Development of Effective Connectivity during Own- and Other-Race Face Processing: A Granger Causality Analysis

Event-related potential correlates of implicit processing of own- and other-race faces in children

Human adults typically experience difficulties in recognizing and discriminating individual faces belonging to racial groups other than their own. The origin of this "other-race" effect is set in infancy, but the understanding of its developmental course is fragmented. We aimed to access the mechanisms of the other-race effect in childhood by unraveling the neural time course of own- and other-race face processing during a masked priming paradigm. White 6- and 7-year-old children (N = 19) categorized fully visible Asian (other-race) or White (own-race) target faces according to gender. Target faces were preceded by masked same-identity or different-identity prime faces, matching the target for race and gender. We showed an early priming effect on the N100 component, with larger amplitude to different-face pairs than to same-face pairs, and a later race effect on the N200 component, with larger amplitude to own-race face pairs than to other-race face pairs. Critically, race did not interact with priming at any processing stage (P100, N100, P200, N200, or P300). Our results suggest that race could have a temporally limited impact on face processing and that the implicit and unconscious identity processing of own- and other-race faces could be similar in 6- and 7-year-olds, depicting an immature other-race effect during childhood.

Neural timing of the other-race effect across the lifespan: A review

Face race influences the way we process faces, so that faces of a different ethnic group are processed for identity less efficiently than faces of one's ethnic group - a phenomenon known as the Other-Race Effect (ORE). Although widely replicated, the ORE is still poorly characterized in terms of its development and the underlying mechanisms. In the last two decades, the Event-Related Potential (ERP) technique has brought insight into the mechanisms underlying the ORE and has demonstrated potential to clarify its development. Here, we review the ERP evidence for a differential neural processing of own-race and other-race faces throughout the lifespan. In infants, race-related processing differences emerged at the N290 and P400 (structural encoding) stages. In children, race affected the P100 (early processing, attention) perceptual stage and was implicitly encoded at the N400 (semantic processing) stage. In adults, processing difficulties for other-race faces emerged at the N170 (structural encoding), P200 (configuration processing) and N250 (accessing individual representations) perceptual stages. Early in processing, race was implicitly encoded from other-race faces (N100, P200 attentional biases) and in-depth processing preferentially applied to own-race faces (N200 attentional bias). Encoding appeared less efficient (Dm effects) and retrieval less recollection-based (old/new effects) for other-race faces. Evidence admits the contribution of perceptual, attentional, and motivational processes to the development and functioning of the ORE, offering no conclusive support for perceptual or socio-cognitive accounts. Cross-racial and non-cross-racial studies provided convergent evidence. Future research would need to include less represented ethnic populations and the developmental population.

Correction of global physiology in resting-state functional near-infrared spectroscopy

Significance: Resting-state functional connectivity (RSFC) analyses of functional near-infrared spectroscopy (fNIRS) data reveal cortical connections and networks across the brain. Motion artifacts and systemic physiology in evoked fNIRS signals present unique analytical challenges, and methods that control for systemic physiological noise have been explored. Whether these same methods require modification when applied to resting-state fNIRS (RS-fNIRS) data remains unclear. Aim: We systematically examined the sensitivity and specificity of several RSFC analysis pipelines to identify the best methods for correcting global systemic physiological signals in RS-fNIRS data. Approach: Using numerically simulated RS-fNIRS data, we compared the rates of true and false positives for several connectivity analysis pipelines. Their performance was scored using receiver operating characteristic analysis. Pipelines included partial correlation and multivariate Granger causality, with and without short-separation measurements, and a modified multivariate causality model that included a non-traditional zeroth-lag cross term. We also examined the effects of pre-whitening and robust statistical estimators on performance. Results: Consistent with previous work on bivariate correlation models, our results demonstrate that robust statistics and pre-whitening are effective methods to correct for motion artifacts and autocorrelation in the fNIRS time series. Moreover, we found that pre-filtering using principal components extracted from short-separation fNIRS channels as part of a partial correlation model was most effective in reducing spurious correlations due to shared systemic physiology when the two signals of interest fluctuated synchronously. However, when there was a temporal lag between the signals, a multivariate Granger causality test incorporating the short-separation channels was better. Since it is unknown if such a lag exists in experimental data, we propose a modified version of Granger causality that includes the non-traditional zeroth-lag term as a compromising solution. Conclusions: A combination of pre-whitening, robust statistical methods, and partial correlation in the processing pipeline to reduce autocorrelation, motion artifacts, and global physiology are suggested for obtaining statistically valid connectivity metrics with RS-fNIRS. Further studies should validate the effectiveness of these methods using human data.

