Associations between genetic factors in individualization of visual perception and components of event-related potentials during assessment of emotional visual stimuli (scenes) with distinct second-order features

Pavel N. Ermakov; Elena V. Vorobyeva; Ekaterina M. Kovsh; Alexander S. Stoletniy; Magomed M. Dalgatov; Fatimet P. Khakunova; Asya K. Bersirova

doi:10.12688/f1000research.22905.1

Home Browse Associations between genetic factors in individualization of visual...

ALL Metrics

-

Views

-

Downloads

Get PDF

Get XML

Export

▬

✚

Research Article

Associations between genetic factors in individualization of visual perception and components of event-related potentials during assessment of emotional visual stimuli (scenes) with distinct second-order features

[version 1; peer review: 1 approved with reservations, 1 not approved]

Pavel N. Ermakov¹, Elena V. Vorobyeva^1,2, Ekaterina M. Kovsh¹, [...] Alexander S. Stoletniy ¹, Magomed M. Dalgatov³, Fatimet P. Khakunova⁴, Asya K. Bersirova⁴

Pavel N. Ermakov¹, Elena V. Vorobyeva^1,2, [...] Ekaterina M. Kovsh¹, Alexander S. Stoletniy ¹, Magomed M. Dalgatov³, Fatimet P. Khakunova⁴, Asya K. Bersirova⁴

PUBLISHED 20 Aug 2020

Author details Author details

¹ Department of Psychophysiology and Clinical Psychology, Southern Federal University, Rostov-on-Don, Rostovskaya oblast, 344065, Russian Federation
² Department of Psychophysiology and Clinical Psychology, Don State Technical University, Rostov-on-Don, Rostovskaya oblast, 344010, Russian Federation
³ Department of Psychology, Dagestan State Pedagogical University, Makhachkala, Republic of Dagestan, 367000, Russian Federation
⁴ Department of Educational Psychology, Adygea State University, Maykop, Republic of Adygea, 385000, Russian Federation

Pavel N. Ermakov
Roles: Data Curation, Funding Acquisition, Writing – Review & Editing

Elena V. Vorobyeva
Roles: Conceptualization, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing

Ekaterina M. Kovsh
Roles: Data Curation, Writing – Original Draft Preparation, Writing – Review & Editing

Alexander S. Stoletniy
Roles: Visualization, Writing – Review & Editing

Magomed M. Dalgatov
Roles: Data Curation, Writing – Original Draft Preparation, Writing – Review & Editing

Fatimet P. Khakunova
Roles: Data Curation, Writing – Original Draft Preparation, Writing – Review & Editing

Asya K. Bersirova
Roles: Data Curation, Writing – Original Draft Preparation, Writing – Review & Editing

OPEN PEER REVIEW

REVIEWER STATUS

Abstract

Background: The aim of this paper is to investigate the associations between polymorphisms in the BDNF, COMT, and HTR2A genes with peculiarity of visual perception. In particular, how the carriers of different genotypes of Indicated genes emotionally evaluating visual scenes with distinct second-order features (images modulated by contrast) and how corresponding process is reflected in event-related brain activity (ERP).
Methods: The study involved students who underwent PCR-based genetic analysis with the release of BDNF, COMT, and HTR2A genotypes. Participants were asked to emotionally assesse the specific stimuli – visual scenes that were generated from contrast modulations. At the same time the EEG were recorded using a 128-electrodes system. The average frequency of responses and ERPs for different emotional evaluations (negative, neutral and positive) were analyzed.
Results: The study showed the BDNF Val/Val polymorphism was associated with the increase in the P2 amplitude in the occipital regions compared to the Val/Met genotype regardless of emotional evaluation. The COMT Met/Met genotype polymorphism associated with the increase of N170 negativity in the occipital regions during evaluation task. The HTR2A polymorphism A/A associated with increase in the P1 amplitude when positive or negative assessment were chosen, and decrease of later positive peak when neutral evaluation was chosen.
Conclusions: The results suggested that emotional evaluation and recognition of visual scenes with distinct second-order features, as well as various strategies for processing visual information, reflected in amplitude and latency of different ERPs components and associated with the different genotypes of BDNF, COMT, and HTR2A genes. The indicated interconnections can act as genetic basis of individualize the mechanisms of visual perception.

Keywords

Second-order visual features, BDNF gene, COMT gene, HTR2A gene, visual scenes, visual perception, emotions, event-related potentials, emotional assessment

Corresponding author: Alexander S. Stoletniy

Competing interests: No competing interests were disclosed.

Grant information: This work was supported by Ministry of Science and Higher Education of the Russian Federation (Project 25.3336.2017/4.6).
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Copyright: © 2020 Ermakov PN et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to cite: Ermakov PN, Vorobyeva EV, Kovsh EM et al. Associations between genetic factors in individualization of visual perception and components of event-related potentials during assessment of emotional visual stimuli (scenes) with distinct second-order features [version 1; peer review: 1 approved with reservations, 1 not approved]. F1000Research 2020, 9:1010 (https://doi.org/10.12688/f1000research.22905.1) First published: 20 Aug 2020, 9:1010 (https://doi.org/10.12688/f1000research.22905.1) Latest published: 20 Aug 2020, 9:1010 (https://doi.org/10.12688/f1000research.22905.1)

Introduction

Despite the fact that at this stage of evolution, the human visual system is the main channel for receiving information that performs complex processes of encoding and decoding stimuli, the mechanisms for recognizing and categorizing visual images still remain under-investigated (Babenko et al., 2011; Graham, 2011; Wilson & Gelb, 1984). In particular, second-order visual features – non-local characteristics of the perceived image, which including various options for contrast, orientation, and spatial frequency – are of special interest to human’s visual system researchers (Babenko et al., 2011; Babenko et al., 2016) These features are image regions characterized by spatial heterogeneities of brightness gradients – the first-order characteristics. These heterogeneities are distinguished by the so-called second-order filters, which detect regions with spatial modulations of contrast, orientation, and spatial frequency in the images. First-order visual mechanisms form the basis for subsequent spatial grouping. This is a multi-channel system that performs local analysis of the orientation of the brightness gradients at various spatial frequencies. Second-order visual mechanisms detect spatial changes and represent a certain set of filters.

A number of experimental studies demonstrated that second-order visual mechanisms are selective towards modulations of contrast, orientation (surface curvature) and spatial frequency (depth) and have different cortical localization. The search for second-order stimuli is pre-attentive (Yavna & Babenko, 2012; Yavna et al., 2012).

Second-order features are known to play an important role in identifying images. The studies aimed at studying the role of second-order visual mechanisms in the recognition of emotional stimuli (especially scenes) are of particular importance today. Scenes are complex visual stimuli. Compared to the mechanisms of visual perception of faces and objects, little attention has been devoted to studying the brain mechanisms underlying processing of scenes (Aftanas et al., 2001; Codispoti et al., 2007; Delplanque et al., 2004; Mavratzakis et al., 2016; Olofsson et al., 2008; Pegna et al., 2004). Due to the fact that the human visual system often recognizes the scenes as combinations of images that include various elements, the study of these mechanisms can help us to clarify our understanding of the process of visual perception in vivo.

