www.ijcrsee.com
403
Vorobyeva, E. V., & Rahimova, E. F. (2025). Spectral Power of Background EEG, Complex Visual-Motor Response, Galvanic
Skin Response and Electrocardiogram Parameters in Adolescents With Autism Spectrum Disorders and Mental Retardation,
International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), 13(2), 403-411
Original scientific paper
Received: February 03, 2025.
Revised: April 27, 2025.
Accepted: May 07, 2025.
UDC:
616.896-07-053.6
616.899-07-053.6
10.23947/2334-8496-2025-13-2-403-411
© 2025 by the authors. This article is an open access article distributed under the terms and conditions of the
Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
*
Corresponding author:
evorob@sfedu.ru
Abstract: The paper presents the results of a study of the parameters of the galvanic skin response, electrocardiogram,
complex visual-motor response parameters and spectral power of the background EEG on a sample of 34 schoolchildren aged 12
to 17 years with autism spectrum disorders and mental retardation. Electroencephalogram and polygraphic channels (electromyo-
gram, galvanic skin response, electrocardiogram) were recorded. Intelligence was diagnosed using the WISC test by D. Wechsler.
The functional state was assessed by complex visual-motor response parameters using the Psychophysiologist device. The study
found that a higher spectral power of the background EEG in the alpha range in the parietal region corresponds to a higher level of
general intelligence in adolescents with autism spectrum disorders and mental retardation. Evaluation of the complex visual-motor
reaction showed that a higher spectral power of the background EEG in the beta-1 range of the right and central occipital region
corresponds to the average class of sensorimotor reactions. A higher spectral power of the background EEG in the beta-2 range
of the right frontal region is noted in adolescents with a higher class of sensorimotor reactions. The obtained results are used
in the development of individual correctional programs for adolescents with autism spectrum disorders and mental retardation.
Keywords: spectral power of background EEG, complex visual-motor reaction, adolescents with autism spectrum
disorders and mental retardation.
Elena Vorobyeva
1*
, Elena Rahimova
1
1
Academy of Psychology and Educational Sciences, Southern Federal University, Rostov-on-Don, Russian Federation,
e-mail:
evorob@sfedu.ru; erahimova@sfedu.ru
Spectral Power of Background EEG, Complex Visual-Motor Response,
Galvanic Skin Response and Electrocardiogram Parameters in
Adolescents With Autism Spectrum Disorders and Mental Retardation
Introduction
There is an increase in the number of children and adolescents with autism spectrum disorders
(ASD) and mental retardation worldwide. With the change in society as well as the receipt of new data on
the specifics of the course of these types of disorders, it is becoming increasingly clear that the integra-
tion of individuals with these characteristics is possible based on knowledge of the psychophysiological
basis of the development of children and adolescents (Vorobyeva and Kaidanovskaya, 2018). Children
with ASD often have brain macrocephaly, with an increase in volume and density recorded in both white
and gray matter, especially in the frontal and temporal lobes (Zhao et al., 2022) and studies of adults
show data on both increased and decreased brain volume (Arutiunian et al., 2023). Structural and func-
tional abnormalities have been found in the basal ganglia, striatum, hippocampus, and hypothalamus
(Zhao et al., 2022). Brain tissue studies show active neuroinflammatory processes in the cortex and
white matter (Pardo et al., 2007), changes in sulcal depth in areas of the brain that are associated with
language (Arutiunian et al., 2023), reduced dendritic branching, increased density of smaller neurons in
the hippocampus and amygdala nuclei, decreased number of Purkinje cells, and underdevelopment of
inhibitory neurons (Pardo et al., 2007). Individuals with ASD have elevated levels of serotonin, glutamate,
aspartate, phenylalanine, histidine, tyrosine, and taurine, and decreased levels of oxytocin, endorphins,
glutamine, and asparagine in the blood (Brister et al., 2022; Zhao, Zhang et al., 2022).
