Currently, there is a high demand worldwide for professional psychologists to help correct emotional status. Various approaches exist for this purpose. Typically, a particular condition is assessed through a survey or questionnaire of the subject, which has limitations due to imprecision and subjectivity. Subjective evaluation is an insufficiently reliable tool since a person may be biased or need an objective understanding of their mental state. Additionally, some people may need to be more responsible or have limited reflective abilities, distorting survey results. However, modern psychophysiological methods can also allow to evaluate the effectiveness of proposed approaches based on quantitative objective data, such as heart rate, galvanic skin response, electroencephalography, etc. This project aims to research psychological and neurophysiological approaches to develop a methodology for evaluate and correct a person's psycho-emotional status.

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system characterized by demyelination and axonal loss. The identification of reliable biological markers for disease activity and progression is essential for predicting the course of the disease and guiding treatment decisions.

Several potential biological markers have been identified for monitoring disease activity in MS. These include imaging techniques such as magnetic resonance imaging (MRI) to assess lesion load and brain atrophy, cerebrospinal fluid (CSF) analysis for inflammatory markers, and blood biomarkers such as cytokines and chemokines. Combining these markers with clinical and demographic factors may improve the accuracy of predicting disease activity.

Predicting disease activity in MS is challenging due to the heterogeneity of the disease course and variability in response to treatment. However, advances in technology and research have provided promising opportunities for identifying reliable biological markers that can aid in predicting disease progression and guiding personalized treatment strategies. Further research is needed to validate these markers and determine their clinical utility in predicting disease activity in MS.

The recent study by Hopp et al. (2023), published in Nature Human Behaviour explores how different moral foundations are represented in the brain and how they are influenced by political beliefs. Participants (n=64) in the study completed a moral judgement task while undergoing fMRI scans, where they rated the moral wrongness of vignettes describing violations of different moral foundations and social norms.

The study demonstrates that the neural signatures associated with moral judgements are distinguishable across different moral foundations and that these signatures are distributed throughout the cortex rather than being localized within specific subregions. Judgements of moral wrongness were slower for moral transgressions compared to non-moral social norm violations, indicating a deeper evaluation process for moral judgements. Each moral violation was judged as more morally wrong than social norm transgressions. Finally, the study provides evidence that political ideology modulates neural representations of moral judgements across different moral foundations, with conservatives rating certain foundations as more relevant to their moral judgement compared to liberals, and vice versa.

Our genomes conceal the history of dozens of thousands generations from close relatives to ancient ancestors who lived millions years ago. In the talk I will present two stories in population genetics which unfold in different time scales. In the first story the expected number of close relatives (p-sisters) in a large sample from population is estimated. It will be illustrated by a case of an arrest of the Golden State Killer from California. The second story is about our new method for detecting genome tracts of ancient human ancestry (Neanderthal and Denisovan) in modern humans. The method is based on a Hidden Markov Model which combines two sources of information simultaneously: it relies both on the known ancient genomes and a modern unadmixed outgroup.

During the seminar I will present a preliminary result of the literature review on cognition as it appears in management research from 2011 till nowadays. My results suggest the there is lack on “umbrella” framework on cognition in management, with several key conceptualization contradicting each other. I wonder if the current state of management research is in alliance with the advancement in neuroeconomics or may be its even fails to comprehend key achievement in your sphere. Our perspective could likewise elevate the avenue of strategic management research at HSE and possibly could lead to cross functional conceptualization efforts.

The upcoming presentation will delve into the study "Dissecting motor skill acquisition: Spatial coordinates take precedence" by Pablo Maceira-Elvira et al., highlighting the brain's approach to prioritizing spatial information in memory over quick execution in the early stages of motor skill learning. It will explore the differential learning processes across age groups and the potential of anodal transcranial direct current stimulation (tDCS) over the motor cortex to enhance motor skill acquisition, particularly in older adults. This session promises insightful discussions on the intersections of neuroscience, aging, and technology, emphasizing the role of noninvasive brain stimulation in cognitive and motor enhancement.