At the same time, we should take into account the influence of individual characteristics on the processes of visual perception. These may include psychological and biological characteristics. The genetic factors in the individualization of visual perception, i.e. genes that can affect the mechanisms of visual perception of images (including emotional scenes) are the catechol-o-methyltransferase (COMT) gene, the brain derived neurotrophic factor (BDNF) gene, the serotonin receptor gene (HTR2A), etc. In the science periodicals numerous studies examine the associations between these genes and individual psychological characteristics, including emotional intelligence, aggression, anxiety, and neuroplasticity and describe neurochemical processes characteristic to carriers of various genotypes. However, the influence of genes on the processes of visual perception, including the mechanisms for recognizing and evaluating (appraising) emotional visual stimuli (scenes) with the distinct second-order features are poorly described. This fact determined the topic of the present investigation. Let us now consider in more detail the functions of these genes.

BDNF - the brain derived neurotrophic factor gene

BDNF is a key molecule involved in the plastic changes associated with learning and memory. The BDNF stimulates the growth of neurons, axons, and dendrites, the formation of synapses and other processes of neuroplasticity not only in early ontogenesis, but also in the brain of the adult organism (Antal et al., 2010). Changes in BDNF expression in the brain structures involved in memory functions and perception processes (Miranda et al., 2019) are associated with human normal and pathological aging, as well as with mental illness. Together with other neurotrophic factors, BDNF plays an important role in the processes of adaptation of brain neurons to various external impacts influences, as well as in their growth, differentiation, and survival (Popova et al., 2017).

It is established that visual experience in the early postnatal period affects the maturation of the visual cortex. Furthermore, it was investigated the characteristics of maturation and plasticity of the visual cortex in mice with elevated level of BDNF (Huang et al., 1999). Under experimental conditions of visual deprivation, the authors found that BDNF overexpression is sufficient for the development of normal activity of the visual cortex in the absence of visual experience. Meanwhile, a decrease in BDNF expression slows down the development of visual areas of the cerebral cortex under conditions of visual deprivation (Gianfranceschi et al., 2003).

Carriers of the BDNF Val/Val genotype with higher cortical plasticity were characterized by a more thorough processing of visual images. This may be explained by a more detailed analysis of the components of visual images which is associated with a higher activation of occipital areas. There is also some evidence that carriers of BDNF Val/Val genotype with higher neural plasticity perform visual-motor adaptation tasks worse than carriers of Val/Met genotype (Ermakov et al., 2017).

Compared to carriers of the Val/Val genotype, those with the Met allele of the BDNF gene demonstrate higher activation in amygdala and hippocampus when recognizing individuals expressing emotions (Vorobyeva et al., 2019). These data indicate the contribution of the BDNF gene to the formation of brain mechanisms underlying anxiety, as well as its possible role in the recognition of emotional stimuli.

Andreatta et al. (2019) showed that carriers of the Met allele of the BDNF gene have a higher level of anxiety. Loewenstern et al., (2019) confirmed this result, providing the following physiological data: the highly anxious carriers of the Met allele of the BDNF gene have stronger functional associations between the left amygdala and the right dorsolateral prefrontal cortex (anxiety phenotype).

According to (Schofield et al., 2009), carriers of the Met/Met genotype of the BDNF gene had higher verbal recall errors and showed increased P300 latency when performing tasks in the oddball paradigm with corresponding alterations in hippocampal and lateral prefrontal activation, and a localized reduction in hippocampal gray matter. Thus, the Met allele affects the fronto-hippocampal systems involved in the selective processing of stimulus information and memory renewal in healthy individuals. Gajewski et al., (2012) described the impact of the Met/Met genotype of the BDNF gene on fronto-striatal associations. Meanwhile, this genotype was associated with a decrease in the severity of the Stroop effect in elderly people, which was accompanied by an increase in the amplitude of the N450 component during task performance. Researchers concluded that carriers of the Met/Met genotype of the BDNF gene were more resistant to interference. In their earlier work (Gajewski et al., 2010) also suggested that superior memory-based task-switching performance in elderly Met-allele carriers manifested itself in that N2 was increased while the P3 was decreased in Met-allele carriers. Beste et al., (2010) associated the Met allele of the BDNF gene with fewer errors during task performance, as well as with a less time stability of information stored in iconic memory (Beste et al., 2011).

COMT - the catechol-o-methyltransferase gene

This gene is associated with the dopamine system of the human brain. The enzyme catechol-O-methyltransferase regulates the transmission of impulses in the nervous system, and therefore can affect various mental processes (Serrano et al., 2019). Carriers of the COMT Met allele differentiate emotions and understand facial expression significantly better than those with the Val allele (Gohier et al., 2014b; Weiss et al., 2014). The structural features of this gene are associated with the activity of working memory (Barnett et al., 2011; Dumontheil et al., 2011; Gosso et al., 2008), multitasking ability (Rosa et al., 2010), anxiety (Hashimoto et al., 2007), extraversion (Reuter & Hennig, 2005) level of organization of regulatory (management) functions (Barnes et al., 2011), impulsivity and novelty seeking (Golimbet et al., 2006), and also the tendency to use psychoactive substances (Lovallo et al., 2019).

Individuals with a high enzymatic activity of COMT (the Val/Val genotype of the COMT gene) are better able to deal with stressful situations, because excess dopamine activity is quickly neutralized. On the other hand, individuals with a low enzymatic activity of COMT (the Met/Met genotype of the COMT gene) are more capable to develop complex plans, calculate the probabilities of events and think about their consequences; they have better memory, the ability to synthesize new information, but in a calm environment, in the absence of stress (Stein et al., 2006).

The data on the associations between the COMT gene genotypes and the brain correlates for facial expression recognition indicate that male carriers of the Met allele have higher values of latency of evoked potentials during perceiving faces; women with this genotype have a more pronounced arousal effect (Tamm et al., 2016). Bender et al., (2012) found that the DAT1 and COMT genes affect the same specific time interval (early contingent negative variation, CNV) associated with preparing for movement. According to (Gómez et al., 2003), the generators of this component are located in the frontal cortex (anterior cingulate gyrus) and in the occipital-temporal visual cortex, which corresponds to the expression of the COMT gene. There is evidence for the linkage of the region of chromosome 22 containing the COMT gene with an integrated phenotype that includes visual-motor dysfunction (Alfimova & Golimbet, 2011).

Kondo et al. (2012) discovered the effect of the COMT gene on speech perception reflected in the induced brain activity, as well as the impact of HTR2A gene on the perception of inverted figures. Later, these authors examined associations between COMT genotypes and recognition accuracy, as well as associations between HTR2A genotypes and the response time for recognition (Kondo et al., 2015).

