Reorganisation of system brain activity while understanding visually presented texts

ISSN 03621197, Human Physiology, 2015, Vol. 41, No. 1, pp. 11–21. © Pleiades Publishing, Inc., 2015.
Original Russian Text © L.O. Tkacheva, I.A. Gorbunov, A.D. Nasledov, 2015, published in Fiziologiya Cheloveka, 2015, Vol. 41, No. 1, pp. 17–28.
Reorganization of System Brain Activity
while Understanding Visually Presented Texts
with the Increasing Completeness of Information
L. O. Tkacheva, I. A. Gorbunov, and A. D. Nasledov
St. Petersburg State University, St. Petersburg, 199034 Russia;
email: [email protected]
Received July 15, 2013
Abstract—The characteristic features of brain activity under variation of the information regimes associated
with the stages of understanding visually presented texts in adult subjects (n = 148) have been studied. An
original methodology for stepbystep presentation of texts has been developed in order to “detect” the psy
chophysiological markers of different degrees of understanding and to identify the successive steps in this pro
cess. The following three stages were determined by spectral analysis and calculation of the fractal dimension
of EEG: “before understanding,” “understanding,” and “after understanding.” The phenomenon of V
shaped changes in the values of EEG fractal dimension was discovered. The first stage is characterized by the
increasing power of EEG spectrum in the high frequency range and by the enhanced fractal dimension of
EEG, which probably reflects the process of idea generation and the search for solutions. At the next stage
(“understanding”), the value of EEG fractal dimension decreases and the spectrum power of the lowfre
quency range increases, which seems to reflect simplification of invariance to the only valid alternative. The
last stage is characterized by an increasing power of EEG spectrum in the highfrequency range and the
increasing value of EEG fractal dimension, which may reflect the intensification of brain activity related to
solution validation. The findings are a step closer to understanding the neurophysiological mechanisms of
system brain activity reorganization while making sense of visually presented texts; they outline the pathway
to elimination of the contradictions existing in the literature as concerns the role of high and lowfrequency
EEG components as markers of the state of understanding.
Keywords: stages of making sense of the texts, psychosemantics, fractal dimension of EEG, EEG γ range,
EEG θ range
DOI: 10.1134/S0362119714060127
In this article, the term “understanding” means the
stage of including new information into the current
context. The major trends of research in the modern
cognitive psychophysiology related to the process of
understanding are the studies of: the cognitive con
scious and unconscious [1, 2]; the recognition of
weak, subthreshold stimuli [3, 4]; the characteristics of
functional hemispheric asymmetry associated with
creativity [5]; and the detection of network organiza
tional patterns of electrical activity of the brain ensur
ing the process of understanding [6, 7].
At the same time, some findings demonstrate that
the process of understanding is accompanied by syn
chronization of bioelectrical brain activity within the
lowfrequency bands of EEG [11, 12]. It is undisputed
that deep brain structures play the key role in the gen
eration of slowfrequency cortical activity. To date, the
role of hippocampus in consolidation of memory
traces and its role as a selective input filter are unques
tionable [13]. It is supposed that the lowfrequency θ
oscillations serve for including new elements in the
current information context and for intensifying the
segregation between different memory elements [14].
Some of the studies show the role of θ activity in the
processes of decoding semantic information [15, 16].
The effect of enhanced power of highfrequency
rhythms was recorded in modeling the situation of cre
ative task solution by many researchers under various
experimental conditions [5, 8]. Description of the
mechanisms of integrative brain activity that provided
higher cognitive processes places emphasis on the
process of neuronal synchronization in the γ band
as a significant and functionally significant phe
nomenon [9, 10].
Thus, in spite of extensive use of different EEG
parameters as markers of the process of understanding
the presented information, the role of high and low
frequency bioelectrical activity of the cortex in the
organization of systemic brain activity, which is per
formed at different stages of information processing, is
still unclear. The objective of our research was to com
pare the variations in EEG in different frequency
bands of different cortical areas of cerebral hemi
spheres when the subject understood the meaning of
visually presented texts with increasing completeness
of information.
