Changes in Brain Wave Amplitude Due to Methadone

Administration based P300 Similar Stimuli

Dwi Esti Kusumandari

, Arifah Nur Istiqomah

, Dessy Novita

, and Arjon Turnip

1,2

Technical Implementation Unit for Instrumentation Development, Indonesian Institute of Sciences, Indonesia

Department of Electrical Engineering, Universitas Padjadjaran, Indonesia

Keywords: EEG, Brain Wave, Methadone, Stimuli.

Abstract: Drug use in Indonesia tends to be increasingly out of control where the number of users continues to

increase every year. The dangers of drugs can cause various adverse effects, including psychotic behavior,

convulsions, and even death due to overdose. The most dominant part disturbed by drugs is the frontal lobe

of the brain, one effect is the reduced concentration of the user. To minimize this addiction, therapy with

methadone (a synthetic drug to replace opioid drugs) is used. In this paper, an experiment with therapeutic

patients to detect changes in brain wave amplitude due to methadone administration was carried out. EEG

data recording of each subject is done using an EEG system with 19 channels. To stimulate the change in

amplitude, each subject is given a stimulus that is by displaying several random images on a monitor. Each

of them consists of 4 images similar to drugs referred to as non-targets and 1 image of drugs called targets.

In one session all images will be displayed randomly for 10 turns (a total of 20 seconds). To minimize

interference or artefacts on the recording, the data is filtered by bandpass (0.5-70 Hz) and wavelet,

respectively. From this experiment it was found that significant changes in brain wave amplitude after

methadone intake were obtained. These results indicate that the use of methadone is very influential on

brain wave activity. The decrease is part of the reduced level of desire to consume drugs.

1 INTRODUCTION

Drugs are substances that, if injected into the

human body, whether orally or taken, inhaled, or

injected, can change a person's thoughts, moods or

feelings, and behaviour [1-4]. Drugs can cause

physical and psychological dependence (addiction).

The abuse of narcotics and illegal drugs among the

younger generation is increasing now. The rise of

deviant behavior of the young generation can

endanger the survival of this nation in the future.

Because youth, as a generation that is expected to be

the successor to the nation, are becoming

increasingly vulnerable to being devastated by

nerve-damaging addictive substances. So that the

young man cannot think clearly. As a result, the

hopeful and intelligent generation of the nation will

remain only memories [5-8]. The target of the spread

of this drug is young people or adolescents. If

averaged, the target age of this drug is the age of

students, which ranges from age 11 to 24 years. This

indicates that the dangers of drugs at any time can

target our students anytime. Narcotics come from

three types of plants, namely opium, cannabis, and

coca. Drug dependence can be interpreted as a

condition that drives a person to consume drugs

repeatedly or continuously. If he does not do so, he

feels addicted (craving) which causes discomfort

and even a very painful feeling to the body [9-10].

Narcotics are substances or medicines that come

from plants or not plants, both synthetic and semi-

synthetic which can cause a decrease or change in

consciousness, loss of pain and can cause

dependence (Law No. 35 of 2009). Psychotropic

substances are substances or drugs, both natural and

synthetic not narcotics, which have psychoactive

properties through selective influences on the central

nervous system that cause changes in mental activity

and behavior. Psychotropic substances are

substances or drugs, both natural and synthetic not

narcotics, which have psychoactive properties

through selective influences on the central nervous

220

Kusumandari, D., Istiqomah, A., Novita, D. and Turnip, A.

Changes in Brain Wave Amplitude Due to Methadone Administration based P300 Similar Stimuli.

DOI: 10.5220/0009471402200224

In Proceedings of the International Conference on Health Informatics and Medical Application Technology (ICHIMAT 2019), pages 220-224

ISBN: 978-989-758-460-2

system that cause changes in mental activity and

behaviour[11-12].

In an effort to minimize the symptoms of drug

addiction, there are several ways commonly done

one of which is methadone therapy. Methadone is a

type of drug that is also a synthetic opioid drug.

however, this drug can be used to prevent symptoms

of craving and the most important of these drugs is

to have a longer life time which is around 22 hours.