HTR2A - the serotonin receptor gene

HTR2A has an inhibitory effect in the visual cortex. It is believed to be associated with episodic memory (Reynolds et al., 2006) and emotional intelligence (Kosonogov et al., 2019). Greater activation of the parieto-occipital areas of the brain during positive or negative judgment of stimuli by carriers of the dominant homozygous G/G genotype of the HTR2A gene may be explained theirs detailed assessment of stimulus images. Along with his, carriers of the recessive homozygous A/A genotype had similar activity in the same areas during positive emotional assessment of stimuli, which can be interpreted same way as G/G genotype (Alekseeva et al., 2017; Ermakov et al., 2017).

An analysis of the previous studies showed that knowledge of the role of genes in providing various mechanisms of perception is insufficient for creating a holistic picture. Certain aspects of this issue were investigated in a study conducted by (Nakagami et al., 2013) in marmosets. This results suggest that the patterns of gene expression that are potentially associated with various stages of visual cognition are different in the neurons of each layer of the visual cortex. The regulation of each neuron of primary visual cortex in marmosets is subjected to various regulating impacts when the activity of the retina changes. It should be related to a highly differentiated laminar structure of marmoset visual systems, reflecting the functions of the activity-dependent gene expression. Consequently, HTR2A gene expression depends on the level of activation of the various retinal layers.

Based upon the foregoing, this study aims to examine the associations between BDNF, COMT, and HTR2A genotypes and individual characteristics of the perception of emotional visual stimuli (scenes) with distinct second-order features.

This study proposes the following research hypotheses

1) Amplitude, spatial, and temporal characteristics of the components of visual event-related potentials in response to emotional visual stimuli (scenes) with distinct second-order features are significantly different in carriers of different BDNF, COMT, and HTR2A genotypes.

2) Characteristics of attribution of emotional valences to visual stimuli (scenes) with distinct second-order features have statistically reliable difference in carriers of different BDNF, COMT, and HTR2A genotypes.

Methods

Ethical statement

The use of experimental subjects is in accordance with ethical guidelines as outlined in the Declaration of Helsinki. In addition, the design of the experiment, the methodological approach, the conditions of confidentiality and use of oral consent for the subjects was performed according to the Code of Ethics of Southern Federal University (SFU, Rostov-on-Don, Russia) and approved ethically by the Academic Council of the Academy of Psychology and Pedagogy of SFU, on 23 March, 2018. Oral consent for participating in research was approved since the study requires only a small amount information about the participant’s genotype, gender and age and no other additional information. It should be noted that all data were encrypted and stored in the laboratory of the Department of psychophysiology and clinical psychology and only research personal had access to it. Before the start, each participant was informed about the goal of the research, procedure, experimental conditions, and safety of their personal data.

Participants and genotype analysis

This study involved 34 participants of both genders from 18 to 28 years (27 female), students of Southern Federal University. The study was conducted from April 27, 2018 to July 10, 2018 at the Laboratory of Psychophysiology and Experimental Psychology, Department of Psychophysiology and Clinical Psychology, Academy of Psychology and Education Sciences, Southern Federal University (Rostov-on-Don, Russia). The participants were recruited in person. Students received bonus points in their academic disciplines for their involvement in the study. All participants reported normal or corrected-to-normal vision and gave oral, informed consent before beginning experimentation. For genotype analysis buccal epithelial cells were collected from participants. Genotyping was carried out by the «Biologicheskie resheniya i tehnologii» (Moscow, Russia), where DNA was extracted from clinical material using the Proba-NK reagent kit («ООО DNK-tehnologii», Russia). Thermocycler CFX96 «Touch» (Bio-Rad, USA) was used for real-time polymerase chain reaction (PCR).

For genetic analysis were used genomic DNA preparations obtained from biological samples using DNA extraction kits with the removal of PCR inhibitors and the presence of at least 100 genomic copies in 1 μl. During the genetic examination, the following DNA sections were analyzed:

– COMT catechol-O-methyltransferase gene (Genebank sequence AY341246, mutation 23753G> A, Val158Met, rs4680 code). Possible genotypes: Val/Val, Val/Met, Met/Met;

– BDNF brain neurotrophic factor gene (GenBank sequence NG_011794, mutation 68690G> A Val66Met, rs6265 code). Possible genotypes: Val/Val, Val/Met, Met/Met;

– HTR2A serotonin receptor gene (GenBank sequence, NG_013011, mutation 4692G> A, rs6311 (Tr2)). Possible genotypes: G/G, G/A, A/A.

The genotyping resulted in the following sample composition:

COMT gene: 9 participants (26.47 %) were carriers of Val/Val genotype, 20 (58.82%) – Val/Met and 5 (14.7 %) – Met/Met;

HTR2A gene: 11 participants (32.35 %) were carriers of A/A genotype, 11 (32.35 %) – A/G and 12 (35.29 %) – G/G;

BDNF gene: 23 participants (67.64 %) were carriers of Val/Val genotype and 11 (32.35%) Val/Met.

Preparing stimuli

For this research, 223 images were selected from a database used in previous experiments: 85 of them are conditionally negative, 75 are neutral and 63 are positive (Ermakov et al., 2016; Ermakov et al., 2017; Stoletniy et al., 2020b; Vorobyeva et al., 2016); stimuli are available as Extended data (Kovsh & Yavna, 2020). To obtain stimuli with corresponding characteristics, the computer model of the second-order visual mechanisms developed by (Babenko & Yavna, 2018) was applied. Figure 1 below demonstrates examples of original images and the results of their processing by the model. Stimuli images were generated from contrast modulations in the carrier frequency range from 4 to 32 cycle per image. Resolution of pictures is 1024х768 (slightly more 16°х12° of visual angle on the 100 cm distance). The average luminance of the generated images was equal to 110 of 256 greyscale (30 cd/m2). The background brightness was adjusted to the same level. All 223 selected images were processed and then organized in a stimulus sequence.

Figure 1. Example of original images that was selected for processing are above; same images processed by a computer model of second-order mechanisms and made up of areas containing contrast modulations are below.

Figure 2. Example of trial sequence with target stimuli and ISI between them.

Procedure

Participants were seated in good lit room, facing a computer screen, at viewing distance of 100 cm. A grey background (30 cd/m²) was on the monitor all the time of trial, with and without stimuli. Stimulus image was presented in center of screen and its duration was 500 ms. The interstimuli interval was 500–1500 ms (Figure 2). Stimulus pictures were presented in random order regardless of their emotional valence. Participants were asked to examine the stimuli in terms of what emotions this images evokes in them. When evaluating the stimulus as negative, it was necessary to press the key 1 on the keyboard for negative assessment, 2 for neutral, 3 for positive. The next image appeared on the screen only after the subject evaluated the previous one and the interval between stimuli was completed. Furthermore, participants were instructed to blink only when stimulus ended.

Analysis of behavioral data and ERP recordings

The frequency of responses was analyzed using the REdaS Package for R, version 0.9.3., in order to calculate confidence intervals for average response rate with α = 0.05 (Maier, 2015).

