scholarly journals A Guide to Parent-Child fNIRS Hyperscanning Data Analysis

2021 ◽  
Author(s):  
Trinh Nguyen ◽  
Stefanie Hoehl ◽  
Pascal Vrticka
Keyword(s):  
Data Analysis ◽  
Near Infrared ◽  
Brain Activity ◽  
Neural Synchrony ◽  
Functional Near Infrared Spectroscopy ◽  
Wavelet Transform Coherence ◽  
Pair Analysis ◽  
Random Pair ◽  
Problem Solving Task ◽  
Parent Child

The use of functional near-infrared spectroscopy (fNIRS) hyperscanning during naturalistic interactions in parent-child dyads has substantially advanced our understanding of the neurobiological underpinnings of human social interaction. However, despite the rise of developmental hyperscanning studies over the last years, analysis procedures have not yet been standardized and are often individually developed by each research team. This article offers a guide on parent-child fNIRS hyperscanning data analysis in MATLAB and R. We provide an exemplary dataset of 20 dyads assessed during a cooperative versus individual problem-solving task, with brain activity measured using 16 channels located over bilateral frontal and temporo-parietal areas. We use MATLAB toolboxes Homer2 and SPM for fNIRS to preprocess the acquired data, and suggest a standardized procedure previously employed in several publications. Next, we calculate interpersonal neural synchrony between dyads using Wavelet Transform Coherence (WTC) and illustrate how to run a random pair analysis to control for spurious correlations in the signal. We then use RStudio to estimate Generalized Linear Mixed Models (GLMM) to account for the bounded distribution of coherence values for interpersonal neural synchrony analyses. With this guide, we hope to offer advice for future parent-child fNIRS hyperscanning investigations and to enhance replicability within the field.

scholarly journals A Guide to Parent-Child fNIRS Hyperscanning Data Processing and Analysis

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4075
Author(s):  
Trinh Nguyen ◽  
Stefanie Hoehl ◽  
Pascal Vrtička
Keyword(s):  
Mixed Models ◽  
Near Infrared ◽  
Generalized Linear Mixed Models ◽  
Neural Synchrony ◽  
Functional Near Infrared Spectroscopy ◽  
Wavelet Transform Coherence ◽  
Pair Analysis ◽  
Random Pair ◽  
Problem Solving Task ◽  
Parent Child

The use of functional near-infrared spectroscopy (fNIRS) hyperscanning during naturalistic interactions in parent–child dyads has substantially advanced our understanding of the neurobiological underpinnings of human social interaction. However, despite the rise of developmental hyperscanning studies over the last years, analysis procedures have not yet been standardized and are often individually developed by each research team. This article offers a guide on parent–child fNIRS hyperscanning data analysis in MATLAB and R. We provide an example dataset of 20 dyads assessed during a cooperative versus individual problem-solving task, with brain signal acquired using 16 channels located over bilateral frontal and temporo-parietal areas. We use MATLAB toolboxes Homer2 and SPM for fNIRS to preprocess the acquired brain signal data and suggest a standardized procedure. Next, we calculate interpersonal neural synchrony between dyads using Wavelet Transform Coherence (WTC) and illustrate how to run a random pair analysis to control for spurious correlations in the signal. We then use RStudio to estimate Generalized Linear Mixed Models (GLMM) to account for the bounded distribution of coherence values for interpersonal neural synchrony analyses. With this guide, we hope to offer advice for future parent–child fNIRS hyperscanning investigations and to enhance replicability within the field.

scholarly journals Neural synchrony in mother–child conversation: Exploring the role of conversation patterns

2020 ◽  
Author(s):  
Trinh Nguyen ◽  
Hanna Schleihauf ◽  
Ezgi Kayhan ◽  
Daniel Matthes ◽  
Pascal Vrtička ◽  
...  
Keyword(s):  
Family Environment ◽  
Near Infrared ◽  
Temporal Dynamics ◽  
Neural Synchrony ◽  
Functional Near Infrared Spectroscopy ◽  
Neural Synchronization ◽  
Turn Taking ◽  
Over Time ◽  
Parent Child

Abstract Conversations are an essential form of communication in daily family life. Specific patterns of caregiver–child conversations have been linked to children’s socio-cognitive development and child-relationship quality beyond the immediate family environment. Recently, interpersonal neural synchronization has been proposed as a neural mechanism supporting conversation. Here, we present a functional near-infrared spectroscopy (fNIRS) hyperscanning study looking at the temporal dynamics of neural synchrony during mother–child conversation. Preschoolers (20 boys and 20 girls, M age 5;07 years) and their mothers (M age 36.37 years) were tested simultaneously with fNIRS hyperscanning while engaging in a free verbal conversation lasting for 4 min. Neural synchrony (using wavelet transform coherence analysis) was assessed over time. Furthermore, each conversational turn was coded for conversation patterns comprising turn-taking, relevance, contingency and intrusiveness. Results from linear mixed-effects modeling revealed that turn-taking, but not relevance, contingency or intrusiveness predicted neural synchronization during the conversation over time. Results are discussed to point out possible variables affecting parent–child conversation quality and the potential functional role of interpersonal neural synchronization for parent–child conversation.

scholarly journals Interpersonal brain synchronization during face-to-face economic exchange between acquainted dyads

2021 ◽  
Author(s):  
Yuto Kikuchi ◽  
Kensuke Tanioka ◽  
Tomoyuki Hiroyasu ◽  
Satoru Hiwa
Keyword(s):  
Near Infrared ◽  
Ultimatum Game ◽  
Cooperative Behavior ◽  
Social Activity ◽  
Economic Exchange ◽  
Functional Near Infrared Spectroscopy ◽  
Face To Face ◽  
The Face ◽  
Pair Analysis ◽  
Random Pair

