ABSTRACT

This chapter presents the neurocognitive poetics perspective on research on literature and poetry reception. The perspective adds models and methods of cognitive neuroscience, machine learning and data science to those of classical and modern (cognitive) poetics, as pioneered by Aristotle, Jakobson, and others. Guided by a comprehensive model of literary reading, it attempts to integrate qualitative and quantitative methods in a spiral approach in which “subjective” experiential data are not considered simply as the exploratory foreplay of quantitative, “objective” behavioural or neuroimaging data but both contribute to hypothesis testing and model development in their own right, ideally in designs combining them.