Sleep Stages as Bifurcations at the Edge of Chaos

2011 ◽  
Author(s):  
Gaetano L. Aiello
Keyword(s):  
Sleep Stages ◽  
Edge Of Chaos

Patterns of Implicit Learning Below the Level of Conscious Knowledge

2010 ◽  
Vol 24 (2) ◽  
pp. 91-101 ◽  
Author(s):  
Juliana Yordanova ◽  
Rolf Verleger ◽  
Ullrich Wagner ◽  
Vasil Kolev
Keyword(s):  
Implicit Learning ◽  
Explicit Knowledge ◽  
Implicit Knowledge ◽  
Knowledge Generation ◽  
Sleep Stages ◽  
Implicit Processing ◽  
Implicit Processes ◽  
Late Night ◽  
On Line ◽  
On Line Learning

The objective of the present study was to evaluate patterns of implicit processing in a task where the acquisition of explicit and implicit knowledge occurs simultaneously. The number reduction task (NRT) was used as having two levels of organization, overt and covert, where the covert level of processing is associated with implicit associative and implicit procedural learning. One aim was to compare these two types of implicit processes in the NRT when sleep was or was not introduced between initial formation of task representations and subsequent NRT processing. To assess the effects of different sleep stages, two sleep groups (early- and late-night groups) were used where initial training of the task was separated from subsequent retest by 3 h full of predominantly slow wave sleep (SWS) or rapid eye movement (REM) sleep. In two no-sleep groups, no interval was introduced between initial and subsequent NRT performance. A second aim was to evaluate the interaction between procedural and associative implicit learning in the NRT. Implicit associative learning was measured by the difference between the speed of responses that could or could not be predicted by the covert abstract regularity of the task. Implicit procedural on-line learning was measured by the practice-based increased speed of performance with time on task. Major results indicated that late-night sleep produced a substantial facilitation of implicit associations without modifying individual ability for explicit knowledge generation or for procedural on-line learning. This was evidenced by the higher rate of subjects who gained implicit knowledge of abstract task structure in the late-night group relative to the early-night and no-sleep groups. Independently of sleep, gain of implicit associative knowledge was accompanied by a relative slowing of responses to unpredictable items suggesting reciprocal interactions between associative and motor procedural processes within the implicit system. These observations provide evidence for the separability and interactions of different patterns of processing within implicit memory.

A New View of Creative Bifurcations and the Edge of Chaos

2012 ◽  
Author(s):  
Frederick David Abraham ◽  
Stanley Krippner ◽  
Ruth Richards
Keyword(s):  
Edge Of Chaos ◽  
New View

Mimetic Monsters

2010 ◽  
Vol 4 (1) ◽  
pp. 85-93
Author(s):  
Timothy Beal
Keyword(s):  
The Other ◽  
Jewish Tradition ◽  
Book Of Job ◽  
Edge Of Chaos ◽  
The Face ◽  
The Relationship

This article reads between two recent explorations of the relationship between religion, chaos, and the monstrous: Catherine Keller’s Face of the Deep and Author's Religion and Its Monsters. Both are oriented toward the edge of chaos and order; both see the primordial and chaotic as generative; both pursue monstrous mythological figures as divine personifications of primordial chaos; both find a deep theological ambivalences in Christian and Jewish tradition with regard to the monstrous, chaotic divine; both are critical of theological and cultural tendencies to demonize chaos and the monstrous; and finally, both read the divine speech from the whirlwind in the book of Job as a revelation of divine chaos. But whereas one sees it as a call for laughter, a chaotic life-affirming laughter with Leviathan in the face of the deep, the other sees it as an incarnation of theological horror, leaving Job and the reader overwhelmed and out-monstered by God. Must it be one way or the other? Can laughter and horror coincide in the face of the deep?

scholarly journals Classification of Brainwaves for Sleep Stages by High-Dimensional FFT Features from EEG Signals

2020 ◽  
Vol 10 (5) ◽  
pp. 1797 ◽  
Author(s):  
Mera Kartika Delimayanti ◽  
Bedy Purnama ◽  
Ngoc Giang Nguyen ◽  
Mohammad Reza Faisal ◽  
Kunti Robiatul Mahmudah ◽  
...  
Keyword(s):  
Machine Learning ◽  
Sleep Stage ◽  
Machine Learning Algorithms ◽  
High Dimensional ◽  
Sleep Stages ◽  
Eeg Signals ◽  
Stage Classification ◽  
Sleep Stage Classification ◽  
Low Dimensional

