Chunming Lu

Use of fNIRS to assess resting state functional connectivity

Recently, resting state functional connectivity (RSFC) studies based on fMRI and EEG/MEG have provided valuable insight into the intrinsic functional architecture of the human brain. However, whether functional near infrared spectroscopy (fNIRS), a suitable imaging method for infant and patient populations, can be used to examine RSFC remains elusive. Using an ETG-4000 Optical Topography System, the present study measured 29 adult subjects (14 females) over the sensorimotor and auditory cortexes during a resting session and a motor-localizer task session. The RSFC maps were computed by seed-based correlation analysis and data-driven cluster analysis. The results from both analyses showed robust RSFC maps, which were not only consistent with the localizer task-related activation results, but also those of previous fMRI findings. Moreover, the strong consistency between the seed-based correlation analysis and the data-driven cluster analysis further validated the use of fNIRS to assess RSFC. The potential influence of a specific low-frequency filtering range (0.04-0.15 Hz and 0.01-0.08 Hz) and three fNIRS parameters (oxy-Hb, deoxy-Hb, and total-Hb) on RSFC results were also examined.

Neural Synchronization during Face-to-Face Communication

Although the human brain may have evolutionarily adapted to face-to-face communication, other modes of communication, e.g., telephone and e-mail, increasingly dominate our modern daily life. This study examined the neural difference between face-to-face communication and other types of communication by simultaneously measuring two brains using a hyperscanning approach. The results showed a significant increase in the neural synchronization in the left inferior frontal cortex during a face-to-face dialog between partners but none during a back-to-back dialog, a face-to-face monologue, or a back-to-back monologue. Moreover, the neural synchronization between partners during the face-to-face dialog resulted primarily from the direct interactions between the partners, including multimodal sensory information integration and turn-taking behavior. The communicating behavior during the face-to-face dialog could be predicted accurately based on the neural synchronization level. These results suggest that face-to-face communication, particularly dialog, has special neural features that other types of communication do not have and that the neural synchronization between partners may underlie successful face-to-face communication.

Altered effective connectivity and anomalous anatomy in the basal ganglia-thalamocortical circuit of stuttering speakers

Combining structural equation modeling (SEM) and voxel-based morphometry (VBM), this study investigated the interactions among neural structures in the basal ganglia-thalamocortical circuit (BGTC) in the left hemisphere of stuttering and non-stuttering speakers. Stuttering speakers (n=12) and non-stuttering controls (n=12) were scanned while performing a picture-naming task and a passive-viewing (baseline) task. Results showed significant differences between stuttering and non-stuttering speakers in both effective connectivity and anatomical structures in the BGTC in the left brain. Specifically, compared to non-stuttering speakers, stuttering speakers showed weaker negative connectivity from the left posterior middle temporal gyrus (PMTG) to the putamen, but stronger positive connectivity from the putamen to the thalamus, from the thalamus to the PMTG and anterior supplementary motor area (preSMA), and from the anterior superior temporal gyrus (ASTG) to the preSMA. Accompanying such altered connectivity were anatomical differences: compared to non-stuttering controls, stuttering speakers showed more grey matter (GM) volume concentration in the left putamen, less GM volume concentration in the left medial frontal gyrus and ASTG, and less white matter volume concentration underlying the left posterior superior temporal gyrus inside the BGTC. These results shed significant light on the neural mechanisms (in terms of both functional connectivity and neural anatomy) of stuttering.

Functional connectivity as revealed by independent component analysis of resting-state fNIRS measurements.

As a promising non-invasive imaging technique, functional near infrared spectroscopy (fNIRS) has recently earned increasing attention in resting-state functional connectivity (RSFC) studies. Preliminary fNIRS-based RSFC studies adopted a seed correlation approach and yielded interesting results. However, the seed correlation approach has several inherent problems, such as neglecting of interactions among multiple regions and a dependence on seed region selection. Moreover, ineffectively reduced noise and artifacts in fNIRS measurements also negatively affect RSFC results. In this study, independent component analysis (ICA) was introduced to meet these challenges in RSFC detection based on resting-state fNIRS measurements. The results of ICA on data from the sensorimotor and the visual systems both showed functional system-specific RSFC maps. Results from comparison between ICA and the conventional seed correlation approach demonstrated, both qualitatively and quantitatively, the superior performance of ICA with higher sensitivity and specificity, especially in the case of higher noise level. The capability of ICA to separate noise and artifacts from resting-state fNIRS data was also demonstrated, and the extracted noise and artifacts were illustrated. Finally, some practical issues on performing ICA on resting-state fNIRS data were discussed.

