Optical mapping of brain activation during the English to Chinese and Chinese to English sight translation

Word Structure Tunes Electrophysiological and Hemodynamic Responses in the Frontal Cortex

To date, it is still unclear how word structure might impact lexical processing in the brain for languages with an impoverished system of grammatical morphology such as Chinese. In this study, concurrent electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) recordings were performed to inspect the temporal and spatial brain activities that are related to Chinese word structure (compound vs. derivation vs. non-morphological) effects. A masked priming paradigm was utilized on three lexical conditions (compound constitute priming, derivation constitute priming, and non-morphological priming) to tap Chinese native speakers' structural sensitivity to differing word structures. The compound vs. derivation structure effect was revealed by the behavioral data as well as the temporal and spatial brain activation patterns. In the masked priming task, Chinese derivations exhibited significantly enhanced brain activation in the frontal cortex and involved broader brain networks as compared with lexicalized compounds. The results were interpreted by the differing connection patterns between constitute morphemes within a given word structure from a spreading activation perspective. More importantly, we demonstrated that the Chinese word structure effect showed a distinct brain activation pattern from that of the dual-route mechanism in alphabetic languages. Therefore, this work paved a new avenue for comprehensively understanding the underlying cognitive neural mechanisms associated with Chinese derivations and coordinate compounds.

Task-Modulated Oscillation Differences in Auditory and Spoken Chinese-English Bilingual Processing: An Electroencephalography Study

Neurophysiological research on the bilingual activity of interpretation or interpreting has been very fruitful in understanding the bilingual brain and has gained increasing popularity recently. Issues like word interpreting and the directionality of interpreting have been attended to by many researchers, mainly with localizing techniques. Brain structures such as the dorsolateral prefrontal cortex have been repeatedly identified during interpreting. However, little is known about the oscillation and synchronization features of interpreting, especially sentence-level overt interpreting. In this study we implemented a Chinese-English sentence-level overt interpreting experiment with electroencephalography on 43 Chinese-English bilinguals and compared the oscillation and synchronization features of interpreting with those of listening, speaking and shadowing. We found significant time-frequency power differences in the delta-theta (1–7 Hz) and gamma band (above 30 Hz) between motor and silent tasks. Further theta-gamma coupling analysis revealed different synchronization networks in between speaking, shadowing and interpreting, indicating an idea-formulation dependent mechanism. Moreover, interpreting incurred robust right frontotemporal gamma coactivation network compared with speaking and shadowing, which we think may reflect the language conversion process inherent in interpreting.

Functional Connectivity Signatures Underlying Simultaneous Language Translation in Interpreters and Non-Interpreters of Mandarin and English: An fNIRS Study

Recent neuroimaging research has suggested that interpreters and non-interpreters elicit different brain activation patterns during simultaneous language translation. However, whether these two groups have different functional connectivity during such a task, and how the neural coupling is among brain subregions, are still not well understood. In this study, we recruited Mandarin (L1)/English (L2) interpreters and non-interpreter bilinguals, whom we asked to perform simultaneous language translation and reading tasks. Functional near-infrared spectroscopy (fNIRS) was used to collect cortical brain data for participants during each task, using 68 channels that covered the prefrontal cortex and the bilateral perisylvian regions. Our findings revealed both interpreter and non-interpreter groups recruited the right dorsolateral prefrontal hub when completing the simultaneous language translation tasks. We also found different functional connectivity between the groups. The interpreter group was characterized by information exchange between the frontal cortex and Wernicke’s area. In comparison, the non-interpreter group revealed neural coupling between the frontal cortex and Broca’s area. These findings indicate expertise modulates functional connectivity, possibly because of more developed cognitive skills associated with executive functions in interpreters.

Optical Mapping of Brain Activity Underlying Directionality and Its Modulation by Expertise in Mandarin/English Interpreting

