MindTalks

...gemeinschaftlich organisiert von:

Dr. Udo Ernst (Fachbereich 1, Computational Neurophysics Lab)

Prof. Dr. Olivia Masseck (Fachbereich 2, Synthetic Biology)

Prof. Dr. Tanja Schultz (Fachbereich 3, Cognitive Systems Lab)

18.11.2024 | 16:15-17:30 

Cognium, Hochschulring 18, Room 2030

Reconciling spatial representations in the hippocampus with episodic memory

Prof. Dr. Sen Cheng

A fundamental question in neuroscience is why the hippocampus, critical for episodic memory in humans, primarily exhibits spatial representations like place cells in many species. This talk proposes that spatial coding emerges naturally when episodic memory systems are engaged in navigation tasks. We demonstrate this using a novel computational model based on memory-augmented neural networks and reinforcement learning. The model autonomously learns to store and retrieve information from an external memory buffer and shows remarkable flexibility: When solving visual tasks, it develops representations of categories and visual features, but when navigating a simulated maze using only visual inputs, it spontaneously develops population-level representations that capture the maze's 2D spatial structure. These findings suggest that spatial representations in the hippocampus are not primary, but rather emerge as a consequence of using episodic memory systems to solve spatial problems, reconciling two major lines of research on the hippocampus that have largely remained separate until now.

09.12.2024 | 16:00-17:30 

Haus der Wissenschaft, Sandstraße 4/5, Olbers-Saal

Apollos Gabe: Neurobiologische und Neuropsychologische Grundlagen des Musizierens

Prof. em. Dr. med. Eckart Altenmüller

Singen und Instrumentalmusik spielen seit Jahrzehntausenden in allen Kulturen eine wichtige Rolle: Mit Musik werden mächtige Emotionen erzeugt, soziale Bindungen vertieft und organisiert und sogar therapeutische Ziele erreicht. Musik vereinigt magische Elemente, uralte kollektive Erfahrungen und höchst lebendige Eigenschaften voll neuer Klänge. Unsere Emotionen beim Hören von Musik hängen stark von Lernprozessen ab und können durch Wissen und Kennen vertieft werden. Starke Emotionen, die zu einem „Gänsehauterlebnis“ führen, treten z.B. häufiger auf, wenn musikalische Strukturparameter erkannt werden. Besonders wirkungsvoll sind dabei überraschende Momente mit Verletzungen der musikalischen Erwartung, aber auch Informationen zum Hintergrund einer Komposition können die Wirkung vertiefen. 

In dem Vortrag werden evolutionäre, musikpsychologische und hirnphysiologische Befunde zu den Wirkungen des Musizierens auf Kinder, Senioren und Menschen mit neurologischen Erkrankungen vorgestellt. Die hirnphysiologischen Grundlagen des Musizierens werden an Beispielen erläutert und ein Bezug zur Entwicklungsgeschichte des Menschen und die Rolle der Musik im “Überlebenskampf” hergestellt. Sicher könnten wir auch ohne Musik überleben, aber eben lange nicht so gut! 

13.01.2025 | 16:15 - 17:30  

Cognium, Hochschulring 18, Room 2030

Language representations in humans and machines

Prof. Dr. Fatma Deniz

Natural language is strongly context-dependent and can be perceived through different modalities. For example, humans can easily comprehend the meaning of language presented through auditory speech and written text. Hence, to understand how language is represented in the human brain there is a necessity to map the different linguistic and non-linguistic information perceived under different modalities across the cerebral cortex. In my talk, I will introduce a computational approach that aims to understand of how the human brain processes linguistic information across modalities by mapping different levels of information to human brain responses. This approach relies on observing the human brain performing tasks in ecologically valid settings, building predictive models of brain responses acquired using functional MRI, and creating generalizable and reproducible results. Using representations derived from neural natural language processing (NLP) systems, I present models of brain responses recorded with functional MRI while human participants comprehend natural narrative stories. I then show how these models lead to a better understanding of language representations in the brain across modalities and languages.

20.01.2025 | 17:00 - 18:30  

Cognium, Hochschulring 18, Room 2030

Flexible behavior through adaptive brain network dynamics

Prof. Dr. Tobias H. Donner

Cognitive behavior rapidly adapts to changing environmental contexts. This flexibility distinguishes cognitive behavior from reflexes. I propose that this flexibility results from the rapid reconfiguration of distributed cortical networks that implement the transformations required by a given task and context. This reconfiguration is enabled by rapid plasticity mechanisms that are controlled by neuromodulators released from the brainstem. To support these claims, I will present human MEG and fMRI experiments, in which we systematically manipulate context variables, such as task rules or environmental volatility. We quantify the resulting changes in content-specific neural interactions (e.g., selective for sensory evidence or behavioral choice), across a large set of cortical regions. We relate these cortical interactions to the dynamics of (proxies of) brainstem modulatory activity. This approach reveals that the structure of cortical interactions changes in a context-dependent manner. These changes are predicted by brainstem modulatory activity, which, in turn, tracks hidden changes in the environment. Preliminary results indicate that the cognitive recruitment of modulatory brainstem systems is impaired in individuals with a high risk of developing psychosis. Our results open a new window on the dynamic brainstem sculpting of large-scale cortical networks for flexible cognitive behavior. I speculate that this sculpting goes awry in many mental disorders. 

27.01.2025 | 16:15 - 17:30  

Cognium, Hochschulring 18, Room 2030

Neurodynamics during quasi-realistic social decision making - Evidence from fMRI-informed multi-channel EEG analyses

Prof. Dr. Thorsten Fehr

There is a variety of well-thought-out models explaining important aspects of complex social decision behaviour in humans. These models address biophysiological, genetical, contextual, socialisatory, internal trait and state conditions, and other potential modulators of social development, current status, and behavioural predictors. There is also some neuroscientific evidence that substantiate several model assumptions regarding the underlying functional neuroanatomy. The here presented series of work focused on both traditional approaches, such as topographical EEG power and ERP analyses at signal space level, and advanced approaches, such as the exploration of state and trait-related dynamics of source space data at neuronal generator level. As expected, EEG signal space data showed topographical differences between distinguishable emotional context entities during social decision making (i.e., neutral, social positive, and reactive aggressive interaction scenarios processed from a first person perspective) and behaviour (i.e., withdraw from the interaction or approach it). Early, middle, and late latency ERPs in different phases of the decision process (event- and response-locked) reflected widely distributed task condition related differences distributed over the scalp. Analogously, oscillatory brain topographies revealed task condition related differences during the decision generation phase in different oscillatory frequency ranges. To get deeper insights into the characteristics of the underlying spatio-temporal brain dynamics, a recently developed social decision source model was applied on band-pass filtered single trial data captured from the decision generation trial phases. Ad hoc appliance (seeding) of the source model revealed high amounts of variance explanation (> 95 percent) in all of the seven separately band-pass-filtered frequency ranges defined between 1.5 and 35 Hz. Quantification of emotion-category related follow-up characteristics (i.e., source dynamics) of the respectively seeded neural generator network (source model) and its relationships to different external variables (e.g., different aggression trait measures) will be shown and discussed with the audience.

Die Vorträge werden größtenteils auf Englisch gehalten (siehe Titel).

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