Discrimination of brain's neuroelectric responses by a decision-making function

Utku, Haluk; Erzengin, Ömer Utku; Çakmak, Emine D.; Karakaş, Sirel

doi:10.1016/s0165-0270(01)00519-2

Cited by 8 publications

(5 citation statements)

References 27 publications

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“…(i) Mathematical and theoretical approaches, including those in the last decades (a) the concepts of chaos, entropy, (b) modeling with neural networks, (c) interpretation of frequency domain approach (newly with wavelet analysis), (d) spatial coherence and temporal coherence [Bullock, 1989;Petsche, 1987;von Stein, 2000]. (ii) Psychological strategies with the use of behavioral paradigms and application of neuropsychological tests [Karakaş et al, 2002;Utku et al, 2002;Galambos et al,1981]. (iii) An important strategy, which is not included in Fig.…”

Section: Why the Eeg Is Important?mentioning

confidence: 99%

Macrodynamics of Electrical Activity in the Whole Brain

Başar

2004

Int. J. Bifurcation Chaos

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The general problem of brain mechanisms involved in perception can now be studied directly by means of new analysis–methods for the activity of large population of neurons. These methods range from indirect means of measuring changes in cerebral blood flow in local regions of the human cortex (functional magnetic resonance imaging, fMRI), or changes in the electrical activity of the human brain with EEG-recording with topological distributed macroelectrodes, to the use of chronically implanted multiple microelectrodes in primates. f MRI has the disadvantage of low temporal resolution and with multiple microelectrodes long distance measurements cannot yet be properly performed. Accordingly, recording of macro-activity (EEG/ERP or MEG) with a time resolution of millisecond-range is the most possibly adequate method to measure the dynamic properties of memory and the integrative brain function. Since neuroscientists have come to the general conclusion that large numbers of different brain regions have to cooperate for any brain function, the analysis of relationships between different regions of the brain is becoming more and more important. Before new progresses and importance of EEG studies research became clear, scientists working with macrodynamics of the brain had a long way to go, in order to elucidate brain functioning. In this tutorial report we explain in a narrative way the developments leading to the concept of Macrodynamics in search of an integrative brain function. Moreover, elements of a brain theory, which we call neurons-brain theory describing the dynamics of electrical activity in the whole brain, are introduced. The concept of superbinding in integrative brain function, which emerged from experimental data, is a consequence of this theory.

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Section: Why the Eeg Is Important?mentioning

confidence: 99%

Macrodynamics of Electrical Activity in the Whole Brain

Başar

2004

Int. J. Bifurcation Chaos

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“…Falkenstein et al, 1999;Righi, Mecacci, & Viggiano, 2009;Sanz et al, 2001), we associate P3 amplitude and the inhibition function in our research. In other studies, the P3 (including so-call 'P3a' and 'P3b') is also suggested to be linked with different types of cognitive abilities, such as working memory updating (Donchin & Coles, 1988), allocation of processing resources (Imai & Tsuji, 2004;Utku, Erzengin, Cakmak, & Karakas, 2002), perceptual awareness (Hon, Epstein, Owen, & Duncan, 2006), sensory discrimination (Molnar, 1999), revision of the mental representation (Pontifex, Hillman, & Polich, 2009), or cognitive self-evaluation (Righi et al, 2009). It would be worthwhile to see if the P3 actually reflects the activity of a fundamental cognitive component of these abilities.…”

Section: Resultsmentioning

confidence: 99%

Influence of Trait-Anxiety on Inhibition Function: Evidence from ERP Studies

Luo¹,

Gu²,

Huang³

2011

Different Views of Anxiety Disorders

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“…Finally, it treats EEG signals as temporally continuous and nonlinear, thus remaining more faithful to the data analyzed. At the current time, it is not clear how this last point advantages our technique compared to other statistical approaches available (e.g., [15][16][17][18][19]); more direct comparisons will be required to investigate this question.…”

Section: Discussionmentioning

confidence: 99%

Functional data analysis of cognitive events in EEG

Thivierge

2007

2007 IEEE International Conference on Systems, Man and Cybernetics

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This paper investigates a data-driven approach to the detection of statistically reliable fluctuations in electroencephalographic (EEG) brain waves. The main advantage of this approach is the ability to automatically identify meaningful sources of variation in signals dominated by large spatiotemporal fluctuations due to noise. The approach is tested on artificial data as well as on EEG signals obtained in a cognitive experiment. Results not only show that the approach can robustly identify meaningful variations in brain activity, but also open possible applications to brain-computer interfaces based on single-trial analyses.

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Discrimination of brain's neuroelectric responses by a decision-making function

Cited by 8 publications

References 27 publications

Macrodynamics of Electrical Activity in the Whole Brain

Macrodynamics of Electrical Activity in the Whole Brain

Influence of Trait-Anxiety on Inhibition Function: Evidence from ERP Studies

Functional data analysis of cognitive events in EEG

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