Correction of Attention in a Learning Ability Task with using

Non-invasive Neurostimulation of Peripheral Nervous System

Vladimir Kublanov, Anna Petrenko and Aleksandra Nabiullina

Research Medical and Biological Engineering Centre of High Technologies, Ural Federal University, Mira 19, 620002,

Yekaterinburg, Russian Federation

Keywords: Neuroscience of Learning, Neuro-electrostimulation, Neuroplasticity, Learning Difficulties, Attention.

Abstract: The paper contains the results of pilot research on neuro-electrostimulation influence with a help of special

field of the current pulses on characteristics of attention, which are some of the main parameters of the learning

process. The method of dynamic correction of the activity of the sympathetic nervous system implemented

by means of the «SYMPATHOCOR-01» device for improving educational and cognitive parameters is

proposed. It is shown that the attention parameters such as speed and productivity can be improved by using

neuro-electrostimulation. Also, it was shown that some of the autonomic nervous system characteristics, in

particular LF and VLF spectral components of heart rate variability, can be chosen as indicators of human

efficiency changes.

1 INTRODUCTION

At the current stage of science and technology

progress, in terms of implementation of new

technologies, people have to be able to materialize

their potential in order to be fully engaged in social

life. During this process, development of learning

technologies and evaluation of individual learning

capabilities have a special role. Providing of effective

training of difficult technical systems specialists is

now becoming an urgent task in connection with a

rapid development of a technical component of

difficult systems amid decrease in general level of

training. It is caused by a number of factors (including

those of exogenous nature) depending on a situation

in each country.

That is why issues related with improving the

efficiency and speed of learning are the most

important at the present time. Generally, learning

capability means the totality of human intellectual

properties, which express the cognitive activity of the

subject and its ability to assimilate new knowledge,

action, complex forms of activity. Expressing general

abilities, learning capability acts as a general

possibility of mental development, achieving more

generalized knowledge systems, common modes of

action. As an empirical characteristics of the human

capacity to learn, learning ability includes many

indicators and parameters of the human personality.

These include, above all, the cognitive capabilities of

humans (features of sensory and perceptual

processes, memory, attention, thought and speech),

personality characteristics - motivation, character,

emotional displays (Hickok and Small, 2016).

Various departments of a brain participate in these

processes. Brain integrates the complex and varied

input signals from several sensor systems

simultaneously for a quick understanding and

evaluating information at performing complex

operations. The relationship of these systems is

carried out by the operation of neural networks

(DARPA, 2016).

According to one of key principles of

neurobiology, our brain is plastic and is constantly

changing as a result of training. The cognitive reserve

and human adaptive responses to stress, traumatic

events and illnesses are formed in the training

process. Thus, the problems associated with learning,

reflect inefficient using of brain resources (The Royal

Society, 2011). There is the idea of activation of these

resources in order to increase the speed and efficiency

of training. Synaptic plasticity can be enhanced by

activation of certain brain areas via peripheral neuro-

electrostimulation. At the same time there is a release

of neurotransmitters associated with the components

of training, such as acetylcholine, dopamine,

serotonin and noradrenaline.

There are assumptions that the conjunction of

Kublanov V., Petrenko A. and Nabiullina A.

Correction of Attention in a Learning Ability Task with using Non-invasive Neurostimulation of Peripheral Nervous System.

DOI: 10.5220/0006159602690275

peripheral neuro-electrostimulation with traditional

learning methods allows to use endogenous neural

circuitry for enhancement of learning quality by

accelerating the setting of neural networks

responsible for the cognitive functions (DARPA,

2016). Therefore, there is an interest to investigate the

possibility of such the approach for education quality

improvement.

In this paper the results of a pilot research of

neuro-electrostimulation of the peripheral nervous

system on characteristics of attention. As noted

above, these characteristics are one of the main

parameters of the learning process.

2 MATERIALS AND METHODS

2.1 Neuro-electrostimulation Method

The «SYMPATHOCOR-01» device, which

generates spatially distributed field of current pulses,

is selected as the neuro-electrostimulation method

(Kublanov, 2008). The device provides multi-channel

percutaneous non-invasive impact on the pathways of

nerve formations and neck ganglia of the sympathetic

nervous system by the method of dynamic correction

of the activity of the sympathetic nervous system

(DCASNS) (Danilov et al., 2015). The

«SYMPATHOCOR-01» device is permitted for use

in medical institutions of the Russian Federation and

has a state certificate of the Federal Service on

Surveillance in Healthcare and Social Development

№ FSR 2007/00757 от 27.09.2007. Application of

the device does not cause side effects (Kublanov et al

2010).

