Toward physics of the mind: Concepts, emotions, consciousness, and symbols

Mathematical approaches to modeling the mind since the 1950s are reviewed, including artificial intelligence, pattern recognition, and neural networks. I analyze difficulties faced by these algorithms and neural networks and relate them to the fundamental inconsistency of logic discovered by Gödel. Mathematical discussions are related to those in neurobiology, psychology, cognitive science, and philosophy. Higher cognitive functions are reviewed including concepts, emotions, instincts, understanding, imagination, intuition, consciousness. Then, I describe a mathematical formulation, unifying the mind mechanisms in a psychologically and neuro-biologically plausible system. A mechanism of the knowledge instinct drives our understanding of the world and serves as a foundation for higher cognitive functions. This mechanism relates aesthetic emotions and perception of beauty to “everyday” functioning of the mind. The article reviews mechanisms of human symbolic ability. I touch on future directions: joint evolution of the mind, language, consciousness, and cultures; mechanisms of differentiation and synthesis; a manifold of aesthetic emotions in music and differentiated instinct for knowledge. I concentrate on elucidating the first principles; review aspects of the theory that have been proven in laboratory research, relationships between the mind and brain; discuss unsolved problems, and outline a number of theoretical predictions, which will have to be tested in future mathematical simulations and neuro-biological research.     

Unforgettable film music: The role of emotion in episodic long-term memory for music

Background  

Specific pieces of music can elicit strong emotions in listeners and, possibly in connection with these emotions, can be remembered even years later. However, episodic memory for emotional music compared with less emotional music has not yet been examined. We investigated whether emotional music is remembered better than less emotional music. Also, we examined the influence of musical structure on memory performance.     

The origins of language and the evolution of music: A comparative perspective

According to Darwin [Darwin, CR. The descent of man, and selection in relation to sex. London: John Murray; 1871], the human musical faculty 'must be ranked amongst the most mysterious with which he is endowed'. Music is a human cultural universal that serves no obvious adaptive purpose, making its evolution a puzzle for evolutionary biologists. This review examines Darwin's hypothesis of similarities between language and music indicating a shared evolutionary history. In particular, the fact that both are human universals, have phrase structure, and entail learning and cultural transmission, suggests that any theory of the evolution of language will have implications for the evolution of music, and vice versa. The argument starts by describing variable predispositional musical capabilities and the ontogeny of prosodic communication in human infants and young children, presenting comparative data regarding communication systems commonly present in living nonhuman primate species. Like language, the human music faculty is based on a suite of abilities, some of which are shared with other primates and some of which appear to be uniquely human. Each of these subcomponents may have a different evolutionary history, and should be discussed separately. After briefly considering possible functions of human music for language acquisition, the review ends by discussing the phylogenetic history of music. It concludes that many strands of evidence support Darwin's hypothesis of an intermediate stage of human evolutionary history, characterized by a communication system that resembled music more closely than language, but was identical to neither. This pre-linguistic system, which could probably referred to as "prosodic protolanguage", provided a precursor for both modern language and music.     

From everyday emotions to aesthetic emotions: Towards a unified theory of musical emotions

The sound of music may arouse profound emotions in listeners. But such experiences seem to involve a ‘paradox’, namely that music – an abstract form of art, which appears removed from our concerns in everyday life – can arouse emotions – biologically evolved reactions related to human survival. How are these (seemingly) non-commensurable phenomena linked together? Key is to understand the processes through which sounds are imbued with meaning. It can be argued that the survival of our ancient ancestors depended on their ability to detect patterns in sounds, derive meaning from them, and adjust their behavior accordingly. Such an ecological perspective on sound and emotion forms the basis of a recent multi-level framework that aims to explain emotional responses to music in terms of a large set of psychological mechanisms. The goal of this review is to offer an updated and expanded version of the framework that can explain both ‘everyday emotions’ and ‘aesthetic emotions’. The revised framework – referred to as BRECVEMA – includes eight mechanisms: Brain Stem Reflex, Rhythmic Entrainment, Evaluative Conditioning, Contagion, Visual Imagery, Episodic Memory, Musical Expectancy, and Aesthetic Judgment. In this review, it is argued that all of the above mechanisms may be directed at information that occurs in a ‘musical event’ (i.e., a specific constellation of music, listener, and context). Of particular significance is the addition of a mechanism corresponding to aesthetic judgments of the music, to better account for typical ‘appreciation emotions’ such as admiration and awe. Relationships between aesthetic judgments and other mechanisms are reviewed based on the revised framework. It is suggested that the framework may contribute to a long-needed reconciliation between previous approaches that have conceptualized music listeners? responses in terms of either ‘everyday emotions’ or ‘aesthetic emotions’.     

