A comparison of dimensional and discrete models for the representation of perceived and induced affect in response to short musical sounds.

Introduction: In musical affect research, there is considerable discussion on the best method to represent affective response. This discussion mainly revolves around the dimensional (valence, tension arousal, energy arousal) and discrete (anger, fear, sadness, happiness, tenderness) models of affect. Here, we compared these models' ability to capture self-reported affect in response to short, affectively ambiguous sounds. Methods: In two online experiments (n1 = 263, n2 = 152), participants rated perceived and induced affect in response to single notes (Exp 1) and chromatic scales (Exp 2), which varied across instrument family and pitch register. Additionally, participants completed questionnaires measuring pre-existing mood, trait empathy, Big-Five personality, musical sophistication, and musical preferences. Results: Rater consistency and agreement were high across all affect scales. Correlation and principal component analyses showed that two dimensions or two affect categories captured most of the variation in affective response. Canonical correlation and regression analyses also showed that energy arousal varied in a manner that was not captured by discrete affect ratings. Furthermore, all sources of individual differences were moderately correlated with all affect scales, particularly pre-existing mood and dimensional affect. Discussion: We conclude that when it comes to single notes and chromatic scales, the dimensions of valence and energy arousal best capture the perceived and induced affective response to affectively ambiguous sounds, although the role of individual differences should also be considered.

Timbral cues for learning to generalize musical instrument identity across pitch register.

Timbre provides an important cue to identify musical instruments. Many timbral attributes covary with other parameters like pitch. This study explores listeners' ability to construct categories of instrumental sound sources from sounds that vary in pitch. Nonmusicians identified 11 instruments from the woodwind, brass, percussion, and plucked and bowed string families. In experiment 1, they were trained to identify instruments playing a pitch of C4, and in experiments 2 and 3, they were trained with a five-tone sequence (F#3-F#4), exposing them to the way timbre varies with pitch. Participants were required to reach a threshold of 75% correct identification in training. In the testing phase, successful listeners heard single tones (experiments 1 and 2) or three-tone sequences from (A3-D#4) (experiment 3) across each instrument's full pitch range to test their ability to generalize identification from the learned sound(s). Identification generalization over pitch varies a great deal across instruments. No significant differences were found between single-pitch and multi-pitch training or testing conditions. Identification rates can be predicted moderately well by spectrograms or modulation spectra. These results suggest that listeners use the most relevant acoustical invariance to identify musical instrument sounds, also using previous experience with the tested instruments.

Copy the In-group: Group Membership Trumps Perceived Reliability, Warmth, and Competence in a Social-Learning Task.

Surprisingly little is known about how social groups influence social learning. Although several studies have shown that people prefer to copy in-group members, these studies have failed to resolve whether group membership genuinely affects who is copied or whether group membership merely correlates with other known factors, such as similarity and familiarity. Using the minimal-group paradigm, we disentangled these effects in an online social-learning game. In a sample of 540 adults, we found a robust in-group-copying bias that (a) was bolstered by a preference for observing in-group members; (b) overrode perceived reliability, warmth, and competence; (c) grew stronger when social information was scarce; and (d) even caused cultural divergence between intermixed groups. These results suggest that people genuinely employ a copy-the-in-group social-learning strategy, which could help explain how inefficient behaviors spread through social learning and how humans maintain the cultural diversity needed for cumulative cultural evolution.

The evolution of high-fidelity social learning.

A defining feature of human culture is that knowledge and technology continually improve over time. Such cumulative cultural evolution (CCE) probably depends far more heavily on how reliably information is preserved than on how efficiently it is refined. Therefore, one possible reason that CCE appears diminished or absent in other species is that it requires accurate but specialized forms of social learning at which humans are uniquely adept. Here, we develop a Bayesian model to contrast the evolution of high-fidelity social learning, which supports CCE, against low-fidelity social learning, which does not. We find that high-fidelity transmission evolves when (1) social and (2) individual learning are inexpensive, (3) traits are complex, (4) individual learning is abundant, (5) adaptive problems are difficult and (6) behaviour is flexible. Low-fidelity transmission differs in many respects. It not only evolves when (2) individual learning is costly and (4) infrequent but also proves more robust when (3) traits are simple and (5) adaptive problems are easy. If conditions favouring the evolution of high-fidelity transmission are stricter (3 and 5) or harder to meet (2 and 4), this could explain why social learning is common, but CCE is rare.

Comparing fitness and drift explanations of Neanderthal replacement.

There is a general consensus among archaeologists that replacement of Neanderthals by anatomically modern humans in Europe occurred around 40-35 ka. However, the causal mechanism for this replacement continues to be debated. Proposed models have featured either fitness advantages in favour of anatomically modern humans or invoked neutral drift under various preconditions. Searching for specific fitness advantages in the archaeological record has proven difficult, as these may be obscured, absent or subject to interpretation. To bridge this gap, we rigorously compare the system-level properties of fitness- and drift-based explanations of Neanderthal replacement. Our stochastic simulations and analytical predictions show that, although both fitness and drift can produce replacement, they present important differences in (i) required initial conditions, (ii) reliability, (iii) time to replacement, and (iv) path to replacement (population histories). These results present useful opportunities for comparison with archaeological and genetic data. We find greater agreement between the available empirical evidence and the system-level properties of replacement by differential fitness, rather than by neutral drift.

Modelling the spread of innovation in wild birds.

We apply three plausible algorithms in agent-based computer simulations to recent experiments on social learning in wild birds. Although some of the phenomena are simulated by all three learning algorithms, several manifestations of social conformity bias are simulated by only the approximate majority (AM) algorithm, which has roots in chemistry, molecular biology and theoretical computer science. The simulations generate testable predictions and provide several explanatory insights into the diffusion of innovation through a population. The AM algorithm's success raises the possibility of its usefulness in studying group dynamics more generally, in several different scientific domains. Our differential-equation model matches simulation results and provides mathematical insights into the dynamics of these algorithms.

Specialized hybrid learners resolve Rogers' paradox about the adaptive value of social learning.

Culture is considered an evolutionary adaptation that enhances reproductive fitness. A common explanation is that social learning, the learning mechanism underlying cultural transmission, enhances mean fitness by avoiding the costs of individual learning. This explanation was famously contradicted by Rogers (1988), who used a simple mathematical model to show that cheap social learning can invade a population without raising its mean fitness. He concluded that some crucial factor remained unaccounted for, which would reverse this surprising result. Here we extend this model to include a more complex environment and limited resources, where individuals cannot reliably learn everything about the environment on their own. Under such conditions, cheap social learning evolves and enhances mean fitness, via hybrid learners capable of specializing their individual learning. We then show that while spatial or social constraints hinder the evolution of hybrid learners, a novel social learning strategy, complementary copying, can mitigate these effects.