Manual classification of sleep stage is a time-consuming but necessary step in the diagnosis and treatment of sleep disorders, and its automation has been an area of active study. The previous works have shown that low dimensional fast Fourier transform (FFT) features and many machine learning algorithms have been applied. In this paper, we demonstrate utilization of features extracted from EEG signals via FFT to improve the performance of automated sleep stage classification through machine learning methods. Unlike previous works using FFT, we incorporated thousands of FFT features in order to classify the sleep stages into 2–6 classes. Using the expanded version of Sleep-EDF dataset with 61 recordings, our method outperformed other state-of-the art methods. This result indicates that high dimensional FFT features in combination with a simple feature selection is effective for the improvement of automated sleep stage classification.

scholarly journals Capturing the Development of Internal Representations in a High-Performing Deep Network for Sleep Stage Classification

2021 ◽  
Vol 2 (4) ◽  
Author(s):  
Sarun Paisarnsrisomsuk ◽  
Carolina Ruiz ◽  
Sergio A. Alvarez
Keyword(s):  
Input Data ◽  
Single Channel ◽  
Sleep Stage ◽  
Quantitative Measure ◽  
Classification Performance ◽  
Sleep Stages ◽  
Layer Depth ◽  
Human Sleep ◽  
Stage Classification ◽  
Sleep Stage Classification

AbstractDeep neural networks can provide accurate automated classification of human sleep signals into sleep stages that enables more effective diagnosis and treatment of sleep disorders. We develop a deep convolutional neural network (CNN) that attains state-of-the-art sleep stage classification performance on input data consisting of human sleep EEG and EOG signals. Nested cross-validation is used for optimal model selection and reliable estimation of out-of-sample classification performance. The resulting network attains a classification accuracy of $$84.50 \pm 0.13\%$$ 84.50 ± 0.13 % ; its performance exceeds human expert inter-scorer agreement, even on single-channel EEG input data, therefore providing more objective and consistent labeling than human experts demonstrate as a group. We focus on analyzing the learned internal data representations of our network, with the aim of understanding the development of class differentiation ability across the layers of processing units, as a function of layer depth. We approach this problem visually, using t-Stochastic Neighbor Embedding (t-SNE), and propose a pooling variant of Centered Kernel Alignment (CKA) that provides an objective quantitative measure of the development of sleep stage specialization and differentiation with layer depth. The results reveal a monotonic progression of both of these sleep stage modeling abilities as layer depth increases.

scholarly journals Sociopolitical Approach to the Launch History of the KBO League: Application of Complex System Paradigm

2021 ◽  
Vol 18 (10) ◽  
pp. 5471
Author(s):  
Won-Chul Bing
Keyword(s):  
Complex System ◽  
Bifurcation Point ◽  
Positive Feedback ◽  
Professional Baseball ◽  
Sports Culture ◽  
Edge Of Chaos ◽  
Study Results ◽  
History Of ◽  
System Paradigm ◽  
Chun Doo Hwan

The Korean Baseball Organization (KBO) League is a sports culture that Koreans love and enjoy most. However, the launch of the KBO League is related to political issues in Korea. The purpose of this study is to explain the launch history of the KBO league through a sociopolitical approach. The history of the KBO league was explained by applying a complex paradigm that explains sociocultural phenomena from a new perspective. This study used historical analysis, a qualitative study approach. Literature related to Korean professional baseball, complex system theory, sports, and politics were reviewed. This study introduces the characteristics and theory of the complex system paradigm and analyzes the history of the KBO League based on this theory. The edge of chaos, bifurcation point, positive feedback, emergence of the theory of complex system are used as elements of an overall theoretical framework to analyze the history and development of the KBO league. The study results are explained in four frameworks. First, the KBO was launched on the edge of chaos, or in the midst of social chaos provoked by Chun Doo-Hwan, who seized power through a military coup. Second, the Chun Doo-Hwan regime launched the professional baseball league to divert the public’s attention from politics to sports and provided support to construct baseball fields as venues for the national pastime. The Chun Doo-Hwan regime’s appeasement policy became a bifurcation point, which promoted the launch of the professional baseball league. Third, from the viewpoint of the complex system paradigm, the launch of the Korean baseball league was enabled by the positive feedback of the Korea professional baseball promotion committee, established in 1975 under the initiative of Korean American businessman Hong Yoon-Hee. Fourth, the Korean professional baseball league led to the emergence of the consumption culture of professional sports, and it became a national leisure and a crucial part of Korea’s sports culture. In terms of sociopolitical, the KBO League started in the dark of Korean society, but it is becoming a vitality for Korean sports culture and health.

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