Neural network modeling of emotion

This article reviews the history and development of computational neural network modeling of cognitive and behavioral processes that involve emotion. The exposition starts with models of classical conditioning dating from the early 1970s. Then it proceeds toward models of interactions between emotion and attention. Then models of emotional influences on decision making are reviewed, including some speculative (not and not yet simulated) models of the evolution of decision rules. Through the late 1980s, the neural networks developed to model emotional processes were mainly embodiments of significant functional principles motivated by psychological data. In the last two decades, network models of these processes have become much more detailed in their incorporation of known physiological properties of specific brain regions, while preserving many of the psychological principles from the earlier models.Most network models of emotional processes so far have dealt with positive and negative emotion in general, rather than specific emotions such as fear, joy, sadness, and anger. But a later section of this article reviews a few models relevant to specific emotions: one family of models of auditory fear conditioning in rats, and one model of induced pleasure enhancing creativity in humans. Then models of emotional disorders are reviewed. The article concludes with philosophical statements about the essential contributions of emotion to intelligent behavior and the importance of quantitative theories and models to the interdisciplinary enterprise of understanding the interactions of emotion, cognition, and behavior.     

Affect-Logic,Embodiment, Synergetics,and the Free Energy Principle: New Approaches to the Understanding and Treatment of Schizophrenia

This theoretical paper explores the affect-logic approach to schizophrenia in light of the general complexity theories of cognition: embodied cognition, Haken’s synergetics, and Friston’s free energy principle. According to affect-logic, the mental apparatus is an embodied system open to its environment, driven by bioenergetic inputs of emotions. Emotions are rooted in goal-directed embodied states selected by evolutionary pressure for coping with specific situations such as fight, flight, attachment, and others. According to synergetics, nonlinear bifurcations and the emergence of new global patterns occur in open systems when control parameters reach a critical level. Applied to the emergence of psychotic states, synergetics and the proposed energetic understanding of emotions lead to the hypothesis that critical levels of emotional tension may be responsible for the transition from normal to psychotic modes of functioning in vulnerable individuals. In addition, the free energy principle through learning suggests that psychotic symptoms correspond to alternative modes of minimizing free energy, which then entails distorted perceptions of the body, self, and reality. This synthetic formulation has implications for novel therapeutic and preventive strategies in the treatment of psychoses, among these are milieu-therapeutic approaches of the Soteria type that focus on a sustained reduction of emotional tension and phenomenologically oriented methods for improving the perception of body, self, and reality.     

Pitch discrimination abilities in classical Arab-music listeners

The current experiment examined pitch discrimination thresholds in listeners of classical Arab music, and listeners of Western popular music. Classical Arab music is characterized by modes (“Maqamat”, plural of “Maqam” in Arabic language) of which the smallest interval is a quarter tone. In contrast, the smallest interval in Western music is a semitone. We hypothesized that daily exposure to a musical style involving minuscule pitch differences may have a positive effect on pitch discrimination abilities. Results demonstrate superior pitch discrimination abilities in the classical Arab music listeners. These results indicate that musical cultures may differ in their influence on perceptual abilities, depending on their basic acoustic characteristics.     

Pitch-interval discrimination and musical expertise: Is the semitone a perceptual boundary?

The ability to discriminate pitch changes (or intervals) is foundational for speech and music. In an auditory psychophysical experiment, musicians and non-musicians were tested with fixed- and roving-pitch discrimination tasks to investigate the effects of musical expertise on interval discrimination. The tasks were administered parametrically to assess performance across varying pitch distances between intervals. Both groups showed improvements in fixed-pitch interval discrimination as a function of increasing interval difference. Only musicians showed better roving-pitch interval discrimination as interval differences increased, suggesting that this task was too demanding for non-musicians. Musicians had better interval discrimination than non-musicians across most interval differences in both tasks. Interestingly, musicians exhibited improved interval discrimination starting at interval differences of 100 cents (a semitone in Western music), whereas non-musicians showed enhanced discrimination at interval differences exceeding 125 cents. Although exposure to Western music and speech may help establish a basic interval-discrimination threshold between 100 and 200 cents (intervals that occur often in Western languages and music), musical training presumably enhances auditory processing and reduces this threshold to a semitone. As musical expertise does not decrease this threshold beyond 100 cents, the semitone may represent a musical training-induced intervallic limit to acoustic processing.     

