29] as well as the brain processes that underly an effective social behaviour [30–38] is becoming a subject of increasing interest. New approaches using simultaneous scanning of groups of participants are being developed to study social cognition [39, 40]. The studies of face-to-face communications in dyads reveal a significant degree of synchronisation in particular brain areas, depending on the performed task [34–36, 38].…”

Section: Introductionmentioning

confidence: 99%

“…The EEG signals were recorded simultaneously at all listeners during the session, while the recording was performed independently for each speaker during his/her narration, see Methods. Note also that, in contrast to the platforms build on the face-to-face communications [39], in this experimental set-up the interaction is unidirectional from speakers to listeners. The self-rated experiences of the listeners collected after each completed session, indicate wide variations of the listener’s concentration to the story, correlating to the previous knowledge, interest, as well as the speaker’s attractiveness and narrative quality.…”

Section: Introductionmentioning

confidence: 99%

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Algebraic Topology of Multi-Brain Connectivity Networks Reveals Dissimilarity in Functional Patterns during Spoken Communications

et al. 2016

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Human behaviour in various circumstances mirrors the corresponding brain connectivity patterns, which are suitably represented by functional brain networks. While the objective analysis of these networks by graph theory tools deepened our understanding of brain functions, the multi-brain structures and connections underlying human social behaviour remain largely unexplored. In this study, we analyse the aggregate graph that maps coordination of EEG signals previously recorded during spoken communications in two groups of six listeners and two speakers. Applying an innovative approach based on the algebraic topology of graphs, we analyse higher-order topological complexes consisting of mutually interwoven cliques of a high order to which the identified functional connections organise. Our results reveal that the topological quantifiers provide new suitable measures for differences in the brain activity patterns and inter-brain synchronisation between speakers and listeners. Moreover, the higher topological complexity correlates with the listener’s concentration to the story, confirmed by self-rating, and closeness to the speaker’s brain activity pattern, which is measured by network-to-network distance. The connectivity structures of the frontal and parietal lobe consistently constitute distinct clusters, which extend across the listener’s group. Formally, the topology quantifiers of the multi-brain communities exceed the sum of those of the participating individuals and also reflect the listener’s rated attributes of the speaker and the narrated subject. In the broader context, the presented study exposes the relevance of higher topological structures (besides standard graph measures) for characterising functional brain networks under different stimuli.

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Section: Resultssupporting

confidence: 61%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Algebraic Topology of Multi-Brain Connectivity Networks Reveals Dissimilarity in Functional Patterns during Spoken Communications

et al. 2016

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“…We adopted the hyperscanning technique to access correlated neural activity across two brains [Montague et al, 2002]. Hyperscanning has mainly been used with fMRI or EEG recording to studying multiagent games and social interactions [Babiloni and Astolfi, 2014;Duan et al, 2013;Dumas et al, 2010;Fliessbach et al, 2007;King-Casas et al, 2005;Koike et al, 2015;Scholkmann et al, 2013b]. It should be noted that fMRI or EEG studies using hyperscanning technique require calibration to account for different sensitivities of the devices.…”

Section: Introductionmentioning

confidence: 99%

Synchronous brain activity during cooperative exchange depends on gender of partner: A fNIRS‐based hyperscanning study

Cheng

2015

Human Brain Mapping

210

189

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Previous studies have shown that brain activity between partners is synchronized during cooperative exchange. Whether this neural synchronization depends on the gender of partner (i.e., opposite or same to the participant) is open to be explored. In current study, we used functional near-infrared spectroscopy (fNIRS) based hyperscanning to study cooperation in a two-person game (female-female, female-male, and male-male) while assaying brain-to-brain interactions. Cooperation was greater in male-male pairs than in female-female pairs, with intermediate cooperation levels for female-male pairs. More importantly, in dyads with partners with opposite gender (female-male pairs), we found significant task-related cross-brain coherence in frontal regions (i.e., frontopolar cortex, orbitofrontal cortex, and left dorsolateral prefrontal cortex) whereas the cooperation in same gender dyads (female-female pairs and male-male pairs) was not associated with such synchronization. Moreover, the changes of such interbrain coherence across task blocks were significantly correlated with change in degree of cooperation only in mixed-sex dyads. These findings suggested that different neural processes underlie cooperation between mixed-sex and same-sex dyadic interactions.

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“…Social neurology uses the term social brain to distinguish the brain functions underlying the social conduct of humans [7,8]. Platforms for simultaneous recording of brain functions in pairs or groups of individuals are being developed generating the appropriate data that allow study of the social brain structure in various situations [5,[9][10][11][12]. Potentials of these experimental and theoretical approaches still remain elusive.…”

Section: Introductionmentioning

confidence: 99%

Origin of Hyperbolicity in Brain-to-Brain Coordination Networks

Tadić¹,

Andjelković²,

Šuvakov³

2018

Front. Phys.

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Hyperbolicity or negative curvature of complex networks is the intrinsic geometric proximity of nodes in the graph metric space, which implies an improved network function. Here, we investigate hidden combinatorial geometries in brain-to-brain coordination networks arising through social communications. The networks originate from correlations among EEG signals previously recorded during spoken communications comprising of 14 individuals with 24 speaker-listener pairs. We find that the corresponding networks are δ-hyperbolic with δ max = 1 and the graph diameter D = 3 in each brain. While the emergent hyperbolicity in the two-brain networks varies satisfying δ max /D/2 ≤ 1 and can be attributed to the topology of the subgraph formed around the cross-brains linking channels. We identify these subgraphs in each studied two-brain network and decompose their structure into simple geometric descriptors (triangles, tetrahedra and cliques of higher orders) that contribute to hyperbolicity. Considering topologies that exceed two separate brain networks as a measure of coordination synergy between the brains, we identify different neural correlation patterns ranging from weak coordination to super-brain structure. These topology features are in qualitative agreement with the listener's self-reported ratings of own experience and quality of the speaker, suggesting that studies of the cross-brain connector networks can reveal new insight into the neural mechanisms underlying human social behavior.

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Cross-Brain Neurofeedback: Scientific Concept and Experimental Platform

Cited by 52 publications

References 16 publications

Algebraic Topology of Multi-Brain Connectivity Networks Reveals Dissimilarity in Functional Patterns during Spoken Communications

Algebraic Topology of Multi-Brain Connectivity Networks Reveals Dissimilarity in Functional Patterns during Spoken Communications

Synchronous brain activity during cooperative exchange depends on gender of partner: A fNIRS‐based hyperscanning study

Origin of Hyperbolicity in Brain-to-Brain Coordination Networks

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