Biological motion is the visual perception of a biological entity engaged in a recognizable activity. This phenomenon encompasses the inherent movement of a changing body in relation to coordinate systems centered on the body or its parts. The biological motion paradigm has been widely used to investigate various aspects of human perception, cognition, and action understanding, making it a fundamental area of study in neurocognitive research. Moreover, research on biological motion has various potential applications, including enhancing users' action understanding in robotics and improving VR and BCI technology for neurological disorders rehabilitation. At the upcoming seminar we are going to talk about fundamental and practical aspects of biological motion research as well as the study we are conducting in the Institute for Cognitive Neuroscience, HSE. 

Self-agency (SA) is defined as the experience of being the agent of one’s own actions, which underlies self-awareness in human interactions with the outside world. One of the processes that seem to rely on self-agency is reality monitoring – the ability to distinguish between memories generated within oneself and derived from external sources. As demonstrated by previous research, the medial prefrontal cortex (mPFC) is considered to represent one neural correlate underlying self-agency. The experience of self-agency is thought to result from being able to reliably predict the sensory outcomes of one’s own actions. This self-prediction ability is necessary for successfully encoding and recalling one’s own thoughts to enable accurate self-agency judgments during reality-monitoring tasks. During my internship at the Department of Psychiatry at the University of California, San Francisco, we investigated whether mPFC activity can causally modulate self-agency in a reality monitoring task by using high-frequency transcranial magnetic stimulation (TMS) to enhance mPFC excitability or TMS targeting a control site.

Artificial intelligence is developing every day and is increasingly penetrating into various areas of our lives, including science. There are pros and cons to using AI, but with proper and honest interaction with neural networks, AI can significantly simplify the process of scientific work, assist in translating academic texts or searching for topical articles. This seminar is dedicated to the specifics of using artificial intelligence in the research activities: we will talk about what AI is, how it can help a scientist, and also conduct a short practical session on using ChatGPT for work purposes. AI cannot replace the human mind, but it can definitely become an integral assistant and provide greater productivity and efficiency in work and study processes.

Reaction times (RTs) are used to study different cognitive and motor processes. In response, the decision and the execution of a motor response are two separate and sequential processes. We propose an adaptive algorithm designed to explicitly estimate the duration of the decision process. The algorithm is based on two assumptions. First, the independence of the decision and reaction execution stages, according to the sequential stage model. Second, the possibility that the decision-making process can be transferred to a preparatory period (PP). In a series of experiments, we found an independent influence of response selection and response execution difficulties on PP duration and RT, respectively. Thus, the adaptive algorithm effectively separates the duration of the preparation period from the time required to execute the motor response. This distinction allows a more precise investigation of decision-making in healthy and cognitively and motor impaired patients.

Phosphenes, light flashes in the absence of a visual stimulus, are an intriguing subject in neuroscience. In this study, we present a methodology for mapping the visual cortex using transcranial magnetic stimulation (TMS) to investigate phosphenes. Phosphenes can arise from various brain stimulation factors, and understanding their mechanisms is becoming increasingly important for comprehending the visual cortex.

We utilized the NBS NEXSTIM system to accurately stimulate the brains of healthy participants. A series of single TMS pulses allowed us to precisely identify regions in the visual cortex capable of eliciting phosphenes. Our research serves as the initial step in creating a detailed map of visual cortex activation in response to TMS stimulation and may have practical applications in medicine and neuropsychology. It contributes to a better understanding of how the brain perceives phosphenes and may serve as a starting point for further studies in the field of the visual cortex and brain activity.

Anxiety has been linked to altered belief formation and uncertainty estimation, impacting learning. Identifying the neural processes underlying these changes is important for understanding brain pathology. Here, we show that oscillatory activity in the medial prefrontal, anterior cingulate and orbitofrontal cortex (mPFC, ACC, OFC) explains anxiety-related learning alterations. In a magnetoencephalography experiment, two groups of human participants pre-screened with high and low trait anxiety (HTA, LTA: 39) performed a probabilistic reward-based learning task. HTA undermined learning through an overestimation of volatility, leading to faster belief updating, more stochastic decisions and pronounced lose-shift tendencies. On a neural level, we observed increased gamma activity in the ACC, dmPFC, and OFC during encoding of precision-weighted prediction errors in HTA, accompanied by sup- pressed ACC alpha/beta activity. Our findings support the association between altered learning and belief updating in anxiety and changes in gamma and alpha/beta activity in the ACC, dmPFC, and OFC.

