Psychoacoustic and Archeoacoustic nature of ancient Aztec skull whistles

Abstract

Many ancient cultures used musical tools for social and ritual procedures, with the Aztec skull whistle being a unique exemplar from postclassic Mesoamerica. Skull whistles can produce softer hiss-like but also aversive and scream-like sounds that were potentially meaningful either for sacrificial practices, mythological symbolism, or intimidating warfare of the Aztecs. However, solid psychoacoustic evidence for any theory is missing, especially how human listeners cognitively and affectively respond to skull whistle sounds. Using psychoacoustic listening and classification experiments, we show that skull whistle sounds are predominantly perceived as aversive and scary and as having a hybrid natural-artificial origin. Skull whistle sounds attract mental attention by affectively mimicking other aversive and startling sounds produced by nature and technology. They were psychoacoustically classified as a hybrid mix of being voice- and scream-like but also originating from technical mechanisms. Using human neuroimaging, we furthermore found that skull whistle sounds received a specific decoding of the affective significance in the neural auditory system of human listeners, accompanied by higher-order auditory cognition and symbolic evaluations in fronto-insular-parietal brain systems. Skull whistles thus seem unique sound tools with specific psycho-affective effects on listeners, and Aztec communities might have capitalized on the scary and scream-like nature of skull whistles.

Fig. 1. Original exemplars and replicas of Aztec skull whistles.

a Human sacrifice with original skull whistle (small red box and enlarged rotated view in lower right) discovered 1987–89 at the Ehecatl-Quetzalcoatl temple in Mexico City, Mexico (burial 20; photo by Salvador Guillien Arroyo, Proyecto Tlatelolco 1987–2006, INAH Mexico). b Three original skull whistle exemplars from the collection of the Ethnological Museum in Berlin (Staatliche Mussen zu Berlin, Germany; photo by Claudia Obrocki). c A computer-tomographically (CT) reconstructed cross-section of the right exemplar in (b) (IV Ca 2621m) showing the four major compartments ((a) tubular airduct with constricted passage, (b) hemispherical counterpressure chamber, (c) collision chamber located between a/b, (d) bell). d Replicas of original skull whistles were built as a copy of original exemplars in shape and material. Exemplars “Replica 2621z” and “Replica 2621v” (manufactured by Arnd Adje Both and Osvaldo Padrón Pérez) as replicas of the original skull whistles with inventory numbers IV Ca 2621z and IV Ca 2621 v as shown in (b). e Digitalization and 3D reconstruction of the skull whistle replicas by using CT scans of the replicas. f 3D models of an original skull whistle (Ethnological Museum IV Ca 2621u) and the Replica 2621z demonstrate the air flow dynamics, construction similarity, and sound generation process.

Fig. 2. Acoustic profiles of skull whistles and the MPS profile.

a Example spectrograms from four skull whistle sound categories, an original skull whistle (SW orig; upper panel) as well as from a replica skull whistle with sounds produced at three different levels of air pressure (SW high, SW med/medium, SW low). b Mean modulation power spectrum (MPS; pwr power level) for original (n = 35) and replica skull whistle sounds (n = 90 for each level, total n = 270) (left upper panel). The other plots show statistical difference maps (log-transformed p-values, n = 2000 permutation statistics) between MPSs for the four skull whistle sound categories compared to sounds from 9 major sound categories (mus musical sound effects, nat nature, ani animal, hum human, int interior, ext exterior, syn synthetic, mex Mexican flutes, ins solo instruments; total n = 2262). The difference maps highlight three MPS patches (−log₁₀(p) > abs(3)) that show relative power differences in skull whistle sounds (left upper panel; patch marked as a —MPS noise patch, patch marked as b —MPS pitch patch, patch marked as c —MPS slow pattern patch For abbreviations of sound categories, see Tab. S1.

Fig. 3. RSA analysis on acoustic profiles and hierarchical clustering analysis.

a Representational similarity analysis (RSA) across all 80 sound categories (left panel) based on a pattern of 1582 acoustic features; dashed vertical lines indicate linear steps (0.2) in similarity. b Enlarged view of the four top lines of the RSA values for the four skull whistle sound categories and their acoustic similarity to sounds of the other 76 categories; sounds are sorted for similarity in descending order (lower values represent higher similarity). c Hierarchical clustering analysis on all sounds and their acoustic features (colored nodes with linkage cluster threshold of c < 2.0). For abbreviations of sound categories, see Tab. S1.