The basic experiment was preceded by a prepara
tory step, which included expert assessment by two
methods and development of a technology for step
bystep presentation of the texts. Three main plotlines
were obtained from 36 classical dramatic plots [17] by
the first method of assessment: (1) adultery followed
by revenge or aggression; (2) intellectual achievements
as a result of riddle solution or cognition of something
new; and (3) outrageous injustice followed by restora
tion of justice. Six stimulus texts were selected as a
result of the second method of assessment (two for
each of the three plotlines). The factor of the influence
of emotions was aligned due to variability of the plots
in different emotional indicators (sign and modality).
The selected texts were divided into eight fragments
(presentations) in such a way that the first, second, and
third presentation would contain 37, 46, and 55% of
openclass words, respectively, and so on, up to the
eighth presentation (100% of openclass words).
Therefore, it was possible to control the gradual
increase in the level of information clarity for the sub
ject in relation to the type of plot. The time of presen
tation for each fragment of each text was calculated in
accordance with the number of words. We give frag
ments 1, 4, and 7 of one of the texts as an example of
stepbystep presentation of texts (see Appendix).
The psychophysiological experiment was carried
out in 148 subjects, 18 to 30 years old, 105 women and
43 men. All subjects were acquainted with experimen
tal conditions and gave their informed written consent
in compliance with the Declaration of Helsinki. EEG
was recorded using a Telepat 104P electroencephalo
graph (bandwidth, 0.5–70 Hz) with a 250Hz sam
pling rate for each channel. Nineteen monopolar leads
were arranged symmetrically according to the Interna
tional 10–20 System (Fp1, Fp2, Fp3, Fp4, F7, F8, С3, С4,
Fz, Cz, Pz, Т3, Т4, Т5, Т6, Р3, Р4, О1, andО2). The aver
aged potential of two ear clip electrodes was used as
reference. EEG was recorded continuously, both in
the background state (quiet wakefulness with the eyes
closed) and when the subjects made tests on under
standing and categorization of the texts (relating them
to one of the plots).
In the beginning of observation, EEG was recorded
with the eyes closed and then with the eyes opened (1
min each). Then, a subject received the instructions
(on a monitor screen and through speakers) explaining
task sequence and ordering to understand the plot type
as soon as possible. Then, six different texts were
sequentially presented on screen display, each of them
being divided into eight presentations with the
increasing degree of information completeness
(see the Appendix). The subject indicated his/her
choice of the plot by pressing the button. It was not
necessary to remember the types of plots; this infor
mation was given in the lower part of the monitor
screen at each presentation of the text. In conclusion,
EEG was recorded again with the eyes closed and
opened (1 min each).
The correlation between different rhythmic com
ponents of EEG was determined by calculating spec
tral powers (Fourier transform) in WinEEG. The
entire 15s EEG segment was analyzed, or a smaller
segment if the subject pressed the button earlier, but no
shorter than 4 s (the minimal window for implementa
tion of the analysis). Spectral analysis was performed
in separate 4s windows at a 2s pace (2s overlapping
from 0 to 4, from 2 to 6, from 4 to 8, etc.). This was
done to enhance the epoch analysis in the analyzed
data segment in order to validate the calculations
excluding artifacts. The mean spectral power values
were calculated for each 4s fragment (for each sub
ject). As a result of this transformation, EEG data are
presented as total powers for the main spectral bands:
Δ (1.5 to 3 Hz), θ (4 to 7.5 Hz), α (8.5 to 14 Hz), β1 (15
to 20 Hz), β2 (21 to 30 Hz), and γ (31 to 45 Hz).
Then, the values of EEG fractal dimension (FD)
were calculated for each subject, for each of the 19
leads, and for each state (“before understanding,”
“understanding,” “after understanding”) via the loga
rithms of power spectrum and frequency [18]. Factor
analysis by the method of principal components (PC)
was used to reduce the dimensions of data [19]. The
method of PC revealed the most informative parame
ters characterizing organization of the work of differ
ent brain regions in the three states of understanding.
For comparability of PC values in different states, the
analysis was performed with the data where the
repeated measurements of the leads (19 × 3 = 57 vari
ables altogether) for the sample of N = 148 were pre
sented as groups of observations. Thus, the analysis
of PC was performed for 19 variables and 148 × 3 =
444 observations.
