scholarly journals Statistical Properties of Musical Creativity: Roles of Hierarchy and Uncertainty in Statistical Learning

2021 ◽  
Vol 15 ◽  
Author(s):  
Tatsuya Daikoku ◽  
Geraint A. Wiggins ◽  
Yukie Nagai
Keyword(s):  
Brain Development ◽  
Statistical Learning ◽  
Temporal Dynamics ◽  
Intention To Use ◽  
Statistical Knowledge ◽  
Structured Information ◽  
Musical Creativity ◽  
The Brain ◽  
Shed Light ◽  
Atypical Brain Development

Creativity is part of human nature and is commonly understood as a phenomenon whereby something original and worthwhile is formed. Owing to this ability, humans can produce innovative information that often facilitates growth in our society. Creativity also contributes to esthetic and artistic productions, such as music and art. However, the mechanism by which creativity emerges in the brain remains debatable. Recently, a growing body of evidence has suggested that statistical learning contributes to creativity. Statistical learning is an innate and implicit function of the human brain and is considered essential for brain development. Through statistical learning, humans can produce and comprehend structured information, such as music. It is thought that creativity is linked to acquired knowledge, but so-called “eureka” moments often occur unexpectedly under subconscious conditions, without the intention to use the acquired knowledge. Given that a creative moment is intrinsically implicit, we postulate that some types of creativity can be linked to implicit statistical knowledge in the brain. This article reviews neural and computational studies on how creativity emerges within the framework of statistical learning in the brain (i.e., statistical creativity). Here, we propose a hierarchical model of statistical learning: statistically chunking into a unit (hereafter and shallow statistical learning) and combining several units (hereafter and deep statistical learning). We suggest that deep statistical learning contributes dominantly to statistical creativity in music. Furthermore, the temporal dynamics of perceptual uncertainty can be another potential causal factor in statistical creativity. Considering that statistical learning is fundamental to brain development, we also discuss how typical versus atypical brain development modulates hierarchical statistical learning and statistical creativity. We believe that this review will shed light on the key roles of statistical learning in musical creativity and facilitate further investigation of how creativity emerges in the brain.

scholarly journals Statistical Properties in Jazz Improvisation Underline Individuality of Musical Representation

NeuroSci ◽  
2020 ◽  
Vol 1 (1) ◽  
pp. 24-43
Author(s):  
Tatsuya Daikoku
Keyword(s):  
Statistical Learning ◽  
Time Course ◽  
Statistical Properties ◽  
Transitional Probability ◽  
Jazz Improvisation ◽  
Statistical Knowledge ◽  
Future State ◽  
Structured Information ◽  
Transitional Probabilities ◽  
The Brain

Statistical learning is an innate function in the brain and considered to be essential for producing and comprehending structured information such as music. Within the framework of statistical learning the brain has an ability to calculate the transitional probabilities of sequences such as speech and music, and to predict a future state using learned statistics. This paper computationally examines whether and how statistical learning and knowledge partially contributes to musical representation in jazz improvisation. The results represent the time-course variations in a musician’s statistical knowledge. Furthermore, the findings show that improvisational musical representation might be susceptible to higher- but not lower-order statistical knowledge (i.e., knowledge of higher-order transitional probability). The evidence also demonstrates the individuality of improvisation for each improviser, which in part depends on statistical knowledge. Thus, this study suggests that statistical properties in jazz improvisation underline individuality of musical representation.

scholarly journals Statistical learning occurs during practice while high-order rule learning during rest period

2020 ◽  
Author(s):  
Romain Quentin ◽  
Lison Fanuel ◽  
Mariann Kiss ◽  
Marine Vernet ◽  
Teodóra Vékony ◽  
...  
Keyword(s):  
Statistical Learning ◽  
Temporal Dynamics ◽  
Rule Learning ◽  
High Order ◽  
Procedural Learning ◽  
Skill Learning ◽  
Rest Periods ◽  
The Brain ◽  
General Skill ◽  
Order Rule

AbstractKnowing when the brain learns is crucial for both the comprehension of memory formation and consolidation, and for developing new training and neurorehabilitation strategies in healthy and patient populations. Recently, a rapid form of offline learning developing during short rest periods has been shown to account for most of procedural learning, leading to the hypothesis that the brain mainly learns during rest between practice periods. Nonetheless, procedural learning has several subcomponents not disentangled in previous studies investigating learning dynamics, such as acquiring the statistical regularities of the task, or else the high-order rules that regulate its organization. Here, we analyzed 506 behavioral sessions of implicit visuomotor deterministic and probabilistic sequence learning tasks, allowing the distinction between general skill learning, statistical learning and high-order rule learning. Our results show that the temporal dynamics of apparently simultaneous learning processes differ. While general skill and high-order rule learning are acquired offline, statistical learning is evidenced online. These findings open new avenues on the short-scale temporal dynamics of learning and memory consolidation and reveal a fundamental distinction between statistical and high-order rule learning, the former benefiting from online evidence accumulation and the latter requiring short rest periods for rapid consolidation.