The electrical brain activity of children with ASD has such features as the lack of expression of
the main rhythm and zonal differences, increased electrical activity of the beta range in combination
www.ijcrsee.com
404
Vorobyeva, E. V., & Rahimova, E. F. (2025). Spectral Power of Background EEG, Complex Visual-Motor Response, Galvanic
Skin Response and Electrocardiogram Parameters in Adolescents With Autism Spectrum Disorders and Mental Retardation,
International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), 13(2), 403-411
with diffuse waves of theta and delta ranges, and reduced amplitude indicators of evoked potentials, an
asymmetric distribution in the occipital regions and a general decrease in alpha rhythm activity, a higher
spectral power of the gamma rhythm (
Zhukova, 2016; Misyuk, 2012). Researchers also note the presence
of hyperexcitable areas of the brain, differences in areas of activity from the norm, changes in coherence
and disruption of information exchange processes between different areas of the brain (Boutros et al.,
2015; Gamirova et al., 2023). Studies also report redundancy of local connections of the cerebral cortex
areas and insufficiency of functional interaction of relatively remote regions (frontal and parietal areas of
the neocortex) (Pavlenko et al., 2023). The features of the disorders vary depending on the type of ASD
and its manifestations. One of the EEG features of people with ASD is the suppression of the mu rhythm
(a subtype of the alpha rhythm recorded during sensorimotor activation). A change in the manifestation of
the mu rhythm can signal a malfunction of mirror neurons (Misyuk et al., 2012; Pavlenko et al., 2023). The
frequency of epileptic seizures reaches 30% in people with ASD (Misyuk et al., 2012), with various forms
of epileptiform activity noted (Boutros et al., 2015; Belousova et al., 2018).
The peripheral nervous system shows reduced phasic and tonic components of the electrodermal
activity in individuals with ASD, as well as no change in amplitude when emotional stimuli are presented
compared to normotypic individuals, indicating autonomic dysregulation (Farmer et al., 2017; Gul et al.,
2020). Signs of increased intracranial pressure are noted (Avtenyuk, 2016). A reduced level of muscle
activation is noted (Borji et al., 2014). Heart rate variability in individuals with ASD is characterized by
increased background heart rate with decreased background peripheral nervous system activity and re-
activity to psychosocial stimuli (Belova et al., 2017).
A lot of attention is paid to differential diagnostics in the work with children with mental retarda-
tion, in particular, an audiological examination is carried out in order to differentiate children with mental
retardation from the children with hearing impairment (Karantysh et al., 2022). Characteristic features of
the EEG of children with mental retardation are a decrease in the frequency of the alpha rhythm and its
unevenness, suppression of the theta rhythm and gamma rhythm, high-amplitude delta rhythm (especially
in the left frontal-temporal region) (Lobasyuk et al., 2021). Non-standard sources of rhythms in the brain
are also noted (Lobasyuk et al., 2023). Active epileptic and paroxysmal disorders are observed (Ünal et
al., 2009). Up to 20% of children with mental retardation have a right lateral profile (Lobasyuk et al., 2021).
The theoretical and methodological basis of this work were formed by the ideas that have been de-
veloped in Russian and international clinical psychology about the specifics of the development of adoles-
cents with ASD and mental retardation (Appe, 2019; Volkmar et al., 2014; Grigorenko, 2018; Dovbnya S.
et al., 2022; Isaev, 2007); standards for psychological assessment of intelligence (Clinical, 2021; Clinical,
2024); psychophysiological approach (Blinova et al., 2017; Blinova et al., 2017; Barbier et al, 2022; Borji
et al, 2014); ideas about the relationship between EEG parameters and intellectual indicators (Gamirova
et al., 2023; Pavlenko et al., 2023; Lobasyuk et al., 2021).
In one of our previous works, a relationship was also established between general intelligence and
functional state in adolescents with ASD and mental retardation (Vorobyeva and Rahimova, 2023).
In correctional and developmental work with adolescents with autism spectrum disorders and men-
tal retardation, the issue of taking into account their individual psychological characteristics (specificly,
intellectual characteristics; neuropsychological characteristics; psychophysiological characteristics, such
as the speed of response and the characteristics of the functional state, manifested in the parameters of
a complex visual-motor reaction, as well as the characteristics of the spectral power of the background
EEG and during activation procedures) remains insufficiently studied.
Materials and Methods
The study involved 34 teenagers (7 girls and 27 boys) aged 12–17 with ASD and mental retarda-
tion, students at the Rostov Specialized Boarding School No. 41 and the Rostov Specialized Boarding
School No. 42 (Rostov-on-Don). The study was conducted individually.
Research methods. The electroencephalograph “Encephalan-EEGR-19/26” manufactured by
“Medicom” in Taganrog (Russia) was used to record the EEG. 21 electrodes were placed according to the
International 10–20 electrode placement system in Fp1, Fp2, Fpz, F3, F4, F7, F8, Fz, C3, C4, Cz, T3, T4,
T5, T6, P3, P4, Pz, O1, O2, Oz positions using a monopolar scheme with ipsilateral earlobe referents.