The software for EEG data visualization (as corre
lation pleiads and visualization of local distribution)
was developed at the Laboratory of Psychophysiology,
Chair of Medical Psychology, St. Petersburg State
University. The influence of the factor of state (3 lev
els: “before understanding,” “understanding,” “after
understanding”) on the power values of Δ, θ, α, β1, β2,
and γ activities of EEG for 19 leads was assessed by
ANOVA with repeated measurements.
The scheme in Figure 1 shows the algorithm that
we used to compare the secondary EEG parameters
recorded in the three pairs of states (“before under
standing,” “understanding,” “after understanding”).
The greatest changes in the process of understand
ing were revealed by pairwise comparison of EEG data
from the three stages according to the scheme pre
sented in Figure 1.
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No. 1 2015
In Figures 2–4, the upwardpointing triangle
denotes statistically significant differences corre
sponding to power increase in the first state (i.e.,
“before understanding”) relative to the second state
(i.e., “understanding”). The increase in EEG power in
the second state relative to the first one is denoted with
a downwardpointing triangle. The triangle sizes and
brightness (three grades) reflect the degrees of signifi
cance of the detected difference.
Statistically significant increase in the powers of
Δ and θ activities was revealed at the instant of under
standing the meaning of the texts relative to other two
states (“before understanding” and “after understand
ing”). Variations were recorded in the frontal areas,
especially in the right hemisphere.
The results of differences in the Δ, θ, and α bands
are presented in Fig. 2.
The maximum power in both Δ and θ EEG bands
was recorded in the state of “understanding,” in rela
tion both to the state “before understanding” and to
the state “after understanding.” Significant changes in
the spectrum power in the α band are observed in the
occipital and frontal regions, also mainly in the right
hemisphere. In the state of “understanding,” the sys
tem brain activity is organized in such a way so that
EEG power increases in the slowwave region of the
spectrum: the Δ and θ bands.
The tendency towards gradual increase in EEG
power in highfrequency bands was observed in pro
portion to the degree of understanding of the material
and the amount of perceived information (see Fig. 3).
Considerable increases in EEG power in the β1 and
β2 bands were recorded in the state “understanding”
relative to the state “before understanding” and in the
state “after understanding” relative to the state
“understanding.” These changes were observed not
only in the anterior cerebral regions but also in the
central and occipital brain regions, being particularly
pronounced in the right hemisphere. The most gener
alized changes in bioelectrical activity during the com
parison of functional states of the brain before and
after understanding were revealed in the γ band
(see Fig. 3c).
The results suggest that the changes in the system
brain activity at an instant of understanding manifest
themselves in local variations of EEG power within a
range of 0.5–13 Hz mainly in the frontal regions,
while the characteristics of brain activity in the process
of understanding the texts manifest themselves mainly
in generalized intensification of the power of highfre
quency EEG spectrum.
One can safely assume that the structure of interre
gional relations undergoes qualitative changes in the
process of understanding, which is accompanied by
reduced redundancy in the system of spatiotemporal
correlations between distantly disconnected cerebral
structures, i.e., reduced chaoticity in organization of
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Fig. 1. The sequence of comparisons of the pairs of states:
1, comparison of the states “before understanding” and
“understanding”; 2, comparison of the states “before
understanding” and “after understanding”; 3, comparison
of the states “understanding” and “after understanding.”
brain activity. It is well known that electrical brain
activity recorded from head surface as EEG is an oscil
lation process characterized by enhanced variability
and nonstationarity and has the properties of chaotic
and fractal dynamics [19]. EEG power spectra do not
always adequately represent the changes in the func
tional state of the brain, whereas the changes in multi
fractal parameters are more informative [20]. An ade
quate mathematical apparatus for quantitative assess
ment of the lowering level of entropy is an increasingly
widely used method for calculating the fractal dimen
sion (FD) of EEG signal [21–23], which we have
attempted to use in order to answer the following ques
tion: Which of the three states of understanding
(“before understanding,” “understanding,” or “after
understanding”) is characterized by the highest degree
of coordination of intercentral relations reflecting the
higher level of organization of spatiotemporal correla
tions and quantitatively represented by the lower val
ues of EEG FD? The EEG FD value was calculated
on the basis of 19 leads and three states (see Fig. 4).
