CAS (Winter 23/24)


As human beings, we have bodies and brains, but another integral part of us is something that appears non-physical, or immaterial to many people, something that we call ‘mind’. Equipped like this, we can experience, remember, forget, and learn, we can make strategic plans, daydream, do research or invent things and nonsense and tell our friends about it or visualize what we come up with to convey our ideas to others. How is it that we do all this?
Many disciplines contribute to the understanding of how our minds and brains work. The lecture series aims to reflect the broad range of perspectives on human and non-human cognition and provides an overview of approaches from a variety of disciplines, such as psychology, neurosciences, psychiatry, psycholinguistics, computer science, economics, philosophy, and others. It also provides exemplary insight into how the different disciplinary perspectives complement each other.


Topics of sessions

16.10. Norman Sieroka (Philosophy, Uni Bremen): A Philosophical Framing and (Pre-)History of Cognitive Science   

Cognition has long been the subject of human thought. Long before there were disciplines such as linguistics, psychology or even neuroscience, questions about cognition, and in particular the relationship between mental and physical states, were the subject of philosophy. This lecture will present some of these enduring questions along the history of modern philosophy. This is not because philosophy has already given convincing or even eternal answers, but because the early answers can serve as a kind of "toy model". From here, further historical developments can then be understood and current efforts combining different disciplines can be meaningfully classified.


23.10. Jan Rummel (Psychology): Experimental approaches to the study of human cognition

Experimental methods are used in cognitive psychology research to test hypotheses about the mechanisms underlying human cognitive functions. In this lecture, an introduction to this method will be provided and the basic concepts of experimental cognitive research will be discussed. Building on these insights, classic theories and their corresponding experimental findings from different areas of cognitive psychology (attention, memory) will be described.


30.10. Thomas Fuchs (Philosophy/Psychiatry): Mind, Brain, and the Body

Theories of embodiment are based on the assumption that cognitive processes are intrinsically embodied; in other words, conscious processes are crucially based on the circular interaction of brain, body and environment. As a collective term for the different approaches to embodiment, the term "4E Cognition" has become common, namely (1) embodied, (2) enactive (realized through action) (3) extended into the environment, (4) embedded in situations and societies. 
4E approaches critically distinguish themselves from the classical paradigm of cognitive science, in which cognition is seen as generating internal representations of the external world. From an embodied and enactive perspective, the function of the brain is not to construct mental representations, but to provide the organism with possibilities for embodied action in the world. Thus, consciousness becomes an overarching, dynamic process that cannot be limited to the brain, but equally involves the living body and its environment.


6.11. Sabina Pauen (Psychology): How to study the development of Mind and Brain (and the body) at a preverbal age

Long before we start to speak, we start to think. But how can we know what goes on in the head of an infant or young toddler if we cannot talk to them? This lecture will provide you with examples of intriguing infant studies addressing processes of visual perception, category formation, functional and causal thinking, problem solving, knowledge transfer, and creative thinking, using behavioral observations and EEG measures to explore young children's mind. You will learn how cognition develops during the first year of life and which role maturation of the brain and body, as well  experiences play in this context.


13.11. Andre Rupp (Neurology): Bridging the gap between perception and physiology: The neural correlates of pitch

Pitch (or ‚tone height‘) is a fundamental attribute of speech and music. However, there are important differences between the physical structure of a sound and the way in which we perceive it. This discrepancy is due to the fact that pitch information is subject to complex processing steps along the auditory pathway. Moreover, at the cortical level, the question arises how different aspects of pitch perception are combined and integrated across time. In this lecture, it will be shown which sounds evoke a pitch and how pitch information is represented at different stages of the auditory system. Based on this, we then turn to the neural signature of pitch contours (melodies), concurrent pitches (harmonies) and musical timbre. Further, we discuss how pitch processing can be studied experimentally, how it can be simulated in computer models, and how it can be utilized in the context of clinical questions.


20.11. Alexander Gutschalk (Neurology): Can we study the neural basis of consciousness in cognitive neuroscience?

Consciousness has long been considered inaccessible to scientific study, but research over the last 30 years has established a taxonomy for such research. This lecture will start with basic definitions of consciousness. Next, disorders of consciousness in clinical neurology will be discussed, and how they are related to specific lesions within the brain. We will then review how basic setups in cognitive neurosciences have been used to study the neural basis of consciousness and in particular conscious perception. Here we will see the difficulty dissociating processes underpinning phenomenal consciousness from other cognitive processes such as attention and decision making. This will lead us to different theoretical models of consciousness that have been proposed in the context of this research. Finally, we will address predictions that some of these models make for consciousness in other species, and more controversially, for artificial intelligence.


27.11. Christian Wolf (Psychiatry): Cognitive Neuroscience of auditory verbal hallucinations (15:00-16:30)

Auditory verbal hallucinations (AVH) are defined as a “sensory experience which occurs in the absence of external stimulation of the relevant sensory organ, but has the compelling sense of reality of a true perception”. The hallucinatory experience is typically not amenable to direct or voluntary control by the experiencer. Patients with various mental disorders experience AVH often as insulting, mortifying and threatening, with deleterious effects on affect, cognition and behavior. In this session, we will look at AVH from a cognitive systems neuroscience perspective. First, we will highlight research paradigms that used polymodal neuroimaging to establish neuromechanistic models of AVH in patients with psychotic disorders, particularly schizophrenia. Further, translational treatment options resulting from this particular line of research will be briefly presented. Eventually, we will move to a transdiagnostic perspective of AVH by looking into neural mechanisms of voice hearing in other mental disorders, such as bipolar and personality disorders.


