Maps of subjective feelings

Abstract

Subjective feelings are a central feature of human life. We defined the organization and determinants of a feeling space involving 100 core feelings that ranged from cognitive and affective processes to somatic sensations and common illnesses. The feeling space was determined by a combination of basic dimension rating, similarity mapping, bodily sensation mapping, and neuroimaging meta-analysis. A total of 1,026 participants took part in online surveys where we assessed (i) for each feeling, the intensity of four hypothesized basic dimensions (mental experience, bodily sensation, emotion, and controllability), (ii) subjectively experienced similarity of the 100 feelings, and (iii) topography of bodily sensations associated with each feeling. Neural similarity between a subset of the feeling states was derived from the NeuroSynth meta-analysis database based on the data from 9,821 brain-imaging studies. All feelings were emotionally valenced and the saliency of bodily sensations correlated with the saliency of mental experiences associated with each feeling. Nonlinear dimensionality reduction revealed five feeling clusters: positive emotions, negative emotions, cognitive processes, somatic states and illnesses, and homeostatic states. Organization of the feeling space was best explained by basic dimensions of emotional valence, mental experiences, and bodily sensations. Subjectively felt similarity of feelings was associated with basic feeling dimensions and the topography of the corresponding bodily sensations. These findings reveal a map of subjective feelings that are categorical, emotional, and embodied.

Keywords: consciousness; emotion; feeling; interoception; somatosensation.

Fig. 1.

Associations between the basic dimensions of subjective experience. Histograms show the distribution for each evaluated dimension with overlaid probability density curves per clustering in Experiment 2. Scatterplots show median z-scores for each of the 100 feelings (see SI Appendix, Fig. S2 for the complete distribution densities). Color coding of the tokens is based on clustering per Experiment 2. Normalized data are modeled with one or two LS regression lines depending on the optimal fit. All reported values are Spearman’s correlations *P < 0.05, **P < 0.005.

Fig. 2.

The feeling space. (Upper) Two-dimensional map of the feeling space based on the sorting task average distance matrix between items arranged by t-SNE and clustered with DBSCAN. Color coding indicates cluster structure; gray feelings do not belong clearly to any cluster. Colored items with black edge are DBSCAN border elements. To retain the information of the distance matrix the closest three items for each node are connected with lines. Thick dark lines are showing distances that belong to the top 33rd percentile of the visualized lines (i.e., the closest items). (Lower) Heatmaps showing how strongly each basic dimension of subjective experience is associated with each discrete feeling at each location of the feeling space. Color coding shows the relative intensity as median z-score (as in Fig. 1) from high (red) to low (blue).

Fig. 3.

Bodily feeling maps. Pixel intensities show regions where each feeling was associated with statistically significant (P < 0.05, FDR corrected) bodily sensations. The data are arranged into the matrix approximately as in Fig. 2; clustering is per Experiment 2. Colorbar indicates the effect size. See SI Appendix, Figs. S4 and S5 for spatial arrangement per t-SNE.

Fig. 4.

Representational similarity between determinants of subjective experience (Spearman’s correlation). Each cell in the matrix represents pairwise RSA between two similarity matrices for the 100 feelings; *P < 0.05 (FDR corrected), **P < 0.005 (FDR corrected, permutation-based significance thresholding).