Optimization of wavelet coherence analysis as a measure of neural synchrony during hyperscanning using functional near-infrared spectroscopy.

SIGNIFICANCE: The expanding field of human social interaction is enabled by functional near-infrared spectroscopy (fNIRS) that acquires hemodynamic signals during live two-person interactions. These advances call for development of methods to quantify interactive processes. Aim: Wavelet coherence analysis has been applied to cross-brain neural coupling. However, fNIRS-specific computations have not been explored. This investigation determines the effects of global mean removal, wavelet equation, and choice of oxyhemoglobin versus deoxyhemoglobin signals. APPROACH: We compare signals with a known coherence with acquired signals to determine optimal computational approaches. The known coherence was calculated using three visual stimulation sequences of a contrast-reversing checkerboard convolved with the canonical hemodynamic response function. This standard was compared with acquired human fNIRS responses within visual cortex using the same sequences. RESULTS: Observed coherence was consistent with known coherence with highest correlations within the wavelength range between 10 and 20 s. Removal of the global mean improved the correlation irrespective of the specific equation for wavelet coherence, and the oxyhemoglobin signal was associated with a marginal correlation advantage. CONCLUSIONS: These findings provide both methodological and computational guidance that enhances the validity and interpretability of wavelet coherence analysis for fNIRS signals acquired during live social interactions

Determining R-parity violating parameters from neutrino and LHC data

In supersymmetric models neutrino data can be explained by R-parity violating operators which violate lepton number by one unit. The so called bilinear model can account for the observed neutrino data and predicts at the same time several decay properties of the lightest supersymmetric particle. In this paper we discuss the expected precision to determine these parameters by combining neutrino and LHC data and discuss the most important observables. We show that one can expect a rather accurate determination of the underlying R-parity parameters assuming mSUGRA relations between the R-parity conserving ones and discuss briefly also the general MSSM as well as the expected accuracies in case of a prospective e+ e- linear collider. An important observation is that several parameters can only be determined up to relative signs or more generally relative phases.Comment: 13 pages, 13 figure

Comparison of Human Social Brain Activity During Eye-Contact With Another Human and a Humanoid Robot

Robot design to simulate interpersonal social interaction is an active area of research with applications in therapy and companionship. Neural responses to eye-to-eye contact in humans have recently been employed to determine the neural systems that are active during social interactions. Whether eye-contact with a social robot engages the same neural system remains to be seen. Here, we employ a similar approach to compare human-human and human-robot social interactions. We assume that if human-human and human-robot eye-contact elicit similar neural activity in the human, then the perceptual and cognitive processing is also the same for human and robot. That is, the robot is processed similar to the human. However, if neural effects are different, then perceptual and cognitive processing is assumed to be different. In this study neural activity was compared for human-to-human and human-to-robot conditions using near infrared spectroscopy for neural imaging, and a robot (Maki) with eyes that blink and move right and left. Eye-contact was confirmed by eye-tracking for both conditions. Increased neural activity was observed in human social systems including the right temporal parietal junction and the dorsolateral prefrontal cortex during human-human eye contact but not human-robot eye-contact. This suggests that the type of human-robot eye-contact used here is not sufficient to engage the right temporoparietal junction in the human. This study establishes a foundation for future research into human-robot eye-contact to determine how elements of robot design and behavior impact human social processing within this type of interaction and may offer a method for capturing difficult to quantify components of human-robot interaction, such as social engagement

Co-localization of theta-band activity and hemodynamic responses during face perception: simultaneous electroencephalography and functional near-infrared spectroscopy recordings

Face-specific neural processes in the human brain have been localized to multiple anatomical structures and associated with diverse and dynamic social functions. The question of how various face-related systems and functions may be bound together remains an active area of investigation. We hypothesize that face processing may be associated with specific frequency band oscillations that serve to integrate distributed face processing systems. Using a multimodal imaging approach, including electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), simultaneous signals were acquired during face and object picture viewing. As expected for face processing, hemodynamic activity in the right occipital face area (OFA) increased during face viewing compared to object viewing, and in a subset of participants, the expected N170 EEG response was observed for faces. Based on recently reported associations between the theta band and visual processing, we hypothesized that increased hemodynamic activity in a face processing area would also be associated with greater theta-band activity originating in the same area. Consistent with our hypothesis, theta-band oscillations were also localized to the right OFA for faces, whereas alpha- and beta-band oscillations were not. Together, these findings suggest that theta-band oscillations originating in the OFA may be part of the distributed face-specific processing mechanism

Interpersonal Agreement and Disagreement During Face-to-Face Dialogue: An fNIRS Investigation