A Neurovisor-136 multi-channel EEG system («Medical Computer Systems», Moscow, Russia) was used to record the EEG from 128 electrodes mounted on elastic cap and referenced on the left and right ears. Electrodes were placed according to 10–5 system (Oostenveld & Praamstra, 2001). EEG signal was digitalized at 1000 Hz, and a bandpass filter of 0.5–50 Hz was applied.

The ERPs were processed using the EEGLAB version 4.11 – an interactive Matlab/Octave toolbox for processing electrophysiological data (Delorme & Makeig, 2004). Before averaging the ERPs, the recordings were filtered and the epochs with eye blinks and other artifact of non-brain origin were rejected. The ERPs were averaged 100 ms before the stimulus onset and 500 ms after it. Baseline was corrected based on 100 ms pre-stimulus period. ERPs were computed and grouped according to type of response that participants gave – negative, neutral and positive and theirs genotype. The ERPs grouped by type of emotional assessment were compared separately for COMT, BDNF, HTR2A samples (For example: COMT x Negative evaluation x Val/Val vs Val/ Met; Val/Val vs Met/Met; Val/Met vs Met\Met etc.). Comparisons were carried out using an unpaired Student’s T-test with p < 0.05. ERPs and topography figures were conducted in EEGLAB. The results from all ERP stimuli are available as Underlying data (Stoletniy et al., 2020a).

Results

Behavioral results

This analysis showed that there was no statistically reliable difference in the average response rate in participants with different BDNF gene genotypes regardless type of assessment of target images (Figure 3, upper line). Nevertheless, it should be noted that the ratio of the average number of choices of neutral responses is the reverse of that when choosing negative and positive judgments; the individual participants with the Val/Val genotype chose the neutral response slightly more often than the participants with the Val/Met genotype.

Figure 3. Bar graphs with confidence intervals (a = 0.05) for the average frequency of assessment responses for stimuli for participants with different genotypes of BDNF, COMT and HTR2A genes.

MM- Met/Met genotype, VM – Val/Met, VV- Val/Val for COMT and BDNF genes; AA – A/A, AG – A/G, GG – G/G for HTR2A gene.

Participants with different COMT genotypes chose negative assessments with an average frequency (about 32–33%). There were no significant differences in the frequency of negative responses in the groups. Nevertheless, the distribution of neutral and positive responses is of more interest (Figure 3, middle line). On the one hand, participants with the Val/Val and Val/Met genotype chose the positive assessment of stimuli significantly more often (19% and 13%, respectively) than carriers of Met/Met. On the other hand, the carriers of the Met/Met genotype were significantly often (18% and 13% compared to Val/Val and Val/Met groups) chose to evaluate the images as neutral. There were no significant differences between the average frequency of choosing the neutral and positive responses between the Val/Met and Val/Val groups.

Carriers of different HTR2A genotypes chose negative responses with different average frequency but no statistically reliable difference, because the confidence intervals do not intersect. Although the histogram has a stepwise character from a higher average frequency for carriers of the A/A genotype (39%) to lower frequency for carriers of the A/G (33%) and G/G (28%) genotype (Figure 3, bottom line). A more interesting situation has developed for the neutral and positive types of responses. Participants with the G/G genotype were significantly more likely (46%) to choose the neutral response when evaluating experimental stimuli than those with the A/A (25%) and A/G (29%) genotypes. On the contrary, the G/G group had chosen positive assessment less often (26%), than A/A (37%) and A/G (37%) groups. There was no statistically reliable difference between the average frequency of choosing the neutral and positive responses between the A/A and A/G groups.

ERP data analyses

BDNF. The comparison of event-related potentials when choosing the negative assessment in the groups of carriers of Val/Met and Val/Val genotypes showed significant differences in the amplitude of the event-related response (p <0.003, t = -3.5) in the time range of 150–230 ms (Figure 4a). As can be clearly seen in the figure, the amplitude of the P2 component of the ERP recorded for negative response in participants with the Val/Val genotype is significantly higher than that of the Val/Met group. When choosing the neutral assessment statistically significant differences was found in latency of 172–227 ms (Figure 4b). The ERP amplitude in the group of carriers of the Val/Val genotype is significantly higher (p < 0.02, t = -1.22) than that of the Val/Met group. Choose of positive response to the stimuli elicited an increase in amplitude of ERP peak in the latency of 133–230 ms. ERP peak for the Val/Val group was significantly higher (p < 0.029, t = -2.36) than that of the Val/Met group (Figure 4c). Table 1 presents the values of the ERPs amplitudes in Oz electrode at a latency of 200 ms for the BDNF group.

Figure 4.

ERP for the groups with Val/Met and Val/Val BDNF genotypes in Oz electrode when choosing the negative (a), neutral (b) or positive (c) assessment of stimuli. The gray bar indicates the latency with statistically significant differences (p < 0.05).

Table 1. Examples of amplitudes for ERP peaks in latency and locations where statistically significant differences were found.

Gene and genotype	Type of response/location/latency/Pick amplitude
*BDNF*	Negative (Oz, 200 ms)	Neutral (Oz, 200 ms)	Positive (Oz, 200 ms)
Val/Met	3.71	4.49	4.05
Val/Val	6.68	7.41	6.56
*COMT*	Negative (Oz, 150 ms)	Neutral (Oz, 150 ms)	Positive (Oz, 150 ms)
Met/Met	-0.54	0.69	0.72
Val/Met	2	3.78	3.76
Val/Val	2.9	3.06	3.57
*HTR2A*	Negative (Oz, 120 ms)	Neutral (Po7, 360 ms)	Positive (Poz, 120 ms)
A/A	6.07	0.53	6.20
A/G	1.87	3.24	4.24
G/G	3.33	2.75	3.72

The topography of the potentials distribution shows that the choice of the negative response caused activation in the occipital regions of the cortex. Moreover, it was higher in the group of carriers of the Val/Val genotype of the BDNF gene (Figure 5a). The choice of the neutral assessment caused activation in the occipital regions of the cortex to a greater extent in the group of carriers of the Val/Val genotype (Figure 5b). Nevertheless, activity in the anterior and central areas of the cerebral cortex is somewhat greater in the group of participants with the Val/Met genotype of the BDNF gene. Selection of the positive assessment caused an increase in the amplitude of positive peaks in the region of 140–230 ms in the occipital regions of the cortex, to a greater extent in carriers of the Val/Val genotype of the BDNF gene, as in both previous cases (Figure 5c).

Figure 5.

Topography of the distribution of potentials at a latency of 200 ms (where statistically significant differences were found) from onset of stimuli when choosing negative (a), neutral (b) or positive (c) assessment for the Val/Met and Val/Val BDNF genotypes.

