Phase synchronization of delta and theta oscillations increase during the detection of relevant lexical information

Choice-dependent delta-band neural trajectory during semantic category decision making in the human brain

Recent human brain imaging studies have identified widely distributed cortical areas that represent information about the meaning of language. Yet, the dynamic nature of widespread neural activity as a correlate of the semantic information processing remains poorly explored. Our state space analysis of electroencephalograms (EEGs) recorded during semantic match-to-category task show that depending on the semantic category and decision path chosen by participants, whole-brain delta-band dynamics follow distinct trajectories that are correlated with participants' response time on a trial-by-trial basis. Especially, the proximity of the neural trajectory to category decision-specific region in the state space was predictive of participants' decision-making reaction times. We also found that posterolateral regions primarily encoded word categories while postero-central regions encoded category decisions. Our results demonstrate the role of neural dynamics embedded in the evolving multivariate delta-band activity patterns in processing the semantic relatedness of words and the semantic category-based decision-making.

Role of joint language control during cross-language communication: evidence from cross-frequency coupling

How do bilingual interlocutors inhibit interference from the non-target language to achieve brain-to-brain information exchange in a task to simulate a bilingual speaker-listener interaction. In the current study, two electroencephalogram devices were employed to record pairs of participants' performances in a joint language switching task. Twenty-eight (14 pairs) unbalanced Chinese-English bilinguals (L1 Chinese) were instructed to name pictures in the appropriate language according to the cue. The phase-amplitude coupling analysis was employed to reveal the large-scale brain network responsible for joint language control between interlocutors. We found that (1) speakers and listeners coordinately suppressed cross-language interference through cross-frequency coupling, as shown in the increased delta/theta phase-amplitude and delta/alpha phase-amplitude coupling when switching to L2 than switching to L1; (2) speakers and listeners were both able to simultaneously inhibit cross-person item-level interference which was demonstrated by stronger cross-frequency coupling in the cross person condition compared to the within person condition. These results indicate that current bilingual models (e.g., the inhibitory control model) should incorporate mechanisms that address inhibiting interference sourced in both language and person (i.e., cross-language and cross-person item-level interference) synchronously through joint language control in dynamic cross-language communication.

Natural brain-information interfaces: Recommending information by relevance inferred from human brain signals

Finding relevant information from large document collections such as the World Wide Web is a common task in our daily lives. Estimation of a user's interest or search intention is necessary to recommend and retrieve relevant information from these collections. We introduce a brain-information interface used for recommending information by relevance inferred directly from brain signals. In experiments, participants were asked to read Wikipedia documents about a selection of topics while their EEG was recorded. Based on the prediction of word relevance, the individual's search intent was modeled and successfully used for retrieving new relevant documents from the whole English Wikipedia corpus. The results show that the users' interests toward digital content can be modeled from the brain signals evoked by reading. The introduced brain-relevance paradigm enables the recommendation of information without any explicit user interaction and may be applied across diverse information-intensive applications.