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The vibraimage technology is applied to evaluate the multiple intelligences by presenting the line-opposite stimuli. The analysis of testing results of 161 and 91 first-year students from two technical universities, St. Petersburg, Russia, is presented. A new method has been introduced for the assessment of the level of introversion and extraversion of a person being tested. Various equations for calculating the psychophysiological state have been studied and common patterns of the psychophysiological responses to the stimuli were revealed. The experiments showed a prevailing negative correlation between the parameters of a person’s energy consumption and information exchange detected by the vibraimage technology. The article discusses the possibility of extending the obtained results to other psychophysiological tests.

Modern psychophysiology for the last 150 years after the fundamental works of Darwin and Sechenov [

One of the trends of the vibraimage technology development is the practical study of the human abilities and construction of the multiple intelligences profile. The concept of multiple intelligences (MI) introduced by Gardner in 1983 [

Since in this study we are only interested in unconscious responses we do not consider any conscious responses (Yes-No answers to the questions). Also, this article will not uncover the principles of the questions and stimuli formation, described in detail in the paper [

The structure of the questionnaire for the MI testing developed in [

In testing the multiple intelligences, a respondent is presented with 24 opposite questions-stimuli on the computer screen. The web camera installed on the same computer registers the psychophysiological response when processing the micro movements of the head with the use of the vibraimage technology [

Current psychophysiological state of the person is defined as an intersection point of two coordinates in the I-E axes [

Different colors of the graphs in

Time dependencies of physiological parameters are traditionally used in the psychophysiological detection of deception (PDD). However, to construct and study the correlation dependencies, the two-way dependencies are commonly used. Thus, we will focus on these dependencies in our further analyses. The type of I-E dependence is determined primarily by the questions-stimuli, as it is the stimulus that detects the change in the PPS of the person being tested. Let us consider examples of three the most pronounced types of correlation dependencies between the I-E parameters during answering the one or pair of questions, namely: negative correlation, no correlation and positive correlation between the information-energy parameters. It follows from observing

PPS state to be established directly in response to the presented stimuli. That being said, we believe that there is no need to waste time for the introduction and presentation of neutral questions (as it is usually done in the PDD tests [

Negative correlation in the PPS changes between two neighboring questions-stimuli primarily reflects the fact that the transition from one question to another increases the information efficiency and decreases the consumed energy, or vice versa, the information efficiency decreases, and the consumed energy increases. Schematically, a typical change in the PPS during the presentation of opposite questions-stimuli with an inverse or negative correlation between information-energy parameters is shown in

We intentionally show and examine the changes in the PPS just by presenting a pair of questions basing on the following considerations. The historical breakthrough and increasing accuracy in the psychophysiological detection of deception are mainly due to the Backster’s concept of transition to comparative testing between close-in-time control and relevant questions [

As the next explicit example, let us consider another graph of the possible type of changes in PPS (shown in

The next example in

In this case, when answering the first and second questions, the psychophysiological response of the person demonstrates the multidirectional movement that includes time intervals with both negative and positive correlation between the information-energy parameters, and the duration of these time intervals is approximately equal. Therefore the total correlation between I-E parameters during the presentation of each question in a pair is close to zero.

In the graphical examples (Figures 4-6) the return to the initial state occurs, however, in practice (

pairs of opposite questions-stimuli the range turns out to be significantly less. If the questionnaire also contains neutral questions, it becomes even more difficult to reveal any common patterns. One of the problems in this case is the practical impossibility to expect a similar statistical reaction at answering the neutral questions by different people. This problem is well known to experts in the psychophysiological detection of deception [

To quantify the changes in the PPS we used several equations, each reflecting a certain model of the PPS changes.

In Equation (1) for calculating PPS introduced in [

d P 1 = ( I i − I i − 1 ) + 2 | E i − 1 − E i | ⋅ sin A , (1)

where:

I i − 1 is the initial reference coordinate of the information characteristic at the initial state of the person within the ith time interval of the observation period;

I i is the final reference coordinate of the information characteristic at the current state of the person within the ith time interval;

E i − 1 is the initial reference coordinate of the energy consumption at the initial state of the person within the ith time interval;

E i is the final reference coordinate of the energy consumption at the current state of the person within the ith time interval;

sin A = ( I i − I i − 1 ) / ( I i − I i − 1 ) 2 + ( E i − 1 − E i ) 2 .

The next Equation (2) for calculating the psychophysiological state proposed in [

d P 2 = ( I i − 1 − I i ) + ( E i − 1 − E i ) , (2)

where the basic parameters are similar to Equation (1):

I i − 1 is the reference coordinate of the informational comfort at the initial state of a person;

I i is the changed reference coordinate of the informational comfort at the current state of a person;

E i − 1 is the reference coordinate of the energy expenditure of the initial state of a person;

E i is the changed reference coordinate of the energy consumption at the current state of a person.

