Mother-child brain-to-brain synchrony captures the temporal similarities in brain signals between dyadic partners, and has been shown to emerge during the display of joint behaviours. Despite the rise in the number of studies that investigate synchrony in naturalistic contexts, the use of varying methodological approaches to compute synchrony remains a central problem. When dyads engage in unstructured social interactions, the wide range of behavioural cues they display contribute to the use of varying lengths of signals to compute synchrony. The present functional Near-infrared Spectroscopy (fNIRS) study investigates how different methods to quantify brain signals during joint and non-joint portions of dyadic play affect the outcome of brain-to-brain synchrony. Three strategies to cope with unstructured data are tested and different signal lengths of 15, 20, 25, 30, 35, 40, 45s were used to determine the optimal method to sensitively capture synchrony. Results showed that using all available portions of the signals generated a greater number of less conservative results compared to the other two strategies, which were to compute the average synchrony for the joint and non-joint signals portions and to compute the difference between the average synchrony of joint and non-joint portions. From the different signal durations, only length portions of 25s to 35s generated significant results. These findings demonstrate that differences in computational approaches and signal lengths affect synchrony measurements and should be considered in naturalistic synchrony studies.

Assessing Computational Methods to Quantify Mother-Child Brain Synchrony in Naturalistic Settings Based on fNIRS Signals / Bizzego, Andrea; Azhari, Atiqah; Esposito, Gianluca. - In: NEUROINFORMATICS. - ISSN 1539-2791. - 2022, 20:2(2022), pp. 427-436. [10.1007/s12021-021-09558-z]

Assessing Computational Methods to Quantify Mother-Child Brain Synchrony in Naturalistic Settings Based on fNIRS Signals

Bizzego, Andrea;Esposito, Gianluca
2022-01-01

Abstract

Mother-child brain-to-brain synchrony captures the temporal similarities in brain signals between dyadic partners, and has been shown to emerge during the display of joint behaviours. Despite the rise in the number of studies that investigate synchrony in naturalistic contexts, the use of varying methodological approaches to compute synchrony remains a central problem. When dyads engage in unstructured social interactions, the wide range of behavioural cues they display contribute to the use of varying lengths of signals to compute synchrony. The present functional Near-infrared Spectroscopy (fNIRS) study investigates how different methods to quantify brain signals during joint and non-joint portions of dyadic play affect the outcome of brain-to-brain synchrony. Three strategies to cope with unstructured data are tested and different signal lengths of 15, 20, 25, 30, 35, 40, 45s were used to determine the optimal method to sensitively capture synchrony. Results showed that using all available portions of the signals generated a greater number of less conservative results compared to the other two strategies, which were to compute the average synchrony for the joint and non-joint signals portions and to compute the difference between the average synchrony of joint and non-joint portions. From the different signal durations, only length portions of 25s to 35s generated significant results. These findings demonstrate that differences in computational approaches and signal lengths affect synchrony measurements and should be considered in naturalistic synchrony studies.
2022
2
Bizzego, Andrea; Azhari, Atiqah; Esposito, Gianluca
Assessing Computational Methods to Quantify Mother-Child Brain Synchrony in Naturalistic Settings Based on fNIRS Signals / Bizzego, Andrea; Azhari, Atiqah; Esposito, Gianluca. - In: NEUROINFORMATICS. - ISSN 1539-2791. - 2022, 20:2(2022), pp. 427-436. [10.1007/s12021-021-09558-z]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/329764
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