Polygraphic channels (electromyogram (EMG), galvanic skin response (GSR), electrocardiogram (ECG))
www.ijcrsee.com
405
Vorobyeva, E. V., & Rahimova, E. F. (2025). Spectral Power of Background EEG, Complex Visual-Motor Response, Galvanic
Skin Response and Electrocardiogram Parameters in Adolescents With Autism Spectrum Disorders and Mental Retardation,
International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), 13(2), 403-411
were used to track and suppress artifacts. Recording was made in an isolated room. The analysis epoch
was 10 minutes. The resistance did not exceed 10 kOhm. The EEG recording was performed with the
“background”, “eyes open”, “eyes closed” functional tests, tests with photo- and phono-stimulation, test
with hyperventilation. This article presents estimates of the spectral power absolute values of the back-
ground EEG in the ranges of delta-1 (0-2 Hz), delta-2 (2-4 Hz), theta (4-7 Hz), alpha (8-12 Hz), beta-1
(14-20 Hz), beta-2 (20-35 Hz).
The children’s version of the D. Wechsler test (WISC) was used in the adaptation of A. Yu. Panasyuk
for the diagnosis of intelligence (Panasyuk, 1991).
The functional state was assessed based on the parameters of the complex visual-motor reaction
(CVMR) using the UPFT-1/30 Psychophysiologist psychophysiological testing device (Medicom MTD,
Russia, Taganrog). The level of sensorimotor reactions (LOSR) was assessed as follows: >0.81 — high;
0.58–0.8 — above average; 0.59–0.36 — average; 0.37–0.1 — below average; < 0.1 — low (Methodical,
2015). Statistica 10.0 was used for statistical processing (Spearman’s rank correlation coefficient, one-
way analysis of variance (ANOVA), post-hoc analysis with Bonferroni correction).
Results
Spectral power absolute values analysis of the background EEG (with closed eyes) was performed.
Table 1 presents the results of spectral power absolute values analysis of background EEG by ranges
(delta-1 (0–2 Hz), delta-2 (2–4 Hz), theta (4–7 Hz), alpha (8–12 Hz), beta-1 (14–20 Hz), beta-2 (20–35
Hz)) in Fp1, Fp2, Fpz, F3, F4, F7, F8, Fz, C3, C4, Cz, T3, T4, T5, T6, P3, P4, Pz, O1, O2, Oz leads.
Table 1. Results of the analysis of spectral power absolute values of background EEG
Positions
Power by range (µV
2
)
Delta-1 Delta-2 Theta Alpha Beta-1 Beta-2
Fp1 9,5±5,6 15,3±7,9 18,1±14,2 21,4±18,4 6,3±4,4 0,1±0,1
Fp2 9,4±4,7 16,0±8,2 21,2±15,5 38,4±44,9 7,9±6,5 0,1±0
Fpz 15,8±7,8 20,7±8,5 19,6±10,8 16,7±11 6,2±3,3 0,1±0,1
F3 10,6±5,8 16,4±8,3 21,4±17,2 39,9±39,3 7,9±6,2 0,1±0,1
F4 10,4±5,0 16,4±8,3 23,7±21,2 63,9±87,4 8,6±5,4 0,1±0
F7 8,9±4,4 14,6±7,2 18,6±13,1 22,5±21,0 6,6±5 0,1±0
F8 9,5±5,6 15,3±7,9 18,1±14,2 21,4±18,4 6,3±4,4 0,1±0,1
Fz 13,1±5,5 20,0±7,6 26,3±14,3 25,4±20 7,9±4,6 0,1±0,1
C3 11,4±6,3 17,5±9,3 23,2±19,0 57,6±61,7 9,6±6,5 0,2±0,2
C4 11,9±5,1 18,1±8,6 26,1±18,8 37,6±35,8 8,4±6,2 0,1±0
Cz 12,1±5,0 20,3±8,5 27,6±18,4 37,4±34,8 8,6±5,9 0,1±0,1
T3 9,4±4,7 16,0±8,2 21,2±15,5 38,4±44,9 7,9±6,5 0,1±0
T4 10,6±5,8 16,4±8,3 21,4±17,2 39,9±39,3 7,9±6,2 0,1±0,1
T5 10,4±5,0 16,4±8,3 23,7±21,2 63,9±87,4 8,6±5,4 0,1±0
T6 11,4±6,3 17,5±9,3 23,2±19,0 57,6±61,7 9,6±6,5 0,2±0,2
P3 12,3±5,5 19,7±9,0 24,8±17,7 72,7±91,5 9,6±6,7 0,1±0
P4 11,7±5,1 17,9±9,6 26,5±19,3 71,3±91,0 10,1±7,5 0,1±0,1
Pz 12,4±5,7 20,1±9,6 26,6±19,1 75,8±96,9 10,2±7,6 0,1±0,1
O1 11,6±6,0 17,2±9,5 21,6±16,1 90,8±97,9 10,7±6,5 0,1±0,1
O2 10,8±5,5 14,5±7,4 22,0±17,0 66,9±56,5 11,9±6,6 0,2±0,2
Oz 11,3±6,1 18,0±10,5 22,3±18,2 75,0±78,4 10,8±6,9 0,2±0,1
www.ijcrsee.com
406
Vorobyeva, E. V., & Rahimova, E. F. (2025). Spectral Power of Background EEG, Complex Visual-Motor Response, Galvanic