Recent neuroimaging research has suggested that unequal cognitive efforts exist between interpreting from language 1 (L1) to language 2 (L2) compared with interpreting from L2 to L1. However, the neural substrates that underlie this directionality effect are not yet well understood. Whether directionality is modulated by interpreting expertise also remains unknown. In this study, we recruited two groups of Mandarin (L1)/English (L2) bilingual speakers with varying levels of interpreting expertise and asked them to perform interpreting and reading tasks. Functional near-infrared spectroscopy (fNIRS) was used to collect cortical brain data for participants during each task, using 68 channels that covered the prefrontal cortex and the bilateral perisylvian regions. The interpreting-related neuroimaging data was normalized by using both L1 and L2 reading tasks, to control the function of reading and vocalization respectively. Our findings revealed the directionality effect in both groups, with forward interpreting (from L1 to L2) produced more pronounced brain activity, when normalized for reading. We also found that directionality was modulated by interpreting expertise in both normalizations. For the group with relatively high expertise, the activated brain regions included the right Broca's area and the left premotor and supplementary motor cortex; whereas for the group with relatively low expertise, the activated brain areas covered the superior temporal gyrus, the dorsolateral prefrontal cortex (DLPFC), the Broca's area, and visual area 3 in the right hemisphere. These findings indicated that interpreting expertise modulated brain activation, possibly because of more developed cognitive skills associated with executive functions in experienced interpreters.

Functional near-infrared spectroscopy can detect low-frequency hemodynamic oscillations in the prefrontal cortex during steady-state visual evoked potential-inducing periodic facial expression stimuli presentation

Brain oscillations are vital to cognitive functions, while disrupted oscillatory activity is linked to various brain disorders. Although high-frequency neural oscillations (> 1 Hz) have been extensively studied in cognition, the neural mechanisms underlying low-frequency hemodynamic oscillations (LFHO) < 1 Hz have not yet been fully explored. One way to examine oscillatory neural dynamics is to use a facial expression (FE) paradigm to induce steady-state visual evoked potentials (SSVEPs), which has been used in electroencephalography studies of high-frequency brain oscillation activity. In this study, LFHO during SSVEP-inducing periodic flickering stimuli presentation were inspected using functional near-infrared spectroscopy (fNIRS), in which hemodynamic responses in the prefrontal cortex were recorded while participants were passively viewing dynamic FEs flickering at 0.2 Hz. The fast Fourier analysis results demonstrated that the power exhibited monochronic peaks at 0.2 Hz across all channels, indicating that the periodic events successfully elicited LFHO in the prefrontal cortex. More importantly, measurement of LFHO can effectively distinguish the brain activation difference between different cognitive conditions, with happy FE presentation showing greater LFHO power than neutral FE presentation. These results demonstrate that stimuli flashing at a given frequency can induce LFHO in the prefrontal cortex, which provides new insights into the cognitive mechanisms involved in slow oscillation.

Causal Cortical Network for Arithmetic Problem-Solving Represents Brain's Planning Rather than Reasoning

Arithmetic problem-solving whose components mainly involve the calculation, planning and reasoning, is an important mathematical skill. To date, the neural mechanism underlying arithmetic problem-solving remains unclear. In this study, a scheme that combined a novel 24 points game paradigm, conditional Granger causality analysis, and near-infrared spectroscopy (fNIRS) neuroimaging technique was developed to examine the differences in brain activation and effective connectivity between the calculation, planning, and reasoning. We discovered that the performance of planning was correlated with the activation in frontal cortex, whereas the performance of reasoning showed the relationship with the activation in parietal cortex. In addition, we also discovered that the directional effective connectivity between the anterior frontal and posterior parietal cortex was more closely related to planning rather than reasoning. It is expected that this work will pave a new avenue for an improved understanding of the neural underpinnings underlying arithmetic problem-solving, which also provides a novel indicator to evaluate the efficacy of mathematical education.

Linking brain activation to topological organization in the frontal lobe as a synergistic indicator to characterize the difference between various cognitive processes of executive functions

Executive functions (EFs) associated with the frontal lobe are vital for goal-orientated behavior. To date, limited efforts have been made to examine the relationships among the behavior, brain activation, and topological organization of functional networks in the frontal lobe underlying various EF tasks, including inhibition, working memory, and cognitive flexibility. In this study, functional near-infrared spectroscopy neuroimaging technique was used to systematically inspect the differences in the brain activation and the topological organization of brain networks between various EF tasks in the frontal lobe. In addition, the relationships between brain activation/network properties and task performances and the relationships between brain activation and network properties were, respectively, examined for different EF tasks. Consequently, we have discovered that the nodal and global properties of the resting-state and task-evoked networks, respectively, exhibited significant correlations with the activation of various brain regions during various EF tasks. In particular, the measure that links the neural activation to the topological organization of the brain networks in the frontal lobe can serve as a synergistic indicator to examine the difference between various EF tasks, which paves a way toward a comprehensive understanding of the neural mechanism underlying EFs.