4.12. Johannes Gerwien (Psycholinguistics): Real-time language processing – the psycholinguistic perspective

How do people extract the meaning of sentences, just as you do while reading this right now? And how do people transform thoughts into language while speaking? The lecture will provide a brief introduction into the main questions of psycholinguistic research and the methods that are most frequently used. I will focus on the topics 'language production' and 'language comprehension', and briefly touch upon the relation between language and non-verbal aspects of cognition.


11.12. Daniela Landert (English Studies): Language and cognition

The question of how language and cognition depend on each other has been a hotly debated topic in linguistics. Does the language that we acquire as our native language influence the way in which we think? Or does the way in which we think shape the structure of the language we speak? 
In this session, we will explore these and related questions from a number of different perspectives. First, we will review research on how spatial reference is encoded in language and how this correlates with the way in which speakers of a given language think about and remember spatial directions. We will then take a brief look at some cognitive restrictions of language production, based on the example of hesitation phenomena. The final part of the session will turn to how language supports cognition, and we will discuss how speakers use linguistic resources to negotiate shared mental models.


18.12. Anette Frank (Computational Linguistics): Natural Language Processing and Language Models – and how do they relate to cognition?

In this session we will look at methods for the computational modeling of language processing and what we know about how they relate to the processing of language in the human brain.   I will start with the notion of layers of representation of language in linguistics and in computational linguistics – which recently celebrated its 61st anniversary.
Computational linguistics has gained solid knowledge of how language and linguistic processing can be modeled with mathematical formalisms and algorithms, by statistical modeling and recently, by way of deep neural network models. But to what extent do these computational models reflect actual cognitive processes in the human brain when it processes language? This question becomes ever more intriguing with recent successes of large language models that seem to reach human-like capabilities in language processing.   I will summarize well-established findings from neuro-scientific research on how the processing of syntax and semantics of language are reflected in specific brain areas – findings that are in accordance with how syntax is modeled in formal language theory.   I will then discuss the notion of meaning in context, illustrating how neural models can learn such meaning through specific learning objectives that seem close to how humans process word meaning, and how such contextualized meanings are represented in neural word embeddings. Again, I summarize findings from the literature on how such representations are reflected in the human brain when it processes language.   Overall, I will illustrate basic principles of how neural models can learn human language(s) jointly with other modalities. Yet, with the ever-increasing size and capabilities of these models, it becomes more and more difficult to trace their internal processes, to judge their ability to reason and generalize, and how far they are from true language understanding.


8.1. Artur Andrzejak (Computer Science): Neuroscience-inspired Artificial Intelligence

Neuroscience-inspired artificial intelligence aims to develop AI systems that learn and act in ways similar to the human brain. This talk will discuss some recent advances in this field, starting with successful examples of neuroscience-inspired machine learning approaches, such as Vector Symbolic Architectures, Hierarchical Temporal Memory, and FlyHash. We also outline recent studies on the similarity of processing in transformers, the deep learning models at the core of Large Language Models, and the structure of brain activities recorded with fMRI during listening tasks. Finally, we discuss the fundamental differences between backpropagation and likely biological learning mechanisms, and explore alternative learning algorithms such as Geoffrey Hinton's forward-forward algorithm. We conclude by examining the implications of these findings for open problems in AI such as one-shot learning, model robustness, and explainability.


15.1. Christiane Schwieren (Economics): Cognition and Behavioral Economics

Behavioral Economics combines insights from psychology and economics, and relies to a large extent on experimental data. As the name says, it is mainly about behavior, sometimes making assumptions about cognitive processes, explicitly or implicitly. With concepts such as expectations, beliefs, or cognitive and non-cognitive skills, however, a large body of economics in fact deals with cognition, in a more or less systematic way. The lecture will give an overview of the various ways economists incorporate cognition in their empirical and theoretical work and the variety of methods used. It will end with a critical evaluation of "cognitive economic" research to date and discuss avenues for fruitful (interdisciplinary) research to deal with economic questions.


22.1. Filip Sadlo (Computer Science): Visual Data Analysis

In this lecture, we cover concepts and selected techniques in visual data analysis. We investigate approaches for data transformation, visual representation, and interactive exploration, and their role in visual sense-making.


29.1. Andreas Draguhn (Physiology): What does the brain tell us about the mind? On the nature (and limits) of neuroscientific contributions to cognitive science.

Neurosciences examine structures and functions of neural systems, including their role in cognitive processes (perception, memory formation and retrieval, decision making, social cognition and many others). In some sense, neuronal processes are causal for such cognitive processes, and claims have been made that Neurosciences explain our behavioral and ‘higher’ cognitive functions. It is, however, not entirely clear what ‘explaining’ means, and how we shall understand the relation between neuroscientific explanations and other, non-physical approaches, e.g. classical psychology, social sciences, pedagogics or law. We will discuss the role and importance of Neurosciences for our self-understanding as human beings, and their potential importance for other disciplines and perspectives. We will also address some major challenges related to the enormous complexity of the brain, the insufficient translation of knowledge into clinical practice, and the lacking consensus about the theoretical foundations of Neurosciences.



  • Artur Andrzejak (Computer Science)
  • Andreas Draguhn (Physiology)
  • Anette Frank (Computational Linguistics)
  • Thomas Fuchs (Philosophy/Psychiatry)
  • Johannes Gerwien (Psycholinguistics)
  • Alexander Gutschalk (Neurology)
  • Daniela Landert (English Studies)
  • Sabina Pauen (Psychology)
  • Jan Rummel (Psychology)
  • Andre Rupp (Neurology)
  • Filip Sadlo (Computer Science)
  • Christiane Schwieren (Economics)
  • Norman Sieroka (Philosophy)
  • Christian Wolf (Psychiatry)



Monday, 16:00 - 18:00


Link to Moodle (the password will be announced in the first session)