Although the neural systems that underlie spoken language are well-known, how they adapt to evolving social cues during natural conversations remains an unanswered question. In this work we investigate the neural correlates of face-to-face conversations between two individuals using functional near infrared spectroscopy (fNIRS) and acoustical analyses of concurrent audio recordings. Nineteen pairs of healthy adults engaged in live discussions on two controversial topics where their opinions were either in agreement or disagreement. Participants were matched according to their a priori opinions on these topics as assessed by questionnaire. Acoustic measures of the recorded speech including the fundamental frequency range, median fundamental frequency, syllable rate, and acoustic energy were elevated during disagreement relative to agreement. Consistent with both the a priori opinion ratings and the acoustic findings, neural activity associated with long-range functional networks, rather than the canonical language areas, was also differentiated by the two conditions. Specifically, the frontoparietal system including bilateral dorsolateral prefrontal cortex, left supramarginal gyrus, angular gyrus, and superior temporal gyrus showed increased activity while talking during disagreement. In contrast, talking during agreement was characterized by increased activity in a social and attention network including right supramarginal gyrus, bilateral frontal eye-fields, and left frontopolar regions. Further, these social and visual attention networks were more synchronous across brains during agreement than disagreement. Rather than localized modulation of the canonical language system, these findings are most consistent with a model of distributed and adaptive language-related processes including cross-brain neural coupling that serves dynamic verbal exchanges

Real-Time Eye-to-Eye Contact Is Associated With Cross-Brain Neural Coupling in Angular Gyrus

Direct eye contact between two individuals is a salient social behavior known to initiate and promote interpersonal interaction. However, the neural processes that underlie these live interactive behaviors and eye-to-eye contact are not well understood. The Dynamic Neural Coupling Hypothesis presents a general theoretical framework proposing that shared interactive behaviors are represented by cross-brain signal coherence. Using functional near-infrared spectroscopy (fNIRS) adapted for hyper scanning, we tested this hypothesis specifically for neural mechanisms associated with eye-to-eye gaze between human participants compared to similar direct eye-gaze at a dynamic video of a face and predicted that the coherence of neural signals between the two participants during reciprocal eye-to-eye contact would be greater than coherence observed during direct eye-gaze at a dynamic video for those signals originating in social and face processing systems. Consistent with this prediction cross-brain coherence was increased for signals within the angular gyrus (AG) during eye-to-eye contact relative to direct eye-gaze at a dynamic face video (p < 0.01). Further, activity in the right temporal-parietal junction (TPJ) was increased in the real eye-to-eye condition (p < 0.05, FDR corrected). Together, these findings advance a functional and mechanistic understanding of the AG and cross-brain neural coupling associated with real-time eye-to-eye contact

Comparison of short-channel separation and spatial domain filtering for removal of non-neural components in functional near-infrared spectroscopy signals

Significance: With the increasing popularity of functional near-infrared spectroscopy (fNIRS), the need to determine localization of the source and nature of the signals has grown. Aim: We compare strategies for removal of non-neural signals for a finger-thumb tapping task, which shows responses in contralateral motor cortex and a visual checkerboard viewing task that produces activity within the occipital lobe. Approach: We compare temporal regression strategies using short-channel separation to a spatial principal component (PC) filter that removes global signals present in all channels. For short-channel temporal regression, we compare non-neural signal removal using first and combined first and second PCs from a broad distribution of short channels to limited distribution on the forehead. Results: Temporal regression of non-neural information from broadly distributed short channels did not differ from forehead-only distribution. Spatial PC filtering provides results similar to short-channel separation using the temporal domain. Utilizing both first and second PCs from short channels removes additional non-neural information. Conclusions: We conclude that short-channel information in the temporal domain and spatial domain regression filtering methods remove similar non-neural components represented in scalp hemodynamics from fNIRS signals and that either technique is sufficient to remove non-neural components

Comparison of Oxyhemoglobin and Deoxyhemoglobin Signal Reliability With and Without Global Mean Removal for Digit Manipulation Motor Tasks

