scholarly journals Multifractals Properties on the Near Infrared Spectroscopy of Human Brain Hemodynamic

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
Truong Quang Dang Khoa ◽  
Vo Van Toi

Nonlinear physics presents us with a perplexing variety of complicated fractal objects and strange sets. Naturally one wishes to characterize the objects and describe the events occurring on them. Moreover, most time series found in “real-life” applications appear quite noisy. Therefore, at almost every point in time, they cannot be approximated either by the Taylor series or by the Fourier series of just a few terms. Many experimental time series have fractal features and display singular behavior, the so-called singularities. The multifractal spectrum quantifies the degree of fractals in the processes generating the time series. A novel definition is proposed called full-width Hölder exponents that indicate maximum expansion of multifractal spectrum. The obtained results have demonstrated the multifractal structure of near-infrared spectroscopy time series and the evidence for brain imagery activities.

2009 ◽  
Vol 02 (04) ◽  
pp. 423-430 ◽  
Author(s):  
TING LI ◽  
LI LI ◽  
QINGMING LUO ◽  
HUI GONG

Working memory is one of the most important functions in our brain, which has been widely studied with unreal-life measured technologies. A functional near-infrared spectroscopy (fNIRS) instrument with a portable and low-cost design is developed, which is capable of providing hemodynamic measurement associated with brain function in real-life situations. Using this instrument, we performed working memory studies involved in Chinese words encoding, verbal, and spatial stem recognition, which are mainly studied with other technologies. Our results show that fNIRS can well assess working memory activities, in comparison with the reported results mainly using other methodologies. Furthermore, we find that hemodynamic change in the prefrontal cortex during all working memory tasks is highly associated with subjects' behavioral data. fNIRS is shown to be a promising alternative to the current methodologies for studying or assessing functional brain activities in natural condition.


2019 ◽  
Vol 35 (2) ◽  
pp. 131-145
Author(s):  
Grzegorz Kolasa ◽  
Filip Rybakowski

Objectives. Functional near-infrared spectroscopy (fNIRS) is one of the fastest developing neuroimaging modalities. Features, such as non-invasiveness, simplicity of application and resistance to motion artefacts, allow to take measurements and to create scientific experiments imitating real life conditions. In this review, we want to focus on the potential of fNIRS in the fields of psychiatry, neurorehabilitation and physical exercise. Additionally, we present the advantages of fNIRS over other neuroimaging techniques like fMRI, PET and EEG/EMG. We also consider potential directions of development and challenges which emerge in front of the fNIRS society. Literature review. The main application in the discipline of neurorehabilitation is to monitor and to observe the repair mechanism of neurons after brain traumas. The non-invasiveness of infra-red light permits to investigate patients of both adult and child psychiatry. The utility of fNIRS as a diagnostic tool and a predictor is proven. Researchers are looking for functional abnormalities within the prefrontal cortex. fNIRS creates new possibilities in terms of exploration of the physical exercise. Recent articles consider which type of effort has the best effect on the hemodynamic response in the cortex. It seems that investigating the impact of the physical activity in group of psychiatric patients is an interesting direction. Conclusions. Currently, we are at the breakthrough in the fNIRS technology. The number of new studies, more precise methods of data analysis, and availability of good quality systems help us to better understand how to design scientific experiments properly and reliably measure the activity of the cerebral cortex.


2009 ◽  
Vol 48 (10) ◽  
pp. D280 ◽  
Author(s):  
Theodore J. Huppert ◽  
Solomon G. Diamond ◽  
Maria A. Franceschini ◽  
David A. Boas

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