The comparison of characteristic features of bio
electrical brain activity on the basis of EEG FD anal
ysis has shown that the minimum level of chaos, i.e.,
the maximum level of certainty, is observed in the state
of “understanding” (see Figs. 4a, 4b), while the states
“before understanding” and “after understanding” are
characterized by the higher level of uncertainty in
organization of interregional relations. At the same
time, it should be noted that the state “before under
standing,” compared to the state “understanding,” is
characterized by the high values of EEG FD mainly in
the anterior central regions, especially in the right
hemisphere. Organizational entropy of brain activity
in the state “after understanding” is characterized by
the generalized variation of EEG FD values, which
encompasses nearly all areas except for posterior
regions. It is interesting that the states “before under
standing” and “after understanding” have the com
mon properties with respect to the parameters of
changes in the EEG FD values; therefore, no signifi
cant differences have been revealed in any lead (see
Fig. 4b). This means that these states have the higher
level of uncertainty compared to the state “under
1 > 2 p < 0.001
2 > 1 p < 0.001
1 > 2 p < 0.01
2 > 1 p < 0.01
1 > 2 p < 0.05
2 > 1 p < 0.05
1 > 2 p < 0.001
2 > 1 p < 0.001
1 > 2 p < 0.01
2 > 1 p < 0.01
1 > 2 p < 0.05
2 > 1 p < 0.05
1 > 2 p < 0.001
2 > 1 p < 0.001
1 > 2 p < 0.01
2 > 1 p < 0.01
1 > 2 p < 0.05
2 > 1 p < 0.05
Fig. 2. Representation of the process of understanding in the variations of EEG power spectrum in lowfrequency bands: (a) Δ
band; (b) θ band; and (c) α band. See the text for explanations.
Two factors accounting for 74.47% of the total vari
ance were obtained by the method of PC. The first fac
tor, F1 (38.30% of total variance), represents the FD
value for the following leads: O1, O2, P3, P4, T6, C4. The
second factor, F2 (36.16% of the total variance), rep
resents this value for the leads Fp1, Fp2, F3, Fz, F4, F7,
and F8. Further, the values of the factors were calcu
lated (by the regression technique) for 444 observa
tions. The resultant two new variables were the calcu
lated estimates of the factors designated as F1 and F2,
respectively. Then, the calculated factors were recon
structed as duplicate measurements for the three states
and represented as 2 × 3 = 6 variables for N =
148 observations. These data were subjected to vari
ance analysis with duplicate measurements: 3level
factor “State” (“before understanding,” “understand
ing,” “after understanding”) and dependent variables
F1 and F2 (the calculated factors). The statistically
significant main effect of the “State” factor (“before
understanding,” “understanding,” “after understand
ing”) (F (2, 296) = 10.96; p < 0.001; magnitude of the
effect = 0.069; the observed power = 0.991) and statis
tically significant orthogonal contrast (F (1, 148) =
13.05; p < 0.001; magnitude of the effect = 0.081; the
observed power = 0.948) were revealed for the second
factor (F2). Table 1 presents descriptive statistics for
the paired differences (shifts) of values: the differences
between the duplicate measurements of F2 in
two states compared.
The values are rounded to the third decimal place.
Thus, the most informative changes in the system
brain activity by the EEG FD parameters have been
recorded in the frontocentral brain areas.
Figure 5 shows the mean values of the factor F2.
The mean values of F2 representing the total FD of
EEG are plotted along the Y axis, and the three types
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1 > 2 p < 0.001
2 > 1 p < 0.001
1 > 2 p < 0.01
2 > 1 p < 0.01
1 > 2 p < 0.05
2 > 1 p < 0.05
1 > 2 p < 0.001
2 > 1 p < 0.001
1 > 2 p < 0.01
2 > 1 p < 0.01
1 > 2 p < 0.05
2 > 1 p < 0.05
1 > 2 p < 0.001
2 > 1 p < 0.001
1 > 2 p < 0.01
2 > 1 p < 0.01
1 > 2 p < 0.05
2 > 1 p < 0.05
Fig. 3. Representation of the process of understanding in the variations of EEG power spectrum: in the (a) А band; (b) β2 band;
and (c) γ band. See the text for explanations.
of states while recognizing the type of plot (“before
understanding,” “understanding,” “after understand
ing”) are plotted along the X axis.