Functional near-infrared spectroscopy (fNIRS) could be well suited for clinical use, such as measuring neural activity before and after treatment; however, reliability and specificity of fNIRS signals must be ensured so that differences can be attributed to the intervention. This study compared the test–retest and longitudinal reliability of oxyhemoglobin and deoxyhemoglobin signals before and after spatial filtering. In the test–retest experiment, 14 participants were scanned on 2 days while performing four right-handed digit-manipulation tasks. Group results revealed greater test–retest reliability for oxyhemoglobin than deoxyhemoglobin signals and greater spatial specificity for the deoxyhemoglobin signals. To further characterize reliability, a longitudinal experiment was conducted in which two participants repeated the same motor tasks for 10 days. Beta values from the two tasks with the lowest and highest test–retest reliability, respectively, in the spatially filtered deoxyhemoglobin signal are reported as representative findings. Both test–retest and longitudinal methods confirmed that task and signal type influence reliability. Oxyhemoglobin signals were more reliable overall than deoxyhemoglobin, and removal of the global mean reduced reliability of both signals. Findings are consistent with the suggestion that systemic components most prevalent in the oxyhemoglobin signal may inflate reliability relative to the deoxyhemoglobin signal, which is less influenced by systemic factors

Signal processing of functional NIRS data acquired during overt speaking

Functional near-infrared spectroscopy (fNIRS) offers an advantage over traditional functional imaging methods [such as functional magnetic resonance imaging (fMRI)] by allowing participants to move and speak relatively freely. However, neuroimaging while actively speaking has proven to be particularly challenging due to the systemic artifacts that tend to be located in the critical brain areas. To overcome these limitations and enhance the utility of fNIRS, we describe methods for investigating cortical activity during spoken language tasks through refinement of deoxyhemoglobin (deoxyHb) signals with principal component analysis (PCA) spatial filtering to remove global components. We studied overt picture naming and compared oxyhemoglobin (oxyHb) and deoxyHb signals with and without global component removal using general linear model approaches. Activity in Broca’s region and supplementary motor cortex was observed only when the filter was applied to the deoxyHb signal and was shown to be spatially comparable to fMRI data acquired using a similar task and to meta-analysis data. oxyHb signals did not yield expected activity in Broca’s region with or without global component removal. This study demonstrates the utility of a PCA spatial filter on the deoxyHb signal in revealing neural activity related to a spoken language task and extends applications of fNIRS to natural and ecologically valid conditions

Frontal temporal and parietal systems synchronize within and across brains during live eye-to-eye contact

Human eye-to-eye contact is a primary source of social cues and communication. In spite of the biological significance of this interpersonal interaction, the underlying neural processes are not well-understood. This knowledge gap, in part, reflects limitations of conventional neuroimaging methods, including solitary confinement in the bore of a scanner and minimal tolerance of head movement that constrain investigations of natural, two-person interactions. However, these limitations are substantially resolved by recent technical developments in functional near-infrared spectroscopy (fNIRS), a non-invasive spectral absorbance technique that detects changes in blood oxygen levels in the brain by using surface-mounted optical sensors. Functional NIRS is tolerant of limited head motion and enables simultaneous acquisitions of neural signals from two interacting partners in natural conditions. We employ fNIRS to advance a data-driven theoretical framework for two-person neuroscience motivated by the Interactive Brain Hypothesis which proposes that interpersonal interaction between individuals evokes neural mechanisms not engaged during solo, non-interactive, behaviors. Within this context, two specific hypotheses related to eye-to-eye contact, functional specificity and functional synchrony, were tested. The functional specificity hypothesis proposes that eye-to-eye contact engages specialized, within-brain, neural systems; and the functional synchrony hypothesis proposes that eye-to-eye contact engages specialized, across-brain, neural processors that are synchronized between dyads. Signals acquired during eye-to-eye contact between partners (interactive condition) were compared to signals acquired during mutual gaze at the eyes of a picture-face (non-interactive condition). In accordance with the specificity hypothesis, responses during eye-to-eye contact were greater than eye-to-picture gaze for a left frontal cluster that included pars opercularis (associated with canonical language production functions known as Broca's region), pre- and supplementary motor cortices (associated with articulatory systems), as well as the subcentral area. This frontal cluster was also functionally connected to a cluster located in the left superior temporal gyrus (associated with canonical language receptive functions known as Wernicke's region), primary somatosensory cortex, and the subcentral area. In accordance with the functional synchrony hypothesis, cross-brain coherence during eye-to-eye contact relative to eye-to-picture gaze increased for signals originating within left superior temporal, middle temporal, and supramarginal gyri as well as the pre- and supplementary motor cortices of both interacting brains. These synchronous cross-brain regions are also associated with known language functions, and were partner-specific (i.e., disappeared with randomly assigned partners). Together, both within and across-brain neural correlates of eye-to-eye contact included components of previously established productive and receptive language systems. These findings reveal a left frontal, temporal, and parietal long-range network that mediates neural responses during eye-to-eye contact between dyads, and advance insight into elemental mechanisms of social and interpersonal interactions