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Vanoncini M, Hoehl S, Elsner B, Wallot S, Boll-Avetisyan N, Kayhan E. Mother-infant social gaze dynamics relate to infant brain activity and word segmentation. Dev Cogn Neurosci 2024; 65:101331. [PMID: 38113766 PMCID: PMC10770595 DOI: 10.1016/j.dcn.2023.101331] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Revised: 11/24/2023] [Accepted: 12/13/2023] [Indexed: 12/21/2023] Open
Abstract
The 'social brain', consisting of areas sensitive to social information, supposedly gates the mechanisms involved in human language learning. Early preverbal interactions are guided by ostensive signals, such as gaze patterns, which are coordinated across body, brain, and environment. However, little is known about how the infant brain processes social gaze in naturalistic interactions and how this relates to infant language development. During free-play of 9-month-olds with their mothers, we recorded hemodynamic cortical activity of ´social brain` areas (prefrontal cortex, temporo-parietal junctions) via fNIRS, and micro-coded mother's and infant's social gaze. Infants' speech processing was assessed with a word segmentation task. Using joint recurrence quantification analysis, we examined the connection between infants' ´social brain` activity and the temporal dynamics of social gaze at intrapersonal (i.e., infant's coordination, maternal coordination) and interpersonal (i.e., dyadic coupling) levels. Regression modeling revealed that intrapersonal dynamics in maternal social gaze (but not infant's coordination or dyadic coupling) coordinated significantly with infant's cortical activity. Moreover, recurrence quantification analysis revealed that intrapersonal maternal social gaze dynamics (in terms of entropy) were the best predictor of infants' word segmentation. The findings support the importance of social interaction in language development, particularly highlighting maternal social gaze dynamics.
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Affiliation(s)
- Monica Vanoncini
- Department of Developmental Psychology, University of Potsdam, Karl-Liebknecht-Str. 24-25, 14476 Potsdam, Germany; Department of Linguistics, University of Potsdam, Karl-Liebknecht-Str. 24-25, 14476 Potsdam, Germany; Department of Developmental and Educational Psychology, University of Vienna, Liebiggasse 5, 1010 Vienna, Austria; Research Focus Cognitive Sciences, University of Potsdam, Germany.
| | - Stefanie Hoehl
- Department of Developmental and Educational Psychology, University of Vienna, Liebiggasse 5, 1010 Vienna, Austria
| | - Birgit Elsner
- Department of Developmental Psychology, University of Potsdam, Karl-Liebknecht-Str. 24-25, 14476 Potsdam, Germany; Research Focus Cognitive Sciences, University of Potsdam, Germany
| | - Sebastian Wallot
- Institute for Sustainability Education and Psychology (ISEP), Leuphana Universität Lüneburg, Universitätsallee 1, 21335, Lüneburg, Germany
| | - Natalie Boll-Avetisyan
- Department of Linguistics, University of Potsdam, Karl-Liebknecht-Str. 24-25, 14476 Potsdam, Germany; Research Focus Cognitive Sciences, University of Potsdam, Germany
| | - Ezgi Kayhan
- Department of Developmental Psychology, University of Potsdam, Karl-Liebknecht-Str. 24-25, 14476 Potsdam, Germany; Research Focus Cognitive Sciences, University of Potsdam, Germany; Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103 Leipzig, Germany
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Schmid S, Saddy D, Franck J. Finding Hierarchical Structure in Binary Sequences: Evidence from Lindenmayer Grammar Learning. Cogn Sci 2023; 47:e13242. [PMID: 36655988 PMCID: PMC10078511 DOI: 10.1111/cogs.13242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 12/15/2022] [Accepted: 01/04/2023] [Indexed: 01/20/2023]
Abstract
In this article, we explore the extraction of recursive nested structure in the processing of binary sequences. Our aim was to determine whether humans learn the higher-order regularities of a highly simplified input where only sequential-order information marks the hierarchical structure. To this end, we implemented a sequence generated by the Fibonacci grammar in a serial reaction time task. This deterministic grammar generates aperiodic but self-similar sequences. The combination of these two properties allowed us to evaluate hierarchical learning while controlling for the use of low-level strategies like detecting recurring patterns. The deterministic aspect of the grammar allowed us to predict precisely which points in the sequence should be subject to anticipation. Results showed that participants' pattern of anticipation could not be accounted for by "flat" statistical learning processes and was consistent with them anticipating upcoming points based on hierarchical assumptions. We also found that participants were sensitive to the structure constituency, suggesting that they organized the signal into embedded constituents. We hypothesized that the participants built this structure by merging recursively deterministic transitions.
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Affiliation(s)
| | - Douglas Saddy
- Centre for Integrative Neuroscience and NeurodynamicsUniversity of Reading
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