Skin Response and Electrocardiogram Parameters in Adolescents With Autism Spectrum Disorders and Mental Retardation,
International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), 13(2), 403-411
The data presented in Table 1 shows that adolescents with ASD and intellectual disability have
absolute spectral power values of background EEG within the normal range in the delta-1, theta and beta-
1 ranges, a wide range of absolute spectral power values in the alpha range, as well as an increase of
absolute spectral power values in the delta-2 range and a decrease in absolute spectral power values in
the beta-2 range compared to age-related normative indicators (
Tereshchenko et al., 2010). The following
descriptive statistics were obtained from the participants’ completion of the WISC test: verbal intelligence
63.7±17.5, non-verbal intelligence 82.5±24.8, general intelligence 69.6±20.4. Analysis of the general
intelligence level showed that 16 people (52%) have the “intellectually poor” level, 4 people have the “bor-
derline” level (13%), 5 people have the “below average” level (16%), 5 people have the “average” level
(16%), 1 person has the “high” level (3%). Results show that the study participants have a statistically
higher level of non-verbal intelligence compared to verbal intelligence (z = 2.7, p < 0.01).
A one-way analysis of variance was carried out for the spectral power absolute values of the back-
ground EEG of different ranges depending on the level of general intelligence. Further, in Figures 1, 2 and
3, statistically significant results of one-factor ANOVA are presented, where the assessment of the level of
general intelligence was used as an independent variable, and the assessment of the spectral power of
the background EEG was used as a dependent variable.
Figure 1. Results of one-way analysis of variance (X-axis – independent variable: general intelligence level (1 - in-
tellectually poor, 2 - borderline level, 3 - below average, 4 - average level); Y-axis – dependent variable – spectral
power absolute values of the background EEG alpha range in P3 lead, μV2.
Figure 2. Results of one-way ANOVA (X-axis – independent variable: general intelligence level (1 – intellectually
poor, 2 - borderline level, 3 - below average, 4 - average level); Y-axis – dependent variable – spectral power
absolute values of the background EEG alpha range in P4 lead, μV2.
www.ijcrsee.com
407
Vorobyeva, E. V., & Rahimova, E. F. (2025). Spectral Power of Background EEG, Complex Visual-Motor Response, Galvanic
Skin Response and Electrocardiogram Parameters in Adolescents With Autism Spectrum Disorders and Mental Retardation,
International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), 13(2), 403-411
Figure 3. Results of one-way ANOVA (X-axis – independent variable: general intelligence level (1 – intellectu-
ally poor, 2 – borderline zone, 3 – below average, 4 – average IQ); Y-axis – dependent variable – spectral power
absolute values of the background EEG apha range in Pz lead, μV2.
As a result of one-way analysis of variance, it was found that there are significant differences in the
EEG spectral power in adolescents with ASD and mental retardation in the alpha range for P3 (F = 4.6, p
< 0.05), P4 (F = 3.99, p < 0.05) and Pz (F = 4.18, p < 0.05) leads. Post-hoc comparisons with Bonferroni
correction showed that a higher level of general intelligence corresponds to a higher EEG spectral power
in the alpha range (all p < 0.05).
