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

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

The role of different tools in cognitive neuroscience


Nikolaus Weiskopf

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

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


Coffee Break


Maria Angela Franceschini

Harvard Medical School, Massachusetts General Hospital,
Athinoula A. Martinos Center for Biomedical Imaging, Charlestwon, USA

NIRS: Recent advances and future prospects


Vadim Nikulin

Dept. of Neurology, 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

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

From DTI to the Human Connectome: Diffusion MRI in Cognitive Neuroscience

Diffusion MRI is used extensively to analyse the relation between white matter microstructure and cognitive function. It allows to image the local orientation of the white matter and to reconstruct the fibre pathways connecting the different parts of the brain. Those connections build the network in the brain which implements the cognitive functions. Additionally it gives a quantitative measure of white matter coherence which is extensively used to study brain development, plasticity and diseases. After a short introduction into diffusion MRI, I will give an overview of the different methods to analyse diffusion MRI which were developed in the last years and show the main applications in cognitive neuroscience. I will focus on the main achievements of the method and show recent advances in the field. The presentation will also include the major challenges and limitations of the method. The lecture will show what we can do with diffusion MRI, what we can expect from the method and how it influences neuroscientific research. It will conclude with future perspectives of diffusion MRI to study of the brain as a network, the connectome.


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.


  Tobias Grossmann

Department of Psychology, University of Virginia, USA

How to build a helpful baby: Neurodevelopmental precursors of altruistic behavior in infancy

One of the most enduring puzzles in biology and psychology is why humans engage in acts of altruism towards genetically unrelated individuals. I will argue in this talk that other-oriented emotional processes play an important role in guiding altruistic behavior from early in ontogeny. In particular, the ability to show concern for others in need and distress is a vital building block for altruistic tendencies among humans. I will first present recent research supporting the view that infants genuinely care about others in need and distress. Importantly, I will also show evidence for a caring continuum, which underpins variability in infant prosocial action. Specifically, I will present results from a longitudinal study in which we demonstrate that differences in attentional and brain responses to viewing others in distress (fearful faces) at 7 months predict altruistic behavior at 14 months of age. This research sheds light on the ontogenetic roots of altruism and attests to infants’ affective competency in engaging prosocially.


Coffee Break


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.


Kristina Musholt

Leipzig University, Leipzig, Germany

Varieties of Understanding Self and Others

It is often assumed that the ability to interact with others is based on the possession of a theory of mind, that is on the ability to ascribe mental states to them in order to predict and explain their behavior. In this talk I will first argue that this view is too simplistic and that there is a variety of ways of understanding and interacting with others, only some of which are based on the explicit ascription of mental states. Second, I will outline how, during ontogeny, these different ways of relating to others contribute to an emerging sense of self. I will aim to show that the development of self-consciousness is a gradual process that goes hand in hand with the development of an understanding of others, and that it is a process in which both children and adults actively participate. In particular, adults provide important forms of “social scaffolding” which are crucial for the development of self-consciousness (and thinking more generally).


Lunch Break

Session 3: Aging

Chair: Veronica Witte


Veronica Witte

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

Impact of lifestyle factors on the aging brain

The trajectories of cognitive abilities across the adult lifespan differ from person to person and are most likely open to change dependent on internal and external factors. While common cardiovascular risk factors such as obesity, hypertension and smoking have been linked to accelerated brain aging, healthy lifestyle habits such as physical exercise and a healthy diet might exert protective effects. However, the underlying mechanisms of how modifiable factors impact human brain structure and function are far from understood. In my talk I will discuss recent findings, controversies and future perspectives.


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


Poster Session III


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

Paul Matthews

FRCP, FMed Sci, Imperial College London, London, UK

Ethical considerations in clinical imaging research

The ethics of any big data human research project is based on recognition of morally relevant interests of participants and the society in which they and the investigator live. They must balance a commitment to autonomy of participants (part of the broader expectation of respect for persons) and preserving any fundamental human rights with the pursuit of a “common good”. Imaging is almost unique amongst clinical tests for its salience to participants. Best management of unexpected incidental findings on imaging examinations of people participating in research protocols outside of the context of their medical care demands involvement of all of those potentially involved – participants, radiographers and research colleagues and medical care-givers who address the problems posed by follow up investigations and any treatments. This will be discussed with support from data prospectively acquired in the UK Biobank Imaging Enhancement that sought to frame the relative benefits and risks of actively seeking to identify potential unexpected pathology for participants in the scanning protocol. This highlighted ways in which this balance is grounded in participant expectations and society’s values as they are reflected in the medical system. It also suggests why the optimal balance differs between societies, research environments and over time.


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.


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

loading content
Go to Editor View