A Computational Model of Tonal Tension Profile of Chord Progressions in the Tonal Interval Space

In tonal music, musical tension is strongly associated with musical expression, particularly with expectations and emotions. Most listeners are able to perceive musical tension subjectively, yet musical tension is difficult to be measured objectively, as it is connected with musical parameters such as rhythm, dynamics, melody, harmony, and timbre. Musical tension specifically associated with melodic and harmonic motion is called tonal tension. In this article, we are interested in perceived changes of tonal tension over time for chord progressions, dubbed tonal tension profiles. We propose an objective measure capable of capturing tension profile according to different tonal music parameters, namely, tonal distance, dissonance, voice leading, and hierarchical tension. We performed two experiments to validate the proposed model of tonal tension profile and compared against Lerdahl’s model and MorpheuS across 12 chord progressions. Our results show that the considered four tonal parameters contribute differently to the perception of tonal tension. In our model, their relative importance adopts the following weights, summing to unity: dissonance (0.402), hierarchical tension (0.246), tonal distance (0.202), and voice leading (0.193). The assumption that listeners perceive global changes in tonal tension as prototypical profiles is strongly suggested in our results, which outperform the state-of-the-art models.     

Composing Music Inspired by Sculpture: A Cross-Domain Mapping and Genetic Algorithm Approach

In this article, a system that takes a 3D model of a sculpture as starting point to compose music is presented. We raised the hypothesis that cross-domain mapping can be an approach to model inspiration. The semantic meaning of the sculpture is not used directly but rather a more abstract approach was used. A Genetic Algorithm was used to obtain results with more musical interest. The results were promising: the majority of the participants gave a classification of 4 out of 5 to the preferred interpretations of the compositions and related them to the respective sculpture. This is a step toward a possible model for inspiration.     

一种音乐情绪参数化的方法

针对目前基于情绪的音乐分类研究存在的弊端,为了方便音乐检索,本文提出一种音乐情绪参数化的方法。该方法通过提取反映音乐情绪的特征向量,然后利用fisher算法进行维数压缩,再通过大量的音乐样本训练得到节奏、音调和音色3个描述音乐情绪的参数,参数的大小反映了情绪的强弱。实验结果表明,音乐情绪参数化的结果符合音乐实际的情绪。     

Fusion research and international scientific collaboration

Physics and technology have played a major role in shaping the development, performance, interpretation and composition of music for many centuries. From the twentieth century, electronics and communications have provided recording and broadcasting that gives access to worldwide music and performers of many musical genres. Early scientific influence came via improved or totally new instruments, plus larger and better concert halls. Instrument examples range from developments of violins or pianos to keyed and valved wood wind and brass that offer chromatic performance. New sounds appeared by inventions of totally new instruments, such as the saxophone or the Theremin, to all the modern electronic influence on keyboards and synthesisers. Electronic variants of guitars are effectively new instruments that have spawned totally original musical styles. All such advances have encouraged more virtuosic performance, larger halls, a wider range of audiences and a consequent demand and ability of composers to meet the new challenges. Despite this immense impact, the role of physics and technology over the last few centuries has mostly been ignored, although it was often greater than any links to arts or culture. Recorded and broadcast music has enhanced our expectations on performance and opened gateways to purely electronically generated sounds, of the now familiar electronic keyboards and synthesisers. This brief review traces some of the highlights in musical evolution that were enabled by physics and technology and their impact on the musical scene. The pattern from the past is clear, and so some of the probable advances in the very near future are also predicted. Many are significant as they will impinge on our appreciation of both current and past music, as well as compositional styles. Mention is made of the difference in sound between live and recorded music and the reasons why none of us ever have precisely the same musical experience twice, even from the same recording. Similarly, it is impossible to appreciate earlier music from the same perspective as occurred when it was first composed and performed, or indeed from later interpretations.     

The quartet theory of human emotions: An integrative and neurofunctional model

Despite an explosion of research in the affective sciences during the last few decades, interdisciplinary theories of human emotions are lacking. Here we present a neurobiological theory of emotions that includes emotions which are uniquely human (such as complex moral emotions), considers the role of language for emotions, advances the understanding of neural correlates of attachment-related emotions, and integrates emotion theories from different disciplines. We propose that four classes of emotions originate from four neuroanatomically distinct cerebral systems. These emotional core systems constitute a quartet of affect systems: the brainstem-, diencephalon-, hippocampus-, and orbitofrontal-centred affect systems. The affect systems were increasingly differentiated during the course of evolution, and each of these systems generates a specific class of affects (e.g., ascending activation, pain/pleasure, attachment-related affects, and moral affects). The affect systems interact with each other, and activity of the affect systems has effects on – and interacts with – biological systems denoted here as emotional effector systems. These effector systems include motor systems (which produce actions, action tendencies, and motoric expression of emotion), peripheral physiological arousal, as well as attentional and memory systems. Activity of affect systems and effector systems is synthesized into an emotion percept (pre-verbal subjective feeling), which can be transformed (or reconfigured) into a symbolic code such as language. Moreover, conscious cognitive appraisal (involving rational thought, logic, and usually language) can regulate, modulate, and partly initiate, activity of affect systems and effector systems. Our emotion theory integrates psychological, neurobiological, sociological, anthropological, and psycholinguistic perspectives on emotions in an interdisciplinary manner, aiming to advance the understanding of human emotions and their neural correlates.     