A variety of bisection tasks will be reviewed in this seminar. Bisection tasks are a category of cognitive tasks that require participants to divide or bisect various stimuli into equal or nearly equal parts. They are commonly used to study various cognitive and perceptual processes, as well as to assess potential deficits in certain clinical populations. Bisection task has the potential to engage attentional, motor, and cognitive processes. Three groups of bisection tasks will be discussed in this seminar based on the level of cognitive processing they require: sensory (activation of low-level cognitive processes), symbolic (processing of symbolic information such as letters or digits), and semantic (lexico-semantic access).

The report will consider examples of bidirectional interactions within the brain-heart axis, as a subject of research in an interdisciplinary field - neurocardiology. The phenomenon of interoception will also be considered, i.e. perception of internal signals of the body. Its violation is associated with the development of somatic, as well as psychosomatic disorders, manifested incl. cardiac symptoms. Interoception is assessed using subjective (heart rate tests) and objective (cardiac evoked potentials) methods. However, at present there is no single approach to assessing interception, since it is a complex phenomenon and depends on many factors. In our study on groups of healthy volunteers and patients with cardiovascular pathology, we compared three modifications of the interception subjective assessment test, correlated their accuracy with the amplitude of cardiac evoked potentials, as well as indicators of the autonomic nervous system (heart rate variability) and body composition.

The project is aimed at choosing the most attractive and eye-catching design for SPAR energy drink among the options submitted by HSE Design Lab students. GSR and eye-tracking methods were used in the experiment. Elena and Alisa will provide profound results about the best SPAR energy drink chosen by the participants (n = 10) and will report the details about methodology and procedure of the conducted experiments. 

Anxiety disorders (such as generalized anxiety disorder, panic disorder, social phobias, separation anxiety disorder) rank high in terms of socioeconomic burden (personal, family, community). Despite a sufficient understanding of the mechanisms of anxiogenesis and the existence of effective therapeutic strategies, the prevalence of phobic anxiety disorders is steadily increasing. Studies have shown that an average of 10 years elapses between the onset of the first symptoms of an anxiety disorder and the time before seeking specialized help (a psychiatrist) (duration of untreated illness). A long period of delay in receiving care leads to chronicity of the condition, the addition of concomitant mental and somatic disorders, worsening response to therapy and overall prognosis of the disease. Thus, the study of psychopathological, socio-psychological and neurobiological (including neuroeconomic) features of the duration of untreated illness in patients with various types of anxiety disorders will reduce the period without effective help and optimize the available treatment and prevention approaches.

We will present preliminary findings of multinational neuroeconomics study of the behavior of individuals from across 11 countries of markedly different socioeconomic and cultural makeup using an experimental approach that reliably captures context effects in reinforcement learning. Preliminary findings show that all samples presented evidence of similar sensitivity to context. Conversely, risk aversion significantly differed across countries.

In this talk, we present research on speech decoding using a small set of minimally invasive electrodes. Our results show that it is possible to decode speech on the level of individual words with this method. The process is split into two stages: first, we recover an Intermediate Speech Representation (ISR) such as a Mel-spectrogram, and then decode the words. We found that using a single shaft or stripe of electrodes only slightly reduces the achievable accuracy compared to using larger electrode sets. Additionally, we found that a compact and interpretable architecture performs well and better than more elaborate solutions, possibly due to a tradeoff between the amount of data and the size of the network. On-off decoding can also be achieved with simpler approaches. Different ISRs are recovered with varying degrees of fidelity, but all result in comparable words decoding accuracy. We also found that the fidelity of the individual ISR recovery correlates with the corresponding words classification accuracy. There was no evidence of decoding from muscular activity or acoustic contamination, and the decoding was done causally to avoid hearing-based decoding. We achieved 7-10-fold chance level accuracy in decoding on the level of individual words. We did not use a language model in this research, which may improve the quality of the results. Transitioning to decoding mouthed or imagined speech is a key step towards developing real-life prosthetic devices. However, training tools still need to be developed.

