Embodied Cognition Group

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About us


As part of the CRC 1528 consortium, the "Embodied Cognition Group", headed by Dr. Neda Shahidi, was established as an early career research group. We aim to understand the cortical basis of ecologically relevant decision-making. In particular, examining the dynamics of neural populations, involved in planning goal-directed behaviors, as well as understanding how interactions between mind and body impact the quality of their decisions. Our group is located at the University and conducts research in close collaboration with the Cognitive Neuroscience Lab at the German Primate Center.

Research

Computational Models of naturalistic brain and body

For decades, the field of neuroscience has greatly benefited from conducting experiments in meticulously controlled environments. This is because the brain's interaction with the outside world is highly complex and the effect of one environmental variability is likely to be confounded by many others. Therefore, classically, neuroscientists probe the brain in repeated and carefully timed conditions, allowing a few variables at a time. Increasing the number of variables, one needs an exponentially higher amount of data to maintain the statistical power, a concept known as the curse of dimensionality. With recent advances in data-driven modeling and high-throughput computing, processing large amount of high-dimensional data in a reasonable time is feasible. Additionally, recording many channels of brain and body activity allows us to study neural correlates of ecologically valid behavior. As the animals' decision process continuously unfolds, we aim to understand the aspects of the decision-making taking place, such as when to decide, where the animal is, and which option was chosen. We identify computational components in cortical areas that represent this process within the high-dimensional space of the activities of anatomical units, a.k.a. spiking neurons. Findings from this research will bring us closer to understanding successes and failures of decision making in real-life scenarios.


Ongoing projects

  • “Predicting the time of choice in macaques in a dyadic foraging task with a human partner”; with Zahra Yousefi (Postdoctoral Researcher at the University of Göttingen)
  • “Predicting Lemur’s social foraging success using recurrent neural networks”; Numa Koudsie (M.Sc. program in physics, University of Göttingen), in collaboration with Claudia Fichtel and Fabian Sinz

  • Related publications

  • Shahidi , Ahmed, Badayeya, Lacal, and Gail (2024) "Free-foraging macaques value information within ambiguous terrains" bioRxiv, doi: 10.1101/2024.10.11.617791
  • Shahidi, Parajuli, Franch, Schrater, Wright, Pitkow, and Dragoi (2024) “Population Coding of Strategic Variables during Foraging in Freely-Moving Macaques.” Nature Neuroscience 27, 772-781doi: 10.1038/s41593-024-01575-w
  • Milton, Shahidi, and Dragoi (2020) “Dynamic States of Population Activity in Prefrontal Cortical Networks of Freely-Moving Macaque."Nature Communications 11, 1948 doi: 10.1038/s41467-020-15803-x


  • Cortical representations of vigilance and active sampling

    Surviving in the wild requires that primates stay aware of their surroundings while focusing on goal-directed activities. We aim to identify the state of vigilance, defined as the degree to which an individual seeks information from their surroundings in macaques and humans by monitoring their bodily and eye movements in controlled naturalistic environments. In macaques, we investigate how the natural states of vigilance are represented in frontal and parietal cortical circuits and influence foraging behavior. We employ a range of computational techniques to understand the richness and complexity of human and macaque behavior in similar scenarios while employing high-throughput electrophysiology to investigate the high-dimensional cortical activity. Findings from this project will help explain the representation of the inner state of vigilance in overt behavior and cortical activity and its potential influence on natural variability in goal-directed behavior.


    Ongoing projects

  • "Neural correlates of active sampling and vigilance in macaques”; Sara Ahmadi Majd (University of Göttingen), in collaboration with Julia Ostner and Oliver Schülke
  • “Predicting macaques’ choices in a dyadic foraging task with a human partner”, with Kacper Ksiezak (M.Sc. program in data science, University of Göttingen), in collaboration with Fabian Sinz

  • Related publication

  • Ksiezak, Burghardt, Shahidi, Gail, and Sinz (2023) "Predicting choices in a dyadic foraging task using gated recurrent networks", extended abstract for Complex Networks 2023 544-549


  • The role of cortico-cortical communication in cognition and perception

    Complex decision-making requires orchestrated activity across many brain areas that are representing external or internal information. Using state-of-the-art electrophysiological devices, we simultaneously probe multiple brain areas, each at many sites. We identify precisely timed coordinated activity across recorded areas to identify their role in decision making.