This time is different from the time possessed by

drugs in general, which is around 3-4 hours. So far,

methadone is quite effective against stopping use of

opioid users, such as heroin, morphine, and cocein.

[9-15]. To identify metadhone's reaction to changes

in brain activity, an experiment involving several

subjects with a recording device using EEG was

conducted [11, 12, 16-17]. Even Related Potential

(ERP) is one of the types of signals that can be

recorded from the brain in the EEG. Sinal is data

that reflects neural bio-electric activity associated

with providing stimulus. ERP component consists of

several components, one of which is a positive

component named P1, P2, P3, or according to the

latency period (P50, P100, P300) [16-22]. Each

component reflects the activation of each neuron.

The ERP signals are very sensitive to the given

stimulus, but psychological factors can also affect

the signal performance [20-22]. The P300

component is a wave that can detect the brain's

implusivity when given a certain stimulus. In this

study, the P300 signal was used to detect the effect

of methadone administration on brain implusivity in

drug addicted patients [16, 18, 23].

EEG-P300 signal is the type of ERP component

chosen to recognize patterns of brain activity due to

drugs in this study. P300 terminology is obtained

from the positive wave polarity at 300 milliseconds

after the stimulus is given. P300 depends on the

duration of the stimulus process but does not depend

on the process of selecting and implementing

responses. The P300 component is more likely to

reflect the cognitive process of processing stimulus

information [24]. Based on the shape and

characteristics of the P300 components, the features

used for identification are the maximum amplitude

and and the frequency. Latency is the time it takes

for the brain to respond to stimuli. In the simple task

of auditing discrimination the latent period is around

300 milliseconds, whereas in the complex decision

making process the latent period can reach 400-800

milliseconds [24, 25].

Research and experiments with proposed

experimental patterns and using brain signal

recording to observe changes in brain activity for

methadone administration are still rarely performed.

In addition to the much lower cost, experiments

using EEG have several advantages such as portable,

non-invasive, and more flexible to be developed

both from software and integration with other

hardware. Another thing that encourages the

implementation of this activity is that researchers are

more flexible in conducting observations from

various points of view as well as bases in choosing

an algorithm that is suitable for the signal character.

Furthermore, this trial was specifically designed

based on the needs and complaints and constraints

faced by psychiatric doctors in hospitals.

2 METHOD

Methadone therapy is expected to reduce drug

use, risk behavior, crime, and increase productivity,

and get family support for narcotics users. In the

experiment, we worked with 8 male respondents

aged 20-40 years who were addicted to drugs and

were undergoing the methadone rehabilitation at

Hasan Sadikin Hospital, Bandung, Indonesia. Data

collection was carried out for 3 days. Respondents

were controlled so as not to consume methadone and

other substances before data collection. For data

processing, 7 channel electrodes were used in the

frontal section (Fp-1, Fp-2, F7, F3, Fz, F4, F8)

according to the 10-20 system.

At the time of recording, subjects were given

stumulus in the form of images collection consist of

4 nontarget images and 1 target images stimulus,

respectively. All stimuli images are randomly

flasshed about 300 milliseconds with pauses of each

100 millisecon (Fig. 1). This collection of images is

displayed with random stimulus arrangements about

10 times or for 20 seconds. EEG data recording is

done before and after 1 hour the subject consume the

methadone.

Fig. 1. The used Stimulus in the Experiment.

Changes in Brain Wave Amplitude Due to Methadone Administration based P300 Similar Stimuli

221

3 RESULTS AND DISCUSSIONS

The process of selecting different images aims to

make it easier for subjects to distinguish targets and

non-targets (Adjusted with the subject's condition as

a drug user). Assumption that subjects who are

familiar with and addicted to drugs will give a

different response when given a target image

stimulation than non-target stimulation both in terms

of amplitude and latency of the EEG-P300

component. Observation of differences in the

components of EEG-P300 before and 1 hour after

the subject consume the methadone. The P300

component when viewing target images will provide

higher amplitude with faster latency than non-target.

Subjects who have not been given methadone have a

higher level of interest in methadone (craving),

consequently the amplitude after consuming

methadone must be lower with slower latency.