The general view of the «SYMPATHOCOR-01»

device is shown in Figure 1.

Figure 1: The general view of the «SYMPATHOCOR-01»

device.

As it is shown on Figure 1, two multi-element

electrodes in the device have a 13 partial electrodes

by which field of current pulses is formed. The partial

electrodes may act as anodes or cathodes depending

on the field direction of the current pulses. Parameters

field of the current pulses can change in the following

range: the amplitude of the partial current pulses from

0 to 100 mA, the pulse duration of the partial current

from 10 to 100 microseconds, the frequency of the

partial current pulses from 1 to 200 Hz.

It is well known, that the processes in the central

nervous system are the basis of all human mental

activity. It is worth to note here the role of the cerebral

circulation: mental performance (attention, memory

and perception, logical thinking) is reduced at the

deterioration of blood supply to the brain. This feature

determines the search for solutions to manage the

blood supply of the brain. Therefore, those

physiological mechanisms of the sympathetic

nervous system are fundamental which allows to

control the tone of the blood vessels of different

caliber.

The most important formations that are involved

in the organization of neuro-electrostimulation are as

follows: glossopharyngeal nerve and its branches,

vagus nerve and its branches, the accessory nerve, the

nerve plexus around the carotid artery, the

sympathetic trunk structures (upper cervical node,

middle cervical node, vertebral ganglion, stellate

ganglion), spinal nerves (C2-C4) forming the cervical

plexus and having in its composition afferents.

Figure 2 shows the conventional areas of the nerve

structures location in the neck.

They are as follows:

Area 1 - location of sympathetic trunk;

Area 2 – location of sleepy plexus;

Area 3 - location preferential cervical spinal plexus;

Area 4 - the vagus nerve;

Area 5 - accessory nerve and branches of the

glossopharyngeal nerve (Kublanov et al., 2015).

Figure 2: Conventional areas of the nerve structures

location in the neck.

Regulating centers of vital functions are placed in

the nuclei of the brain stem, midbrain, pons and the

cerebellum, as well as - in the autonomic nuclei of the

brain and spinal cord. Many of the mentioned

pathways are located in the neck.

The nervous formations of neck area are closely

associated with brainstem, which have two-side

connections with midbrain, cerebellum, thalamus,

hypothalamus and the large brain cortex. Presence of

these connections provides participation of the neck

nervous formations in analysis of sensory

stimulation, regulation of the muscle tonus,

autonomic and the highest integrative functions

(Moore et al., 2013, Netter, 2014).

As a stimulation targets can be used not only the

superior cervical ganglia of the sympathetic nervous

system and (or) the stellate ganglion, but also other

components of the sympathetic trunk, the afferent

branches of the cervical plexus, cranial nerves and

their branches (IX, X and XI pair) that are conductive

paths nerve structures of the brainstem. And it

significantly extends the capabilities of the

neurostimulation method (Kublanov et al., 2015).

The stimulation of neck nodes of the sympathetic

trunk affects both the vascular tone of arteries of the

brain, and autonomic spinal nucleus (Klosovskiy,

1951). Thus, our hypothesis is that neuro-

electrostimulation system is able to fully modulate the

autonomic processes and to affect motor control and

cognitive function.

Features of the neuro-electrostimulation realized

using the «SYMPATHOCOR-01» device:

 the target of neuro-electrostimulation can be

changed in accordance with current task by

selecting of partial electrodes as anodes of the

multi-element electrode which involved in

formation of the current pulse field;

 biotropic parameters of field of current pulse

(amplitude, frequency and duration) are selected

in accordance with the state of autonomic balance:

activity of the sympathetic nervous system is

blocked at sympathicotonia, and is activated at

vagotonia;

 the frequency of switching the partial electrodes

of the multi-electrode performing the role of

anodes is at least by N times smaller than the

switching frequency of the partial electrodes

performing the role of cathodes;

 commutation (switching) of these electrodes is

performed either clockwise, or counter-

clockwise, or in the arbitrary order by a random

law (Kublanov, Petrenko and Babich, 2015).

Parameters of the current pulsed field were as

follows: the amplitude of the partial current pulses is

4mA, the pulse duration of the partial current is 50

microseconds, the frequency of the partial current

pulses is 80 Hz.

2.2 Method for the Estimation of

Attention Parameters

The study was approved by the local ethics committee

at the Ural State Medical University in accordance

with the protocol number 8 on October 16, 2015.

The study involved 15 participants aged 18 to 35

years who gave their informed consent to voluntary

participate in the study.

The study consisted of 4 stages. The sequence

diagram of the experiment is shown in Table 1.

Table 1: Sequence diagram.

№ stage Name of stage Duration, min.

