Thesis Topics and Regulations

Thesis Regulations

Thesis Rules and Regulations 

Rules App 1: Statement CW Topic 

Rules App 2: Statement CW Topic Exchange 

Rules App 3: Statement MT Topic

Rules App 4: Statement MT Topic Exchange 

Rules App 5: Thesis Manual 

Rules App 6: Supervisor Evaluation Form 

Rules App 7:Review Form 

Thesis Topics 

Vasily Klucharev, Faculty of Social Sciences | School of Psychology: Professor 

1. Neuroscience of social influence, persuasion, propaganda   
2. Neuroeconomics of the decisions under risk
3. Neuroeconomics studies of the cognitive dissonance 
4. Neuroeconomics of the financial decisions 

Anna Shestakova, PhD, Director of the Centre for Cognitive and Decision Making

        1. Neurocognitive mechanisms of consumer behavior. Neuromarketing.
        2. Cognitive function in individuals with motor deficits. 


Yury Shtyrov, Centre for Cognition & Decision Making: Leading Research Fellow:

1. Neural dynamics of language comprehension and production
2. Cognitive control in communication
3. Sensory-motor integration and embodied cognition
4. Psychological and psychophysiological bases of numeracy
5. Interactions between domain-specific and domain-general cognitive systems
6. Language acquisition
7. Communication deficits (e.g. aphasia)
8. Cognitive and neural mechanisms of bilingualism

Tadamasa Sawada, Faculty of Social Sciences | School of Psychology: Associate Professor    

1. Haptic/Tactile perception: perception of a shape of an object (haptic) and of texture (tactile)
2. Visual perception of a 3D shape
3. Visual perception of depth (e.g. stereo, familiarity, texture-gradient)
4. Practical problems in analysis and statistics   

                       
Matteo Feurra, Faculty of Social Sciences | School of Psychology: Associate Professor

1. Long-term Memory Processes     
2. Motor Control and Mirror Neurons System by Non Invasive Brain Stimulation (TMS, tDCS, tACS)      
3. Disentangling Working Memory System trough sub-components investigation           
4. Non invasive Brain Stimulation and Decision Making   
5. Methods: Testing Transcranial Electrical Stimulation effects by different stimulation waveforms     
6. Methods: Combining Non Invasive Brain Stimulation with EEG       

Boris Gutkin, Centre for Cognition & Decision Making: Leading Research Fellow:

1. Modelling the mechanism and functional significance of neuronal oscillations in cognitive tasks
2. Modelling complexity in neural dynamics
3. Modelling drug addiction
4. Modelling decision processes and their modulation by supply and demand
5. Developing novel financial market modelling methods

                       
Marie Arsalidou, Faculty of Social Sciences | School of Psychology: Associate Professor

1. MRI (e.g., fMRI, rsfMRI, DTI), cognition and development
2. Eye-tracking, cognition and development
3. EEG, cognition and development  
                        
Dmitry V. Lyusin , Scientific-Educational Laboratory for Cognitive Research: Leading Research Fellow     

1. Mood congruency in the processing of emotional stimuli.
2. Cognitive foundations of emotion differentiation.
3. Affective vs. non-affective executive functions.
4. The role of negative affect in Stroop Incongruity Effect.

  
                          
Boris V. Chernyshev, Faculty of Social Sciences | School of Psychology | Department of Psychophysiology: Associate Professor 

1. Electrophysiological markers and brain mechanisms of spontaneous attentional lapses   
2. Psychophysiology of individual differences in fluctuations of attention          
3. Mind-wandering as a possible cause of spontaneous attentional lapses
4. Psychophysiology of intra-modal and inter-modal feature binding: the relative role of automatic and attentional processes.       
5. Relationship between attention and awareness studied with visual evoked potentials.    
6. Brain mechanisms of Kanizsa illusion: MEG study.       
7. Brain mechanisms of ultrarapid acquisition of "embodied" word meaning: MEG study.