scholarly journals Statistical learning occurs during practice while high-order rule learning during rest period

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Romain Quentin ◽  
Lison Fanuel ◽  
Mariann Kiss ◽  
Marine Vernet ◽  
Teodóra Vékony ◽  
...  
Keyword(s):  
Statistical Learning ◽  
Temporal Dynamics ◽  
Rule Learning ◽  
Rest Period ◽  
High Order ◽  
Procedural Learning ◽  
Skill Learning ◽  
Rest Periods ◽  
The Brain ◽  
Order Rule

AbstractKnowing when the brain learns is crucial for both the comprehension of memory formation and consolidation and for developing new training and neurorehabilitation strategies in healthy and patient populations. Recently, a rapid form of offline learning developing during short rest periods has been shown to account for most of procedural learning, leading to the hypothesis that the brain mainly learns during rest between practice periods. Nonetheless, procedural learning has several subcomponents not disentangled in previous studies investigating learning dynamics, such as acquiring the statistical regularities of the task, or else the high-order rules that regulate its organization. Here we analyzed 506 behavioral sessions of implicit visuomotor deterministic and probabilistic sequence learning tasks, allowing the distinction between general skill learning, statistical learning, and high-order rule learning. Our results show that the temporal dynamics of apparently simultaneous learning processes differ. While high-order rule learning is acquired offline, statistical learning is evidenced online. These findings open new avenues on the short-scale temporal dynamics of learning and memory consolidation and reveal a fundamental distinction between statistical and high-order rule learning, the former benefiting from online evidence accumulation and the latter requiring short rest periods for rapid consolidation.

Flow

2019 ◽  
pp. 167-185
Author(s):  
Jeanne Nakamura ◽  
Dwight C.K. Tse ◽  
Shannon Shankland
Keyword(s):  
Intrinsic Motivation ◽  
Temporal Dynamics ◽  
Psychological State ◽  
Flow Experience ◽  
Flow State ◽  
Shed Light

Flow is an optimal psychological state characterized by the enjoyment of deep absorption in what one is doing. This psychological state is autotelic (i.e., rewarding in itself); experiencing flow intrinsically motivates individuals to engage in activities that are conducive to it. Research on the flow experience has shed light on the phenomenology of intrinsic motivation since Csikszentmihalyi (1975) first introduced the flow concept. This chapter (a) describes the dimensions and conditions of the flow experience, (b) reviews research on its psychological covariates, (c) highlights conceptual and operational differences among four flow-related constructs, (d) discusses theory and research on the temporal dynamics of flow experience, and (e) summarizes research on the neurophysiology of the flow state.

scholarly journals Stability and flexibility in multisensory sampling: insights from perceptual illusions

2019 ◽  
Vol 121 (5) ◽  
pp. 1588-1590 ◽  
Author(s):  
Luca Casartelli
Keyword(s):  
Temporal Dynamics ◽  
Multisensory Processing ◽  
General Idea ◽  
Perceptual Illusions ◽  
The Brain ◽  
Multisensory Processes

Neural, oscillatory, and computational counterparts of multisensory processing remain a crucial challenge for neuroscientists. Converging evidence underlines a certain efficiency in balancing stability and flexibility of sensory sampling, supporting the general idea that multiple parallel and hierarchically organized processing stages in the brain contribute to our understanding of the (sensory/perceptual) world. Intriguingly, how temporal dynamics impact and modulate multisensory processes in our brain can be investigated benefiting from studies on perceptual illusions.

scholarly journals Resilience, plasticity and robustness in gene expression during aging in the brain of outbred deer mice

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
E Soltanmohammadi ◽  
Y Zhang ◽  
I Chatzistamou ◽  
H. Kiaris
Keyword(s):  
Gene Expression ◽  
Cholesterol Metabolism ◽  
Expression Profiles ◽  
Deer Mice ◽  
Abrupt Changes ◽  
Transcriptional Changes ◽  
Thrombospondin 4 ◽  
Whole Transcriptome ◽  
The Brain ◽  
Shed Light