Leader emergence through interpersonal neural synchronization.

Significance Great leaders are often great communicators. However, little is known about the neural basis of leader–follower communication. Only recently have neuroscientists been able to examine interpersonal neural synchronization (INS) between leaders and followers during social interactions. Here, we show that INS is significantly higher between leaders and followers than between followers and followers, suggesting that leaders emerge by synchronizing their brain activity with that of the followers. Moreover, the quality rather than frequency of the leaders’ communications makes a significant contribution to the increase of INS. This result supports the “quality of communication” hypothesis in leader emergence. Finally, our results show that leadership can be predicted shortly after the onset of a task based on INS as well as communication behaviors. The neural mechanism of leader emergence is not well understood. This study investigated (i) whether interpersonal neural synchronization (INS) plays an important role in leader emergence, and (ii) whether INS and leader emergence are associated with the frequency or the quality of communications. Eleven three-member groups were asked to perform a leaderless group discussion (LGD) task, and their brain activities were recorded via functional near infrared spectroscopy (fNIRS)-based hyperscanning. Video recordings of the discussions were coded for leadership and communication. Results showed that the INS for the leader–follower (LF) pairs was higher than that for the follower–follower (FF) pairs in the left temporo-parietal junction (TPJ), an area important for social mentalizing. Although communication frequency was higher for the LF pairs than for the FF pairs, the frequency of leader-initiated and follower-initiated communication did not differ significantly. Moreover, INS for the LF pairs was significantly higher during leader-initiated communication than during follower-initiated communications. In addition, INS for the LF pairs during leader-initiated communication was significantly correlated with the leaders’ communication skills and competence, but not their communication frequency. Finally, leadership could be successfully predicted based on INS as well as communication frequency early during the LGD (before half a minute into the task). In sum, this study found that leader emergence was characterized by high-level neural synchronization between the leader and followers and that the quality, rather than the frequency, of communications was associated with synchronization. These results suggest that leaders emerge because they are able to say the right things at the right time.

Detecting resting-state functional connectivity in the language system using functional near-infrared spectroscopy

Functional connectivity has become one of the important approaches to understanding the functional organization of the human brain. Recently, functional near-infrared spectroscopy (fNIRS) was demonstrated as a feasible method to study resting-state functional connectivity (RSFC) in the sensory and motor systems. However, whether such fNIRS-based RSFC can be revealed in high-level and complex functional systems remains unknown. In the present study, the feasibility of such an approach is tested on the language system, of which the neural substrates have been well documented in the literature. After determination of a seed channel by a language localizer task, the correlation strength between the low frequency fluctuations of the fNIRS signal at the seed channel and those at all other channels is used to evaluate the language system RSFC. Our results show a significant RSFC between the left inferior frontal cortex and superior temporal cortex, components both associated with dominant language regions. Moreover, the RSFC map demonstrates left lateralization of the language system. In conclusion, the present study successfully utilized fNIRS-based RSFC to study a complex and high-level neural system, and provides further evidence for the validity of the fNIRS-based RSFC approach.