The changes in the F2 value reflecting the EEG FD
shift are statistically significant and take the form of a
Vshaped curve. Hence, this value is relatively high at
the stage “before understanding,” decreases abruptly
at the stage “understanding,” and increases again at
the stage “after understanding.” The background
EEG was recorded in the beginning, the middle, and
at the end of the session; however, the primary mea
surements did not show any substantial change in the
Significance of the revealed Vshaped change in
the EEG FD value was verified by multivariate
ANOVA with repeated measurements for all of the
seven leads as dependent variables (Fp1, Fp2, F3, Fz,
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F4, F7, F8). Figure 6 shows the mean value of EEG
FD for six leads before, during and after under
The value of the “State” effect for all leads (Pillai’s
trace test) was 7.6%. The effect is statistically signifi
cant for 6 out of 7 leads; the effect magnitudes for
these six leads were 2.5% to 8.9% and, taking into
account quadraticity of the effect, based on the criteria
of intragroup quadratic contrasts, the effect magni
tudes for separate leads were 4.7% to 12.6%. Thus, the
analysis of characteristics of variation of EEG FD val
ues in the six most informative EEG leads confirms
the appropriateness of the revealed Vshaped distribu
tion of the level of entropy characterizing brain activ
ity in three states of understanding.
1 > 2 p < 0.001
2 > 1 p < 0.001
1 > 2 p < 0.01
2 > 1 p < 0.01
1 > 2 p < 0.05
2 > 1 p < 0.05
Fig. 4. The changes in EEG fractal dimension values by 19 leads in the three pairs of states.
The analysis of spectral power characteristics
makes it possible to ascertain the specific activity of
frontal brain regions at all stages of understanding. To
date, it is indisputable that the prefrontal cortex plays
a special role in formulating goals and objectives,
developing plans and cognitive strategies, and assess
ing actions as success or failure [24]. The data on the
key role of the prefrontal cortex in recognition of frag
mented images were obtained from the analysis of
regional eventrelated potentials [25], while the model
of realtime stimulus comparison showed the most
marked involvement of the frontal cortex in working
memory at the stage of comparing the current infor
mation with the trace of the preceding stimulus [26].
At the initial stages of “information pumping,” the
amount of perceivable information was not related to
the level of certainty, since the level of clarity had
remained obscure up to the third presentation of the
text with the increase of information flow. Then, a cer
tain critical point was reached at a certain instance of
time, most often in the interval of the third to
sixth presentation of the text, which was accompanied
by the appearance of θ activity. It is noteworthy that
the burst of electrical activity in the θrange (4 to 7.5
Hz) was recorded precisely at the instant of under
standing and encompassed mainly the frontal and
central leads of both hemispheres and the frontotem
poral region of the right hemisphere (Fp1, Fp2, F3, F4,
Fz, F8). It was probably connected with the activity of
limbic brain structures responsible for maintenance of
voluntary attention and with the processes of informa
tion comparison and consolidation in working mem
ory [14]. The study of episodic memory has shown that
brain activity in the theta range (5 to 9 Hz) may serve
as a neuronal marker of selective search and retrieval
of information [27].
It can be assumed that any problemsolving pro
cess in the situation of uncertainty is related to the
alternating predominance of high and lowfrequency
activities representing the phases of increasing amount
and crystallization of the sense of information. The
analysis of connection between physiology and poten
tial functional roles of the rhythms reveals the possibil
ity of sequential transition of γ slots into θ cycles, and
such variations and switching over of the rhythms are
supposed to maintain different components of cogni
tive act [28]. The alternation of synchronization and
desynchronization phases in the θ and γ bands was 1
revealed in the study of formation of traces of episodic
memory in patients during restorative therapy after
neurosurgical intervention [29]. Interesting results
were obtained from the study of interaction between
phasic relationships during visual target detection,
when obtaining a result is related to the appearance of
a cross connection between low and highfrequency
activities [30]; the development of cognitive strategy in
the situation of uncertainty, when first the context of
situation and only then the percept was processed, also
showed the alternation of slow and highfrequency
activities [31]. The following characteristics of the
topography of functional connections by the θ rhythm
were revealed: localization of interaction foci of in the
frontal polar areas and integration of these frontal
areas with the anteriorassociative and temporal
Descriptive statistics for paired differences (shifts) in the values of factor F2 from one state of understanding to another (N = 148)
of paired states
Before understanding – Understanding
Understanding – After understanding
Before understanding – After understanding
of the shift
95% confidence interval
of the mean difference (shift)
lower limit
upper limit
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No. 1 2015
In the process
understanding of understanding understanding
Fig. 5. The Vshaped curve of the change in the total EEG
fractal dimension (FD) value at three stages of under
standing. There is a characteristic drop in the EEG FD
values at the stage of “understanding.”
