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Regular version of the site

Keynote Lecturers and Invited Speakers

Keynote Lecturers

Raul Gainetdinov

Emerging pharmacology of Trace Amine-Associated Receptors (TAARs): Emotions and Social Dimensions
St. Petersburg State University, Russia

Trace amines are endogenous biogenic amine compounds classically regarded as composing beta-phenylethylamine, p-tyramine, tryptamine, p-octopamine, and others. Vertebrates express a family of receptors termed trace amine-associated receptors (TAARs). Humans possess 6 functional receptors: TAAR1, TAAR2, TAAR5, TAAR6, TAAR8 and TAAR9. With the exception of TAAR1, all other TAAR are expressed in olfactory epithelium neurons, where they detect diverse innate odors, including pheromones. Outside the olfactory system, TAAR1 is the most thoroughly studied with both central and peripheral roles. TAAR1 has been already identified as a novel therapeutic target for schizophrenia. Among other TAARs, TAAR5 represents the most interest as regard to depression, since it is expressed in limbic brain areas and TAAR5 knockout mice have remarkable alterations in emotional behaviors. Thus, anxiolytic and/or antidepressant action of future TAAR5 antagonists could be predicted. Data from TAAR5 and other TAAR knockout mice indicate that TAARs are not just olfactory receptors sensing innate socially-relevant odors, but also play important neuronal functions in the limbic brain areas. In general, “olfactory” TAAR-mediated brain circuitry may represent a previously unappreciated neurotransmitter system involved in the transmission of innate odors into emotional behavioral responses.

Vasily Klucharev

Brain-to-brain synchrony in urban spaces: brains in the cities
University of Amsterdam, the Netherlands / HSE University, Russia

Today, 55% of the world's population lives in urban areas, a proportion that is expected to increase to 68% by 2050. To test cognitive mechanisms in real-world settings we have to study the perception of urban environments in more details. Many theoretical accounts emphasize a strong tendency of humans to focus on and prefer natural environments that restore cognitive resources. Previous studies demonstrated people focus on fewer specific features of natural environments as compared to built environments. Thus, green urban environments less frequently destruct our attention and, consequently, can restore cognitive resources of our brains. It suggests that similarity of the brain activity across people could increase in green as compared to built environments, since, in the built environments, people are differently engaged in the processing of the overloading diverse environmental stimuli. In the EEG study, we measured the correlation of neural responses among 30 participants using an inter-subject correlation (ISC) approach. The ISC measures shared brain activity in response to natural stimuli. According to ISC approach, participants who are strongly and similarly engaged with the stimulus exhibit strong neural responses that are highly correlated across all participants. We applied ISC analysis to study the similarity of the brain activity of a group of people as they were exposed to videos of walks through parks, boulevards and busy roads. EEG of the subjects was recorded with 64-channel EEG, while they were watching the videos which showed a five-min walk through an urban environment. We found that average similarity across brain activity was particularly strong during observation of parks as compared to observation of highways and boulevards. Such stronger intrasubject brain synchronization measured by ISCs indicates increasing similarity of mental states across individuals in green urban spaces. We found that parks increase intersubject synchronization of the EEG activity particularly in the delta band that reflects the most evolutionary old and phylogenetically preserved cortical activity. Overall, our results suggest that during urban walks in busy boulevards and highways people’s attention is distracted, that lead to a weaker brain synchronization between individuals

Invited Speakers

Veeky Baths

Multimodal framework and fusion of EEG, graph theory and sentiment analysis for the prediction and interpretation of consumer decision
Birla Institute of Technology and Science Pilani, India