Moreover, a higher level of general intelligence corresponds to a higher spectral power of the
EEG in the alpha range. As a result of completing the task on complex visual-motor reaction (it was pos-
sible to assess the visual-motor reaction time in 31 teenagers), the following indicators were assessed:
average reaction time (ms) 666.9±197.6, integral reliability index (IRI) 29.3±25.9, standard deviation
(ms) 211.5±101.5, number of anticipations 2.4±3.5, number of incorrect answers 1.4±1.4, number of
omissions 2.0±3.1, total number of errors 6.1±6.6, class of sensorimotor reactions 1.9±1.55, assessment
of the level of sensorimotor reactions 0.17±0.23. The assessment of the level of sensorimotor reactions
showed that seven (23%) adolescents with ASD and mental retardation failed to complete the task during
the complex visual-motor reaction test, due to the fact they completed the task too slowly, made a critically
large number of errors or did not understand the instructions. Further, the number of adolescents with
ASD and mental retardation who completed the complex visual-motor reaction task was distributed as fol-
lows: the first (low) class of sensorimotor reactions was detected in eight adolescents (26%), the second
(below average) class - in four adolescents (13%), the third (average) class - in six adolescents (19%), the
fourth (above average) class - in five adolescents (16%), the fifth (high) class - in one adolescent (3%).
A one-way analysis of variance was performed for the absolute values of the spectral power of
the background EEG of different ranges depending on the class of sensorimotor reactions. The results of
the conducted one-factor ANOVA on the influence of the class of sensorimotor reactions on the spectral
power of the background EEG are presented in Figures 4, 5, 6.
www.ijcrsee.com
408
Vorobyeva, E. V., & Rahimova, E. F. (2025). Spectral Power of Background EEG, Complex Visual-Motor Response, Galvanic
Skin Response and Electrocardiogram Parameters in Adolescents With Autism Spectrum Disorders and Mental Retardation,
International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), 13(2), 403-411
Figure 4. Results of one-way ANOVA (X-axis – independent variable: sensorimotor reaction class (0 – no class,
1 – low, 2 – below average, 3 – average, 4 – above average, 5 – high); Y-axis – dependent variable – spectral
power absolute values of the background EEG beta-1 range in O2 lead, μV2.
Figure 5. Results of one-way ANOVA (X-axis – independent variable: sensorimotor reaction class (0 – no class,
1 – low, 2 – below average, 3 – average, 4 – above average, 5 – high); Y-axis – dependent variable – spectral
power absolute values of the background EEG beta-1 range in Oz lead, μV2.
Figure 6. Results of one-way analysis of variance (X-axis – independent variable: sensorimotor reaction class (0
– no class, 1 – low, 2 – below average, 3 – average, 4 – above average, 5 – high); Y-axis – dependent variable –
spectral power absolute values of the background EEG beta-2 range in F8 lead, μV2.
www.ijcrsee.com
409
Vorobyeva, E. V., & Rahimova, E. F. (2025). Spectral Power of Background EEG, Complex Visual-Motor Response, Galvanic
Skin Response and Electrocardiogram Parameters in Adolescents With Autism Spectrum Disorders and Mental Retardation,
International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), 13(2), 403-411
The conducted one-factor ANOVA allowed us to determine the parameters of the EEG spectral
power in the background of adolescents with ASD and mental retardation: in the beta1 range for O2 (F
= 4.53, p < 0.05) and Oz (F = 3.18, p < 0.05) leads; in the beta2 range for F8 (F = 4.81, p < 0.05) lead.
Post-hoc analysis with Bonferroni correction showed that the average class of sensorimotor reactions cor-
responded to higher spectral power values in the beta-1 range; a higher class of sensorimotor reactions
corresponded to higher spectral power values in the beta-2 range (all p < 0.05).
One-factor ANOVA also showed that, depending on the class of sensorimotor reactions, there were
statistically significant differences in the spectral power of the galvanic skin response (F = 18.8; p < 0.01)
and electrocardiogram (F = 513.31; p < 0.01) data recorded during the background electroencephalogram
recording.
Discussions
As shown by the results obtained in this work, a higher level of intelligence corresponds to a higher
EEG spectral power in the alpha range for P3, P4 and Pz leads in adolescents with ASD and mental re-
tardation. This may indicate instability of information processing processes, which existing data confirms
(Boutros et al., 2015; Arutiunian et al., 2023; Gamirova et al., 2023). In our work, it was found that, accord-
ing to the parameters of the complex visual-motor reaction, the average class of sensorimotor reactions in
adolescents with ASD and mental retardation corresponds to higher values of the EEG spectral power of
the beta-1 range for O2 and Oz leads, and a higher class of sensorimotor reactions corresponds to higher
values of the spectral power in the beta-2 range for F8 lead. An increase in the parameters of sensorimo-
tor reactions at the EEG level corresponds to an increase in the high-frequency component in the right
frontal region in adolescents with ASD and mental retardation, which can be regarded as an increase in
the activation of the right frontal cortex.
It was also found in our work that in relation to the parameters of a complex visual-motor reaction,
a higher class of sensorimotor reactions corresponds to higher spectral power values of the GSR and
ECG, that is, at a higher level of the functional state, the peripheral nervous system is more activated.