The talk will cover face approximation method, key terms, types of reconstructions, sources for craniofacial research, examples of approximation methods. The second part will cover the plausibility of the method and identification criteria and the effect of experience on human skull and face recognition. Directions of future research will be discussed. The talk will be in Russian, with parallel translation to English.

Although the neurocognitive mechanisms underlying decision-making under risk are already quite well understood, only a few studies deal with culturally specific aspects of risk perception, which is especially relevant for Russia, where so many different ethnic groups live side by side. To fill this gap, we conducted a pilot behavioral study whose main purpose was to examine cross-cultural differences in risk perception and risk-taking preferences on the example of two ethnic groups, Russians and Armenians, living in Moscow. In this talk, I will present the results of our behavioral study and, in conclusion, briefly outline our future research plan.

Our project is aimed at examining the cognitive dissonance (CD) processing in terms of the functions of its key neural correlates, which are posterior medial frontal cortex (pMFC) and dorsolateral prefrontal cortex (DLPFC), and from the perspective of the exact timing and sequence of pMFC and DLPFC involvement in the CD identification and reduction processes. Online repetitive transcranial magnetic stimulation (rTMS) as the active method of influencing cognitive processes in different time moments was chosen as the most optimal method to address our goal. However, TMS neurochronometrical study is possible on the basis of the most optimal paradigm in terms of its efficiency in evoking CD and avoiding artifacts. Thus, the first part of our study is targeted at searching for the most suitable paradigm for our main research question, while the second part includes elaborating and realizing the online rTMS protocol.

Negative affect with high arousal can disturb attention. The cause of this disturbance can be found in the field of executive functions (primarily Inhibition). According to literature the neural basis for producing and sustaining EF is prefrontal cortex, more specifically DLPFC.Our study proposes that electrical stimulation (tDCS) of DLPFC region can decrease the influence of negative affect with high arousal on attention due to strengthen “control system”. Flanker task will be used to assess attention. We created two versions of flanker task: neutral and emotional. Participants will undergo neutral and emotional flanker tasks after tDCS. Also, during participants’ performance EGG will be recorded. As a result, we expect that the difference in efficiency between neutral and emotional flanker task before stimulation will be greater than after stimulation. Also, we expect that before stimulation the amplitude of error-related negativity (ERN) for errors will be greater than after stimulation. Design of the study and anticipated results will be discussed in more details.

Impulsivity often occurs with anxiety and affects the quality of executive functions. Using the eye-tracking method, we tested the influence of the level of impulsivity on oculomotor activity in participants with high anxiety. Twenty volunteers with a high level of anxiety and a low level of impulsivity (HA + LI) and fourteen volunteers with a high level of anxiety and a high level of impulsivity (HA + HI) performed anti-saccade tasks in three blocks, which differ in time of the target stimulus appearance (step, overlap, gap). The target stimuli were images of neutral, positive, or negative emotions in the step, gap blocks.  A square served as peripheral stimuli in the overlap sequence. The groups differed in the latency of regular errors in the overlap sequence and the amplitude of regular errors in the gap sequence. Individuals with HA+HI demonstrated regular errors with a higher latency in the overlap block and a lower amplitude in the gap block only in response to neutral stimuli. Our results imply that reduced inhibitory control and impaired attention in the HA+HI group could manifest in the increased latency and decreased amplitude of regular errors in the antisaccade task when viewing neutral images.

Although healthy eating nudges have extensively been studied, there is limited research on sugar-related interventions. The results of these studies are inconsistent and are mainly based on labels (e.g. "sugar-free"), which is not considered a particularly effective type of intervention (Cadario and Chandon, 2019). Healthy eating calls are more effective especially if they are communicated from a high credibility source (Cadario and Chandon, 2019; Binder et al., 2020). In our experiments (behavioral, EEG, fMRI), we investigate how healthy eating calls (in particular, first-person narrative by a nutritionist) can decrease the willingness to pay for sugar-containing food. I will first present the results of our behavioral pilot and then we may discuss our expected results of the EEG and fMRI experiments, which will be conducted in the following weeks.