COMT. The comparison of ERPs in the groups of participants with the Val/Met and Val/Val genotypes did not show significant differences regardless of assessment type: for negative, p < 0.94, t = -0.06; for neutral, p < 0.59, t = -1.7; for positive, p <0.95, t = -0.10 (Figure 6a–c, solid and intermittent waves on the figures). On the contrary, amplitude of the event-related potentials in participants with the Met/Met genotype is significantly lower compared to Val/Val and Val/Met groups during every type of assessment (Figure 6, a, b, c, dotted wave). For negative evaluation this differences were observed in latency to the 110 to 175 ms (Val/Met - p < 0.03, t = -2.33; Val/Val - p < 0.03, t = 0.6), for neutral in 120 to 170 ms (Val/Met - p < 0.006, t = -3.10, Val/Val - p < 0.03, t = 2.19), for positive - 135 to 155 ms (Val/Met - p <0.02, t = -1.39, Val/Val - p <0.03, t = -2.39). It should be noted that the amplitude of the event-related potential for Met/Met is higher when participants assessed stimuli as the neutral and positive, then negative ones. Table 1 presents the values of the ERPs amplitudes in Oz electrode at a latency of 150 ms for the COMT group.

Figure 6.

ERP for the groups with Val/Met, Val/Val and Met/Met COMT genotypes in Oz electrode when choosing the negative (a), neutral (b) or positive (c) assessment of stimuli. The gray bar indicates the latency with statistically significant differences (p < 0.05). Significant differences between ERPs in Val/Val and Val/Met groups were not found.

Topography of potentials clearly shows a decrease in activity of occipital regions in the Met/Met group in latency of 150 ms comparing to Val/Met and Val/Val groups. On the contrary Val/Met and Val/Val group showed increase in activity also in the occipital regions of the brain (Figure 7a–c).

Figure 7.

Topography of the distribution of potentials at a latency of 150 ms (where statistically significant differences were found) from onset of stimuli when choosing negative (a), neutral (b) or positive (c) assessment for the Met/Met, Val/Met and Val/Val COMT genotypes.

HTR2A. Comparing the ERPs of A/G and G/G genotype groups showed no statistical difference between them, regardless of assessment type – negative (p < 0.17, t = 1.41), neutral (p < 0.56, t = -0.59) or positive (p < 0.84, t = -0.19). At the same time, chose a negative response type demonstrated that the amplitude of ERP in carriers of the A/A genotype was significantly different from such of the A/G genotype (p < 0.03, t = 2.29) and G / G (p < 0.04, t = 3.12) in the range of 117–133 ms from the onset of stimulus (Figure 8a). Choosing neutral response by carriers of A/A genotype reflected in significant decrease of ERP component’s amplitude in 350–370 ms latency compared to A/G (p < 0.02, t = -2.47) and G/G (p < 0.03, t = -2.25) groups (Figure 8b). Similar to ERP comparison for negative assessment, evaluating stimuli as positive by carriers A/A genotype showed significant increase of ERP amplitude in latency 105 to 124 ms compared to such in A/G (p < 0.01, t = 2.72) and G/G (p <0.03, t = 2.32) genotype carriers (Figure 8c). Table 1 presents the values of the ERPs amplitudes in Oz, Po7 and Poz electrodes at a latency of 120 and 360 ms for the HTR2A group.

Figure 8.

ERP for groups with different HTR2A genotypes in Oz, Po7 and Poz electrodes when choosing negative (a), neutral (b) or positive (c) assessment respectively. The gray bar indicates the latency with statistically significant differences (p < 0.05). Significant differences between ERPs in A/G and G/G groups were not found.

The topography of the distribution of potentials shows a high positivity when choosing negative assessment mainly in the occipital regions of the A/A group and a tendency to decrease of it in same regions in the group of carriers of the A/G genotype, and to a greater extent – in carriers of the G/G genotype (Figure 9a). In the neutral response situation ERP amplitude distribution in carriers of the A/A genotype is somewhat homogeneous over the entire surface of the scalp. However, in carriers of the A/G and G/G genotypes it is much greater in the occipital and parietal regions (Figure 9b). When choosing the positive response, high-amplitude ERPs are localized in the occipital regions. Moreover, the activity in the A/A group is most higher, to a lesser extent it is expressed in the A/G group, and even lower in G/G groups (Figure 9c).

Figure 9.

Topography of the distribution of potentials at a latency of 120 ms from onset of stimuli (where statistically significant differences were found) when choosing negative (a) or positive (c) and 360 ms when choosing neutral (b) assessment for the A/A, A/G and G/G HTR2A genotypes.

Discussion

As shown in the Results section, the BDNF Val/Val genotype is associated with a predominance of neutral assessment of visual stimuli processed by second-order filters. Neutral, positive, and negative judgments of visual stimuli are associated with a significantly higher positivity of the P2 component in the occipital electrodes, which may be explained by the fact that compared to the carriers of BDNF Val/Met genotype the carriers of the BDNF Val/Val genotype consumed large brain resources for recognition and differentiation of stimuli, experiencing difficulties in the implementation of these processes. Moreover, brain activity in the anterior and central areas is more pronounced in carriers of the Val/Met genotype. We obtained similar results in previous series of the experiment (during recognition of unprocessed visual stimuli), which may indicate that the Met allele of the BDNF gene is associated with more efficient processes of recognition of emotional scenes (Ermakov et al., 2017). This feature can be explained by a more intense activation of the structures of the limbic system (Vorobyeva et al., 2019) and stronger functional cortico-limbic bonds (Loewenstern et al., 2019), activated during recognition of facial expression in carriers of the Met allele of the BDNF gene.

According to our results, when judging the stimulus as negative, neutral, or positive negativity was reliably expressed in 110–175 ms (i.e., there is a higher, more negative amplitude of the N170 component) in the occipital electrodes in carriers of the COMT Met/Met genotype.

This aspect may be related to the fact that, when evaluating scenes with distinct second-order features, the carriers of the COMT Met/Met genotype primarily pay attention to the facial expression of individuals depicted in the stimulus pictures and assess the emotional valence of the stimulus based on these data (Eimer & Holmes, 2007). However, this process consumes more brain resources to recognize faces emotional expression.

According to a number of studies, carriers of the COMT Met/Met genotype have higher indices of emotional intelligence (Kosonogov et al., 2019), more successfully differentiate and express emotions (Gohier et al., 2014a). Carriers of the COMT Met/Met genotype more decently respond to positive stimuli. The Val/Val genotype is associated with less intense feelings in negative experience, i.e. their level of life satisfaction is less dependent on external events (Kovalenko & Pavlenko, 2009; Shield et al., 2004)

The HTR2A G/G genotype is associated with a significantly more frequent evaluation of stimuli with distinct second-order features as neutral ones, as well as with a significantly rarer assessed of stimuli as positive ones. The A/A genotype is associated with a significantly higher amplitude of the P1 peak, recorded mainly in the occipital regions of the brain when evaluating visual stimuli processed by second-order filters as positive or negative ones; with a significantly lower wave amplitude in the range of 350–370 ms when assessed as emotionally neutral. These results may indicate that carriers of A/A genotype consume more brain resources at the stage of distinguishing of a significant stimulus among insignificant ones, experiencing difficulties in the implementation of this process (difficulties in pre-attentive processing; component P1 is associated with selectivity of attention), and less resources are consumed duding categorization and conscious evaluation of the emotional content of stimuli (Kovalenko & Pavlenko, 2009; Polich, 2012).

