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To the Roots of the Sense of Self: Proposals for a Study on the Emergence of Body Awareness in Early Infancy Through a Deep Learning Method

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Abstract

In the psychological field, the study of the interaction between the caregiver and the child is considered the context of primary development. Observing how infants interact with their mothers, in the first year of their life, has allowed researchers to identify behavioural indicators useful to highlight the crucial role of their synchronisation, within the behavioural and cognitive domain. The aim of this study is to employ a new observational method, mediated by an artificial neural network model, to systematically study the complex bodily gestural interaction between child and caregiver, which concurs in the development of the child’s bodily awareness, and how the quality of early interactions affects the child’s relationship with his body. The first part will deal with qualitative observational methods, their limits and the object of the study; the second part will describe the reference theory; the third part will describe the neural network model, the details of the proposed study and the expected results. We hypothesise that this model could be used for the construction of a tool that could compensate for some of the critical shortcomings that lie within observational methods in the field of psychology.

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Di Sarno, A.D. et al. (2020). To the Roots of the Sense of Self: Proposals for a Study on the Emergence of Body Awareness in Early Infancy Through a Deep Learning Method. In: Esposito, A., Faundez-Zanuy, M., Morabito, F., Pasero, E. (eds) Neural Approaches to Dynamics of Signal Exchanges. Smart Innovation, Systems and Technologies, vol 151. Springer, Singapore. https://doi.org/10.1007/978-981-13-8950-4_37

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