Classification of types of stuttering symptoms based on brain activity

Among the non-fluencies seen in speech, some are more typical (MT) of stuttering speakers, whereas others are less typical (LT) and are common to both stuttering and fluent speakers. No neuroimaging work has evaluated the neural basis for grouping these symptom types. Another long-debated issue is which type (LT, MT) whole-word repetitions (WWR) should be placed in. In this study, a sentence completion task was performed by twenty stuttering patients who were scanned using an event-related design. This task elicited stuttering in these patients. Each stuttered trial from each patient was sorted into the MT or LT types with WWR put aside. Pattern classification was employed to train a patient-specific single trial model to automatically classify each trial as MT or LT using the corresponding fMRI data. This model was then validated by using test data that were independent of the training data. In a subsequent analysis, the classification model, just established, was used to determine which type the WWR should be placed in. The results showed that the LT and the MT could be separated with high accuracy based on their brain activity. The brain regions that made most contribution to the separation of the types were: the left inferior frontal cortex and bilateral precuneus, both of which showed higher activity in the MT than in the LT; and the left putamen and right cerebellum which showed the opposite activity pattern. The results also showed that the brain activity for WWR was more similar to that of the LT and fluent speech than to that of the MT. These findings provide a neurological basis for separating the MT and the LT types, and support the widely-used MT/LT symptom grouping scheme. In addition, WWR play a similar role as the LT, and thus should be placed in the LT type.

Neural anomaly and reorganization in speakers who stutter A short-term intervention study

Objectives: The aim of the current study was to differentiate between neural activity that represents neural anomalies that are responsible for persistent developmental stuttering (PDS) from the activity that is a result of compensating for stuttering. This was done by investigating alterations to the intrinsic functional architecture of speech-language processes of patients with PDS before and after a short-term intervention. Methods: The resting-state functional connectivity (RSFC) and cortical thickness were examined before and after the intervention. The structural data were used to validate the functional results. Fifteen stuttering patients who received intervention (PDS+), 13 stuttering patients who did not receive intervention (PDS−), and 13 fluent controls participated. Results: Before the intervention, both groups of PDS patients showed significant RSFC and cortical thickness reductions in the left pars-opercularis (PO) and RSFC increases in the cerebellum, as compared to fluent controls. The intervention was effective in reducing stuttering in PDS+ patients and lowering their RSFC in the cerebellum to the level of fluent controls. The intervention effect was specific to the PDS+ group (it was not evident in the PDS− group). The intervention did not change RSFC and cortical thickness in the left PO, which remained at its preintervention level. Conclusions: The results suggest that the left PO is a locus where the intrinsic functional architecture of speech-language processes is altered in PDS patients, suggesting an etiologic role of this region in PDS. The cerebellum showed intervention-induced neural reorganization, suggesting a compensatory response when stuttering occurs.

Resting-state functional connectivity assessed with two diffuse optical tomographic systems

Functional near-infrared spectroscopy (fNIRS) is recently utilized as a new approach to assess resting-state functional connectivity (RSFC) in the human brain. For any new technique or new methodology, it is necessary to be able to replicate similar experiments using different instruments in order to establish its liability and reproducibility. We apply two different diffuse optical tomographic (DOT) systems (i.e., DYNOT and CW5), with various probe arrangements to evaluate RSFC in the sensorimotor cortex by utilizing a previously published experimental protocol and seed-based correlation analysis. Our results exhibit similar spatial patterns and strengths in RSFC between the bilateral motor cortexes. The consistent observations are obtained from both DYNOT and CW5 systems, and are also in good agreement with the previous fNIRS study. Overall, we demonstrate that the fNIRS-based RSFC is reproducible by various DOT imaging systems among different research groups, enhancing the confidence of neuroscience researchers and clinicians to utilize fNIRS for future applications.

Neural substrates of visual perceptual learning of simple and complex stimuli.

OBJECTIVE The two experiments described here used event-related potentials (ERPs) to investigate whether perceptual learning of different complexities of stimuli involves different levels of visual cortical processing in human adults. METHODS Reaction times and ERPs were recorded during 3 consecutive training sessions in which subjects discriminated between simple stimuli made of line segments or complex stimuli made of compound shapes. RESULTS Reaction times in both experiments were shortened across training sessions. For simple stimuli, training resulted in a decreased N1 (125-155ms) and an increased P2 (180-240ms) over the occipital area. For complex stimuli, however, training resulted in a decreased N1 (125-155ms) and N2 (290-340ms) and an increased P3 (350-550ms) over the central/parietal areas. CONCLUSIONS These findings suggest that perceptual learning modifies the response at different levels of visual cortical processing related to the complexity of the stimulus. SIGNIFICANCE The neuronal mechanisms involved in perceptual learning may depend on the nature (e.g. the complexity) of the stimuli used in the discrimination task.