Helmholtz, Riemann, and the Sirens: Sound, Color, and the “Problem of Space”

Emerging from music and the visual arts, questions about hearing and seeing deeply affected Hermann Helmholtz’s and Bernhard Riemann’s contributions to what became called the “problem of space [Raumproblem],” which in turn influenced Albert Einstein’s approach to general relativity. Helmholtz’s physiological investigations measured the time dependence of nerve conduction and mapped the three-dimensional manifold of color sensation. His concurrent studies on hearing illuminated musical evidence through experiments with mechanical sirens that connect audible with visible phenomena, especially how the concept of frequency unifies motion, velocity, and pitch. Riemann’s critique of Helmholtz’s work on hearing led Helmholtz to respond and study Riemann’s then-unpublished lecture on the foundations of geometry. During 1862–1870, Helmholtz applied his findings on the manifolds of hearing and seeing to the Raumproblem by supporting the quadratic distance relation Riemann had assumed as his fundamental hypothesis about geometrical space. Helmholtz also drew a “close analogy … in all essential relations between the musical scale and space.” These intersecting studies of hearing and seeing thus led to reconsideration and generalization of the very concept of “space,” which Einstein shaped into the general manifold of relativistic space-time.     

Modeling the cultural evolution of language

The paper surveys recent research on language evolution, focusing in particular on models of cultural evolution and how they are being developed and tested using agent-based computational simulations and robotic experiments. The key challenges for evolutionary theories of language are outlined and some example results are discussed, highlighting models explaining how linguistic conventions get shared, how conceptual frameworks get coordinated through language, and how hierarchical structure could emerge. The main conclusion of the paper is that cultural evolution is a much more powerful process that usually assumed, implying that less innate structures or biases are required and consequently that human language evolution has to rely less on genetic evolution.     

Markov chains or the game of structure and chance

Markov chains provide us with a powerful tool for studying the structure of graphs and databases in details. We review the method of generalized inverses for Markov chains and apply it for the analysis of urban structures, evolution of languages, and musical compositions. We also discuss a generalization of Lévy flights over large complex networks and study the interplay between the nonlinearity of diffusion process and the topological structure of the network.     

Darwinian demons, evolutionary complexity, and information maximization

Natural selection is shown to be an extended instance of a Maxwell's demon device. A demonic selection principle is introduced that states that organisms cannot exceed the complexity of their selective environment. Thermodynamic constraints on error repair impose a fundamental limit to the rate that information can be transferred from the environment (via the selective demon) to the genome. Evolved mechanisms of learning and inference can overcome this limitation, but remain subject to the same fundamental constraint, such that plastic behaviors cannot exceed the complexity of reward signals. A natural measure of evolutionary complexity is provided by mutual information, and niche construction activity--the organismal contribution to the construction of selection pressures--might in principle lead to its increase, bounded by thermodynamic free energy required for error correction.     

An investigation into the linear and nonlinear correlation of two music walk sequences

In order to investigate the features of a multiple-part musical score which enhance its appeal to the listener’s ear, this study performs a robust analysis of the correlation between two musical sequences. In the proposed approach, a series of notes are extracted from seven well-known classical pieces of music and are converted into one-variable “music walks”. The linear correlation between pairs of music walks is assessed using the conventional linear correlation coefficient, while the nonlinear correlation is examined using the mutual information concept. The results show that even though two musical time walks may exhibit virtually no linear correlation, they invariably have a certain degree of nonlinear correlation. In other words, to truly understand the correlation between two musical sequences, it is necessary to consider not only the linear correlation between them, but also the nonlinear correlation. In addition, it is shown that the normalized mutual information coefficient between musical sequences has a relatively low value and varies significantly over the course of the musical score. Thus, it can be inferred that the appeal of a musical score stems at least in part from significant variations in both the melody and the rhythm of the constituent parts such that the overall score has a rich and unpredictable property.     

YIN,a fundamental frequency estimator for speech and music

An algorithm is presented for the estimation of the fundamental frequency (F0) of speech or musical sounds. It is based on the well-known autocorrelation method with a number of modifications that combine to prevent errors. The algorithm has several desirable features. Error rates are about three times lower than the best competing methods, as evaluated over a database of speech recorded together with a laryngograph signal. There is no upper limit on the frequency search range, so the algorithm is suited for high-pitched voices and music. The algorithm is relatively simple and may be implemented efficiently and with low latency, and it involves few parameters that must be tuned. It is based on a signal model (periodic signal) that may be extended in several ways to handle various forms of aperiodicity that occur in particular applications. Finally, interesting parallels may be drawn with models of auditory processing.