Subjects are in a state of craving if given a drug

stimulus will respond more quickly and be expressed

by a smaller (faster) latency. The decrease in

amplitude value is also supported by the influence of

methadone which tends to make the subject sleepy

where theta waves increase and beta waves decrease.

The filtered and extracted EEG signals (subject 6)

(a) before and (b) after methadone intake are given

in Fig. 3.

Fig. 3 Filtered EEG Signals (a) Before and (b)

After Methadone Intake.

In Fig. 4 clearly visible the changes in the

regularity of the extracted signal pattern after

consuming methadone. The regularity of the signals

between these channels is a representation of the

calmness and comfort of the subject. This indication

shows that the effect of methadone consumption can

be significantly seen in brain activity within a 1 hour

period of drug use.

Fig. 4 Extracted EEG Signals using wavelet

method: (a) before, and (b) after Methadone Intake

After processing the data, comparison of

subjects' responses to target and non-target image

stimuli can be seen by comparing the results of the

average amplitude and latency of all subjects in

Table 1. In general (both before and after consuming

methadone) the results of amplitude due to target

stimulus tend to produce higher amplitude and

slower latency for non-targets. Before consuming

methadone, subjects 3 and 6 had lower amplitudes

towards nontarget. Similar results were also found

after consuming methadone in which subjects, 3, 6,

and 7 had lower amplitudes towards nontarget. This

is due to the type of drug consumed by the subject

which is very varied which causes methadone

therapy to be less effective in the subject. In

addition, the dose of methadone used during

methadone therapy does not decrease and remains

high, which is likely due to the efforts of subjects

who are old enough so that the process of new

neuron growth is much slower. Another possibility

is that subjects 3, 6, and 7 showed positive urine test

results using benzo during experiments. The use of

benzo will certainly strengthen each other against

the use of methadone which causes the subject to be

sleepy. This result is in accordance with the decrease

in amplitude and tends to increase the latency value.

Except for subjects 4 and 8, a decrease in the

amplitude of the EEG-P300 signal was found after

being given methadone. A decrease in amplitude

indicates a decrease in the respondent's desire to

consume drugs or a reduced level of subject

concentration. Meanwhile, faster latency after using

methadone indicates an increase in respondents'

awareness after using methadone. In subjects 4 and

8, the amplitude and latency after being given

methadone have a higher value compared to before

using methadone. This difference occurred because

it was suspected that subjects 4 and 8 did not take

methadone treatment regularly, and they were more

likely to take other drugs than methadone during the

ICHIMAT 2019 - International Conference on Health Informatics and Medical Application Technology

222

treatment period. This can be proven from the dose

of methadone given at the time of the study was

almost the same as the highest dose of the subject

even though the subjects had been undergoing

methadone therapy for 2 and 6 years, respectively. A

similar dose of methadone is thought to be not

strong enough and does not work optimally to

reduce craving on the subject. In addition, there are

benzo levels and a history of amphetamine use

which can cause methadone not to function

optimally in decreasing drug use.

Table 1. Amplitude dan Latency of all subject

before and after methadone intake (Target and

nontarget)

All data is then grouped by target, non-target,

both before and after consuming methadone, then

averaged, so that the graph in Fig.5. y-axis indicates

amplitude in microvolts and x-axis indicates latency

in milliseconds. Subject data 1 in Table 1 has a very

high amplitude value, so it is not included in the

average data processing. The data anomaly is likely

to occur because of the influence of the environment

during the data collection process.

Fig. 5. Comparison of EEG-P300 Amplitude and

Latency before and after Methadone Intake.

From the experimental results, the pre-methadone

signal obtained in the target image has slightly lower

amplitude than post-methadone, and has shorter

latency. A decrease in amplitude after a subject

consumes methadone indicates a decrease in the

subject's desire to consume drugs. The reduced

latency in post-methadone indicates the higher level

of concentration or awareness of the subject which is

characterized by the faster subject responding to an

impulse. This majority statement is consistent with

the initial assumption that the amplitude tends to

decrease after consuming methadone with latency

which tends to be slower. The inaccuracy of the

results obtained can occur because post-methadone

data retrieval is done 1 hour after the subject drinks

methadone, while methadone only reacts optimally

to the brain after more than 3 hours. This allows the

implantivity response to the target image to be lower

than at 1 hour after the subject took methadone.