In Equation (3), proposed in this paper, the PPS changes are considered as deviations with respect to the common PPS center, computed as a sum of respective deviations of the information and energy components. Thus this characteristic takes into account two factors: the effect of the questions-stimuli and the tendency of the psychophysiological system to stabilize and return to the equilibrium state.

d P 3 = ( I i − I 0 ) − ( E i − E 0 ) , (3)

where the basic calculation parameters are similar to those in Equation (1):

I 0 is the reference coordinate of the integral (central or average) information state of a person;

I i is the changed reference coordinate of the information comfort at the current state of a person;

E 0 is the reference coordinate of the integral (central or average) energy state of a person;

E i is the changed reference coordinate of the energy consumption at the current state of a person.

To test the research hypothesis (the prevailing negative correlation between the information and energy parameters for the line-opposite MI testing) and reveal the common patterns of the psychophysiological response in answering opposite questions, two groups of first-year students of technical universities of St. Petersburg, Russia, were tested for multiple intelligences. The first group consisted of 161 technical students of the St. Petersburg State Electrotechnical University (LETI), the second group consisted of 93 economist students from the St. Petersburg State Technological University (SPSTU). The number of tested students was determined in a natural way. The students of selected specialities came to the test for additional information on their abilities. The tested students were from 17 to 24 years old. 86% of the participants were white Russian, 14% were Caucasian. An almost equal gender distribution was observed: 60% of males in LETI and 65% females in PPSTU. All the test participants gave their verbal consent. The testing was conducted in the second half of 2017 with the use of the VibraMI software [

Apart from constructing the multiple intelligences profile for each student, the VibraMI software detects and records a considerable amount of statistical characteristics and dependencies of the psychophysiological parameters obtained during the MI testing into Excel files. The statistical software VibraStatMI [

One of the informative parameters is P_near, a parameter characterizing the correlation between adjacent psychophysiological responses computed for the whole test group. This parameter is only defined at the extreme points of the PPS position after each question and does not take into account the I-E correlation during the time of the question presentation. We will consider the correlation diagrams obtained for this parameter from different Equations (1), (2), and (3) indicating the correlation of the PPS changes over neighboring questions.

The correlation coefficient P_Ref is computed between the parameters of the psychophysiological state for the questions equidistant from the questionnaire center. It is also defined at the extreme points of the PPS position after each question.

From

The Pearson correlation coefficient is computed for each pair of responses to the neighboring questions-stimuli of the MI test (

It is important to note that, despite the significant difference in Equations (1) and (2), the form of the correlation diagrams is almost identical and the correlation values deviate only in the third digits.

The correlation between the PPSs for neighboring questions-stimuli, computed from Equation (3), gives us a completely different picture of the distribution than those from Equations (1) and (2).

Let us consider an analogous series of correlation diagrams obtained in the PPS analysis using the same equations, but between the similar in meaning questions that have the opposite (centrally symmetric) order numbers in the line of questions in the MI questionnaire (e.g., first-last, second-last-to-one, etc.).

The diagram in

The type of diagram in

The diagram shown in

The type of the same diagrams obtained from the testing of another sample of 91 economist students is approximately analogous to those shown in Figures 7-12.

Now we will consider the correlation between the increment of information and

energy (changes in I and E parameters), i.e. the correlation coefficient dIdE computed within the time of answering each question-stimulus. Values of the correlation coefficient dIdE for the test of 161 students group is shown in

The difference between

Thus, the hypothesis of the negative correlation between I-E parameters is corroborated by the testing results of the groups of students. The typical changes in the PPS shown in

At the same time, it should be noted that the revealed common patterns have been obtained for a sufficiently large statistical sample homogeneous in age and education level. In addition, this testing was significant for the respondents, and they worried about the result. In order to approach the conclusions from a different perspective we also consider examples of correlation diagrams between the I-E parameters obtained with individual tests and get the average results.

In each particular case of testing, the correlation between the I-E parameters usually is of the oppositely directed type. Examples are shown in

It is worth noting that in the example in

Despite the fact that some of the individual cases of MI testing show positive I-E correlations for some questions, the group-average correlation is generally negative for each question. An example of such averaging over the testing group of 161 students is shown in

The result shown in

The conclusions about the correlations of the psychophysiological responses can be considered consistent as our results practically coincide for two independent tested groups of several hundred people. The study has revealed an additional rule: the more uniform the group structure is, the more pronounced the leading types of intelligences will be in the resulting MI profile of the group. For example, the subdivision of 161 students into unsuccessful students (

On the contrary, the uniting people with different abilities and life interests into the common tested group leads to the equalization of the general statistics and the uniform distribution of the types of multiple intelligences over a large group of different people. This result is quite important and can be used to check the adequacy of the questions-stimuli presented in testing. For example, if after checking a large sample it turns out that one type of MI is the leading, then the most likely this is due to the incorrect assignment of stimuli responsible for the leading type of intelligence. This effect was observed in the first version of the questionnaire where the natural intelligence (NL) was found predominant for the most of non-related groups. Only after correction of questions-stimuli aimed at revealing the natural intelligence, the relative importance of the natural

intelligence in the MI profile returned to normal and was no longer the leading type in non-specific groups [