regions of the left hemisphere, as well as with the pari
etal and occipital regions of both hemispheres [32].
Investigation of the dynamics of interhemispheric
interaction in the processes of selective coding of the
memory revealed a similar neurophysiological mecha
nism of alternating synchronization of bioelectrical
brain activity at the level of θ and γ bands of EEG [33].
The recording of local field potentials showed that
lowfrequency oscillations contributed to the appear
ance of interzonal crosscorrelations and modulated
the highfrequency γactivity within certain regions
[34]. It is known that the oscillatory fluctuations of
local field potentials in the θ and γ bands are involved
not only in different parts of working memory but also
in assessment of the novelty and sequence of events,
induction of plasticity in the course of coding, as well
as information consolidation and retrieval from mem
ory [35–36]. The process of understanding seems to be
crystallization of information at the level of semantic
relations. Within the scope of psychosemantics it is
assumed that more information can be perceived
with more semantic relations actualized at a given
moment [37].
Significant changes in the α band power were
observed in the occipital and frontal lobes, especially
in the right hemisphere (Fp1, Fp2, C4, T4, Pz, T6, O1,
O2); in the state “before understanding,” the α rhythm
power was higher in the temporal and central areas of
the right hemisphere and lower in the frontal areas. It
is in agreement with the study of the role of rhythmic
synchronization in the α band for enhancing the accu
racy and efficiency of communication between differ
ent brain regions when providing active attention [38].
In the process of understanding, the EEG α band
power considerably decreased in the occipital and
Vol. 41
Mean EEG FD values by 6 leads
Mean factor values F2
No. 1
Fig. 6. Variations of the mean EEG fractal dimension (FD)
values by 6 leads at the three stages of understanding.
posttemporal areas. It seems that α rhythm may be
considered in the context of its role in information
processing, as well as in connection with the inhibitory
function related to attention: suppression and choice
[39]. In addition, the physiological role of α activity is
known to provide pulse inhibition of reducing expen
ditures on information processing for a potential area,
accompanied by reduction of α activity and synchro
nization in the γ band [40]. The study of verbal creative
activity has shown that complication of the task may
result in strengthening of the activation component
representing more intensive use of brain resources
and, accordingly, inversion of the dependence of cre
ativity level on the level of cortical inactivation accom
panied by EEG power attenuation in the α band, espe
cially in the anterior and parietal cortex [41].
Regarding the variations of three states in the β1
band, we have observed the most marked changes in
the state “after understanding.” This is most likely to
be related to the situation of solution validation by a
subject. It is interesting that the posttemporal lead Т6
is activated in all three states in the β1 band (p < 0.01),
while the Pz lead is employed in the state “before
understanding” (p < 0.01). It is known that the dorsal
parietal cortex is involved mainly in the processing of
spatial properties of external signals and is part of the
visual spatial attention system [42]. Probably, the acti
vation patterns that we have obtained are related to the
specific features of experimental situation: the conflict
of alternative solutions in a subject, which is in
agreement with the results of choice situation
modeling [43].