The brain state of motor imagery is reflected in the causal information of functional near-infrared spectroscopy

BACKGROUND

Brain-computer interface (BCI) is a promising neurorehabilitation strategy for ameliorating post-stroke function disorders. Physiological changes in the brain, such as functional near-infrared spectroscopy (fNIRS) dedicated to exploring cerebral circulatory responses during neurological rehabilitation tasks, are essential for gaining insights into neurorehabilitation mechanisms. However, the relationship between the neurovascular responses in different brain regions under rehabilitation tasks remains unknown.

OBJECTIVE

The present study explores the fNIRS interactions between brain regions under different motor imagery (MI) tasks, emphasizing functional characteristics of brain network patterns and BCI motor task classification.

METHODS

Granger causality analysis (GCA) is carried out for oxyhemoglobin data from 29 study participants in left- and right-hand MI tasks.

RESULTS

According to research findings, homozygous and heterozygous states in the two brain connectivity modes reveal one and nine channel pairs, respectively, with significantly different (P < 0.05) GC values under the left- and right-hand MI tasks in the population. With reference to the total 10 channel pairs of causality differences between the two brain working states, a support vector machine is used to classify the two tasks with an overall accuracy of 83% for five-fold cross-validation.

CONCLUSION

As demonstrated in the present study, fNIRS offers causality patterns in different brain states of MIBCI motor tasks. The research findings show that fNIRS causality can be used to assess different states of the brain, providing theoretical support for its application to neurorehabilitation assessment protocols to ultimately improve patients' quality of life.Video Abstract: http://links.lww.com/WNR/A653.

Atypical development of emotional face processing networks in autism spectrum disorder from childhood through to adulthood

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MEG connectivity to emotional faces in ASD and typical controls 6–39 years of age was investigated.

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Distinct age-related changes in connectivity were observed in the groups to happy and angry faces.

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Age-related between-group differences in functional connectivity were found in gamma band.

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Emotion-specific age-related between-group differences were seen in beta.

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Findings highlight specific neurodevelopmental trajectories to emotional faces in ASD vs. TD.

Impairments in social functioning are hallmarks of autism spectrum disorder (ASD) and atypical functional connectivity may underlie these difficulties. Emotion processing networks typically undergo protracted maturational changes, however, those with ASD show either hyper- or hypo-connectivity with little consensus on the functional connectivity underpinning emotion processing. Magnetoencephalography was used to investigate age-related changes in whole-brain functional connectivity of eight regions of interest during happy and angry face processing in 190 children, adolescents and adults (6–39 years) with and without ASD. Findings revealed age-related changes from child- through to mid-adulthood in functional connectivity in controls and in ASD in theta, as well as age-related between-group differences across emotions, with connectivity decreasing in ASD, but increasing for controls, in gamma. Greater connectivity to angry faces was observed across groups in gamma. Emotion-specific age-related between-group differences in beta were also found, that showed opposite trends with age for happy and angry in ASD. Our results establish altered, frequency-specific developmental trajectories of functional connectivity in ASD, across distributed networks and a broad age range, which may finally help explain the heterogeneity in the literature.

The Role of Racial and Developmental Experience on Emotional Adaptive Coding in Autism Spectrum Disorder

Sensitivity to emotional face aids in rapid detection and evaluation of others, such that by school-age, children and youth exhibit adult-like patterns when the prolonged viewing of an emotional face distorts the perception of a subsequent face. However, the developmental considerations of this phenomenon (known as emotional adaptive coding) are unclear given ongoing maturational and experiential changes, including the influence of own-race experiences or the lack of face expertise, as is evident in autism spectrum disorder (ASD). This study addressed whether emotional adaptive coding is sensitive to factors of face perception expertise, specifically self-race and developmental experience, in adults (age 19-28 years) and youth (age 10-16 years). Emotional adaptive coding was not influenced by race expertise (i.e., other versus same race identity) in White and Asian adults. Emotional adaptation coding during childhood and adolescence is consistent with adults, though youth with ASD exhibited stronger adaptor after-effects in response to other-race faces, relative to TD youth and adults. By extending prior work to examine the integration of race and emotional adaptive coding in ASD, we discovered that the strength of response in ASD is atypical when viewing other-race faces, which clarifies the role of racial and facial experience on emotional face adaption.