The aim of the study is to propose a multimodal framework using Electroencephalography (EEG), Eye-Tracking and Sentiment Analysis to understand Consumer behaviour. To decode the information about the perception of consumers and the decision-making mechanism that operates within a highly complex process in the brain, neuroscientists are now integrating computational approaches and neuroimaging for better understanding of such processes (Hubert & Kenning, 2008). In this study, we have used EEG and sentiment analysis in the area of marketing. In the first study, we used Electroencephalography (EEG) and Event-Related Potentials (ERP) to capture consumer responses to highly familiar products images. EEG signals were analysed from the 27 participants were used to extract P1, N1, P300, N400 and Late Posterior components. The analysis showed that the early ERP components viz., P1, N1 and P300 can differentiate between consumer liking and disliking of products while the late ERP components N400 and Late Posterior components cannot in the highly familiar product category. The results indicate that after continuous exposure, consumer preference towards highly-familiar products occurs as a part of automatic, unconscious mental processes irrespective of the product properties. In the second study, we investigated sentiment analysis for statements and opinions given by people in social media. In this study, the dataset consisted of statements in mixed coded language (consisting of words/phrases from two languages). We combined BERT (Binary Encoded Representation using Transformers) models of the native languages and conducted sentiment analysis on both the languages individually. We further combined the two results to arrive at a sentiment score for the statement. The classification accuracy is marginally better than single code sentiment analysis. Using our approach, we are able to increase the sentiment classification accuracy to 87% (averaging over the analysis of three datasets). Traditional approaches that do not translate the language gave an accuracy of about 84%. The increase can be attributed to the contextual effects that an emotional word can have in a specific language that is generally lost in translation. In light of the information given, many studies have been carried out in the literature about eye- tracking technique, which has a significant influence on neuromarketing that draws the attention of the academic community. These studies discuss how long the consumer looks and focuses, which visual is more remarkable, and how much eye stroke (twitch) it receives, is to measure the visual attention and intensity of the points that the subjects look at in an ad brochure with the eye-tracking device. Our results show that these neuroscience techniques can be used in marketing to better understand the conscious and unconscious consumers’ thinking and tailor specific marketing strategy.

Nina Kazanina

Frequency-tagging paradigm in application to language: recent advances and limitations
University of Bristol, UK / HSE University, Russia

Following a convincing application of the frequency-tagging paradigm in face processing and vision research (see Norcia et al 2015 for a review), the paradigm has been adapted for research on language processing. In this talk I go over various studies to exemplify which research questions can benefit from the method, as well as discuss its inherent limitations.

Krishna Prasad Miyapuram

Decoding Brain oscillations while Listening Songs, Watching Movies, and Meditating
Indian Institute of Technology Gandhinaga, India

Non-invasive measurement of brain function has been a hallmark of human neuroscience. The great amount of temporal resolution that electroencephalography (EEG) offers makes it possible to study brain function at the same speed at which cognitive processes occur. Traditional approaches have been limited to studying event-related responses with limited ecological validity. Natural stimulation like listening to music and watching movies offer a step in the direction of understanding how complex stimuli are dynamically processed by our brains. Neuronal activity, by default, is better understood in terms of oscillations i.e. spikes per second. EEG due to its high temporal resolution allows one to study brain oscillations at different frequency bands that are of interest in various cognitive processes. Neural entrainment refers to the mirroring of the frequencies of individual stimulations by the brain waves. Audio stimuli, particularly constitute a wide range of frequencies - way beyond those that can be typically measured using EEG. Movies too have varying content that makes it difficult to discern the dynamic processing of audio-visual stimulation by brain waves. Yet, another case study that I would discuss would be meditation, which is driven in its entirety by the internal states of the person, rather than any external stimulation. In all these approaches, newer computational tools have emerged that allow one to study neural correlates in naturalistic scenarios. Machine learning methods render the fascinating idea of brain reading possible. This talk will give examples from multiple case studies of decoding brain signals during naturalistic scenarios.

Ioannis Ntoumanis

How expert persuasion can decrease willingness to pay for sugar-containing food
HSE University, Russia

Although sugar is a key cause of obesity, there is scarce research exploring what can influence individuals to consume less sugar. In our experiment, we investigate how a healthy eating call - first-person narrative by a health expert - affects individuals’ willingness to pay (WTP) for sugar-free and sugar-containing food products. First, I will present our recently published behavioral results, which demonstrate that the health expert’s narrative can decrease individuals’ WTP for sugar-containing food, but does not modulate their WTP for sugar-free food. This confirms earlier research suggesting that consumers may conform to healthy eating calls by rather devaluating unhealthy food products than by increasing the value of healthy ones. Next, I will present preliminary results of an EEG study with a similar experimental design, which aims to underpin the aspects of neural responses to the same healthy eating call that can predict the efficacy of expert persuasion. Finally, I will discuss our research hypotheses for an fMRI study in the same research direction. Overall, the goal of our multimodal project is to evaluate neuroimaging as a tool to design and assess health-related advertisements before they are released to the public.