Vadim Nikulin, Centre for Cognition & Decision Making: Leading Research Fellow:

1. Functional significance of neuronal oscillations in sensory, motor and cognitive tasks
2. Complexity in neural dynamics
3. Cortico-muscular interactions in normal subjects and patients (e.g. stroke)
4. Development of the novel analytic and recording techniques for EEG/MEG                 

Olga V. Dragoy, Faculty of Humanities, Center for Language and Brain: Director

1. Neural foundations of language processing (MRI, electrophysiological and neurostimulation evidence)       
2. Psycholinguistic studies (behavioral and eye-tracking evidence)
3. Bilingualism and crosslinguistic studies
4. Language assessment and rehabilitation in brain-damaged populations (with aphasia, tumors, epilepsy)
5. Normal and pathological language acquisition
6. Interaction between language and other cognitive functions 

                     
Alexey A. Kotov, Scientific-Educational Laboratory for Cognitive Research: Senior Research Fellow       

1. Contemporary versions the hypothesis of linguistic relativity: the influence of language on categorization      
2. Development of early childhood concepts from perceptual categories to inductive inferences
3. Early strategies in mapping new words onto objects by children from 2 to 4 years      
4. Models of multiple systems of categorical learning: parallel or sequential functioning                      

 Beatriz Martin-Luengo, Senior Research Fellow, Center for Cognition and Decision Making, HSE

1. Metacognition and second language acquisition.
2. Neural correlates of false memories.

Projects available in the MEG lab of the Higher School of Economics

 P1. Clinical biomarkers for epilepsy surgery in intracranial stereo EEG

 P2. HFO as clinical biomarkers for epilepsy surgery in MEG

 P3. HFO as clinical biomarkers for epilepsy surgery in MEG

 P4 Characterization of the temporal and spatial dynamics of the nested oscillations in human NREM sleep: sEEG study

 P5 The relation between mesial temporal lobe and posterior parietal cortex along the span of working memory capacity

 P6 Spatial and temporal working memory identified by distinct oscillatory activity

 P7 How are sensory predictions modulated by behaviour? A MEG study

 P8 Cortico-hippocampal connectivity in associative memory processing: a stereo-EEG study

 P9. What are experts made of? Uncovering expertise in motor sequence learning

 P10. Increasing motor sequence learning expertise: A meditation approach

 

Olga Sysoeva, Leading researcher, Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Sciences
 
1.     Rapid brain system for semantic analysis of written words. 

Natural language processing is getting more into the focus of cognitive neuroscientists (Broderick et al.,2018). We are extending this approach into reading and would like to examine dynamics of brain activity during rapid serial presentation of engaging text. The study of brain activity provides the answer that we cannot get with any behavioral technique - the timing of the rapid processes simultaneously running within our brain. Indeed, while it takes quite a lot for you to read this text (about 10 seconds on average), your brain needs less than 100 ms to distinguish whether the word is abstract or concrete (Sysoeva et al., 2007). How can we use this intriguing finding to improve our reading skills? In your thesis this topic can be expanded into subconscious analysis of written words. The goal is to describe the neurophysiological mechanisms of rapid semantic analysis using EEG/MEG technique. 

2.     Time perception: gene-brain-behavior. 

Our subjective perception of time can be studied by objective methods of psychophysics and EEG/MEG. Moreover, we can track individual differences in this ability into genetic polymorphisms (Sysoeva et al., 2010). The topic of your thesis might be related to neurophysiological mechanisms of time perception and its influence by external factors (Sysoeva et al., 2013; Portnova et al.,2010). How other psychological traits (e.g. impulsivity) correlate with individual differences in time perception converging into similar neurogenetic pathways. Alternation in the subjective time flow in different neuropsychiatric conditions might be also considered. While the main part of the work will be based on human studies, we might be able to examine some of our hypotheses in the experiments with rodents.