An optical window into brain function in children and adolescents: A systematic review of functional near-infrared spectroscopy studies

Despite decades of research, our understanding of functional brain development throughout childhood and adolescence remains limited due to the challenges posed by certain neuroimaging modalities. Recently, there has been a growing interest in using functional near-infrared spectroscopy (fNIRS) to elucidate the neural basis of cognitive and socioemotional development and identify the factors shaping these types of development. This article, focusing on the fNIRS methods, presents an up-to-date systematic review of fNIRS studies addressing the effects of age and other factors on brain functions in children and adolescents. Literature searches were conducted using PubMed and PsycINFO. A total of 79 fNIRS studies involving healthy individuals aged 3-17 years that were published in peer-reviewed journals in English before July 2020 were included. Six methodological aspects of these studies were evaluated, including the research design, experimental paradigm, fNIRS measurement, data preprocessing, statistical analysis, and result presentation. The risk of bias, such as selective outcome reporting, was assessed throughout the review. A qualitative synthesis of study findings in terms of the factor effects on changes in oxyhemoglobin concentration was also performed. This unregistered review highlights the strengths and limitations of the existing literature and suggests directions for future research to facilitate the improved use of fNIRS in developmental cognitive neuroscience research.

Video-based motion-resilient reconstruction of three-dimensional position for functional near-infrared spectroscopy and electroencephalography head mounted probes

Significance: We propose a video-based, motion-resilient, and fast method for estimating the position of optodes on the scalp. Aim: Measuring the exact placement of probes (e.g., electrodes and optodes) on a participant's head is a notoriously difficult step in acquiring neuroimaging data from methods that rely on scalp recordings (e.g., electroencephalography and functional near-infrared spectroscopy) and is particularly difficult for any clinical or developmental population. Existing methods of head measurements require the participant to remain still for a lengthy period of time, are laborious, and require extensive training. Therefore, a fast and motion-resilient method is required for estimating the scalp location of probes. Approach: We propose an innovative video-based method for estimating the probes' positions relative to the participant's head, which is fast, motion-resilient, and automatic. Our method builds on capitalizing the advantages and understanding the limitations of cutting-edge computer vision and machine learning tools. We validate our method on 10 adult subjects and provide proof of feasibility with infant subjects. Results: We show that our method is both reliable and valid compared to existing state-of-the-art methods by estimating probe positions in a single measurement and by tracking their translation and consistency across sessions. Finally, we show that our automatic method is able to estimate the position of probes on an infant head without lengthy offline procedures, a task that has been considered challenging until now. Conclusions: Our proposed method allows, for the first time, the use of automated spatial co-registration methods on developmental and clinical populations, where lengthy, motion-sensitive measurement methods routinely fail.

Top-down knowledge rapidly acquired through abstract rule learning biases subsequent visual attention in 9-month-old infants

Visual attention is an information-gathering mechanism that supports the emergence of complex perceptual and cognitive capacities. Yet, little is known about how the infant brain learns to direct attention to information that is most relevant for learning and behavior. Here we address this gap by examining whether learning a hierarchical rule structure, where there is a higher-order feature that organizes visual inputs into predictable sequences, subsequently biases 9-month-old infants' visual attention to the higher-order visual feature. In Experiment 1, we found that individual differences in infants' ability to structure simple visual inputs into generalizable rules was related to the change in infants' attention biases towards higher-order features. In Experiment 2, we found that increased functional connectivity between the PFC and visual cortex was related to the efficacy of rule learning. Moreover, Granger causality analyses provided exploratory evidence that increased functional connectivity reflected PFC influence over visual cortex. These findings provide new insights into how the infant brain learns to flexibly select features from the cluttered visual world that were previously relevant for learning and behavior.

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.

