IMPRS NeuroCom Summer School 2018


TUESDAY, 26 June




Opening Remarks

Session 1: Tools and Techniques in Cognitive Neuroscience: Part I

Chair: Arno Villringer

09:30 10:00

Arno Villringer

Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.

The role of different tools and instruments in cognitive neuroscience.


Nikolaus Weiskopf

Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.

Probing the functional and anatomical meso- and microstructure with magnetic resonance imaging (MRI)


Coffee Break


Maria Angela Franscheschini

MGH, Boston, USA.

NIRS: Recent advances and future prospects


Vadim Nikulin

Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.

Neural Oscillations in EEG / MEG research



Session 1: Tools and Techniques in Cognitive Neuroscience, Part II

Chair: Arno Villringer


Alfred Anwander

Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.



Til Ole Bergmann

Department of Neurology & Stroke, and Hertie Institute for Clinical Brain Research, University Hospital Tübingen, Eberhard Karls University of Tübingen, Tübingen, Germany

Transcranial brain stimulation and its combination with EEG/MEG


Coffee Break


Moritz Grosse Wentrup

Max Planck Institute for Intelligent Systems, Tuebingen, Germany.

Brain-Computer Interfacing: Moving from the Lab into the Wild


Arno Villringer

Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.



Poster Session I


Welcome Barbecue


Session 2: Social Interaction

Chair: Pascal Vrticka


Giacomo Rizzolatti

Istituto di Neuroscienze, Consiglio Nazionale delle Ricerche – CNR, Parma, Italy and Dipartimento di Neuroscienze, Università di Parma, Parma, Italy

The “mirror” brain

Mirror mechanism is a basic neural mechanism that transforms sensory representations of others’ actions into motor representations of the same actions in the brain of the observer. In the first part of my talk I will describe the functions of the mirror mechanism located in the parieto-fontal network of monkeys and humans. I will show that this mechanism enables one to understand others in an immediate, phenomenological way, without recourse to cognitive inferential processing. In the second part of my talk I will discuss the role of the mirror mechanism in understanding basic Darwinian emotions. I will focus on disgust, fear and happines and will demonstrate the role of the mirror mechanism in empathic experience of these emotions, contrasting it to their mere cognitive recognition. The data on emotions will lead me to the last part of my talk where I will present stereo-EEG data on action and emotion recognition. Stereo-EEG allows one to go beyond the static three-dimensional maps obtained with fMRI providing a four dimensional picture (space plus time) of brain activations during different types of actions.


Victoria Leong

Department of Psychology, Cambridge, UK
Eye contact and social connectedness with infants

Eye contact is one of the earliest and most powerful communicative signals within the social repertoire of human infants. Well before language is acquired as a communicative tool, infants already eloquently exchange eye gaze signals with adults in a temporally-contingent and meaningful manner. This early synchronisation of gaze patterns (through joint attention and gaze-following) creates social connectedness within parent-infant dyads, which is strategic for early survival. It is perhaps unsurprising then, that even from birth, neonates already prioritise the neural processing of eye gaze cues from adult partners. In fact, it is now known that infants can seek and create their own earliest social networks, using gaze to flag their own, and others’ attentional status. But what exactly happens when infants “go online” to engage with adult partners - and why is this state of social connectedness important? In this talk, I will demonstrate how dyadic EEG can be used to peer into the neuro-social network of infants, where connections occur not just within brains, but also between brains. Observed through this intimate social lens, eye contact between partners is found to trigger powerful bursts of dyadic neural coupling – an effect that is not evident when brain activity is assessed alone, without reference to the partner. Further, when adult and infant brains are locked in close temporal alignment, infants’ own communicative efforts are stimulated and released, and the stage is set for effective social learning. I will conclude by discussing the future potential offered by, and challenges inherent in, this deep merging of social and neuroscience methods into a new coherent science of interpersonal cognition.


Coffee Break


Kristina Musholt

Leipzig University, Leipzig, Germany.


Daniel Haun

Leipzig University,Leipzig, Germany.

Species-specific aspects of childhood social behavior

Human children rely on others all the time. Children learn from others, cooperate with others, enjoy each others’ company. At the same time, they bind themselves to others. They are for example willing to conform to others - sometimes even while demoting their own opinions and preferences. This orientation towards others is championed as a necessary condition for human sociality. Variation across species in preferences to cooperate with others or in tendencies to empathize with others identified several unique features of human sociality. Several of these species-specific social features, such as for example overimitation and normative conformity, share roots in the same underlying species-specific mechanism: self-similarity preference, i.e. Liking others who are like me. This homophily-based account includes two closely related claims. First, children preferentially affiliate with, cooperate with and learn from similar others. Second, since members of the child’s social group tend to prefer individuals that are similar to themselves, children can mediate their social relationships by attempting to manage their own similarity to others.It is looking towards others, other species, other cultures, that reveals the species unique ways in which we enjoy, select and consider others. I will present several current studies related to these theoretical claims, including cross-species and cross-cultural developmental comparisons.


Lunch Break

Session 3: Aging

Chair: Veronica Witte




Joseph Castellano

Icahn School of Medicine at Mount Sinai, New York, USA.

