Journal of Evolutionary Biochemistry and Physiology, volume 58, issue 4, pages 1130-1141
Use of Naïve Bayes Classifier to Assess the Effects of Antipsychotic Agents on Brain Electrical Activity Parameters in Rats
Sysoev Yu I
1, 2, 3, 4
,
Shits D D
1
,
Puchik M M
1
,
Prikhodko V A
1, 4
,
Idiyatullin R D
1
,
Kotelnikova A A
1
,
Okovityi S V
1, 4
3
Publication type: Journal Article
Publication date: 2022-07-01
Quartile SCImago
— Quartile WOS
Q4
Impact factor: 0.6
ISSN: 00220930, 16083202
Biochemistry
Physiology
Ecology, Evolution, Behavior and Systematics
Abstract
Research and development of novel methods to determine the effects of antipsychotic agents is an important challenge for experimental biomedicine. Although behavioural tests, the ones most commonly used for pharmacological screening, are quite efficient for the evaluation of drug effects on animal anxiety and locomotion, they hardly allow to detect antipsychotic activity. Pharmacoelectroencephalography (pharmaco-EEG), which is based on the principle of different psychoactive agents producing distinct changes in brain electrical activity, could represent a viable alternative approach to that task. The rapid evolution of machine learning techniques has opened new possibilities for using pharmaco-EEG data for the purposes of classification and prediction. This work describes an experimental approach to the assessment of specific activity and pharmacological profiling of antipsychotic agents using naïve Bayes classifier, a simple probabilistic classifier widely employed in biomedical research. The experiments were conducted in white outbred male rats with chronically implanted electrocorticographic electrodes. To serve as the training set, a library was assembled containing electrocorticograms (ECoG) following the administration of antipsychotic agents: chlorpromazine, haloperidol, droperidol, tiapride, and sulpiride. For each sample, ECoG parameters before and after drug administration were calculated, and a total of 132 amplitude and spectral signal parameters were taken into analysis. Principal component analysis was used to reduce dimensionality. Using naïve bayes classifier, we were able to detect and qualify distinct effects of antipsychotic agents on brain electrical activity parameters in rats, allowing them to be differentiated from phenazepam, a benzodiazepine tranquilizer with sedative properties. Moreover, this approach proved effective to distinguish among the antipsychotics as well as between them and other agents with similar receptor binding affinity profiles, e.g., the tricyclic antidepressant amitriptyline. Thus, the method we propose can be used to discern between antipsychotic and sedative effects of drugs as well as to compare the effects across different antipsychotic agents.
Citations by journals
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Journal of Evolutionary Biochemistry and Physiology
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Journal of Evolutionary Biochemistry and Physiology
2 publications, 66.67%
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Brain Sciences
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Brain Sciences
1 publication, 33.33%
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1
2
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Citations by publishers
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2
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Pleiades Publishing
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Pleiades Publishing
2 publications, 66.67%
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Multidisciplinary Digital Publishing Institute (MDPI)
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Multidisciplinary Digital Publishing Institute (MDPI)
1 publication, 33.33%
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1
2
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- We do not take into account publications that without a DOI.
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- Statistics recalculated weekly.
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Sysoev Yu. I. et al. Use of Naïve Bayes Classifier to Assess the Effects of Antipsychotic Agents on Brain Electrical Activity Parameters in Rats // Journal of Evolutionary Biochemistry and Physiology. 2022. Vol. 58. No. 4. pp. 1130-1141.
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Sysoev Yu. I., Shits D. D., Puchik M. M., Prikhodko V. A., Idiyatullin R. D., Kotelnikova A. A., Okovityi S. V. Use of Naïve Bayes Classifier to Assess the Effects of Antipsychotic Agents on Brain Electrical Activity Parameters in Rats // Journal of Evolutionary Biochemistry and Physiology. 2022. Vol. 58. No. 4. pp. 1130-1141.
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TY - JOUR
DO - 10.1134/s0022093022040160
UR - https://doi.org/10.1134%2Fs0022093022040160
TI - Use of Naïve Bayes Classifier to Assess the Effects of Antipsychotic Agents on Brain Electrical Activity Parameters in Rats
T2 - Journal of Evolutionary Biochemistry and Physiology
AU - Sysoev, Yu I
AU - Shits, D D
AU - Puchik, M M
AU - Prikhodko, V A
AU - Idiyatullin, R D
AU - Kotelnikova, A A
AU - Okovityi, S V
PY - 2022
DA - 2022/07/01 00:00:00
PB - Pleiades Publishing
SP - 1130-1141
IS - 4
VL - 58
SN - 0022-0930
SN - 1608-3202
ER -
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@article{2022_Sysoev,
author = {Yu I Sysoev and D D Shits and M M Puchik and V A Prikhodko and R D Idiyatullin and A A Kotelnikova and S V Okovityi},
title = {Use of Naïve Bayes Classifier to Assess the Effects of Antipsychotic Agents on Brain Electrical Activity Parameters in Rats},
journal = {Journal of Evolutionary Biochemistry and Physiology},
year = {2022},
volume = {58},
publisher = {Pleiades Publishing},
month = {jul},
url = {https://doi.org/10.1134%2Fs0022093022040160},
number = {4},
pages = {1130--1141},
doi = {10.1134/s0022093022040160}
}
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Sysoev, Yu. I., et al. “Use of Naïve Bayes Classifier to Assess the Effects of Antipsychotic Agents on Brain Electrical Activity Parameters in Rats.” Journal of Evolutionary Biochemistry and Physiology, vol. 58, no. 4, Jul. 2022, pp. 1130-1141. https://doi.org/10.1134%2Fs0022093022040160.
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