Face Processing in Infancy and Beyond: The Case of Social Categories

Prior reviews of infant face processing have emphasized how infants respond to faces in general. This review highlights how infants come to respond differentially to social categories of faces based on differential experience, with a focus on race and gender. We examine six different behaviors: preference, recognition, scanning, category formation, association with emotion, and selective learning. Although some aspects of infant responding to face race and gender may be accounted for by traditional models of perceptual development, other aspects suggest the need for a broader model that links perceptual development with social and emotional development. We also consider how responding to face race and gender in infancy may presage responding to these categories beyond infancy and discuss how social biases favoring own-race and female faces are formed.

Maturational trajectories of local and long-range functional connectivity in autism during face processing

Autism spectrum disorder (ASD) is characterized neurophysiologically by, among other things, functional connectivity abnormalities in the brain. Recent evidence suggests that the nature of these functional connectivity abnormalities might not be uniform throughout maturation. Comparing between adolescents and young adults (ages 14-21) with ASD and age- and IQ-matched typically developing (TD) individuals, we previously documented, using magnetoencephalography (MEG) data, that local functional connectivity in the fusiform face areas (FFA) and long-range functional connectivity between FFA and three higher order cortical areas were all reduced in ASD. Given the findings on abnormal maturation trajectories in ASD, we tested whether these results extend to preadolescent children (ages 7-13). We found that both local and long-range functional connectivity were in fact normal in this younger age group in ASD. Combining the two age groups, we found that local and long-range functional connectivity measures were positively correlated with age in TD, but negatively correlated with age in ASD. Last, we showed that local functional connectivity was the primary feature in predicting age in ASD group, but not in the TD group. Furthermore, local functional connectivity was only correlated with ASD severity in the older group. These results suggest that the direction of maturation of functional connectivity for processing of faces from childhood to young adulthood is itself abnormal in ASD, and that during the processing of faces, these trajectory abnormalities are more pronounced for local functional connectivity measures than they are for long-range functional connectivity measures.

Preliminary Evidence of "Other-Race Effect"-Like Behavior Induced by Cathodal-tDCS over the Right Occipital Cortex, in the Absence of Overall Effects on Face/Object Processing

Neuromodulation techniques such as tDCS have provided important insight into the neurophysiological mechanisms that mediate cognition. Albeit anodal tDCS (a-tDCS) often enhances cognitive skills, the role of cathodal tDCS (c-tDCS) in visual cognition is largely unexplored and inconclusive. Here, in a single-blind, sham-controlled study, we investigated the offline effects of 1.5 mA c-tDCS over the right occipital cortex of 86 participants on four tasks assessing perception and memory of both faces and objects. Results demonstrated that c-tDCS does not overall affect performance on the four tasks. However, post-hoc exploratory analysis on participants' race (Caucasian vs. non-Caucasians), showed a "face-specific" performance decrease (≈10%) in non-Caucasian participants only. This preliminary evidence suggests that c-tDCS can induce "other-race effect (ORE)-like" behavior in non-Caucasian participants that did not show any ORE before stimulation (and in case of sham stimulation). Our results add relevant information about the breadth of cognitive processes and visual stimuli that can be modulated by c-tDCS, about the design of effective neuromodulation protocols, and have important implications for the potential neurophysiological bases of ORE.

Mapping effective connectivity within cortical networks with diffuse optical tomography

Understanding how cortical networks interact in response to task demands is important both for providing insight into the brain's processing architecture and for managing neurological diseases and mental disorders. High-density diffuse optical tomography (HD-DOT) is a neuroimaging technique that offers the significant advantages of having a naturalistic, acoustically controllable environment and being compatible with metal implants, neither of which is possible with functional magnetic resonance imaging. We used HD-DOT to study the effective connectivity and assess the modulatory effects of speech intelligibility and syntactic complexity on functional connections within the cortical speech network. To accomplish this, we extend the use of a generalized psychophysiological interaction (PPI) analysis framework. In particular, we apply PPI methods to event-related HD-DOT recordings of cortical oxyhemoglobin activity during auditory sentence processing. We evaluate multiple approaches for selecting cortical regions of interest and for modeling interactions among these regions. Our results show that using subject-based regions has minimal effect on group-level connectivity maps. We also demonstrate that incorporating an interaction model based on estimated neural activity results in significantly stronger effective connectivity. Taken together our findings support the use of HD-DOT with PPI methods for noninvasively studying task-related modulations of functional connectivity.