<i>Information and Self-Organization: A Macroscopic Approach to Complex</i> <i>Systems</i>

Haken, Hermann; Fraser, Andrew M.

doi:10.1119/1.15809

Cited by 405 publications

(444 citation statements)

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“…Researchers have proposed the concept of metastability to account for such transition dynamics (Bressler and Kelso, 2001;Friston, 1997;Haken, 1988;Kelso and Fuchs, 1995). Based on this concept, a theory of "coordination dynamics" has been developed, which states that systems can flexibly switch from one coordination state to another (Fuchs and Jirsa, 2007;Kelso, 2010;Tognoli and Kelso, 2014).…”

Section: Microstates and The Phenomenon Of Discrete Epochs Of Cognitionmentioning

confidence: 99%

EEG microstates as a tool for studying the temporal dynamics of whole-brain neuronal networks: A review

2018

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SummaryThe present review discusses a well-established method for characterizing resting-state activity of the human brain using multichannel electroencephalography (EEG). This method involves the examination of electrical microstates in the brain, which are defined as successive short time periods during which the configuration of the scalp potential field remains semi-stable, suggesting quasi-simultaneity of activity among the nodes of largescale networks. A few prototypic microstates, which occur in a repetitive sequence across time, can be reliably identified across participants. Researchers have proposed that these microstates represent the basic building blocks of the chain of spontaneous conscious mental processes, and that their occurrence and temporal dynamics determine the quality of mentation. Several studies have further demonstrated that disturbances of mental processes associated with neurological and psychiatric conditions manifest as changes in the temporal dynamics of specific microstates. Combined EEG-fMRI studies and EEG source imaging studies have indicated that EEG microstates are closely associated with resting-state networks as identified using fMRI. The scale-free properties of the time series of EEG microstates explain why similar networks can be observed at such different time scales.The present review will provide an overview of these EEG microstates, available methods for analysis, the functional interpretations of findings regarding these microstates, and their behavioral and clinical correlates.

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Section: Microstates and The Phenomenon Of Discrete Epochs Of Cognitionmentioning

confidence: 99%

EEG microstates as a tool for studying the temporal dynamics of whole-brain neuronal networks: A review

2018

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“…Instead, open systems self-organize macroscopic structure for the purposes of offloading entropy into the environment. By doing so, they regulate energy flow and promote the emergence of macroscopic structure [44,45]. Physical time is purely sequential, described by a tenseless relational parameter [52], and characterized by a number created by the processing of 'energy of reconfiguration' information carried by "signals".…”

Section: Physical Timementioning

confidence: 99%

“…Five classical physiological bands are shown for the same raw EEG signal: delta (1-3 Hz); theta (4-6 Hz); alpha (7-13 Hz); beta (15-25 Hz); and gamma (35)(36)(37)(38)(39)(40)(41)(42)(43)(44)(45). These basic EEG bands are assumed to reflect different functional processes in the brain.…”

Section: Figure 6 Composition Of the Eeg Signal From Different Frequmentioning

confidence: 99%

Natural world physical, brain operational, and mind phenomenal space–time

Fingelkurts

Neves

2010

Physics of Life Reviews

166

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Concepts of space and time are widely developed in physics. However, there is a considerable lack of biologically plausible theoretical frameworks that can demonstrate how space and time dimensions are implemented in the activity of the most complex life-system -the brain with a mind. Brain activity is organized both temporally and spatially, thus representing space-time in the brain. Critical analysis of recent research on the space-time organization of the brain's activity pointed to the existence of so-called operational space-time in the brain. This space-time is limited to the execution of brain operations of differing complexity. During each such brain operation a particular short-term spatio-temporal pattern of integrated activity of different brain areas emerges within related operational space-time. At the same time, to have a fully functional human brain one needs to have a subjective mental experience. Current research on the subjective mental experience offers detailed analysis of space-time organization of the mind. According to this research, subjective mental experience (subjective virtual world) has definitive spatial and temporal properties similar to many physical phenomena. Based on systematic review of the propositions and tenets of brain and mind space-time descriptions, our aim in this review essay is to explore the relations between the two. To be precise, we would like to discuss the hypothesis that via the brain operational space-time the mind subjective space-time is connected to otherwise distant physical space-time reality.Key words: spatial, temporal, consciousness, cognition, operation, architectonics, EEG, field, metastability, physics, coordinative dynamics, self-organization, cortex.

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“…Phase flow patterns, however, may also underlie the perceptual recognition of distinct motor processes (Perdikis & Jirsa, 2010; see also Muchisky & Bingham, 2002). For the purposes of visual identification of human movement, visual recognition of biological motion may proceed through the extraction of these (macroscopic) dynamical structures (Haken, 1996(Haken, , 2000(Haken, , 2004. A powerful and statistically unbiased method to extract the low-dimensional dynamics in high-dimensional movement patterns is principal component analysis (PCA; see Daffertshofer, Lamoth, Meijer, and Beek, (2004) for a tutorial).…”

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confidence: 99%

Anticipation of tennis-shot direction from whole-body movement: The role of movement amplitude and dynamics

Smeeton

Huys²

2011

Human Movement Science

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While recent studies indicate that observers are able to use dynamic information to anticipate whole-body actions like tennis shots, it is less clear whether the action's amplitude may also allow for anticipation. We therefore examined the role of movement dynamics and amplitude for the anticipation of tennis shot direction. In a previous study, movement dynamics and amplitude were separated from the kinematics of tennis players' forehand groundstrokes. In the present study, these were manipulated and tennis shots were simulated. Three conditions were created in which shot direction differences were either preserved or removed: Dynamics-PresentAmplitude-Present (D P A P ), Dynamics-Present-Amplitude-Absent (D P A A ), and Dynamics-Absent-Amplitude-Present (D A A P ). Nineteen low-skill and fifteen intermediate-skill tennis players watched the simulated shots and predicted shot direction from movements prior to ball-racket contact only. Percent of correctly predicted shots per condition was measured. On average, both groups' performance was superior when the dynamics were present (the D P A P and D P A A conditions) compared to when it was absent (the D A A P condition). However, the intermediateskill players performed above chance independent of amplitude differences in shots (i.e., both the D P A P and D P A A conditions), whereas the low-skill group only performed above chance when amplitude differences were absent (the D P A A condition). These results suggest that the movement's dynamics but not their amplitude provides information from which tennis-shot direction can be anticipated.Furthermore, the successful extraction of dynamical information may be hampered by amplitude differences in a skill dependent manner.Movement Amplitude and Dynamics in Anticipation 3

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Information and Self-Organization: A Macroscopic Approach to Complex Systems

Cited by 405 publications

References 0 publications

EEG microstates as a tool for studying the temporal dynamics of whole-brain neuronal networks: A review

EEG microstates as a tool for studying the temporal dynamics of whole-brain neuronal networks: A review

Natural world physical, brain operational, and mind phenomenal space–time

Anticipation of tennis-shot direction from whole-body movement: The role of movement amplitude and dynamics

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