The higher values of the peripheral nervous system performance indicators in adolescents with ASD and
mental retardation obtained in our work are also consistent with the information on the features of its work
in these groups of adolescents (Gul et al., 2020).
Conclusions
1. In adolescents with ASD and mental retardation, a higher level of general intelligence corresponds
to a higher spectral power of the EEG in the alpha range in the parietal region.
2. Evaluation of the complex visual-motor reaction showed that the average class of sensorimotor
reactions in adolescents with ASD and mental retardation corresponds to a higher spectral power
in the beta-1 range of the right and central occipital region; a higher class of sensorimotor reactions
corresponds to a higher spectral power in the beta-2 range of the right frontal region.
3. A higher class of sensorimotor reactions corresponds to higher spectral power values of the galvanic
skin response and electrocardiogram.
Obtained results contribute to the theoretical basis of psychophysiology and psychology of adoles-
cents with ASD and mental retardation. The obtained data is used to draw up a plan for psycho-correc-
tional and psycho-developmental work.
Acknowledgments
The authors would like to express their sincere gratitude to the 34 participants who cooperated in this study.
Conflict of interests
The authors declare no conflict of interest.
www.ijcrsee.com
410
Vorobyeva, E. V., & Rahimova, E. F. (2025). Spectral Power of Background EEG, Complex Visual-Motor Response, Galvanic
Skin Response and Electrocardiogram Parameters in Adolescents With Autism Spectrum Disorders and Mental Retardation,
International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), 13(2), 403-411
Author Contributions
Conceptualization and methodology, Vorobyeva E.; formal analysis, Rahimova E.; writing—original
draft preparation, Vorobyeva E., Rahimova E.; writing—review and editing, Vorobyeva E., Rahimova E.;
All authors have read and agreed to the published version of the manuscript.
References
Appe, F. (2019). Vvedenie v psixologicheskuyu teoriyu autizma. [Introduction to the psychological theory of autism]. Moscow.
Terevinf. 217.
Arutiunian, V., Gomozova, M., Minnigulova, A., Davydova, E., Pereverzeva, D., Sorokin, A., Tyushkevich, S., Mamokhina, U.,
Danilina, K., & Dragoy, O. (2023). Structural brain abnormalities and their association with language impairment in
school–aged children with autism spectrum disorder. Scientic Reports. 13(1). 1172.
https://www.nature.com/articles/
s41598-023-28463-w
Avtenyuk, A. S. (2016). Atonicheskaya forma umstvennoj otstalosti: klinika i simptomatika. Dissertaciya kandidata medicinskix
nauk. [Atonic form of intellectual disability: clinical features and symptoms. Dissertation of candidate of medical sci-
ences]. St. Petersburg. 130.
Barbier, A., Chen, J. H., & Huizinga, J. D. (2022). Autism Spectrum Disorder in Children Is Not Associated with Abnormal
Autonomic Nervous System Function: Hypothesis and Theory. Frontiers in Psychiatry. 13.
https://doi.org/10.3389/
fpsyt.2022.830234
Belousova, E. D., & Zavadenko, N. N. (2018). E`pilepsiya i rasstrojstva autisticheskogo spektra u detej. [Epilepsy and autism
spectrum disorders in children]. Journal of Neurology and Psychiatry named after S. S. Korsakov. 118(5-2). 80-85.
https://doi.org/ 10.17116/jnevro20181185280
Belova, A. N., Borzikov, V. V., Kuznetsov, A. N., & Komkova, O. V. (2017). Aktivnost` vegetativnoj nervnoj sistemy` po rezul`tatam
issledovaniya variabel`nosti serdechnogo ritma u detej s rasstrojstvami autisticheskogo spektra (obzor). [Activity of the
autonomic nervous system according to the results of the study of heart rate variability in children with autism spectrum
disorders (review)]. Medical Almanac. 50(5). 130-136.
Blinova, N. G., Koshko, N. N., & Akbirov, R. M. (2017). Morfofunkcional`ny`e i psixoziologicheskie osobennosti detej s narush-
eniyami umstvennogo razvitiya. [Morphofunctional and psychophysiological characteristics of children with intellectual
disability]. Bulletin of Kemerovo State University. 71(3). 110-116.