1 Base line 5

2 Stress testing (Bourdon- test) 10

Neuro-electrostimulation

procedure

Repeated stress testing

(Bourdon test)

Methodology «Bourdon test» was used for the

estimation of attention parameters (Brunner, 2006).

Table filled with symbols formed randomly was

presented to participants at Bourdon test

performance. Looking through the table row by row,

the participants must locate and highlight certain

characters. Bourdon test is designed to assess the

stability of the volume and switching of attention. The

quality of the test was assessed by the speed of

browsing, the general number of errors, the number

of omission errors, the number of commission errors,

the number of scanned characters and productivity

index. Prior to the study subjects were conducted a

training session to familiarize themselves with the

Bourdon test. Training session and research carried

out on different days.

The adapted subjective questionnaire of acute

mental fatigue by A.B. Leonova was used to assess

the mental fatigue (Leonova and Velichkovskaia,

2002). The questionnaire contains 18 statements

describing different degrees of mental fatigue. Index

of mental fatigue (IMF) was calculated based on these

data. Mental fatigue is the most important factor that

limits human performance in the workplace,

especially in learning activities (Karpenko, 2008).

IMF estimation was carried out after each stage of the

study.

Electrocardiogram (ECG) was recorded during

1,2 and 4 stages. The characteristics of heart rate

variability (HRV) were analyzed as a physiological

indicator of changes of the human functional state

during the study. Encephalan - EEGR-19/26

(Medicom MTD, RF, Taganrog) was used to register

the HRV signal.

It is known that the spectral components of HRV

reflect the physiological changes in the body and

allow to find patterns in the regulation of

physiological and mental (psycho-emotional)

condition of the person: HF component reflects the

activity of the parasympathetic part of the autonomic

nervous system, in particular vagus activity and the

power of respiratory waves; LF component

characterizes the state of the sympathetic division of

the autonomic nervous system, in particular, the

system of regulation of vascular tone; VLF spectral

component is closely related to psycho-emotional

stress and the functional state of the cerebral cortex

(Baevsky, 2001).

Analysis of the spectral components of HRV data

was performed using the in-house software developed

in MATLAB.

«STATISTICA 10.0» software applications were

used for statistical analysis of the obtained data in the

course of study.

3 RESULTS

Analysis of variance with repeated measures of

variables (ANOVA) was carried out to assess changes

of the attention parameters obtained in the course of

study "before" and "after" correction procedure with

using neuro-electrostimulation. The main purpose of

the ANOVA is to study the importance of differences

between the of mean values by comparing variance.

As a result of ANOVA significant variance were

received in changing the speed performance, the

productivity index, and the number of scanned

characters. No significant changes were observed for

parameters of the general number of errors, the

number of omission errors, the number of

commission errors. These values are significant at p

≤ 0.05 level. Figures 3-5 shows the average values of

the variables obtained in the course of study "before"

and "after" correction procedure with the noted

standard deviation.

Also, the processing of IMF at different stages of

research were evaluated by using ANOVA. Figures 6

shows the average values of IMF at various stages of

study with the noted standard deviation.

Figure 3: Variance analysis of the speed of browsing

"before" and "after” correction procedure.

Figure 4: Variance analysis of the productivity "before" and

"after” correction procedure

Figure 5: Variance analysis of the number of scanned

characters "before" and "after” correction procedure.

Thus the average IMF value in course of the stress test

on the second stage of the study increases, that

indicates the appearance of mild mental fatigue. But

after neuro-electrostimulation correction procedure

IMF reduces and returns to the original background

values in the third stage of the study.

Relative values of the spectral components HFn,

LFn and VLFn were calculated in processing of the

HRV data. At the assessment of the relative values of

the HRV spectral components at different stages of

Figure 6: Variance analysis of the IMF at each stage of

research.

the study significant differences were obtained in LFn

and VLFn components. No significant differences

were observed in the HFn component. VLFn

component is increased in the course of stress test,

and LFn is reduced in the course of stress test. After

the neuro-electrostimulation correction procedure

VLFn and LFn components are approaching to initial

background values. Figure 7 shows the average

values of the HRV spectral components at different

stages of the study with the noted standard deviation.

Figure 7: Variance analysis of the HRV spectral

components at each stage of research.

The results are shown in Tables 2-3.

Then linear discriminant analysis was applied to

determine which variables distinguish (discriminate)

states of participants "before" and "after" neuro-

electrostimulation correction procedure. A step-by-

step analysis algorithm was used to make the analysis.

At each step all variables are reviewed and the only

one selected that contributes the most to the

difference between states. This variable is included in

the model at this stage, and the next step follows

(Duda et al., 2000).

