Neurocognitive poetics: methods and models for investigating the neuronal and cognitive-affective bases of literature reception

Abstract

A long tradition of research including classical rhetoric, esthetics and poetics theory, formalism and structuralism, as well as current perspectives in (neuro)cognitive poetics has investigated structural and functional aspects of literature reception. Despite a wealth of literature published in specialized journals like Poetics, however, still little is known about how the brain processes and creates literary and poetic texts. Still, such stimulus material might be suited better than other genres for demonstrating the complexities with which our brain constructs the world in and around us, because it unifies thought and language, music and imagery in a clear, manageable way, most often with play, pleasure, and emotion (Schrott and Jacobs, 2011). In this paper, I discuss methods and models for investigating the neuronal and cognitive-affective bases of literary reading together with pertinent results from studies on poetics, text processing, emotion, or neuroaesthetics, and outline current challenges and future perspectives.

Keywords: Panksepp-Jakobson hypothesis; absorption; emotion potential; fiction feeling hypothesis; foregrounding; immersion; neuroaesthetics; neurocognitive poetics; neuroliterature; poetic function.

Figure 1

Illustration of the Panksepp-Jakobson hypothesis linking neurobiological theories of emotion with complex linguistic models. Bottom-left: four core affect systems (fear, rage, panic, and seeking; taken from Panksepp, 1998). Top-right: illustration of Jakobson’s extension of Bühler’s organon model of language describing the interplay between six language functions always operating in any communicative act in different mixtures.

Figure 2

4 × 4 matrix illustrating four levels of text crossed with four groups of features, with one example feature for each cell of the matrix.

Figure 3

Example computation of emotion potential (EP = abs(valence x arousal)) and processing fluency (PF = frequency x imageability) for a passage from Harry Potter. x-axis: text; y-axis: z-values of EP (in red) and PF (in blue). Note thate EP and PF values are only shown for words contained in the BAWL.

Figure 4

(Taken from Hsu et al., 2014). Top: fMRI results: the mid-cingulate gyrus showing a significant correlation difference between passage immersion ratings and BOLD response in the Fear vs. Neutral conditions, cross-hair highlighting the peak voxel (Montreal Neurological Institute coordinate [x, y, z] = [8, 14, 39]). The color bar indicates t-values. Bottom: The estimated response strength in the peak [8, 14, 39] for both experimental conditions. The error bars represent 90% confidence intervals.

Figure 5

(Taken from Bohrn et al., 2013). fMRI results showing parametric effects of beauty evaluation in the right caudate nucleus extending to putamen and anterior rostral part of the MFC. (voxel height threshold at p < 0.005, cluster width threshold of 24 voxel).

Figure 6

Simplified sketch of the NCPM (adapted from Jacobs, 2011, 2014, 2015) with a fast upper route triggered by BG text elements, and a slower lower route responding to FG elements (see text for explanation).