The data on the β2 band are comparable with the
results of analysis of EEG coherence in the β band
during verbal–mnestic activity. The maximum coher
ence values have been found for distant connections of
posttemporal and parietal regions of the left hemi
sphere with frontal areas of both hemispheres and with
central areas of the right hemisphere [44]. We have
observed the β2 band power increase in the process of
understanding in the occipital, right posterior and
anterior temporal leads, as well as in the left frontal
lead (р < 0.01). This is in agreement with the results of
the study of creative thinking, when fundamental dif
ferences in spectral power were obtained in the high
frequency band in the left parietal, right occipital, left
and right temporal cortex [45]. In the state “after per
ception” there occurs a significant power increase in
the β2 range, mainly in the frontal areas; these changes
are spread over the frontal, central, and even parietal
leads but with the lower significance (p < 0.05).
The dynamics of variations in the γ band activity in
the three states demonstrates a gradual increase in
γ activity in accordance with the amount of perceived
and comprehended information. The most significant
changes are recorded in the frontal, parietal and
occipital areas, particularly in the right hemisphere
(Fp1, Fp2, F7, F8, P4, T4, T6, O1, O2; p < 0.001). The
state “after understanding,” compared to the state
“understanding,” is characterized by an increase in
γ rhythm power, especially in the right hemisphere.
The enhancement of highfrequency rhythmic pat
terns was also observed when modeling the situation of
conscious and unconscious word processing [46].
A relationship between enhanced γ rhythm power and
activation of the attention system was revealed [47].
Comparative study of changes in the spectral activity
of EEG during the solution of verbal creative and non
creative tasks showed significant enhancement of
rhythm powers in the β2 and γ bands during the solu
tion of creative tasks [48].
Summarizing the abovedescribed changes in orga
nization of system brain activity demonstrated by the
analysis of EEG parameters, we should emphasize a
distinct tendency of significant enhancement of the
power of slow rhythms in the Δ and θ bands at the
instance of understanding the sense of the text relative
to other two states. These changes mostly affect frontal
areas, especially those of the right hemisphere. In
highfrequency EEG bands (12–45 Hz), intensifica
tion of the tendency towards an increase in rhythm
frequency is accompanied by enhancement of EEG
power in a subject making sense of the text. This pro
cess encompasses both occipital and anterior brain
The results of EEG FD calculation for 19 leads and
three states presented in Figures 5 and 6 are of partic
ular interest: the maximum values were shown for
“before understanding”; the values drastically
decreased for “understanding”; and the values
increased for “after understanding.” This dynamics
probably reflects the stages of choice and decision
making, as well as solution validation. The first state
(“before understanding”) is characterized by intense
searching for the solution and high information com
plexity in brain activity; that is why the values of EEG
fractal dimension are so high at this stage. It is known
that the higher FD values correspond to the higher
complexity of the system; hence, these values can be
considered as a measure of stochasticity of the studied
process [49, 50]. The state “understanding” is related
to decision making and simplification of system com
plexity to a single choice; therefore, at this stage we
observe the lowest values of EEG FD. It has been
shown that the values of EEG dimension recorded in
healthy subjects in the state of rest are relatively low
[51]. It is interesting that the state of rest and the state
of “understanding” are characterized by comparative
simplicity of brain activity. The state “after under
standing” is characterized by higher values and
enhanced information complexity of brain activity.
This fact deserves particular attention. Apparently,
when the text plot is understood by the subject, usually
upon the fourth to sixth presentation (see the Appen
dix), in the future, it should cause no increase in the
EEG FD values. However, we can see a persistent
trend of a significant increase in this value in all sub
jects. It is most likely to be related to the specificity of
experimental conditions: presentations of the text
continue to the end (eight presentations) irrespective
of the time of understanding; hence, the subject is in
the situation of validating the correctness of his/her
choice and begins to pay attention to additional infor
mation that was excluded at the instance of under
Thus, in the scope of description of putative neuro
physiological mechanisms of the process of under
standing verbal information, we may assume the exist
ence of different regimes in the integrative brain activ
ity, which is in agreement with the modern concepts of
the leveled spatial organization of intersystem interac
tion [52] and network interactions underlying cogni
tive processes [53]. The first regime is intended for sit
uations of intense search for and generation of ideas
and choosing the only correct solution among several
alternatives followed by the validation of correctness of
this solution; it manifests itself in the states “before
understanding” and “after understanding.” This
regime is accompanied by intensification of EEG
power in the γ and β frequency bands, as well as in the
frontal cortex of both hemispheres, especially the right
hemisphere, and is accompanied by the increase in
EEG FD values. The second information regime of
brain activity is switched on in the state of “under
standing”; it is characterized by enhanced EEG power
in the lowfrequency θ band and, in addition, a
decrease in EEG FD value. This regime is activated by
the situation of “simplification” of a set of variants to
the single alternative. Probably, the biological sense of
this information regime consists in consolidation of
information in the context of semantic relations.