Borji, R., Zghal, F., Zarrouk, N., Sahli, S., & Rebai, H. (2014). Individuals with intellectual disability have lower voluntary muscle
activation level. Research in Developmental Disabilities. 35(12). 3574–3581.
https://doi.org/10.1016/j.ridd.2014.08.038
Boutros, N. N., Lajiness-O’Neill,, R., Zillgitt A., Richard, A. E., & Bowyer, S. M. (2015). EEG changes associated with autistic
spectrum disorders. Neuropsychiatric Electrophysiology. 1(3). 1–20. https://doi.org/10.1186/s40810-014-0001-5
Brister, D., Rose, S., Delhey, L., Tippett, M., Jin ,Y., Gu, H., & Frye, R. E. (2022). Metabolomic Signatures of Autism Spectrum
Disorder. Journal of Personalized Medicine. 12(10):1727. https://doi.org/10.3390/jpm12101727
Farmer, G. D., Baron–Cohen, S., & Skylark, W. J. (2017). People with autism spectrum conditions make more consistent deci-
sions. Psychological Science. 28(8). 1067–1076. https://doi.org/ 10.1177/0956797617694867
Gamirova, R. G., Sana, A. R., Gorobets, E. A., & Sana, D. R. (2023). Rasstrojstva autisticheskogo spektra u detej: diag-
nosticheskaya znachimost` e`lektroe`ncefalograi. [Autism spectrum disorders in children: diagnostic signicance of
electroencephalography]. Bulletin of modern clinical medicine. 16(2). 80-88.
Grigorenko, E. L. (2018). Rasstrojstva autisticheskogo spektra. Vvodny`j kurs. Uchebnoe posobie dlya studentov. [Autism
spectrum disorders. Introductory course. Textbook for students]. Moscow. Praktika. 280.
Gul, A. А., Sudirman, R., Sheikh, U. U., Lee, Y. K., & Zakaria, N. (2020). Signicance of Electrodermal Activity Response in
Children with Autism Spectrum Disorder. Indonesian Journal of Electrical Engineering and Computer Science. 19(2).
1208–1216. https://doi.org/10.11591/ijeecs.v19.i2.pp1113-1120
Dovbnja, S., Morozova, T., Zalogina, A., & Monova, I. (2022). Deti s rasstrojstvami autisticheskogo spektra v detskom sadu i
shkole: Praktiki s dokazannoj e`ffektivnost`yu. [Children with autism spectrum disorders in kindergarten and school:
Practices with proven effectiveness]. Moscow. Alpina PRO. 168.
Isaev, D. N. (2007). Umstvennaya otstalost` u detej i podrostkov. Rukovodstvo. [Intellectual disability in children and adoles-
cents. Manual]. St. Petersburg. Rech. 384.
Karantysh, G. V., Muratova, M. A., Guterman, L. A., Mendzheritsky, A. M., & Vorobyeva, E. V. (2022). Diagnostika i korrekciya
sluxovogo vospriyatiya u detej 8–10-letnego vozrasta s umstvennoj otstalost`yu. [Diagnostics and correction of audi-
tory perception in children aged 8–10 years with intellectual disability]. Russian Psychological Journal. 2022. 19(4).
47-70.
https://doi.org/10.21702/rpj.2022.4.3
Klinicheskie rekomendacii «Umstvennaya otstalost` u detej i podrostkov». [Clinical guidelines «Intellectual disability in children
and adolescents»]. Ministry of Health of the Russian Federation. 2023.
www.ijcrsee.com
411
Vorobyeva, E. V., & Rahimova, E. F. (2025). Spectral Power of Background EEG, Complex Visual-Motor Response, Galvanic
Skin Response and Electrocardiogram Parameters in Adolescents With Autism Spectrum Disorders and Mental Retardation,
International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), 13(2), 403-411
Klinicheskie rekomendacii «Rasstrojstva autisticheskogo spektra v detskom vozraste: diagnostika, terapiya, prolaktika, re-
abilitaciya». [Clinical guidelines «Autism spectrum disorders in childhood: diagnostics, therapy, prevention, rehabilita-
tion»]. Ministry of Health of the Russian Federation. 2024.
Lobasyuk, B. A., Bartsevich, L. B., & Zamkovaya, А. V. (2021). Analysis of electrogenesis’ changes in intellectual disability
persons by using computer electroencephalography. Journal of Education, Health and Sport. 11(11). 249–265.
https://
doi.org/10.12775/JEHS.2021.11.11.025
Lobasyuk, B. A., Bartsevich, L. B., & Zamkovaya, A. V. (2023). The use of multiple regression analysis to study the relationship
between the amplitudes of EEG rhythms within one derivation with intellectual disability. Journal of Education Health
and Sport. 47(1). 42–58. https://doi.org/10.12775/JEHS.2023.47.01.004
Metodicheskij spravochnik «Ustrojstvo psixoziologicheskogo testirovaniya UFPT-1/30 - «Psixoziolog». [Methodological ref-
erence book “Device for psychophysiological testing UFPT-1/30 - «Psychophysiologist»]. Taganrog. Medikom MTD.