3.    Neurobiological profiles of neurodevelopmental disorders

By recording the EEG and extracting its activity related to particular sensory and cognitive processes we aim to construct non-invasive objective psychophysiological profiles of different neurodevelopmental disorders. While our previous works were mostly focused on autism spectrum disorders and its syndromic forms, currently we aim to extend our focus to other disorders with noticeable speech and language problems, including dyslexia. The thesis topic might be linked to different aspects within the above identified framework, including application of advanced EEG analysis techniques, including machine learning to the unique EEG datasets.

For inquiries: olga.v.sysoeva@gmail.com

Oksana Zinchenko, PhD, Research Fellow, International Laboratory of Social Neurobiology

1. Neuroscience of envy (peripheral vegetative markers as a predictor of antisocial behavior).
2. Social cognition in a time of COVID-19.
3. Cascade model of prefrontal activation in decision-making (exploration-exploitation strategies): MEG study. 

Maria Del Carmen Herrojo-Ruiz, Leading Research Fellow:Institute for Cognitive Neuroscience

1. Neurobiological mechanisms underlying the impact of anxiety and depression on motor learning [MEG, computational modelling, behaviour]

 

Main goals and objectives: This project aims to characterise the neural mechanisms underlying impaired motor learning and performance in subclinical anxiety, and, separately, subclinical depression, to identify risk factors or early biomarkers for potential development of mood and anxiety disorders. As an additional goal, the project will determine the role of anxiety in the development of motor complications in functional (psychogenic) motor disorders, a condition with a high prevalence of comorbid anxiety. This will pave the way for future studies into the role of anxiety and depression in a broader range of disorders with motor impairment and in rehabilitation settings.

 

Research methodology and anticipated research outcomes: To achieve those goals, the project will examine neural and computational components of motor learning in healthy individuals with different levels of trait anxiety and different subclinical depression scores. Analysis of neural oscillations in MEG signals across relevant brain regions as well as their interactions will allow us to identify neurophysiological markers associated with the deleterious effect of anxiety or depression on motor learning and performance in these populations. In addition, the project will analyse alterations in MEG connectivity patterns and oscillatory activity in functional motor disorders, and determine how comorbid anxiety contributes to the deterioration of motor behaviour in this patient population.

 

Outcome: You will learn all the aspects related to modelling decision-making behaviour with current approaches in the field of Computational Psychiatry. You will also learn to interpret and discuss your data in light of current theories in cognitive neuroscience, decision making and anxiety and mood disorders. You will learn analysis of MEG oscillations in the sensor and source space.

2. Neurobiological mechanisms underlying the impact of anxiety and depression on motor learning [MEG, computational modelling, behaviour]

Main goals and objectives:This project aims to characterise the neural mechanisms underlying impaired motor learning and performance in subclinical anxiety, and, separately, subclinical depression, to identify risk factors or early biomarkers for potential development of mood and anxiety disorders. As an additional goal, the project will determine the role of anxiety in the development of motor complications in functional (psychogenic) motor disorders, a condition with a high prevalence of comorbid anxiety. This will pave the way for future studies into the role of anxiety and depression in a broader range of disorders with motor impairment and in rehabilitation settings.

Research methodology and anticipated research outcomes: To achieve those goals, the project will examine neural and computational components of motor learning in healthy individuals with different levels of trait anxiety and different subclinical depression scores. Analysis of neural oscillations in MEG signals across relevant brain regions as well as their interactions will allow us to identify neurophysiological markers associated with the deleterious effect of anxiety or depression on motor learning and performance in these populations. In addition, the project will analyse alterations in MEG connectivity patterns and oscillatory activity in functional motor disorders, and determine how comorbid anxiety contributes to the deterioration of motor behaviour in this patient population.

Outcome: You will learn all the aspects related to modelling decision-making behaviour with current approaches in the field of Computational Psychiatry. You will also learn to interpret and discuss your data in light of current theories in cognitive neuroscience, decision making and anxiety and mood disorders. You will learn analysis of MEG oscillations in the sensor and source space.