Thus, the process of understanding, as we see it,
occurs at the lower disagreement between predictions
Vol. 41
No. 1 2015
and real events, which is reflected in the energetically
more optimal state of nerve cells involved in this func
tional system.
In all likelihood, the more complex is the problem,
the larger group of nerve cells is needed for its solution
and the most complicated is the observed dynamics of
interaction between the elements. However, in our
opinion, the disagreement between the conceptual
schema existing in the brain (which describes the
observed events) and the sensory flow coming in to the
analyzers makes the main contribution to the dynam
ics of interaction between nerve cells. If the scheme
correctly describes the reality, the bioelectric dis
charges of brain cells are synchronized, which pro
vides more energyefficient existence of cells and
reduces the complexity of their interaction.
In EEG dynamics, this process is represented by
the degree of complexity of a signal, which can be
measured by calculating its EGG FD. In the terms
conventional for EEG analysis, the increase and
1 decrease in complexity correspond to desynchroniza
tion and synchronization, respectively. Probably, the
process of complication of EEG dynamics, which
reflects the contradiction between the conceptual
schema and the real situation and is accompanied by
enhanced dimensions of the functional system and
employment of new cells for the latter, is not local; it
affects a pretty large group of leads and entire func
tional units of the brain. In our opinion, the decrease
in EEG FD value reflects the decrease in disagreement
2 between conceptual schemas and real situation, which
is represented at the physiological level by the modifi
cation of synaptic connections in a given functional
system, which corresponds to the conceptual schema
optimal for the given situation.
This study was supported by the Russian Founda
tion for the Humanities, project no. 130600637.
A Sample of Methodology
for StepbyStep Presentation of Text
Text: “The Eagle and the Fox” (plot: injustice;
experts' opinions coincided by 100%).
1. *** to settle close to each other, *** because of
***. *** high *** under shrubs below. *** into ***.
*** came back, understood what ***, *** misera
ble—not *** because *** left for her *** *** week
could ***? *** pay for *** friendship *** brought ***
to *** it to the *** the wind *** blew *** bright ***
burnt *** not *** fox ***.
4. The eagle and the fox decided *** to settle close
to each other, *** friendship *** because of ***. The
eagle *** *** high tree, *** under shrubs below. ***
Vol. 41
No. 1
the fox *** the prey, *** got hungry, *** into ***, ***
with ***. *** came back, understood what ***, ***
miserable—not only because *** cubs *** but rather
*** not ***: *** could not ***. *** was left for her ***
the offender: *** *** the week one ***? *** soon the
eagle *** pay for *** friendship. *** offered *** field;
*** to *** and *** burning entrails. *** soon as *** it
to the nesting place, *** strong wind blew, *** bright
*** burnt *** they *** not ***; and *** the fox ***
them *** in the face of the eagle.
7. The eagle and the fox decided to be friends and
*** settle close to each other, so that the friendship
would be *** because of ***. The eagle nested on a tall
tree, *** the fox gave birth to her cubs under shrubs
below. But once the fox *** the prey, and the eagle got
hungry, flew down into ***, seized *** cubs and
gorged them with his eaglets. *** came back, under
stood what had happened, *** was miserable—not
only because her cubs were dead but rather because
*** she could not revenge: she could not catch *** the
bird. Everything that was left for her was *** the
offender: what else the *** week one can do? But soon
the eagle had to pay for *** friendship. Somebody
offered a goat *** in the field; the eagle flew down to
the sacrificial altar and brought the burning entrails
from there. And as soon as he *** it to the nesting
place, *** strong wind blew, *** thin old twigs ***
with a bright flame. The burnt eaglets fell onto the
ground—they *** not fly yet; and then the fox ***
them all in the face of the eagle.
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Translated by E. Makeeva
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