Drug abuse that is not controlled slowly will have a

negative impact on thoughts, behavior, and social

relations. However, permanent effects will occur on

the body that can slowly destroy the system and

function of the brain which culminates in permanent

disability or even death.

4 CONCLUSIONS

Methadone intake by the drug rehabilitation patients

causes a decrease in the brain's implusivity to given

stimuli which indicates a decrease in the level of

desire for drugs after being given methadone. The

main results of the present analysis indicated that the

subjects have a longer P300 latency and a lower

P300 amplitude after consuming methadone. This

study revealed that drug patients have abnormalities

in the P300 component, which may reflect deficits in

cognitive function.

ACKNOWLEDGEMENTS

This research was supported by Technical

Implementation Unit for Instrumentation

Development, Indonesian Institute of Sciences and

funded by RISTEKDIKTI by INSINAS 2019,

Indonesia.

REFERENCES

Undang-Undang Republik Indonesia, Tentang

Psikotropika, Nomor 5 Tahun, 1997.

http://hukum.unsrat.ac.id/uu/uu_5_97.htm

University of Florida. "Club Drugs Inflict Damage Similar

To Traumatic Brain Injury." ScienceDaily.

ScienceDaily, 30 November 2007.

<www.sciencedaily.com/releases/2007/11/07112912

1127.htm>

Mukherjee S., “Alcoholism and its effects on the central

nervous system”, Curr Neurovasc Res., 10(3):256-

62, 2013.

Amplitude

(uV)

Latency

(ms)

Amplitude

(uV)

Latency

(ms)

Amplitude

(uV)

Latency

(ms)

Amplitude

(uV)

Latency

(ms)

Subject 1 314.8755 286 162.9096 526 26.4366 562 8.2277 600

Subject 2 39.7248 386 34.6898 2 19.0109 86 2.5528 486

Subject 3 38.7495 76 11.8405 576 50.1381 236 14.9654 600

Subject 4 8.7280 174 10.4094 558 3.7651 324 2.5209 196

Subject 5 14.4102 424 4.3683 134 2.1886 552 0.3239 304

Subject 6 2.6643 218 2.6840 600 6.4819 134 19.6049 560

Subject 7 6.4835 590 1.9905 322 3.8031 372 3.0156 542

Subject 8 16.5735 600 28.1349 194 10.3552 280 5.8296 278

Subject

Target Stimulant

Non-Target Stimulant

Pre-Methadone

Post-Methadone

Pre-Methadone

Post-Methadone

Changes in Brain Wave Amplitude Due to Methadone Administration based P300 Similar Stimuli

223

Sabino V., Cottone P., “Sigma Receptors and Alcohol Use

Disorders”, Handb Exp Pharmacol., 244:219-236,

2017. doi: 10.1007/164_2016_97.

Scott, L.L. et al, “Small molecule modulators of

σ2R/Tmem97 reduce alcohol withdrawal-induced

behaviors, Neuropsychopharmacology. 43(9):1867-

1875, 2018.

Sabino, V., Hicks, C., “Cottone P Sigma Receptors and

Substance Use Disorders”, Adv Exp Med Biol.,

964:177-199, 2017.

Dorsen C, Palamar J, Shedlin MG, “Ceremonial "plant

medicine" use and its relationship to recreational

drug use: an exploratory study”, Addict Res

Theory.27(2):68-75, 2019.

Pastor A, Conn J, O'Brien CL, Teng J, Loh M, Collins L,

MacIsaac RJ, Bonomo Y., “Clinicians feel

comfortable discussing alcohol but not illicit drug

use with young adults with type 1 diabetes: a survey

of clinicians”, Diabet Med. 2019 Sep 17. doi:

10.1111/dme.14136

Wang, GY, Kydd, R.,Wouldes, T.A, Jensen, M., Russell,

B.R., “Changes in resting EEG following methadone

treatment in opiate addicts”, Clinical

Neurophysiology, Vol. 126, No. 5, May 2015, pp.

