**2.2 Subjects**

researches, sniffing and smelling were important function of the "active olfaction" [6, 7]. On the other hand, imitation of smelling hands and the behavior of putting the hands together were investigated as an activation of mirror neurons and an

In the analysis of brain activity, fMRI, PET, EEG, and MEG are usually applied. In general fMRI and PET are suitable to measure the metabolism of physiological activities but not suitable to measure the real-time changes of neuronal activities. On the other hand, it is known that the advantage of MEG is suitable to obtain the real-time changes of the presiding neural activities in the brain by millisecond time resolution [13, 14]. MEG method is more excellent than EEG method because no distortion of an electro-resistance in the brain was found. So, we applied MEG experiments to this study for the estimation of signal source in the brain.

In our MEG experiments, we used to trace the cortical current by the first-order differential planar type of DC-SQUID sensors. This MEG sensor system has the

The determination of a current source is very precise and useful because the current source exists in the maximum of absolute magnetic field values [15]. This estimated main current source was the largest dipole, and the second and the third

To improve up fittingness of the estimation, we applied "spatiotemporal dipole fit theory" introduced by Scherag et al. [16] in which the time-varying amplitude of each dipole was applied at every 50 ms intervals. For the estimation of the signal source, we applied time-varying analysis method to obtain the most suitable MEG dipole which is called equivalent current dipole. From this time-varying analysis, we obtained the most suitable single dipole at every 50 ms in real-time analysis

The event-related responses (ERPs) in the human brain were studied as an inner mental state or the various psychological factors having an inner origin in the brain, for example, using measuring brain waves and so on. A P300 response peak in brain waves was researched as a response of "cognitive function" by using "oddball paradigm" experiment [17–19]. This P300m response (the magnetic P300 response peak is called as P300m in the MEG experiment) was investigated for the olfactory cognitive function, too. From these reasons, we can study P300m response to test

The alpha-amylase value in the saliva is known as a kind of marker and an index of stress states in human [21, 22]. So we can have alpha-amylase in the saliva to test the stress state for the response of olfactory function in human before or after

The purpose of this study is to clarify that smelling "Zuko" incense rubbing into

In this MEG experiment, "Zuko" incense rubbing the powder into the hands

These materials were produced especially by Nippon Kodo Co. Ltd. in Japan as follows. This new material is called as a code name "Nou-Katsu-Gassho-Ko" (in

the hands and putting the hands together more activate the human brain than smelling incense odors using sticks burned such as the responses obtained from our

previous study and to show how specific areas in the brain are activated.

Japanese) including the following three basic materials:

greatest advantage of using the differential planar type of device.

current dipoles were smaller and weaker than the first main dipole.

operation of the default-mode network [8–12].

*Sino-Nasal and Olfactory System Disorders*

continuously.

the cognitive ability of olfaction [20].

smelling "Zuko" incense.

**2. Materials and methods**

**2.1 Materials**

is used.

**174**

From the previous 11 Japanese volunteer subjects, in this analysis 10 subjects (5 males, 5 females) between the ages of 22 and 58 years (mean age 41 11 years) were chosen. These subjects were tested by using the previous two types of incense sticks for the effects of the simultaneous smelling incense odor and putting the hands together. However, for only one subject N1 in the previous 11 subjects, it was tested how his brain showed the response to smelling a "Zuko" incense into the hands and putting the hands together by using the analyses of MEG and MRI experiment [23].

On the other hand, in this experiment new other 10 subjects (5 males, 5 females) between the ages of 31 and 73 years (mean age 54.1 7.8 years) who were selected with higher ages than the above subjects participated. They were tested by using "Zuko," an incense which were rubbed into their hands for the effects of simultaneous smelling."

All subjects had no significant smell loss, and they were given the informed consent perfectly by the ethical committee on human studies under Helsinki treaty in both AIST and Aino University in Japan.

#### **2.3 Methods of MEG experiments and algorithms of source estimation**

#### *2.3.1 Signal source estimation using the theory of "spatiotemporal dipole fit"*

In this study, we applied to the signal source an estimation by using "spatiotemporal dipole fit" theory [16]. We obtained the value of an estimated current dipole continuously using a unit time step by step at every 50 ms, in turn. From these timevarying analyses, the most suitable dipole was obtained at the most reliable time for MEG data in the experiment. This "time-varying analysis" is the method using time-varying covariate (also called time-dependent covariate) in statistics, particularly in survival analyses. It reflects the phenomenon that a covariate is not necessarily constant through the whole study to get the suitable higher goodness of fit (GOF) for the estimation [24].

In this study, we were selecting the most suitable dipole from these dipoles estimated in time varying at every 50 ms. In these single dipoles for this timevarying estimation method, the most reliable ECD was of course obtained as a very higher goodness of fit (GOF) more than 80% by using the above time-varying analysis. These ECDs were fitted using iterative algorithms which estimated the source parameters in order to explain the MEG data as accurate as possible [25, 26]. A smoothing spline is also used to propose a novel model for the time-varying quantile of the univariate time series using a state-space approach. A correlation is further incorporated between the dependent variable and its one-step-ahead quantile. Using a Bayesian approach, an efficient Markov chain Monte Carlo algorithm is described where we use the multi-move sampler, which generates simultaneously latent time-varying quantiles [27].