The properties and characteristics of cognitive systems are traditionally determined through their manifestations in external behavior. The data accumulating in recent years show that the cognitivity of the system can be deduced from the activity of its nervous elements. These facts give us a new look at the very nature of the phenomenon of cognition.

Empathy is supposed to play a functional role in prosocial behavior. However, there has been behavioral evidence that people do not empathize everyone equally. Shihui Han presented studies that show brain imaging evidence for racial ingroup bias in empathy for pain. These studies reveal multiple-level neural mechanisms underlying racial ingroup bias in empathy. Professor also discussed potential intervention of racial ingroup bias in empathy and its social implications.

Recording of the seminar

We consider new measures of centrality in networks, which take into account parameters of nodes and group influence of nodes to nodes. Several examples are discussed.

Existing studies show that there is a positive association between pro-migrant integration policies and the subjective well-being of immigrants. However, there is a lack of research elucidating the relations between migrant integration policies and the subjective well-being of the host (i.e., non-migrant) population. This study is based on European data and uses multilevel analysis to clarify the relations between migrant integration policy (both as a whole and its 8 separate components such as: Labour market mobility and Family reunion) and the subjective well-being of the non-immigrant population in European countries. We examined relations between the Migrant Integration Policy Index (MIPEX) for 22 countries in Europe and subjective well-being, as assessed by the European Social Survey (ESS) data. The results demonstrated that there is a positive relation between the MIPEX and subjective well-being for non-immigrants. Considering different components of the MIPEX separately, we found most of them being positively related to the subjective well-being of non-immigrants. As no negative relationship was identified between any of the eight MIPEX components and subjective well-being, policies in favour of immigrant integration also seem to benefit the non-immigrant population.

Recording of the seminar

Neuroscientific research in the past two decades has consistently pointed to the involvement of two separate factors in empathy (Shamay-Tsoory, 2011; Zaki & Ochsner, 2012). On the one hand, affect sharing (AS), is a vicarious resonance with others’ somatovisceral affective states. It is prompted by neural systems supporting affect perception, such as the sensory cortices and amygdala; salience detection, which involves anterior portions of the cingulate cortex (ACC) and the insula. On the other hand, theory-of-mind (ToM) denotes the attribution of mental states to others based on cognitive representation. It implicates a network including the medial prefrontal cortex, superior temporal sulcus, temporo-parietal junction, precuneus, posterior cingulate cortex, and the temporal poles. In my talk, I will review the evidence on the dissociation of these networks. I will also present neuroimaging findings about oppositional and complementary relations between them during the processing of naturalistic audiovisual content.

Shamay-Tsoory, S. G. (2011). The neural bases for empathy. Neuroscientist, 17(1), 18–24. https://doi.org/10.1177/1073858410379268

Zaki, J., & Ochsner, K. (2012). The neuroscience of empathy: progress, pitfalls and promise. Nature Neuroscience. https://doi.org/10.1038/nn.3085

In striving for experimental control, studies of human episodic memory have focused mainly on encoding of brief, stationary events. Such events, while providing a high degree of control, bear little resemblance to real-life memory and constrain the questions that can be asked. I will demonstrate how use of naturalistic stimuli enables us to address previously unaskable questions, discussing a set of fMRI studies in which we asked when episodic memories are formed. Using film clips as a proxy for real-life memory, we found that hippocampal activity time-locked to the offset of events, but not their onset or duration, is linked to subsequent memory. In a subsequent study we analysed brain activity of over 200 participants who viewed a naturalistic film and found that the hippocampus responded both reliably and specifically to shifts between scenes. Taken together, these results suggest that during encoding of a continuous experience, event boundaries drive hippocampal processing, potentially reflecting the encoding of bound representations to long-term memory. I will discuss how this surprising finding opened a new avenue of research, asking what is encoded in episodic encoding – is each element encoded independently, or is the entire episode encoded as a cohesive unit?