Interpersonal brain synchronization (IBS) has been observed during social interactions and involves various factors, such as familiarity with the partner and type of social activity. A previous study has shown that face-to-face interactions in pairs of strangers increase IBS. However, it is unclear whether this can be observed when the nature of the interacting partners is different. Herein, we aimed to extend these findings to pairs of acquaintances. Neural activity in the frontal and temporal regions was recorded using functional near-infrared spectroscopy hyperscanning. Participants played an ultimatum game that required virtual economic exchange in two experimental settings: the face-to-face and face-blocked conditions. Random pair analysis confirmed whether IBS was induced by social interaction. Contrary to the aforementioned study, our results did not show any cooperative behavior or task-induced IBS increase. Conversely, the random pair analysis results revealed that the pair-specific IBS was significant only in the task condition at the left and right superior frontal, middle frontal, orbital superior frontal, right superior temporal, precentral, and postcentral gyri. Our results revealed that face-to-face interaction in acquainted pairs did not increase IBS and supported the idea that IBS is affected by "with whom we interact and how."

Making social neuroscience less WEIRD: Using fNIRS to measure neural signatures of persuasive influence in a Middle East participant sample

2019 ◽  
Author(s):  
Shannon Burns ◽  
Lianne N. Barnes ◽  
Ian A. McCulloh ◽  
Munqith M. Dagher ◽  
Emily B. Falk ◽  
...  
Keyword(s):  
Prefrontal Cortex ◽  
Near Infrared ◽  
Brain Activity ◽  
Health And Safety ◽  
Social Neuroscience ◽  
Functional Near Infrared Spectroscopy ◽  
Future Directions ◽  
Neuroscience Research ◽  
Neuropsychological Functions ◽  
Arabic Speaking

The large majority of social neuroscience research uses WEIRD populations – participants from Western, educated, industrialized, rich, and democratic locations. This makes it difficult to claim whether neuropsychological functions are universal or culture specific. In this study, we demonstrate one approach to addressing the imbalance by using portable neuroscience equipment in a study of persuasion conducted in Jordan with an Arabic-speaking sample. Participants were shown persuasive videos on various health and safety topics while their brain activity was measured using functional near infrared spectroscopy (fNIRS). Self-reported persuasiveness ratings for each video were then recorded. Consistent with previous research conducted with American subjects, this work found that activity in the dorsomedial and ventromedial prefrontal cortex predicted how persuasive participants found the videos and how much they intended to engage in the messages’ endorsed behaviors. Further, activity in the left ventrolateral prefrontal cortex was associated with persuasiveness ratings, but only in participants for whom the message was personally relevant. Implications for these results on the understanding of the brain basis of persuasion and on future directions for neuroimaging in diverse populations are discussed.

scholarly journals Cortical Activity Linked to Clocking in Deaf Adults: fNIRS Insights with Static and Animated Stimuli Presentation

2021 ◽  
Vol 11 (2) ◽  
pp. 196
Author(s):  
Sébastien Laurent ◽  
Laurence Paire-Ficout ◽  
Jean-Michel Boucheix ◽  
Stéphane Argon ◽  
Antonio Hidalgo-Muñoz
Keyword(s):  
Near Infrared ◽  
Brain Activity ◽  
Time Estimation ◽  
Cognitive Effort ◽  
Deaf People ◽  
Vehicle Speed ◽  
Neural Basis ◽  
Functional Near Infrared Spectroscopy ◽  
The Road ◽  
Deaf Adults

The question of the possible impact of deafness on temporal processing remains unanswered. Different findings, based on behavioral measures, show contradictory results. The goal of the present study is to analyze the brain activity underlying time estimation by using functional near infrared spectroscopy (fNIRS) techniques, which allow examination of the frontal, central and occipital cortical areas. A total of 37 participants (19 deaf) were recruited. The experimental task involved processing a road scene to determine whether the driver had time to safely execute a driving task, such as overtaking. The road scenes were presented in animated format, or in sequences of 3 static images showing the beginning, mid-point, and end of a situation. The latter presentation required a clocking mechanism to estimate the time between the samples to evaluate vehicle speed. The results show greater frontal region activity in deaf people, which suggests that more cognitive effort is needed to process these scenes. The central region, which is involved in clocking according to several studies, is particularly activated by the static presentation in deaf people during the estimation of time lapses. Exploration of the occipital region yielded no conclusive results. Our results on the frontal and central regions encourage further study of the neural basis of time processing and its links with auditory capacity.

scholarly journals Functional Near-Infrared Spectroscopy for the Classification of Motor-Related Brain Activity on the Sensor-Level

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2362 ◽  
Author(s):  
Alexander E. Hramov ◽  
Vadim Grubov ◽  
Artem Badarin ◽  
Vladimir A. Maksimenko ◽  
Alexander N. Pisarchik
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
High Efficiency ◽  
Brain Activity ◽  
Blood Oxygenation ◽  
Hemispheric Lateralization ◽  
Motor Execution ◽  
Functional Near Infrared Spectroscopy

Sensor-level human brain activity is studied during real and imaginary motor execution using functional near-infrared spectroscopy (fNIRS). Blood oxygenation and deoxygenation spatial dynamics exhibit pronounced hemispheric lateralization when performing motor tasks with the left and right hands. This fact allowed us to reveal biomarkers of hemodynamical response of the motor cortex on the motor execution, and use them for designing a sensing method for classification of the type of movement. The recognition accuracy of real movements is close to 100%, while the classification accuracy of imaginary movements is lower but quite high (at the level of 90%). The advantage of the proposed method is its ability to classify real and imaginary movements with sufficiently high efficiency without the need for recalculating parameters. The proposed system can serve as a sensor of motor activity to be used for neurorehabilitation after severe brain injuries, including traumas and strokes.

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