In the course of discriminant analysis, the

variables that make the most significant contribution

to the discrimination states of participants "before"

Table 2: Average values of the Bourdon test parameters and

IMF in the groups "before" and "after" correction.

Variable Before After

Standard

deviation

IMF 13 5 2

Number of scanned

characters

1561 1971 108

General number of

errors

26 24 6

Number of

omission errors

24 19 6

Number of

commission errors

9 5 5

Speed of browsing 167 197 7

Productivity 1,30 1,53 0,05

Table 3: Average relative values of the HRV spectral

components in the groups "before" and "after" correction.

Variable Before After

Standard

deviation

HFn

0,16 0,15 0,02

LFn 0,29 0,35 0,02

VLFn 0,48 0,42 0,03

and "after" neuro-electrostimulation correction

procedure were chosen. They are as follows: number

of scanned characters, speed of browsing,

productivity, IMF, LF

and VLF

spectral

components. Productivity is linearly dependent on the

number of scanned characters, speed of browsing, so

these variables can be excluded. Thus, the four

variables were chosen for discrimination.

With the help of these defined variables, a

discriminant function can be created, which is a linear

equation of the following type:

a + b



х



b



x



b

x









…



are selected variables, a is a constant, and



...b

are the regression coefficients.

Discriminant functions were built in the two-

dimensional plane, in which axes are selected

variables.

The results are shown in Figures 8-10.

spectral component was excluded from the

number of variables, because it does not affect the

accuracy of discrimination

. Thus, the discriminant

function consists of 3 variables: productivity, IMF

and VLF

The corresponding discriminant function and its

equation are shown in Figure 11.

The accuracy of the classification of states of

participants "before" and "after" neuro-

electrostimulation correction procedure is 88,5%.

Figure 8: Discriminant functions for states of participants

"before" and "after" neuro-electrostimulation in the

productivity, LF

and VLF

spectral components axes.

Figure 9: Discriminant function for states of participants

"before" and "after" neuro-electrostimulation in the

productivity and IMF axes.

Figure 10: Discriminant functions for states of participants

"before" and "after" neuro-electrostimulation in the IMF,

and VLF

spectral components axes.

4 DISCUSSIONS

Analysis of the obtained results showed the

following:

1. Significant changes were obtained for the

speed of browsing, productivity index and the number

Figure 11: Discriminant function for states of participants

"before" and "after" neuro-electrostimulation

of scanned characters. An average of the speed

browsing and productivity increased up 18%, and the

number of characters scanned up 26%.

2. IMF increased at Bourdon test performance

but after the correction procedure using

"SIMPATHOCOR-01" it dropped and returned to the

original background values.

3. Significant differences were obtained in LF

and VLF

components. No significant differences

were observed in the HF

component. VLF

spectral

component increases at performing the Bourdon test

that indicating the psycho-emotional stress, and LF

spectral component reduces that indicating the

decrease in vascular tone, but after the neuro-

electrostimulation correction procedure the indices of

spectral components normalize.

4. As the result of discriminant analysis three

variables were selected, by which the discriminant

function was built for states of participants "before"

and "after" neuro-electrostimulation correction

procedure. They are as follows: productivity, IMF,

and VLF

spectral components. This indicates the

need for an integrative assessment of physiological

and psychometric data.

Thus, during the course of this pilot study it was

showed that the method neuro-electrostimulation of

the peripheral nervous system allows to enhance and

to activate the attention parameters, namely speed of

browsing and productivity, and reduce index of

mental fatigue. At the same time indicators of human

efficiency changes are changes of some

characteristics of the autonomic nervous system, in

particular LF

and VLF

spectral components.

5 CONCLUSIONS

The received data in the course of the pilot study

shown that the application the «SYMPATHOCOR-

01» device for neuro-electrostimulation of the

peripheral nervous system can improve attention

parameters, namely speed of browsing and

productivity. It can demonstrate activation of the

mechanisms underlying human cognitive activity.

Thus, realization of the neuroplasticity principle can

allow to control development of a nervous system and

to intensify process of training and restoration of a

cognitive reserve.

Knowledge of the pathophysiological

mechanisms underlying neuroplasticity, will

optimize therapeutic approaches for development of

science-based correction techniques to restore and to

improve cognitive abilities

(Zhivolupov et al., 2013).

The results of the research can be applied in the

design programs aimed to improve the learning

efficiency and the development of techniques for the

cognitive abilities correction. Also the follow-up

work will involve clinical trials on patients with

various diseases associated with impaired attention

parameters.

ACKNOWLEDGEMENTS

The work was supported by Act 211 Government of

the Russian Federation, contract № 02.A03.21.0006.

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