The nature of self is one of the most controversial questions throughout the history of philosophy and science. Different approaches emphasize different aspects of this construct including emotional, cognitive, and social self. Moreover, some authors deny its reality altogether claiming that the self is just an illusion. From the point of view of social science, the intersubjective or social aspects are the most important aspects of self. One of the most popular approaches to the study of these aspects is contrasting self-referential with other-referential processing in the trait adjective judgment task. In our study, using fMRI functional connectivity data, we aimed to directly compare the involvement of the default mode network (DMN) versus external attention-related task-positive networks (TPN) during self- and other- referential processing for different others varying in the degree of their closeness to the self. We hypothesized that the DMN versus TPN balance should linearly decrease during evaluation of self, close-other, distant-other, and an unpleasant person.

Successful investing is challenging, since stock prices are difficult to consistently forecast. Recent neuroimaging evidence suggests, however, that activity in brain regions associated with anticipatory affect may not only predict individual choice, but also forecast aggregate behavior out-of-sample. 

Thus, in two experiments, we specifically tested whether anticipatory affective brain activity in healthy humans could forecast aggregate changes in stock prices. Using Functional Magnetic Resonance Imaging (FMRI), we found in a first experiment (n=34, 6 females; 140 trials per subject) that Nucleus Accumbens (NAcc) activity forecast stock price direction, whereas Anterior Insula (AIns) activity forecast stock price inflections. In a second preregistered replication experiment (n=39, 7 females) that included different subjects and stocks, AIns activity still forecast stock price inflections. Importantly, AIns activity forecast stock price movement even when choice behavior and conventional stock indicators did not (e.g., previous stock price movements), and classifier analysis indicated that forecasts based on brain activity should generalize to other markets. By demonstrating that AIns activity might serve as a leading indicator of stock price inflections, these findings imply that neural responses associated with anticipatory affect may extend to forecasting aggregate choice in dynamic and competitive environments such as stock markets.

The concept of mentality in actual research is revealed. The importance of the category of analytic-holistic thinking is emphasized (including its manifestations at the inter- and intracultural level). The articles are analyzed, which describe the brain support of behavior in mental variations, including those related to various types of activity and forms of social interaction. The results are interpreted from the standpoint of a systemic evolutionary approach. The evolutionary aspect of the existence of intra- and intercultural variations is discussed.

People frequently interpret the same information differently, based on their prior beliefs and views. This may occur in everyday settings, as when two friends are watching the same movie, but also in more consequential circumstances, such as when people interpret the same news differently based on their political views. The role of subjective knowledge in altering how the brain processes narratives has been explored mainly in controlled settings. Yaara Yeshurun presented two projects that examines neural mechanisms underlying narrative interpretation “in the wild” -- how responses differ between two groups of people who interpret the same narrative in two coherent, but opposing ways. In the first project were manipulated participant’s prior knowledge to make them interpret the narrative differently, and found that responses in high-order areas, including the default mode network, language areas and subsets of the mirror neuron system, tend to be similar among people who share the same interpretation, but different from people with an opposing interpretation. In contrast to the active manipulation of participants’ interpretation in the first study, in the second (ongoing) project were examined these processes in a more ecological setting. Taking advantage of people’s natural tendencies to interpret the world through their own (political) filters, we examine these mechanisms while measuring their brain response to political movie clips. These studies are intended to deepen our understanding of the differences in subjective construal processes, by mapping their underlying brain mechanisms.