943-950

Yang, L., et. al., “The effects of methadone maintenance

treatment on heroin addicts with response inhibition

function impairments: Evidence from event-related

potentials”, Journal of Food and Drug Analysis, Vol.

23, pp. 260-266, 2015.

Turnip, A. et al, “Brain Mapping of drug addiction in

witdrawal condition based P300 Signals, J. Phys.:

Conf. Ser. Vol. 1007 , pp. 012060, 2018.

Turnip, A., Kusumandari, D. E., Hidayat, T., Hidayat, T.,

“Brain Mapping of Low and High Implusivity based

P300 Signals, Journal of Physics: Conference Series,

Vol. 1007, 2018.

Hu, B., et al, “Effective brain network analysis with

resting-state EEG data: a comparison between

heroin abstinent and non-addicted subjects, Journal

of Neural Engineering, Vol. 14, No. 4, 2017.

Wang GY, Kydd R, Wouldes TA, Jensen M, Russell BR,

“Changes in resting EEG following methadone

treatment in opiate addicts”, Clin Neurophysiol.

Vol.126(5), pp. 943-50, 2015.

Malik E, Adelson M, Sason A, Schreiber S, Peles E.,

“Outcome of Patients With High Depressive

Symptoms on Admission to Methadone

Maintenance Treatment”, J. Dual Diagn., 1-10,

2019. doi: 10.1080/15504263.2019.1656353.

Turnip, A. et al, “Detection of Drug Effects on Brain

Activity using EEG-P300 with Similar Stimuli”, IOP

Conference Series: Materials Science and

Engineering, Vol. 220, 2018.

Iskandar, S., Kusumandari, D. E., and Turnip, A.,

“Artifact Removal with Independent Component

Analysis for 2D Brain Mapping of Drugs User

before and after Taking Methadone, Internetworking

Indonesia Journal, Vol.1 1, No.1, pp. 29-33, 2019.

Turnip, A., Kusumandari, D. E., and Pamungkas, D. S.,

“Drug Abuse Identification based EEG-P300

Amplitude and, Latency with Fuzzy Logic

Calssifier”, International Conference on Applied

Engineering (ICAE), 2018.

Maurage, P. Et al, “Is the P300 deficit in alcoholism

associated with early visual impairments (P100,

N170)? An oddball paradigm”, Clinical

Neurophysiology 118 (2007) 633–644

Motlagh, F., Ibrahim, F., Rashid, R., Seghatoleslam, T.,

Habil, H., “Investigation of Brain

Electrophysiological Properties among Heroin

Addicts: Quantitative EEG and Event-Related

Potentials”, Journal of Neuroscience Research

,00:00–00 (2016)

Ceballos, N. A., Bauer, L. O., Houston, R. J., “Recent

EEG and ERP Findings in Substance Abusers”, Clin

EEG Neurosci . 2009 April ; 40(2): 122–128.

Wang, GY, Kydd, R.,Wouldes, “Resting EEG and ERPs

findings in methadone-substituted opiate users: a

review”, Acta Neurol Belg (2015) 115:539–546.

Turnip, A., Esti, K.D., Amri, M.F., Simbolon, A.I.,

Suhendra, M.A., Iskandar, S. and Wirakusumah,

F.F., 2017, July. Detection of Drug Effects on Brain

Activity using EEG-P300 with Similar Stimuli. IOP

Conference Series: Materials Science and

Engineering, 220(1), pp. 012042.

Sutton S, Braren M, Zubin J, John ER. Evoked-potential

correlates of stimulus uncertainty. Science. (1965)

150:1187–8. doi: 10.1126/science.150.3700.1187

Kayser J, Tenke CE. Issues and considerations for using

the scalp surface Laplacian in EEG/ERP research: a

tutorial review. Int J Psychophysiol. (2015) 97:189–

209. doi: 10.1016/j.ijpsycho.2015.04.012.

ICHIMAT 2019 - International Conference on Health Informatics and Medical Application Technology

224