Fig. 4. Perceptual ratings on sounds.

a All 2567 sounds were perceptually rated by n = 70 human listeners along 4 dimensions (arousal, valence, urgency, naturalness) on a 10-point Likert scale. Shown are 2D plots with valence (negative −5, positive 5) on the y-axis and the other scales on the x-axis. Skull whistle sounds are color-coded in red; 9 major sound categories are color-coded in blue-to-yellow. b Mean, median, and distribution of ratings for each of the 13 sound categories. Rating on all four scales revealed a high inter-rater consistency (valence ICC = 0.78, F_2566,23094 = 4.611, p < 0.001, CI_95% [0.77 0.80]; arousal ICC = 0.71, F_2566,23094 = 3.450, p < 0.001, CI_95% [0.69 0.73]; urgency ICC = 0.80, F_2566,23094 = 5.037, p < 0.001, CI_95% [0.79 0.81]; naturalness ICC = 0.78, F_2566,23094 = 4.597, p < 0.001, CI_95% [0.77 0.79]). Red-colored bars at the bottom of plots indicate significant differences from the skull whistle categories (p < 1e^-5, FDR corrected, posthoc coefficient test; see Tab. S2–S5 for full statistics on posthoc comparisons); blue-colored bars at the top of plots indicate differences within the skull whistle categories (p < 1e^-5, FDR corrected, posthoc coefficient test; see Tab. S2–5). For abbreviations of sound categories, see Tab. S1.

Fig. 5. RSA analysis on perceptual ratings on sounds and hierarchical clustering analysis.

a Representational similarity analysis (RSA) on the pattern of perceptual ratings (left panel); dashed vertical lines indicate linear steps (0.2) in similarity. b Enlarged view of the four top lines are the RSA values for the four skull whistle sound categories and their perceptual similarity to sounds of the other 76 categories; sounds are sorted for similarity in descending order (lower values represent higher similarity). c Hierarchical clustering analysis on all sounds and their perceptual ratings (colored nodes with linkage cluster threshold of c < 2.0). For abbreviations of sound categories, see Tab. S1.

Fig. 6. Free categorical and emotional labeling of sounds.

a Human listeners (n = 40) labeled 200 sounds (4 skull whistle categories, 8 other sound categories) with a substantive label (“Labels”) describing the origin or source of the sound (upper panel) as well as with an adjective label (“Adjectives”) describing their emotional response to the sound (lower panel). Plots show the sorted frequency of labels used as the relative number (relative nb = total nb of label multiplied by the percentage of listeners using the label; y-axis is relative nb/100); plots only show results for the four skull whistle categories. Asterisks indicate significance p < 0.05 (significant difference of observed frequency above expected probability), binomial test, FDR corrected; see Tab. S6-7. b To perform a correspondence analysis (CA) on the labels, we re-labeled the original labels along the 9 major sound categories and 8 major emotional dimensions according to the model by Plutchik. Re-labeling was done based on the classification probabilities of n = 7 independent raters. *p < 0.05, binomial test, FDR corrected; see Tab. S8-9. c Explained variance of the dimensions resulting from the CA; dimensions 1–3 explained >61% of the variance in the data. d Dimensions 1–3 of the CA for categorical labels and emotional adjectives. e Probability for classifying sounds skull whistle sounds and sounds form 5 other categories as originating from an “animated”, “technical”, or environmental source. Left plot is for the experiment including original skull whistles (n = 76), right plot is for the experiment including replica skull whistles (n = 58). f Reaction time and accuracy data from the dichotic listening experiment, where humans discriminated low/high tone on the attended ear while presenting other sounds or silence on the unattended ear. Left plot is for the experiment including original skull whistles (n = 47), the right plot is for the experiment including replica skull whistles (n = 47).

Fig. 7. Brain responses to skull whistle sounds.

a Functional brain activity in human listeners (n = 32) when comparing activity for skull whistles with activity for all other 5 general sound categories. b Brain activity when contrasting skull whistle with animated sounds (human, animal; left panel) and with artificial sounds (technical, instrument; right panel). c Functional connectivity patterns from seed regions in the right fronto-parietal network that were significant for processing skull whistle sounds (upper panel), and for the left (mid panel) and right auditory cortex regions (lower panel) that were significant for processing other sounds. Voxel-level threshold of p = 0.005 combined with an FWE-corrected cluster-level threshold of p = 0.05. d Representational similarity matrices (RSM) for acoustic and percental patterns of the sounds included in the neuroimaging experiment. Bottom plots show the RSM for the skull whistle sounds only (rev, reversed coding), corresponding to the black box in the upper panels. e Brain areas with significant cross-correlation between the acoustic and perceptual similarity patterns and measures of neural similarity between sound categories. All brain activity from contrasts includes a voxel threshold p < 0.05 (FWE corrected), cluster threshold k = 10.