Conclusions

The analysis of the electrical activity of the brain in carriers of various genotypes of the BDNF, COMT, and HTR2A genes when choosing different types of responses in attributing emotional valences to visual scenes processed by the filters with the distinct second-order features enabled us to draw the following conclusions.

BDNF

1) In carriers of the Val/Val genotype the amplitude of the P2 component of visual event-related potentials in the occipital regions of the brain is higher than in carriers of the BDNF Val/Met genotype, regardless of the type of response chosen when evaluating the presented images.

2) The highest ERP amplitude of the three possible assessments (positive, negative, neutral) was found in the response recorded in the neutral evaluation of the presented stimuli; this fact is valid for carriers of the BDNF Val/Val and Val/Met genotypes.

3) Regardless of the type of stimuli, the participants chose responses of different modalities with approximately the same frequency.

COMT

1) In the group of participants with the COMT Met/Met genotype for all the three types of responses (regardless the stimuli images) the induced brain activity is characterized by a significant increase in negativity in peak amplitude latency from 120 to 170 ms and occurs mainly in the occipital cortex brain.

2) When carriers of Met/Met assessed the stimuli as negative the amplitude of this early ERP component is showed increasing negativity, compared with that when choosing neutral or positive responses.

3) Met/Met genotype carriers statistically reliably chose neutral assessment more often and positive less often than carriers of other two genotypes.

HTR2A

1) There were no statistically significant differences between the ERP waves in carriers of the HTR2A A/G and G/G genotypes, regardless of the choice of the emotional valences of responses. On the contrary, A/A group had statistically reliable differences in ERPs peaks compared to A/G and G/G genotypes carriers.

2) When choosing negative and positive assessment, carriers of A/A genotype had statistically reliable differences in early latency peak that had large amplitude, compared to A/G and G/G genotypes carriers. Contrariwise, in neutral assessment situation, a statistically reliable differences in ERPs shifted to later positive peak (around 360 ms) that had an increasing negativity in participants with A/A genotype.

3) The localization of activity also has differences in carriers of different HTR2A genotypes. When choosing negative and positive responses, the topography of significant high-amplitude components of the ERP shows their localization in the occipital regions; with a late latent significant ERP when choosing a neutral type of responses, increased activity also affects the parietal areas (which is more reliable to carriers of the A/G and G/G genotypes compared to carriers of the A/A genotype).

4) G/G genotype carriers were significantly more often chose neutral response and less often positive response for stimuli than carriers of other two genotypes.

In this study, associations between the BDNF, COMT, and HTR2A genotypes and individual characteristics of the perception of emotional visual stimuli with distinct second-order features were investigated. The findings of the study confirmed both hypotheses of the research. Furthermore, the results lead to conclusion that the images preserving second-order features, where all the homogeneous areas are removed, contain all the necessary information for their successful recognition. This may be explained by the work of autonomous mechanisms operating at a pre-attentive stage of visual processing (Babenko & Yavna, 2018). At the same time, various genotypes are associated with varying degrees of success of the pre-attentive and conscious stages of processing emotional visual stimuli (scenes), which confirms the hypothesis that there are genetic factors that individualize the mechanisms of visual perception.

Data availability

Underlying data

Open Science Framework: EEGLAB datasets for study of event-related potentials during categorization of emotionally-charged and neutral images with distinct second-order features in carriers of polymorphisms of the COMT, HTR2A, BDNF genes. https://doi.org/10.17605/OSF.IO/PDHGZ (Stoletniy et al., 2020a).

This project contains the follow underlying data:

1_Negative estimation (ERP datasets recorded when participant chose negative assessment of stimuli).
2_Neutral estimation (ERP datasets recorded when participant chose neutral assessment of stimuli).
3_Positive estimation (ERP datasets recorded when participant chose positive assessment of stimuli).
Data Characteristics.xlsx (detailed description of datasets files).
Data Description.docx (detailed description of experiment condition and datasets).

Extended data

Open Science Framework: Stimuli database for studying emotional assessment of emotionally-charged images with distinct second-order features. https://doi.org/10.17605/OSF.IO/WY2VF (Kovsh & Yavna, 2020).

This project contains all visual stimuli provided for this study, alongside a data description list of the image features.

Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).

