KEYWORDS: Head, Brain, Signal detection, Cerebral cortex, Monte Carlo methods, Tissues, Visible radiation, Visualization, Data modeling, Brain activation
Using the visible Chinese human data set, which faithfully represents human anatomy, we visualize the light propagation in the head in detail based on Monte Carlo simulation. The simulation is verified to agree with published experimental results in terms of a differential path-length factor. The spatial sensitivity profile turns out to seem like a fat tropical fish with strong distortion along the folding cerebral surface. The sensitive brain region covers the gray matter and extends to the superficial white matter, leading to a large penetration depth (>3 cm). Finally, the optimal source-detector separation is suggested to be narrowed down to 3-3.5 cm, while the sensitivity of the detected signal to brain activation reaches the peak of 8%. These results indicate that the cerebral cortex folding geometry actually has substantial effects on light propagation, which should be necessarily considered for applications of functional near-infrared spectroscopy.
A dual-modality method combining continuous-wave near-infrared spectroscopy (NIRS) and event-related potentials (ERPs) was developed for the Chinese-character color-word Stroop task, which included congruent, incongruent, and neutral stimuli. Sixteen native Chinese speakers participated in this study. Hemodynamic and electrophysiological signals in the prefrontal cortex (PFC) were monitored simultaneously by NIRS and ERP. The hemodynamic signals were represented by relative changes in oxy-, deoxy-, and total hemoglobin concentration, whereas the electrophysiological signals were characterized by the parameters P450, N500, and P600. Both types of signals measured at four regions of the PFC were analyzed and compared spatially and temporally among the three different stimuli. We found that P600 signals correlated significantly with the hemodynamic parameters, suggesting that the PFC executes conflict-solving function. Additionally, we observed that the change in deoxy-Hb concentration showed higher sensitivity in response to the Stroop task than other hemodynamic signals. Correlation between NIRS and ERP signals revealed that the vascular response reflects the cumulative effect of neural activities. Taken together, our findings demonstrate that this new dual-modality method is a useful approach to obtaining more information during cognitive and physiological studies
Functional near-infrared brain imaging (fNIRI) and event-related potential (ERP) were used simultaneous to detect the
prefrontal cortex (PFC) which is considered to execute cognitive control of the subjects while performing the Chinese
characters color-word matching Stroop task with event-related design. The fNIRI instrument is a portable system
operating at three wavelengths (735nm & 805nm &850nm) with continuous-wave. The event-related potentials were
acquired by Neuroscan system. The locations of optodes corresponding to the electrodes were defined four areas
symmetrically. In nine native Chinese-speaking fit volunteers, fNIRI measured the hemodynamic parameters (involving
oxy-/deoxy- hemoglobin) changes when the characteristic waveforms (N500/P600) were recorded by ERP. The
interference effect was obvious as a longer reaction time for incongruent than congruent and neutral stimulus. The
responses of hemodynamic and electrophysiology were also stronger during incongruent compared to congruent and
neutral trials, and these results are similar to those obtained with fNIRI or ERP separately. There are high correlations,
even linear relationship, in the two kinds of signals. In conclusion, the multi-modality approach combining of fNIRI and
ERP is feasible and could obtain more cognitive function information with hemodynamic and electrophysiology signals.
It also provides a perspective to prove the neurovascular coupling mechanism.
Functional Near-Infrared Spectroscopy (fNIRS) is a powerful non-invasive method to measure hemodynamic changes in
tissues, while electroencephalography (EEG) provides excellent neuronal-electrical information in functional brain
mapping. We developed an fNIRS/ERP instrument which can concurrently monitor the electrical neuronal activation and
the hemodynamic response for the study of neurovascular coupling of the human brain. The probe of the instrument
consists of 1 LED operating at three different wavelengths (735 nm & 805 nm & 850 nm) and 2 photodiodes (PDs) with
the interoptode distance up to 3 cm, and an Ag-AgCl electrode lies in the center of the LED-PD pairs. The four
components are encapsulated in a black sponge to decrease the interference of outside light as well as facilitate the
placement on the forehead. The signals from the PDs and the electrode separately pass though two adjustable
amplify-filter circuits which amplify the weak signals and block the high frequency interferences. A high speed data
acquisition board samples the modulated signals under the control of a home-made software. The time resolution of the
instrument achieves less than 10ms, which makes it realizable to compare the fNIRS data with the ERP data.
Fluorescence recovery after photobleaching (FRAP) has become a popular technique to investigate the behavior of protein in living cells. There are various mathematical models for the processing of FRAP data. Among them, Compartmental modeling enables researchers to extract information such as the association and dissociation constants, distribution of a protein between mobile and immobilized pools, and the effective diffusion transfer coefficient of the molecule under study. This model is a simple system of linear ordinary differential equations, and its solution used to fit the FRAP data is a simple two exponential function. Therefore, Gustavo Carrero and some other scientists suggest the use of this model. However we find that the length of FRAP data affects the stabilization of data processing. We believe that it is the two-exponential fitting function that causes the instabilization. This paper attempts the study of fitting FRAP data using three exponential sum function and gets better and more stable fitting. As researchers begin to focus on the relative influence of protein domains within individual protein, this approach will allow a quantitative assessment of the relative effect of different molecular interactions on the steady-state distribution of protein in vivo.
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