https://www.uke.de/english/physicians-and-scientists/wissenschaftlerprofilseite_cristina_becchio.html

Keywords:
kinematic coding; action; mindreading; social transmission of information

Research Theme:
Our lab explores how everyday movements—like reaching for an object—reveal what is on our minds: what we want, what we fear, what we expect, and even what we believe. Using experimental and computational tools, we examine how information about mental states is encoded, read out, transmitted and transformed during naturalistic interaction. By uncovering the principles of this transmission, we aim to bridge social cognition and action.

https://www.inf.uni-hamburg.de/en/inst/ab/lt/people/chris-biemann.html

Keywords:
computational linguistics, neural representation learning, large language-vision models

Research Theme:
We research on all aspects of natural language processing, with a focus on low-resource languages and on applications/demonstrators. Topics range from dataset creation for benchmarking for multimodal data over foundational research in representation learning and adaptation to productive use of AI components in user-facing systems such as retrieval-augmented-generation systems and information access to large corpora. In computational neuroscience, we have explored the use of corpus data for modelling and predicting behavioral signals, as well as using behavioral data for enhancing explanation and transparency of large language models.

https://sites.google.com/view/buechellab/christian-b%C3%BCchel

keywords:
Pain, learning, reinforcement learning, neuropharmacology

Research Theme:
The BuechelLab focuses on understanding the mechanisms underlying pain perception and modulation using computational and experimental approaches. A decade ago, we developed a computational Bayesian pain model that can explain how expectation, control, and other contextual factors can influence the experience of pain. Beyond this, we investigate Pavlovian learning mechanisms in the context of pain to understand how associative processes shape pain responses. Our research also explores the neuropharmacological underpinnings of pain and learning by integrating experimental data with computational models.

http://www.csi-lab.de/

https://tobiasdonner.net/

Keywords:
Decision-making, Distributed cognition, Brain network dynamics, Neuromodulation

Research Theme:
Work in my laboratory aims to the understand the internal state dependence of distributed cognitive computations in the human brain, with a focus on inference and decision-making We build explicit bridges between computational, algorithmic, and implementation levels of analysis of brain function. We combine computational modelling of behavior with assessment of the underlying cortical population codes and internal brain states, such as arousal or prior expectations. We complement these assessments with pharmacological manipulations of specific neurotransmitter systems. This integrative approach has provided insights into the neurobiological foundations of puzzling aspects of human cognition including the sources of behavioral variability or pervasive violations of rationality in human decision-making. The approach is also shedding light on the aberrations of brain states and cognition in brain disorders.

Keywords:
Cognitive neuroscience, systems neuroscience, neurophysiology, oscillations, connectivity

Research Theme:
The central focus of my research is the dynamics of brain networks which I address at multiple spatial and temporal scales using neurophysiological approaches in humans and animals. My key goal is to relate neural dynamics (particularly oscillations) and functional coupling across neural populations to sensorimotor and cognitive functions. To this end, I study the temporal dynamics of neural activity and neural interactions in the context of sensory processing, multisensory and sensorimotor integration, emotion, decision making, attention and consciousness.

https://kaysonfakhar.com/

http://www.inims.de/

Keywords:
Neuroimmunology, Neurodegeneration, Systems biology, Multiple sclerosis

Research Theme:
We seek to better understand the development and progression of neuroimmunological and neuroinfectious diseases with particular emphasis on multiple sclerosis to translate molecular findings into drug treatment and improve clinical care. In order to achieve this goal, we systematically study immunology, neurobiology and patient care using a wide methodological spectrum.

https://www.uke.de/english/physicians-and-scientists/arztprofilseite_j%C3%BCrgen_gallinat.html

http://uhh.de/inf-sp

Keywords:
Speech Processing, Audio-visual, Enhancement, Source Separation, Diffusion Models

Research Theme:
Prof. Dr.-Ing. Timo Gerkmann’s research focuses on speech and audio signal processing, with special emphasis on speech enhancement and source separation. He develops algorithms that improve the quality and intelligibility of speech signals in noisy environments, benefiting applications like hearing aids, voice-controlled systems, and telecommunications. His work combines statistical signal processing and machine learning methods. He is also active in audio-visual fusion and computational auditory scene analysis.

http://glascherlab.org/

keywords:
Theory of Mind, Social decision-making, cooperation and competition, belief updating, cognitive modeling,EEG hyperscanning, fMRI

Research Theme:
The central focus of my research is the question how we build mental models of the world and of other people (i.e. Theory of Mind), how we communicate with them how we use these models in predicting others’ actions in different interactional contexts (e.g. cooperation and competition). We follow a neurocomputational approach by developing cognitive models of the behavioral response and then utilizing these models in the analysis of the neural signals recorded using EEG hyperscanning or fMRI.