In our source reconstruction analysis, three main components were characterized. The first was related to the definition of the solution space, and the second was reconstructed by the information of the physical and geometrical characteristics of the head. The third was treated by modeling the propagation of the source electromagnetic fields through various tissues in the brain [28, 29]. In these inverse

operations, a forward model was used according to some criterion, a unique source distribution to get the unique inverse solution.

**2.4 An MEG experiment for the previous smelling "Zuko" incense and putting**

For only one subject N1 in the previous 11 subjects, it was tested how his brain showed the response to smelling "Zuko" incense into the hands and putting the

MEG response data were measured at the following five mode states, (1) control state, (2) cognitive testing mode using "auditory oddball paradigm" without smelling "Zuko" incense rubbing into the hands, (3) smelling "Zuko" incense into the hands mode without putting the hands together, (4) the mode of smelling "Zuko" incense rubbing into the hands and putting the hands together, and (5) cognitive testing mode using "auditory oddball paradigm" with smelling "Zuko" incense into

Control state was measured under no smelling "Zuko" and no putting the hand

2.For the next mode, cognitive testing mode using "auditory oddball paradigm" without smelling "Zuko" incense rubbing into the hands, regardless of whether the subject did or did not have the habit of putting his or her hands

During this cognitive testing mode using "auditory oddball paradigm" without smelling "Zuko" incense rubbing into the hands, the subject held the optical sensor by a hand and pushed the button with the right thumb quickly when he/she caught a rare tone. The averaged MEG response was measured by adding the raw MEG data collected about 100 times by pushing the optical sensor button. By using the above mode, we tried to measure the subject's cognitive ability on the peak of the so-called P300m of cognitive MEG response and own singular characteristic active area for cognition, and we have examined to compare how the brain activity is different for the habit and no habit behavior of putting the hand together in daily

3.Next, in the mode of smelling "Zuko" incense into the hands without putting the hands together, the subject rubbed "Zuko" incense into his/her both hands in advance at the preparation room. In this MEG experiment, he/she smelled "Zuko" incense of his/her one hand and at random time pushed the optical sensor button with his/her thumb by another hand. We measured the MEG response of "Zuko" incense into the hand and obtained the active brain area and have examined to compare how the brain activity is different for the habit and no habit behavior of putting the hand together in daily life. The averaged MEG response was measured by adding the raw MEG data collected about 100

4. In the next mode that included smelling "Zuko" incense into the hands and putting the hands together, we measured the MEG response and active brain area of both brain activities: smelling "Zuko" incense into the hands in synchronization with active inspiration (i.e., sniffing and smelling "Zuko" incense odor) and the behavior of putting the hands together [30]. In this

**the hands together for one subject in the previous 11 subjects**

*Smelling "Zuko": Incense Rubbing into the Hands and Smelling the Hands Activates…*

hands together by using the analyses of MEG and MRI experiment [23].

**2.5 MEG experiments for five mode states**

*DOI: http://dx.doi.org/10.5772/intechopen.88987*

1.MEG experiments for control state

together or praying in daily life.

times by pushing the optical sensor button.

the hands.

together.

life.

**177**

## *2.3.2 Data acquisition*

Our planar type DC-SQUD system is useful for the determination of the current dipole of brain activity source where it exists at the maximum of absolute magnetic field value. Data acquisition was applied after starting the signal during the time of 500 ms by using MATLAB software. In our MEG experiment, the subjects sniff an incense odor by using his own nose, and when he starts to sniff, he pushed the optical sensor button as a trigger. To record time-varying MEG amplitude value, we used a sampling interval every 50 ms.

#### *2.3.3 ICA algorithms*

This independent component analysis (ICA) program [30] was applied to our input data of MEG experiments. ICA is one method of blind source separation and a computational method for separating a multivariate signal into additive subcomponents. In ICA algorithms, if the subcomponents are non-Gaussian signals, they are statistically independent from each other. The number of components was five for the estimation. The criteria of ICA estimation on the total five components for selecting are determined to 85% (independent rate) to all other components (non-Gaussian components) of data.

As a general definition of ICA algorithms, the MEG data are represented by the observed random vector: x = *(x1,...,xm)T* and the hidden components as the random vector s = *(s1,…,sn*) *T* . The task is to transform the observed data x, using a linear static transformation W as *s = Wx* into an observable vector of maximally independent components s measured by some function F(*S1,…Sn*) of independence.

### *2.3.4 MRI system*

This MRI system is a 0.4 T Hitachi open type MRI system (AIRIS-Light MRI system, permanent magnetic type, made in Hitachi Co. Ltd. in Japan). These experiments were performed in the Kansai center in Ikeda city, National Institute of Advanced Industrial Science and Technology (AIST) in Japan.