Machine learning has pushed the study of brain health beyond comparing group averages. The statistical view of machine learning as function approximation in high dimensions is attractive for clinical neuroscience as it lends itself towards robust modeling of clinical endpoints from rich and heterogenous input data (Engemann et al., 2018). A full realization of this research program currently hinges upon meeting important challenges related to the reality of data in clinical neuroscience. In the small-sample regime, common to clinical neuroscience studies, pooling various imaging and electrophysiology modalities places a premium on strong domain knowledge, good priors and flexible handling of missing inputs (Engemann et al., 2020, Sabbagh et al., 2020). When the actual endpoint of interest, e.g. neuropsychiatric diagnosis, is expensive to acquire, the total number of labeled samples may not suffice to enable high-fidelity machine learning. In such situations, developing proxy measures derived from widely available labeled targets, such as age, provides a viable workaround (Engemann et al., 2020, Dadi et al., 2020). Even when data is available in abundance, the study of mental health often poses the additional challenge that, in contrast to somatic medicine no confirmatory measures exist such as plasma-assessment of insulin levels in diabetes. Here, building various proxy measures becomes a way of life and, depending on the target of interest, behavioral and sociodemographic input data can become the go-to modality for studying mental health (Dadi et al., 2020). This raises the question if machine learning itself can be used to automatically extract proxy measures from brain signals without explicit choice of one specific proxy target. Recent advances in deep learning and non-linear independent component analysis have given rise to the self-supervised learning paradigm. Applied to EEG data, SSL readily captures the structure of clinical recordings reflecting various factors such as the clinical operator, electrode selection, date, age, sleep stages and neuropsychiatric pathology (Banville et al.,2020). While causal mechanisms are still under investigation powered by experimental approaches, the statistical learning paradigm offers a viable tool for studying mental health using multiple imaging, electrophysiological and behavioral techniques capitalizing on all available data.

Recent economic theories of choice under risk postulate that the observed risk-taking behavior in monetary domain may be determined by the valuation of money (i.e. how much a person values one additional dollar, or a marginal utility of money) as well as specific perception of probabilities (i.e. probability weighting). However, existing neuroeconomic studies of risk taking usually focus on the analysis of the degree of the observed risk taking per se without disentangling its individual components. Recent neuroeconomic research suggests that posterior parietal cortex (PPC) may play a role in risky decision-making. In the present study, we employ transcranial magnetic stimulation to explore the effects of decreased PPC excitability on distinct components of risky choice. We report three main findings. First, participants tend to make safer choices after the stimulation of the left PPC. Second, this shift in preferences results from both decreased valuation of monetary rewards as well as a higher distortion of probabilities. Finally, because both of these changes shift preferences towards safer choices, this also makes decision-making process easier for participants which results in an increased consistency of choices.

A powerful way to investigate the source of individual differences in various characteristics is genetically informative study. Starting from classical twin designs it nowadays incorporates not only quantitative genetics, but molecular genetics as well. In neuroscience genetically informative design can help to disentangle different factors underlying the relationship between neuronal dynamics and cognitive functions. In the present talk we will overview the current state in the genetically informative studies in neuroscience and present the design of the ongoing study carried out on the basis of MEG Center.

To what extent does genetic influence on economic behavior matter and can be enhanced or weakened by environmental factors? The answer to this question will help to understand the main biological pathways of economic behavior. Eugenia's report addressed this issue, taking it apart. She first showed some preliminary results from her Shanghai lab on how environmental factors caused by stress influence decision making. In this study, she used students and participants from China in general with economic tasks and stress questionnaires, and collected and analyzed saliva and hair samples. Stress questionnaires track signs of "stress" or measure perceived stress, saliva samples provide a measure of cortisol concentration at a specific point in time, and hair cortisol can correspond to chronic stress. She went on to share the work of her colleagues on how rodents can be stressed through physical restraint or pharmacology and whether this alters their behavior in the risk task. Finally, she discussed the existing genetic associations with risks and timing preferences, summarizing recent (GWAS studies across the entire genomic association) work.

The use of naturalistic stimuli while collecting data about the brain (for example, watching a feature film, listening to an audiobook, listening to music) has proven to be a very powerful tool for studying brain activity in a living setting. However, the additional uncontrollable complexity of naturalistic stimuli has posed new challenges for developing methods for understanding brain data as measured by naturalistic paradigms.In this talk, Enrico Glerean presented techniques such as intersubject correlation, intersubject phase synchronization, intersubject functional connectivity, and intersubject similarity analysis. These techniques have proven to be very useful in understanding the similarities and differences between individual brains processing complex naturalistic stimuli in healthy and clinical populations.

In recent years there has been a large discussion on the influence media has on people’s views, attitudes, and beliefs. Advances in technologies and the increasing presence of mass media in people’s lives raise a question about the methods which could decrease susceptibility to media influence. Media literacy skills and the ability to critically analyze media narratives could be considered as such methods.