Natalia Shemyakina

Influence of competition conditions on ERP components during creative thinking
Sechenov Institute of Evolutionary Physiology & Biochemistry, Russia

Human is a social creature, therefore the influence of social conditions on the persons’ cognitive activity becomes a valuable topic of neuroscience. Social competition as the stress factor could be crucial for decision making in conditions of generation and self-comparison of ideas. The one of the known approaches to facilitate the outcomes in creative problem solving is the brainstorming when a group of people meet to generate new ideas and solutions around a specific domain of interest by removing inhibitions (critics and stress). There was shown [Fink et al., 2010, 2012] that perception of other people's ideas when performing an alternative uses task contributed to an increase in the originality of the ideas created by the participant. However, what happens if we create a competitive situation in idea generation and stress to be the first with suggestion? Will we support the data and have more interesting ideas from the subjects? How will the brains of participants react to the competitive conditions in creative task? We will speak about ERP correlates, behavioral data in hyper scanning and individual performance of alternative uses test.

Feng Sheng

Decomposing loss aversion
Zhejiang University, China

Loss-averse decisions, in which one avoids losses at the expense of gains, are highly prevalent. However, the underlying mechanisms remain controversial. The prevailing account highlights a valuation bias that overweighs losses relative to gains, but an alternative view stresses a response bias to avoid choices involving potential losses. Here we couple a computational process model with eye-tracking and pupillometry to develop a physiologically grounded framework for the decision process leading to accepting or rejecting gambles with equal odds of winning and losing money. Overall, loss-averse decisions were accompanied by preferential gaze toward losses and increased pupil dilation for accepting gambles. Using our model, we found gaze allocation selectively indexed valuation bias, and pupil dilation selectively indexed response bias. Finally, we demonstrate that our computational model and physiological biomarkers can identify distinct types of loss-averse decision makers who would otherwise be indistinguishable using conventional approaches. Our study provides an integrative framework for the cognitive processes that drive loss-averse decisions and highlights the biological heterogeneity of loss aversion across individuals.

Anna Shepelenko

Predictors of charitable behavior: a research into emotions and the intersubject correlations of neurophysiological fluctuations
HSE University, Russia

Conscious perception of identical narratives causes synchronization of neurophysiological fluctuations in different subjects. The level of this intersubject correlation (ISC) is considered to be an indicator of audience engagement and has found its application in neuromarketing to assess the attractiveness of advertising messages. Expanding the scope of this method, we applied it to the analysis and efficacy of charity appeals. As a result, we have shown that charity videos cause significant ISC heart rate (ISC-HR), which is positively correlated with donation size. In the future, we plan to study the synchronization of brain activity during the conscious processing of charitable messages using fMRI and EEG methods, which can become the basis for evaluating the effectiveness of charitable advertising.

Yury Shtyrov

Word learning in and out of context: multimodal neuroimaging data
Aarhus University, Denmark / HSE University, Russia

Humans excel in quickly and efficiently learning new words, building up lexicons of many thousands of words. Despite its clear importance, this vital word acquisition ability and its neural bases in the brain remain unclear. Even though behavioural manifestations of learning are evident near instantly (e.g., we can start using new words immediately after hearing or reading them), the bulk of neuroimaging work has largely studied slow neural changes associated with months or years of practice. To overcome this gap, we used a variety of state-of-the-art neuroimaging tools, including EEG, MEG, MRI, TMS and tDCS, as well as bespoke learning paradigms to tackle rapid brain mechanisms underpinning different types of word acquisition. Our studies used both passive exposure to novel spoken and written words and contextual learning designs engaging different strategies for word acquisition. The results show a network of cortical areas that take part in online word and morpheme acquisition, which exhibit immediate functional and structural plasticity. This plasticity depends on multiple factors, including phonology, semantic references, individual language experience, age etc. Distinct cortical mechanisms become involved depending on the type of learning and semantic and morphological content of novel words. Furthermore, we show that these cortical learning systems can be modulated using neurostimulation tools to boost word acquisition outcomes, which may in the future lead to development of new applications, therapies and interventions.