2015. 122 p.
Misyuk, N. N., Dokukina, T. V., Marchuk, S. A., Sergeeva, N. A., & Greben, S. A. (2012). Nejroziologicheskie issledovaniya
pri autizme. [Neurophysiological studies in autism]. Psychiatry, psychotherapy and clinical psychology. 10(4). 96-109.
Panasyuk, A. Yu. (1991). Adaptirovanny`j variant metodiki Vekslera. [An adapted version of the Wechsler method]. Moscow. 79 p.
Pardo, C. A., & Eberhart, C. G. (2007). The Neurobiology of Autism. Brain Pathology. 17(4). 434–447. https://doi.org/10.1111/
j.1750-3639.2007.00102.x
Pavlenko, V. B., Kaida, A. I., Klinkov, V. N., Mikhailova, A. A., Orekhova, L. S., & Portugalskaya, A. A. (2023). Osobennosti
reaktivnosti μ–ritma E`E`G u detej s rasstrojstvami autisticheskogo spektra v situaciyax pomogayushhego povedeniya.
[Features of the reactivity of the EEG μ-rhythm in children with autism spectrum disorders in situations of helping be-
havior]. Bulletin of the Russian State Medical University. 2. 24-30.
https://doi.org/10.24075/vrgmu.2023.009
Tereshchenko, E. P., Ponomarev, V. A., Müller, A., & Kropotov, Yu. D. (2010). Normativny`e znacheniya spektral`ny`x xara-
kteristik EEG zdorovy`x ispy`tuemy`x ot 7 do 89 let. [Normative values of spectral characteristics of EEG of healthy
subjects from 7 to 89 years old]. New studies. 36(1). 5-17.
https://www.elibrary.ru/item.asp?id=17069571
Unal, O., Ozcan, O., Oner, O., Akcakin, M., Aysev, A., & Deda, G. (2009). EEG and MRI ndings and their relation with
intellectual disability in pervasive developmental disorders. World Journal of Pediatrics. 5(3). 196–200. https://doi.
org/10.1007/s12519-009-0037-y
Volkmar, F. R., & Weisner, L. A. (2014). Autizm: Prakticheskoe rukovodstvo dlya roditelej, chlenov sem`i i uchitelej. [Autism: A
Practical Guide for Parents, Family Members, and Teachers]. Ekaterinburg. Rama Publishing. 224 p.
Vorobyeva, E.V., & Kaidanovskaya, I.A. (2018). Psixoziologiya detej i podrostkov. Uchebnoe posobie. [Psychophysiology of
children and adolescents. Study guide]. Rostov-on-Don. Publishing house of SFedU. 175 p.
Vorobyeva, E.V., & Rahimova, E.F. (2023). Ocenka intellekta i funkcional`nogo sostoyaniya detej 12-15 let s rasstrojstvom
autisticheskogo spektra i umstvennoj otstalost`yu. [Assessment of intelligence and functional state of children aged
12-15 years with autism spectrum disorder and intellectual disability]. Proceedings of the international scientic confer-
ence «Ananyev Readings - 2023. Man in the modern world: potentials and prospects of developmental psychology».
Petersburg, Kirillitsa Publishing House. 123.
Zhao, F., Zhang, H., Wang, P., Cui, W., Xu, K., Chen, D., Hu, M., Li, Z., Geng, X., & Wei, S. (2022). Oxytocin and serotonin
in the modulation of neural function: Neurobiological underpinnings of autism–related behavior. Frontiers in Neurosci-
ence. 16. https://doi.org/10.3389/fnins.2022.919890
Zhao, X., Zhu, S., Cao, Y., Cheng, P., Lin, Y., Sun, Z., Jiang, W., & Du, Y. (2022). Abnormalities of Gray Matter Volume and Its
Correlation with Clinical Symptoms in Adolescents with High–Functioning Autism Spectrum Disorder. Neuropsychiatric
Disease and Treatment. 18. 717–730.
https://doi.org/10.2147/NDT.S349247
Zhukova, M. A. (2016). Osobennosti EEG–ritmov u lyudej s RAS. [Features of EEG rhythms in people with ASD]. Psychological
Science and Education. 21(3). 47-55. https://doi.org/10.17759/pse.2016210306