The aim of the proposed research is to look at media literacy skills as a possible cognitive tool which allows to decrease conformity in the context of media narrative interpretation. In order to do so, we are going to compare the differences in the narrative interpretations among those who apply media literacy skills and those who do not. We will consider the differences and similarities in brain activity during the narratives processing using electroencephalography and inter-subject correlation method.

In our day to day lives we are constantly immersed in streams of sensory events like sounds or images, which very often follow repetitive patterns (Garrido et al., 2009). Because of these patterns, it is possible to use past experience to predict future events, before these occur, for example the sound of a siren might predict the arrival of an ambulance.

Cortical and subcortical brain regions allow us to extract patterns from repeating events, and form predictions about the future (Barascud et al., 2016). Forming predictions can take place either in cases where they are relevant to our actions i.e. while paying attention to environmental stimuli, but also in an automatic way, i.e. while our levels of arousal are low (Tzovara et al., 2015) and attention is distracted (Chouiter et al., 2015). Although actions and behavioural relevance have a strong effect on sensory processing, it still remains unknown how they may alter the generation of sensory predictions, and therefore the learning of new patterns.

In this study we will use magnetoencephalography (MEG), in combination with eye-tracking and behavioural metrics, in order to study how the formation of predictions is affected by participants’ behaviour.

Offline seminar: Armyansky, 4, 118

Identification of stable and heritable individual differences in functional brain organization is essential for understanding the biological bases of both normal-range individual differences (cognitive abilities, personality) and psychopathology. This lecture evaluated the utility of resting-state and task-related functional Magnetic Resonance Imaging (fMRI) measures as indicators of individual differences in brain function. In addition, a comparative analysis of strengths and weaknesses of fMRI and electrophysiology (EEG/ERP) methods was provided.

Offline seminar: Armyansky, 4, 118

Trust is known as the most important factor in the efficiency of economic and social processes, characterizing the level of development of public institutions (Knack & Keefer, 1997). Traditional methods of measuring trust in survey research (for example, using the World Value Survey methodology) show a rather low level of trust in Russia compared to other countries (Algan & Cahuc, 2013). Unlike survey methods, the trust investment game (Berg e.a., 1995; Johnson and Mislin, 2011) provides an opportunity to measure the level of trust people have in each other under real incentives.

In 2020, we conducted an online trust experiment in 12 Russian cities, representing all federal districts, with the participation of more than 2,000 people. The participants in the experiment - registered users of the Yandex-Toloka crowdsourcing platform - made decisions during the experiment with respect to participants from all cities (double strategic method), which made it possible to collect almost 25 thousand decisions and stimulated expectations regarding the decisions of opponents - the same participants from other cities.

The participants of the experiment – registered users of the Yandex-Toloka crowdsourcing platform-made decisions in the course of the experiment in relation to participants from all cities (double strategic method), which allowed us to collect almost 25 thousand decisions and stimulated expectations about the decisions of opponents – the same participants from other cities.The results showed that motivated measures of trust (trust) and its justifications (trustworthiness) may be more valid from an economic point of view than the survey ones - in particular, unlike the latter, they are correlated with GRP. The levels of motivated trust in Russia (58%) and its justification (44%) were even slightly higher than global trends, and generally meet the expectations of the participants themselves. At the same time, we find negative and positive discrimination between representatives of different regions in relation to each other, clustering of cities by levels of trust, and interregional differences in decision-making mechanisms regarding trust or distrust of counter-partners from other regions.

In the seminar, Ivan Sterligov, the director of the HSE Scientometrics Centre, gave a talk about the main bibliometric indicators of journals, scientists, and organizations, and will pay attention to wrong indicators usage in Russian and international practice. The talk covered the pros and cons of impact-factor, SNIP, SJR, CiteScore, Eigenfactor, citation normalization, H-index and its derivatives,  and expert’s journal ratings. Also, there was a demonstration of sources of scientometric information: analytical tools (SciVal and InCites) and VoSviewer, an instrument for scientometric network visualization. Attendees had an opportunity to ask any questions about the use of scientometrics in HSE, including staff research.

Offline seminar: Armyansky, 4, 118