A novel phase analysis method for examining fNIRS neuroimaging data associated with Chinese/English sight translation

In this study, a phase method for analyzing functional near-infrared spectroscopy (fNIRS) signals was developed, which can extract the phase information of fNIRS data by using Hilbert transform. More importantly, the phase analysis method can be further performed to generate the brain phase activation and to construct the brain networks. Meanwhile, the study of translation between Chinese and English has been exciting and interesting from both the language and neuroscience standpoints due to their drastically different linguistic features. In particular, inspecting the brain phase activation and functional connectivity based on the phase data and phase analysis method will enable us to better understand the neural mechanism associated with Chinese/English translation. Our phase analysis results showed that the left prefrontal cortex, including the dorsolateral prefrontal cortex (DLPFC) and frontopolar area, was involved in the translation process of the language pair. In addition, we also discovered that the most significant brain phase activation difference between translating into non-native (English) vs. native (Chinese) language was identified in the Broca's area. As a result, the proposed phase analysis approach can provide us an additional tool to reveal the complex cognitive mechanism associated with Chinese/English sight translation.

Neuroticism and conscientiousness respectively positively and negatively correlated with the network characteristic path length in dorsal lateral prefrontal cortex: A resting-state fNIRS study

BACKGROUND

Accumulating evidence shows that the dorsal lateral prefrontal cortex (dlPFC) is implicated in personality traits. In this study, resting-state functional near infrared spectroscopy (fNIRS) combined with small-world analysis was utilized to examine the relationship between the network properties of dlPFC and personality traits.

METHODS

Thirty college students (aged between 20 and 29) were recruited from the University of Macau campus, whose personality scores were accessed with the NEO-FFT questionnaire. Graph theory combined with resting-state fNIRS data was used to quantify the network properties of dlPFC, whereas Pearson correlation analysis was performed to generate the relationship between the small-world indicators and personality scores.

RESULTS

Compared to matched random networks, the resting-state brain networks exhibited a larger clustering coefficient (C_p , 0.1-0.66), shorter characteristic path length (L_p , 0.1-0.66), and higher global (E_g , 0.1-0.66) and local efficiency (E_loc , 0.1-0.65). In particular, conscientiousness (r = -0.63) and neuroticism (r = 0.40) respectively showed negative and positive correlation with the L_p .

CONCLUSIONS

The resting-state functional brain networks in dlPFC exhibited the small-world properties. In addition, participants with higher conscientiousness scores showed a shorter L_p .

Concurrent mapping of brain activation from multiple subjects during social interaction by hyperscanning: a mini-review

Social interaction plays an essential role in acquiring knowledge and developing our own personalities in our daily life. Meanwhile, functional magnetic resonance imaging (fMRI)-, electroencephalograph (EEG)-, and functional near inferred spectroscopy (fNIRS)-hyperscanning, enables us to concurrently map brain activation from two or more participants who are engaged in social interaction simultaneously. In this review, we first highlight the recent technologies advances and the most significant findings towards social interaction by using the hyperscanning method. In addition, we also illustrate several well-designed hyperscanning tasks that have been extensively adopted for the study of social interaction. Basically, hyperscanning contains six categories of experimental paradigms that can track the interactive neural process of interest. Furthermore, it contains two main elucidated neural systems which are involved in social interaction, including the mirror neuron system (MNS) and mentalizing system (MS). Finally, future research directions and clinical implications that are associated with hyperscanning are also highlighted and discussed.

Optical mapping of prefrontal brain connectivity and activation during emotion anticipation

Accumulated neuroimaging evidence shows that the dorsal lateral prefrontal cortex (dlPFC) is activated during emotion anticipation. The aim of this work is to examine the brain connectivity and activation differences in dlPFC between the positive, neutral and negative emotion anticipation by using functional near-infrared spectroscopy (fNIRS). The hemodynamic responses were first assessed for all subjects during the performance of various emotion anticipation tasks. And then small-world analysis was performed, in which the small-world network indicators including the clustering coefficient, average path length, average node degree, and measure of small-world index were calculated for the functional brain networks associated with the positive, neutral and negative emotion anticipation, respectively. We discovered that compared to negative and neutral emotion anticipation, the positive one exhibited enhanced brain activation in the left dlPFC. Although the functional brain networks for the three emotion anticipation cases manifested the small-world properties regarding the clustering coefficient, average path length, average node degree, and measure of small-world index, the positive one showed significantly higher clustering coefficient and shorter average path length than those from the neutral and negative cases. Consequently, the small-world network indicators and brain activation in dlPPC were able to distinguish well between the positive, neutral and negative emotion anticipation.