The present study investigates brain-to-brain coupling, defined as inter-subject correlations in the hemodynamic response, during natural verbal communication. We used functional near-infrared spectroscopy (fNIRS) to record brain activity of 3 speakers telling stories and 15 listeners comprehending audio recordings of these stories. Listeners’ brain activity was significantly correlated with speakers’ with a delay. This between-brain correlation disappeared when verbal communication failed. We further compared the fNIRS and functional Magnetic Resonance Imaging (fMRI) recordings of listeners comprehending the same story and found a significant relationship between the fNIRS oxygenated-hemoglobin concentration changes and the fMRI BOLD in brain areas associated with speech comprehension. This correlation between fNIRS and fMRI was only present when data from the same story were compared between the two modalities and vanished when data from different stories were compared; this cross-modality consistency further highlights the reliability of the spatiotemporal brain activation pattern as a measure of story comprehension. Our findings suggest that fNIRS can be used for investigating brain-to-brain coupling during verbal communication in natural settings.

An accurate measure of mental workload level has diverse neuroergonomic applications ranging from brain computer interfacing to improving the efficiency of human operators. In this study, we integrated electroencephalogram (EEG), functional near-infrared spectroscopy (fNIRS), and physiological measures for the classification of three workload levels in an n-back working memory task. A significantly better than chance level classification was achieved by EEG-alone, fNIRS-alone, physiological alone, and EEG+fNIRS based approaches. The results confirmed our previous finding that integrating EEG and fNIRS significantly improved workload classification compared to using EEG-alone or fNIRS-alone. The inclusion of physiological measures, however, does not significantly improves EEG-based or fNIRS-based workload classification. A major limitation of currently available mental workload assessment approaches is the requirement to record lengthy calibration data from the target subject to train workload classifiers. We show that by learning from the data of other subjects, workload classification accuracy can be improved especially when the amount of data from the target subject is small.

Compared with blocked, random practice resulted in enhanced learning through better performance and less cognitive load for retention and transfer of simulated laparoscopic tasks.

Abstract. Functional near infrared spectroscopy (fNIR) is a noninvasive, portable optical imaging tool to monitor changes in hemodynamic responses (i.e., oxygenated hemoglobin (HbO)) within the prefrontal cortex (PFC) in response to sensory, motor or cognitive activation. We used fNIR for monitoring PFC activation during learning of simulated laparoscopic surgical tasks throughout 4 days of training and testing. Blocked (BLK) and random (RND) practice orders were used to test the practice schedule effect on behavioral, hemodynamic responses and relative neural efficiency (EFF rel-neural ) measures during transfer. Left and right PFC for both tasks showed significant differences with RND using less HbO than BLK. Cognitive workload showed RND exhibiting high EFF rel-neural across the PFC for the coordination task while the more difficult cholecystectomy task showed EFF rel-neural differences only in the left PFC. Use of brain activation, behavioral and EFF rel-neural measures can provide a more accurate depiction of the generalization or transfer of learning.

Fulfillment of the basic psychological needs for competence, relatedness, and autonomy is believed to facilitate people's integrative tendencies to process psychological conflicts and develop a coherent sense of self. The present study therefore used event-related potentials (ERPs) to examine the relation between need fulfillment and the amplitude of conflict negativity (CN), a neurophysiological measure of conflict during personal decision making. Participants completed a decision-making task in which they made a series of forced choices according to their personal preferences. Three types of decision-making situations were created on the basis of participants' unique preference ratings, which were obtained prior to ERP recording: low-conflict situations (choosing between an attractive and an unattractive option), highconflict approach-approach situations (choosing between two similarly attractive options), and high-conflict avoidance-avoidance situations (choosing between two similarly unattractive options). As expected, CN amplitudes were larger in high-relative to low-conflict situations, and source localization analyses suggested that the anterior cingulate cortex was the generating structure of the CN. Most importantly, people reporting higher need fulfillment exhibited larger CN amplitudes in avoidance-avoidance situations relative to lowconflict situations; to a lesser extent, they also exhibited larger CN amplitudes in approach-approach situations relative to low-conflict situations. By contrast, people reporting lower need fulfillment exhibited CN amplitudes that poorly discriminated the three decision situations. These results suggest that need fulfillment may promote self-coherent functioning by increasing people's receptivity to and processing of events that challenge their abilities to make efficient, self-congruent choices.