Faculty Opinions recommended

References

Aftanas LI, Varlamov AA, Pavlov SV, et al.: Affective picture processing: Event-related synchronization within individually defined human theta band is modulated by valence dimension. Neurosci Lett. 2001; 303(2): 115–118. PubMed Abstract | Publisher Full Text
Alekseeva D, Ermakov P, Babenko V, et al.: Studying the Functional Equivalence of Mechanisms for Emotion Perception and Emotion Generation by Means of Evoked Potentials [Issledovanie s pomoshh’ju vyzvannyh potencialov funkcional’noj jekvivalentnosti mehanizmov vosprijatija i generacii jemocij]. Russian Psychological Journal. 2017; 14(4): 97–120.
Alfimova MV, Golimbet VE: Genes and neurophysiological characteristics of cognitive processes: A research review [Geny i nejrofiziologicheskie pokazateli kognitivnyh processov: Obzor issledovanij]. I.P. Pavlov Journal of Higher Nervous Activity. 2011; 61(4): 389–401.
Andreatta M, Neueder D, Genheimer H, et al.: Human BDNF rs6265 polymorphism as a mediator for the generalization of contextual anxiety. J Neurosci Res. 2019; 97(3): 300–312. PubMed Abstract | Publisher Full Text
Antal A, Chaieb L, Moliadze V, et al.: Brain-derived neurotrophic factor (BDNF) gene polymorphisms shape cortical plasticity in humans. Brain Stimul. 2010; 3(4): 230–237. PubMed Abstract | Publisher Full Text
Babenko V, Ermakov P, Safina Z: Interhemispheric asymmetry of reactions to spatial modulation of local visual characteristics [Mezhpolusharnaja asimmetrija reakcij na prostranstvennye moduljacii lokal’nyh zritel’nyh priznakov]. Russian Psychological Journal. 2016; 13(4): 181–196. Publisher Full Text
Babenko VV, Yavna DV, Solov’ev AA, et al.: Spatial selectivity of visual mechanisms sensitive to contrast modulation **This article is a development of the report “Adjusting second-order visual filters to the orientation of the envelope,” presented at the conference Applied Optics–2010. Appl Opt. 2011; 78(12): 771–776. Publisher Full Text
Babenko V, Yavna D: Competition for attention of spatial modulations of brightness gradients [Konkurencija za vnimanie prostranstvennyh moduljacij gradientov jarkosti]. Russian Psychological Journal. 2018; 15(3): 160–189. Publisher Full Text
Barnes JJM, Dean AJ, Nandam LS, et al.: The Molecular Genetics of Executive Function: Role of Monoamine System Genes. Biol Psychiatry. 2011; 69(12): e127–e143. PubMed Abstract | Publisher Full Text
Barnett JH, Xu K, Heron J, et al.: Cognitive effects of genetic variation in monoamine neurotransmitter systems: A population-based study of COMT, MAOA, and 5HTTLPR. Am J Med Genet B Neuropsychiatr Genet. 2011; 156(2): 158–167. PubMed Abstract | Publisher Full Text | Free Full Text
Bender S, Rellum T, Freitag C, et al.: Time-Resolved Influences of Functional DAT1 and COMT Variants on Visual Perception and Post-Processing. PLoS One. 2012; 7(7): e41552. PubMed Abstract | Publisher Full Text | Free Full Text
Beste C, Kolev V, Yordanova J, et al.: The Role of the BDNF Val66Met Polymorphism for the Synchronization of Error-Specific Neural Networks. J Neurosci. 2010; 30(32): 10727–10733. PubMed Abstract | Publisher Full Text | Free Full Text
Beste C, Schneider D, Epplen JT, et al.: The functional BDNF Val66Met polymorphism affects functions of pre-attentive visual sensory memory processes. Neuropharmacology. 2011; 60(2–3): 467–471. PubMed Abstract | Publisher Full Text
Codispoti M, Ferrari V, Bradley MM: Repetition and Event-related Potentials: Distinguishing Early and Late Processes in Affective Picture Perception. J Cogn Neurosci. 2007; 19(4): 577–586. PubMed Abstract | Publisher Full Text
Delorme A, Makeig S: EEGLAB: An open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J Neurosci Methods. 2004; 134(1): 9–21. PubMed Abstract | Publisher Full Text
Delplanque S, Lavoie ME, Hot P, et al.: Modulation of cognitive processing by emotional valence studied through event-related potentials in humans. Neurosci Lett. 2004; 356(1): 1–4. PubMed Abstract | Publisher Full Text
Dumontheil I, Roggeman C, Ziermans T, et al.: Influence of the COMT Genotype on Working Memory and Brain Activity Changes During Development. Biol Psychiatry. 2011; 70(3): 222–229. PubMed Abstract | Publisher Full Text
Eimer M, Holmes A: Event-related brain potential correlates of emotional face processing. Neuropsychologia. 2007; 45(1): 15–31. PubMed Abstract | Publisher Full Text | Free Full Text
Ermakov P, Kovsh E, Vorobyeva E: Features of induced brain activity in female carriers of various genotypes using the maoa-uVNTR marker when evaluating emotional scenes [Osobennosti vyzvannoj aktivnosti mozga devushek-nositel’nic razlichnyh genotipov po markeru MAOA -uVNTR pri ocenke jemocional’no okrashennyh scen]. Russian Psychological Journal. 2016; 13(4): 232–253. Publisher Full Text
Ermakov P, Vorobyeva E, Kovsh E, et al.: Features of evoked brain activity during recognition of emotional images in carriers of polymorphic variants of the BDNF and HTR2A genes [Osobennosti vyzvannoj aktivnosti mozga pri analize izobrazhenij jemociogennogo haraktera u nositelej polimorfnyh variantov genov BDNF i HTR2A]. Experimental Psychology. 2017; 10(3): 65–85. Publisher Full Text
Gajewski PD, Hengstler JG, Golka K, et al.: The Met-genotype of the BDNF Val66Met polymorphism is associated with reduced Stroop interference in elderly. Neuropsychologia. 2012; 50(14): 3554–3563. PubMed Abstract | Publisher Full Text
Gajewski PD, Wild-Wall N, Schapkin SA, et al.: Effects of aging and job demands on cognitive flexibility assessed by task switching. Biol Psychol. 2010; 85(2): 187–199. PubMed Abstract | Publisher Full Text
Gianfranceschi L, Siciliano R, Walls J, et al.: Visual cortex is rescued from the effects of dark rearing by overexpression of BDNF. Proc Natl Acad Sci U S A. 2003; 100(21): 12486–12491. PubMed Abstract | Publisher Full Text | Free Full Text
Gohier B, Senior C, Radua J, et al.: Genetic modulation of the response bias towards facial displays of anger and happiness. Eur Psychiatry. 2014a; 29(4): 197–202. PubMed Abstract | Publisher Full Text
Gohier B, Senior C, Radua J, et al.: Genetic modulation of the response bias towards facial displays of anger and happiness. Eur Psychiatry. 2014b; 29(4): 197–202. PubMed Abstract | Publisher Full Text
Golimbet VE, Alfimova MV, Gritsenko IK, et al.: The relationship among dopaminergic genes and extraversion and novelty seeking [Svjaz’ genov dofaminergicheskoj sistemy s jekstraversiej i poiskom novizny]. I.P. Pavlov Journal of Higher Nervous Activity. 2006; 56(4): 457–463.
Gómez CM, Marco J, Grau C: Preparatory visuo-motor cortical network of the contingent negative variation estimated by current density. NeuroImage. 2003; 20(1): 216–224. PubMed Abstract | Publisher Full Text
Gosso MF, de Geus EJC, Polderman TJC, et al.: Catechol O -methyl transferase and dopamine D2 receptor gene polymorphisms: Evidence of positive heterosis and gene–gene interaction on working memory functioning. Eur J Hum Genet. 2008; 16(9): 1075–1082. PubMed Abstract | Publisher Full Text
Graham NV: Beyond multiple pattern analyzers modeled as linear filters (as classical V1 simple cells): Useful additions of the last 25 years. Vision Res. 2011; 51(13): 1397–1430. PubMed Abstract | Publisher Full Text
Hashimoto R, Noguchi H, Hori H, et al.: A possible association between the Val158Met polymorphism of the catechol-O-methyl transferase gene and the personality trait of harm avoidance in Japanese healthy subjects. Neurosci Lett. 2007; 428(1): 17–20. PubMed Abstract | Publisher Full Text