Systemic aging as a model to study neurodegenerative diseases


Coffee Break




Poster Session II


Session 4: Modeling the mind

Chair: Thomas Knoesche


Roshan Cools

Radboud University, Nijmegen, NL.

Chemistry of the adaptive mind

A failure to adapt to novel or changing environmental demands is a core feature of a wide variety of neuropsychiatric disorders as well as the normal states of stress and fatigue. I will review the neurochemistry of flexible cognitive control, which has been associated primarily with frontostriatal circuitry. Many drugs affect the functioning of this circuitry, but the direction and extent of drug effects vary across individuals and tasks. Apparently paradoxical effects are often observed, where the same medication causes both cognitive enhancement as well as cognitive side effects. I will present neurobiological research that is beginning to elucidate the nature of these contrasting effects and the factors underlying the large variability across individuals and behaviours. For example, I will illustrate how we are starting to resolve the large variability in catecholaminergic drug effects by going beyond classic models of prefrontal cortex and building on recent advances that highlight a role for the catecholamines in the flexibility-stability tradeoff as well as value-based learning and decision making. The work has considerable implications for the understanding of and treatment development for abnormalities characterized by compulsivity such as Parkinson's disease and addiction.


Uri Hasson

Princeton University, Princeton, USA.

How the brain accumulates and communicate memories as life unfolds over time?

Cognition materializes in an interpersonal space. At present, little is known about the neural substrates that underlie our ability to communicate with other brains in naturalistic settings. In the talk I will introduce novel methodological and analytical tools for characterizing the neural responses during production and comprehension of complex real-life speech. By directly comparing the neural activity timecourses during production and comprehension of the same narrative, we were able to identify areas in which the neural activity is correlated (coupled) across the speaker’s and listener’s brains during communication. Furthermore, the listener brain activity mirrors that of the speaker with a constant delay of three seconds. This neural coupling was eliminated when the communication signals were misaligned. Finally, the stronger the speaker-listener coupling the greater listener comprehension. I will demonstrate how the observed coupling of production and comprehension-based processes serves as a mechanism by which brains share information as well as episodic memories.


Coffee Break


Shinji Nishimoto

CiNet, Osaka, JPN.

Modeling internal representations in the brain

In our daily lives, our brains continually process diverse, complex, and dynamic sensory information to generate appropriate inferences regarding the world and ourselves. Elucidating how the brain works under such a complex flow of information is a fundamental goal of systems neuroscience. Toward this goal, we build quantitative models that explain the relationship between natural experiences and brain activity, measured using various techniques, including functional magnetic resonance imaging and single-cell recordings. By utilizing sufficiently high dimensional feature spaces that mediate brain activity and sensory information, we have built models that can be generalizable to arbitrary novel natural experiences. Such models can be used to reveal visual and semantic representations of the brain, to quantify how cognitive demands warp the representations, and to decode objective and subjective experiences from brain activity. In this lecture, I will introduce methodology and recent advancements in this field.



Session 5: Big Data and Neuroethics

Chair: Arno Villringer

13:30 - 14:00

Philipp Kellmeyer

University of Freiburg, Germany.

Big Brain Data: Ethical, legal and social challenges from big data and advanced machine learning in neuroscience

The technological convergence of big data and advanced machine learning, particularly artificial neural networks for 'deep learning', facilitates a number of potentially transformative applications in basic and clinical neuroscience. Yet, the collection of large amounts of biomedical data, particularly brain data, and the ability to extract highly personal information from these data, produces significant ethical, legal and social challenges. Apart from the question of data security and the legal and moral accountability of 'black-box' medical AI systems, the talk will also address the question of whether brain data should be considered as a special class of biomedical data and develop ideas on the effective regulation and governance of intelligent systems in basic and clinical neuroscience.


Paul Matthews

Imperial College Lonon, London, UK.


Danilo Bzdok

Uniklinik RWTH Aachen, Aachen, Germany.

The advent of big data in neuroscience: Implications for science and society

Neuroimaging datasets are constantly increasing in resolution, sample size, multi-modality, and meta-information complexity. This opens the brain imaging field to a more data-driven machine-learning regime (e.g., minibatch optimization, structured sparsity, deep learning), while analysis methods from the domain of classical statistics remain dominant (e.g., ANOVA, Pearson correlation, Student's t-test). Special interest may lie in the statistical learning of scalable generative models that explain brain function and structure. Instead of merely solving classification and regression tasks, they could explicitly capture properties of the data-generating neurobiological mechanisms. Python-implemented examples for such supervised and semisupervised machine-learning techniques will be provided as applications to the currently biggest neuroimaging dataset from the Human Connectome Project (HCP) data-collection initiative as well as the prospective epidemiological UK Biobank. The emphasis will be put on the feasability of deep neural networks and semisupervised architectures in imaging neuroscience. The successful extraction of structured knowledge from current and future large-scale neuroimaging datasets will be a critical prerequisite for our understanding of human brain organization in healthy populations and psychiatric/neurological disease, while raising new ethical concerns for our society.


Panel Discussion


Coffee Break


Feedback, Poster Prizes, and Final Remarks

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