Abstract Background Genes that belong to the same network are frequently co-expressed, but collectively, how the coordination of the whole transcriptome is perturbed during aging remains unclear. To explore this, we calculated the correlation of each gene in the transcriptome with every other, in the brain of young and older outbred deer mice (P. leucopus and P. maniculatus). Results In about 25 % of the genes, coordination was inversed during aging. Gene Ontology analysis in both species, for the genes that exhibited inverse transcriptomic coordination during aging pointed to alterations in the perception of smell, a known impairment occurring during aging. In P. leucopus, alterations in genes related to cholesterol metabolism were also identified. Among the genes that exhibited the most pronounced inversion in their coordination profiles during aging was THBS4, that encodes for thrombospondin-4, a protein that was recently identified as rejuvenation factor in mice. Relatively to its breadth, abolishment of coordination was more prominent in the long-living P. leucopus than in P. maniculatus but in the latter, the intensity of de-coordination was higher. Conclusions There sults suggest that aging is associated with more stringent retention of expression profiles for some genes and more abrupt changes in others, while more subtle but widespread changes in gene expression appear protective. Our findings shed light in the mode of the transcriptional changes occurring in the brain during aging and suggest that strategies aiming to broader but more modest changes in gene expression may be preferrable to correct aging-associated deregulation in gene expression.

scholarly journals The brain timewise: how timing shapes and supports brain function

2015 ◽  
Vol 370 (1668) ◽  
pp. 20140170 ◽  
Author(s):  
Riitta Hari ◽  
Lauri Parkkonen
Keyword(s):  
Human Brain ◽  
Brain Imaging ◽  
Brain Function ◽  
Temporal Dynamics ◽  
Generative Models ◽  
Network Activity ◽  
Brain Diseases ◽  
Specific Information ◽  
Non Invasive ◽  
The Brain

We discuss the importance of timing in brain function: how temporal dynamics of the world has left its traces in the brain during evolution and how we can monitor the dynamics of the human brain with non-invasive measurements. Accurate timing is important for the interplay of neurons, neuronal circuitries, brain areas and human individuals. In the human brain, multiple temporal integration windows are hierarchically organized, with temporal scales ranging from microseconds to tens and hundreds of milliseconds for perceptual, motor and cognitive functions, and up to minutes, hours and even months for hormonal and mood changes. Accurate timing is impaired in several brain diseases. From the current repertoire of non-invasive brain imaging methods, only magnetoencephalography (MEG) and scalp electroencephalography (EEG) provide millisecond time-resolution; our focus in this paper is on MEG. Since the introduction of high-density whole-scalp MEG/EEG coverage in the 1990s, the instrumentation has not changed drastically; yet, novel data analyses are advancing the field rapidly by shifting the focus from the mere pinpointing of activity hotspots to seeking stimulus- or task-specific information and to characterizing functional networks. During the next decades, we can expect increased spatial resolution and accuracy of the time-resolved brain imaging and better understanding of brain function, especially its temporal constraints, with the development of novel instrumentation and finer-grained, physiologically inspired generative models of local and network activity. Merging both spatial and temporal information with increasing accuracy and carrying out recordings in naturalistic conditions, including social interaction, will bring much new information about human brain function.

Bone-brain crosstalk and potential associated diseases

2016 ◽  
Vol 28 (2) ◽  
Author(s):  
Audrey Rousseaud ◽  
Stephanie Moriceau ◽  
Mariana Ramos-Brossier ◽  
Franck Oury
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
Brain Development ◽  
Cognitive Functions ◽  
Intimate Relationship ◽  
Whole Body ◽  
Reciprocal Relationships ◽  
Skeletal Homeostasis ◽  
The Central Nervous System ◽  
The Brain

AbstractReciprocal relationships between organs are essential to maintain whole body homeostasis. An exciting interplay between two apparently unrelated organs, the bone and the brain, has emerged recently. Indeed, it is now well established that the brain is a powerful regulator of skeletal homeostasis via a complex network of numerous players and pathways. In turn, bone via a bone-derived molecule, osteocalcin, appears as an important factor influencing the central nervous system by regulating brain development and several cognitive functions. In this paper we will discuss this complex and intimate relationship, as well as several pathologic conditions that may reinforce their potential interdependence.

Neurodevelopment in the first three years: implications for child development, professional practice and policy

2014 ◽  
Vol 9 (2) ◽  
pp. 154-164 ◽  
Author(s):  
Danya Glaser
Keyword(s):  
Brain Development ◽  
Brain Activity ◽  
Brain Maturation ◽  
Policy And Practice ◽  
Content Type ◽  
Key Issues ◽  
And Function ◽  
The Relationship ◽  
The Brain ◽  
Brain Connections

Purpose – The purpose of this paper is to outline brain structure and development, the relationship between environment and brain development and implications for practice. Design/methodology/approach – The paper is based on a selected review of the literature and clinical experience. Findings – While genetics determine the sequence of brain maturation, the nature of brain development and functioning is determined by the young child's caregiving environment, to which the developing brain constantly adapts. The absence of input during sensitive periods may lead to later reduced functioning. There is an undoubted immediate equivalence between every mind function – emotion, cognition, behaviour and brain activity, although the precise location of this in the brain is only very partially determinable, since brain connections and function are extremely complex. Originality/value – This paper provides an overview of key issues in neurodevelopment relating to the development of young children, and implications for policy and practice.

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