Huang ZJ, Kirkwood A, Pizzorusso T, et al.: BDNF Regulates the Maturation of Inhibition and the Critical Period of Plasticity in Mouse Visual Cortex. Cell. 1999; 98(6): 739–755. PubMed Abstract | Publisher Full Text
Kondo HM, Kitagawa N, Kitamura MS, et al.: Separability and Commonality of Auditory and Visual Bistable Perception. Cereb Cortex. 2012; 22(8): 1915–1922. PubMed Abstract | Publisher Full Text
Kondo HM, Nomura M, Kashino M: Different Roles of COMT and HTR2A Genotypes in Working Memory Subprocesses. PLoS One. 2015; 10(5): e0126511. PubMed Abstract | Publisher Full Text | Free Full Text
Kosonogov V, Vorobyeva E, Kovsh E, et al.: A review of neurophysiological and genetic correlates of emotional intelligence. International Journal of Cognitive Reseacrh in Science, Engineering and Education. 2019; 7(1): 137. Publisher Full Text
Kovalenko АА, Pavlenko VB: Emotional Significance of the Stimulus and Features of the Personality as Factors Reflected in the Pattern of Evoked EEG Potentials. Neurophysiology. 2009; 41(4): 282–302. Publisher Full Text
Kovsh E, Yavna D: Stimuli database for studying emotional assessment of emotionally-charged images with distinct second-order features. 2020. http://www.doi.org/10.17605/OSF.IO/WY2VF
Loewenstern J, You X, Merchant J, et al.: Interactive effect of 5-HTTLPR and BDNF polymorphisms on amygdala intrinsic functional connectivity and anxiety. Psychiatry Res Neuroimaging. 2019; 285: 1–8. PubMed Abstract | Publisher Full Text | Free Full Text
Lovallo WR, Cohoon AJ, Sorocco KH, et al.: Early-Life Adversity and Blunted Stress Reactivity as Predictors of Alcohol and Drug use in Persons With COMT (rs4680) Val158Met Genotypes. Alcohol Clin Exp Res. 2019; 43(7): 1519–1527. PubMed Abstract | Publisher Full Text | Free Full Text
Maier MJ: Companion package to the book “R: Einführung durch angewandte Statistik.” R Package Version 0.9.3. 2015.
Mavratzakis A, Herbert C, Walla P: Emotional facial expressions evoke faster orienting responses, but weaker emotional responses at neural and behavioural levels compared to scenes: A simultaneous EEG and facial EMG study. NeuroImage. 2016; 124(Pt A): 931–946. PubMed Abstract | Publisher Full Text
Miranda M, Morici JF, Zanoni MB, et al.: Brain-Derived Neurotrophic Factor: A Key Molecule for Memory in the Healthy and the Pathological Brain. Front Cell Neurosci. 2019; 13: 363. PubMed Abstract | Publisher Full Text | Free Full Text
Nakagami Y, Watakabe A, Yamamori T: Monocular inhibition reveals temporal and spatial changes in gene expression in the primary visual cortex of marmoset. Front Neural Circuits. 2013; 7: 43. PubMed Abstract | Publisher Full Text | Free Full Text
Olofsson JK, Nordin S, Sequeira H, et al.: Affective picture processing: An integrative review of ERP findings. Biol Psychol. 2008; 77(3): 247–265. PubMed Abstract | Publisher Full Text | Free Full Text
Oostenveld R, Praamstra P: The five percent electrode system for high-resolution EEG and ERP measurements. Clin Neurophysiol. 2001; 112(4): 713–719. PubMed Abstract | Publisher Full Text
Pegna AJ, Khateb A, Michel CM, et al.: Visual recognition of faces, objects, and words using degraded stimuli: Where and when it occurs. Hum Brain Mapp. 2004; 22(4): 300–311. PubMed Abstract | Publisher Full Text | Free Full Text
Polich J: Neuropsychology of P300. Oxford handbook of event-related potential components. 2012; 159–188. Publisher Full Text
Popova NK, Ilchibaeva TV, Naumenko VS: Neurotrophic factors (BDNF and GDNF) and the serotonergic system of the brain. Biochemistry (Mosc). 2017; 82(3): 308–317. PubMed Abstract | Publisher Full Text
Reuter M, Hennig J: Association of the functional catechol-O-methyltransferase VAL158MET polymorphism with the personality trait of extraversion. Neuroreport. 2005; 16(10): 1135–1138. PubMed Abstract | Publisher Full Text
Reynolds CA, Jansson M, Gatz M, et al.: Longitudinal change in memory performance associated with HTR2A polymorphism. Neurobiol Aging. 2006; 27(1): 150–154. PubMed Abstract | Publisher Full Text
Rosa EC, Dickinson D, Apud J, et al.: COMT Val158Met polymorphism, cognitive stability and cognitive flexibility: An experimental examination. Behav Brain Funct. 2010; 6(1): 53. PubMed Abstract | Publisher Full Text | Free Full Text
Schofield PR, Williams LM, Paul RH, et al.: Disturbances in selective information processing associated with the BDNF Val66Met polymorphism: Evidence from cognition, the P300 and fronto-hippocampal systems. Biol Psychol. 2009; 80(2): 176–188. PubMed Abstract | Publisher Full Text
Serrano JM, Banks JB, Fagan TJ, et al.: The influence of Val158Met COMT on physiological stress responsivity. Stress. 2019; 22(2): 276–279. PubMed Abstract | Publisher Full Text
Shield AJ, Thomae BA, Eckloff BW, et al.: Human catechol O-methyltransferase genetic variation: Gene resequencing and functional characterization of variant allozymes. Mol Psychiatry. 2004; 9(2): 151–160. PubMed Abstract | Publisher Full Text
Stein DJ, Newman TK, Savitz J, et al.: Warriors Versus Worriers: The Role of COMT Gene Variants. CNS Spectr. 2006; 11(10): 745–748. PubMed Abstract | Publisher Full Text
Stoletniy A, Kovsh E, Vorobyeva E: EEGLAB datasets for study of event-related potentials during categorization of emotionally-charged and neutral images with distinct second-order features in carriers of polymorphisms of the COMT, HTR2A, BDNF genes. 2020a. http://www.doi.org/10.17605/OSF.IO/PDHGZ
Stoletniy A, Kovsh E, Yavna D: Stimul database for studying emotional assessment of emotionally-charged images. 2020b. http://www.doi.org/10.17605/OSF.IO/ZYG54
Tamm G, Kreegipuu K, Harro J: Perception of emotion in facial stimuli: The interaction of ADRA2A and COMT genotypes, and sex. Prog Neuropsychopharmacol Biol Psychiatry. 2016; 64: 87–95. PubMed Abstract | Publisher Full Text
Vorobyeva E, Hakunova F, Skirtach I, et al.: A review of current research on genetic factors associated with the functioning of the perceptual and emotional systems of the brain. SHS Web of Conferences. 2019; 70: 09009. Publisher Full Text
Vorobyeva E, Kovsh E, Yavna D: Visual evoked potentials elicited by culturally-specific images in women with different levels of hostility. Int J Psychophysiol. 2016; 108: 69. Publisher Full Text
Weiss EM, Freudenthaler HH, Fink A, et al.: Differential Influence of 5-HTTLPR - Polymorphism and COMT Val158Met—Polymorphism on Emotion Perception and Regulation in Healthy Women. J Int Neuropsychol Soc. 2014; 20(5): 516–524. PubMed Abstract | Publisher Full Text
Wilson HR, Gelb DJ: Modified line-element theory for spatial-frequency and width discrimination. J Opt Soc Am A. 1984; 1(1): 124–131. PubMed Abstract | Publisher Full Text
Yavna D, Babenko V: Psychophysical and psychophysiological evidence for specificity of second-order visual mechanisms [Psihofizicheskie i psihofiziologicheskie dokazatel’stva specifichnosti zritel’nyh mehanizmov vtorogo porjadka]. Proceedings of the 16th International Conference on Neurocybernetics. 2012; 412–415.
Yavna D, Babenko V, Soloviev A: Cortical localization of second-order visual mechanisms. 41(Perception. Supplement. 35th European Conference on Visual Perception (2-6 September, Alghero, Italy). Abstracts.): 2012; 249.

Comments on this article Comments (0)

Version 1

VERSION 1 PUBLISHED 20 Aug 2020