    Ongoing project

  • “Investigating Inter-area covariance in primates’ frontoparietal network via latent space modelling”; René Burghardt (Ph.D. program in data science, University of Göttingen), in collaboration with Fabian Sinz and Alexander Gail

  • Related publication

  • Shahidi, Andrei, Hu, and Dragoi (2019) “High-Order Coordination of Cortical Spiking Activity Modulates Perceptual Accuracy.” Nature Neuroscience 22, 1148-1158 doi: 10.1038/s41593-019-0406-3


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    Project Team

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    Neda Shahidi

    (Group leader)
    University of Göttingen
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    Neda Shahidi

    Neda Shahidi

    (Group leader)
    University of Göttingen
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    Neda Shahidi

    Zahra Yousefi Darani

    (Postdoctoral Researcher)
    University of Göttingen
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    Zahra Yousefi Darani

    Zahra Yousefi Darani

    Zahra is fascinated by the underlying algorithms the brain employs to generate behavior, make decisions, and use of mathematical models to explain naturalistic behavior. She is now working on understanding how naturalistic decisions are made and when they occur. She earned her bachelor's degree in biology and her master's degree in physiology from the University of Isfahan, Iran. Zahra pursued a PhD in cognitive neuroscience at SISSA in Trieste, Italy, then began her first postdoctoral position at DPZ and her second position and the University of Göttingen.

    Sara Ahmadi Majd

    (PhD Student)
    University of Göttingen
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    Sara Ahmadi Majd

    Sara Ahmadi Majd

    Sara is passionate about the intersection of artificial intelligence and neuroscience, using AI to improve neuroscience research while drawing inspiration from neuroscience to develop AI algorithms. Her previous study investigated these integrative techniques. She has a bachelor's degree in physics and a master's degree in cognitive sciences from the University of Tehran. She is now working on her PhD at the University of Göttingen, where her project investigates the neural correlates of vigilance during decision-making in free-moving macaques. She is fascinated by the mechanics that drive decision-making, especially in uncertain situations.

    Kacper Ksiezak

    (Master Student)
    University of Göttingen
    Kacper Ksiezak

    Kacper Ksiezak

    (Master Student)
    University of Göttingen
    Kacper Ksiezak

    Numa Koudsie

    (Research Assistant)
    University of Göttingen
    Numa Koudsie

    Numa Koudsie

    Numa's fields of research interest are Complex Systems in biophysics and climate physics, multi-particle systems in molecular and planetary systems, symplectic geometry, application of information theory in neuroscience and social networks. He holds a Bachelor’s degree in Physics and is currently pursuing a Master’s in Physics with a focus on theoretical physics and complex systems. Numa also works as a full-time teaching assistant in Physics, Mathematics, and Informatics at the International School Reinsdorf Carl Hahn GmbH.

    Alumni

    Renè Burghardt

    Master student
    University of Göttingen
    Rene Burghardt

    Renè Burghardt

    René's research interests lie at the intersection of artificial intelligence and neuroscience, focusing on understanding the mammalian brain through computational approaches. With a B.Sc. in Computer Science from Humboldt University in Berlin and an M.Sc. in Applied Data Science specializing in computational neuroscience from the University of Göttingen, he is now a PhD candidate in the Neuronal Intelligence group of Fabian Sinz. By leveraging AI, particularly foundation models, his work seeks to unravel the principles of neural computation and the mechanisms of inter-area communication within the brain.

    Sophie Atzpodien

    Research Assistant

    Sophie Atzpodien

    Research Assistant

    Hanah Lüschen

    Research Assistant

    Hanah Lüschen

    Research Assistant



    Head of the Group:

    Dr. Neda Shahidi

    Head of the Early Career Group

    SFB 1528 - Cognition of Interaction

    Kellnerweg 4,

    37077 Göttingen

    Tel.: +49-551-3851-307

    Contact