https://www.psy.uni-hamburg.de/en/arbeitsbereiche/kognitive-modellierung-und-neurowissenschaften-des-entscheidens/personen/sebastian-gluth.html

Keywords:
cognitive modeling, decision making, reinforcement learning, attention, neuroimaging

Research Theme:
The focus of the Cognitive Modelling & Decision Neuroscience Lab in Hamburg are the research areas of judgement and decision making, attention, memory and reward-based learning. By using mathematical models of cognition (cognitive modeling), recordings of gaze patterns (eye tracking), and neuroscientific methods (e.g., fMRI, EEG), we seek to understand how humans make decisions, how they improve decisions by learning, and how this is influenced by attention and memory.

https://www.uke.de/allgemein/arztprofile-und-wissenschaftlerprofile/wissenschaftlerprofilseite_claus_hilgetag.html

Keywords:
Network neuroscience, Neuro-inspired AI, Human brain connectivity and architecture, General models of normal and perturbed neural activity, Causal inference of brain functions

Research Theme:
Our main research interest is the understanding of fundamental organizational principles of brain connectivity, activity and function by means of computational analysis and modeling, and the translation of our findings into clinical applications. Combining integrative approaches of network neuroscience with expertise in advanced biomedical signal processing, our interdisciplinary research team and their projects link the fields of neuroscience and biology with computer science and AI, physics, and neurology. Examples of ongoing projects are the modelling of the development, activity and plasticity of diverse neural networks, the exploration of their functions in the context of reservoir computing paradigms, an understanding of causal interactions in brain networks, as well as investigations of network dysfunction in different neurological conditions.

https://www.psy.uni-hamburg.de/arbeitsbereiche/klinische-psychologie-und-psychotherapie/personen/lincoln-tania.html

Keywords:
mechanisms of delusion formation and change, belief updating, intervention

Research Theme:
The aim of my research is to understand how distorted beliefs in the context of mental health problems occur, why they are maintained and how they can be changed. My main interest is in delusions, a severe form of distorted, maladaptive beliefs. To study the underlying cognitive mechanisms of delusion formation and maintenance, I combine experimental, neurophysiological and computational modelling approaches with ambulatory assessments of autonomic and questionnaire data. I use the knowledge gained from these approaches to improve interventions for people with delusions.

https://www.uke.de/english/physicians-and-scientists/mitarbeiterprofilseite_stefano_panzeri.html

Keywords:
neural coding, neural network modeling, sensation and decision-making

Research Theme:
Our laboratory develops computational tools (analysis methods and models) aimed at understanding how the interactions between neurons and among networks of neurons shape brain functions such as sensation and decision making and produce naturalistic behaviors.

https://www.medicalschool-hamburg.de/ueber-uns/team/team-fakultaet-medizin/oliver-schmitt/
https://neuroviisas.med.uni-rostock.de/neuroviisas.shtml

keywords:
Connectonomics, computational modeling, neuroanatomical mapping, neural plasticity, structure-function relationships

Research Theme:
Research of the Schmitt team integrates neuroanatomy, connectomics, and computational neuroscience to elucidate the structure-function relationships within the brain. His lab employs advanced neuroimaging, modeling, and simulation techniques to explore hierarchical brain organization, connectivity changes in disease states such as stroke and multiple sclerosis, and mechanisms of neural plasticity and compensation. The work emphasizes the development and use of detailed connectome databases and dynamic models to predict functional impairments and recovery, supporting both basic neuroscience and translational applications.

https://schucklab.gitlab.io

Keywords:
Replay, Task representations, Neural Networks, fMRI

Research Theme:
Our lab investigates the cognitive, neural, and computational mechanisms underlying human learning, using fMRI alongside behavioral, eye-tracking, and computational modeling approaches. To his end, we have developed analytical tools that allow us to track fast sequential replay in humans using fMRI. Our work demonstrates that learning continues beyond the immediate experience, including during rest and sleep, via hippocampal and cortical replay. We also investigate how internal cognitive maps in the brain and neural networks support generalization and interact with value learning systems and how learning differs in conditions like anxiety and aging.

https://www.psy.uni-hamburg.de/arbeitsbereiche/kognitionspsychologie.html

Keywords:
memory transformation, adaptive memory, instrumental control, stress

Research Theme:
At the intersection of experimental psychology, neuroscience, and endocrinology, our lab focuses on three core questions: (i) how emotion and stress shape cognition; (ii) how memories evolve over time and adapt to new information; and (iii) how actions and decisions can be both flexible and efficient. To address these questions, we combine behavioral experiments with neuroimaging, brain stimulation, pharmacological interventions, and cognitive modeling.