The new Equation (3) proposed in this paper, based on the deviation from the common center of gravity, showed the basically expected result: the increase of values of the inverse correlation coefficients between psychophysiological responses to distant in time but similar in meaning questions-stimuli (

According to the previous algorithms, the main effect is made by the stimulus while the other effects can be neglected. However, as shown in

Near identical correlation diagrams (

If the prevailing inverse correlation between I-E parameters was not observed in the tested groups, the correlation diagrams calculated from Equations (1) and (2) could differ significantly. Now we will try to answer the question, “Why the correlation between I-E parameters was predominantly negative, although it is known that in some cases it can be close to zero or positive?”. As mentioned above, this paper presents the results of testing the first-year students who were afraid that the test results could lead to their expulsion from the university. Such psychological pressure during the testing process itself definitely affected the students’ PPS. For comparison, the test results for a professor are given below. The professor absolutely did not care about the testing result, but rather showed interest and a positive attitude to obtaining the test results. As a result, the type of correlations strongly differs from those shown by the students (see

The above results can be explained in a somewhat unexpected way, using the concepts of introversion and extraversion introduced by Jung about 100 years ago [

terms extraversion and introversion rather freely, attributing their own psychological meanings to these concepts and ignoring Jung’s original assumption of an opposite direction of the energy flow in extraverts and introverts. However, our experiments make it possible to explicitly distinguish two of these PPSs by the direction of the energy movement. In this case, a PPS should be called introverted if a negative correlation between the energy and information parameters of the person is observed when responding to the opposite stimuli (positive and negative). Accordingly, a PPS should be called extraverted if a positive correlation between the energy and information parameters of the person is observed when responding to the opposite stimuli. In the tests conducted, the psychological pressure exerted on the students created the prerequisites for their generally introvert behavior, while their professor, interested in cooperation, showed himself as an extravert.

The next question is whether the conclusions drawn are applicable to other types of psychophysiological testing, for example, for lie detection, also remains open. The results give hope that the approach might be helpful in making the psychophysiological detection of deception more scientifically grounded and practically applicable. It is certainly tempting to use the obtained results for various psychological and psychophysiological tests aimed at identifying potential personal qualities, for example, human variability [

It cannot be ruled out that the method of assessing the PPS changes in information-energy coordinates can be the basis for any psychophysiological testing, and the direction of the PPS vector more objectively represents the subject's response to the stimulus than the relatively subjective positive or negative perception of the stimulus.

In spite of their apparent mathematical abstractness, the above examples allow us to draw the specific practical conclusions:

1) The relationship between the information and energy personal characteristics, revealed using the vibraimage technology, makes it possible to assess the changes in the individual PPS and determine the combination of the psychophysiological characteristics of a person.

2) The proposed methodology for the classification of a person as an introvert/extravert by monitoring the direction of energy changes in response to the opposite questions-stimuli presentation will enable us to more objectively evaluate this characteristic of personality.

3) The PPS changes during the MI testing with the presentation of significantly opposite stimuli show a predominantly inverse correlation between the information-energy (I-E) parameters (see

4) The PPS changes during MI testing with the presentation of opposite stimuli can be described by Equation (1) (with the priority of the information component) and (2) (with equal importance to the information and energy components). The calculation of the PPS according to Equations (1) and (2) shows similar results. Presumably, Equation (1) has a wider application and can be used to characterize people with various personality types.

5) The line-opposite questions-stimuli method provides the maintenance of the normal PPS in the quasi-stationary state because each pair of opposite stimuli shifts the PPS state from the integral center in opposite directions. It is an open question whether any neutral questions should be included into the questionnaire because the effect of neutral questions on the PPS is unpredictable. This leads to the uncertainty complicating the analysis of the psychophysiological response to opposite questions.

6) The better understanding of the PPS changes in response to stimuli will address a wide range of issues in conducting practical tests, since a deviation from the typical statistical behavior can be considered abnormal, caused, for example, by an attempt to hide information or evade an answer to a question. Of course, each case must be considered separately as there may be single deviations associated with random or methodological errors.

7) This work is an essential step towards developing the efficient testing methodology. The study of a particular case of the opposite testing allowed us to establish the statistical relationship between the presented stimuli and trends of the PPS changes. The chosen information-energy scale for the PPS characteristic proved to be effective and relevant for tracking even minor changes in the PPS of the person being tested.

Minkin, V. and Myasnikova, E.M. (2018) Using Vibraimage Technology to Analyze the Psychophysiological State of a Person during Opposite Stimuli Presentation. Journal of Behavioral and Brain Science, 8, 218-239. https://doi.org/10.4236/jbbs.2018.85015