Optophysiology Lab

led by Prof. Ilka Diester

Our Research

The ability to move is a fundamental feature of most animals which allows them to actively interact with our environment. We are investigating the underlying neural mechanisms and circuits of this ability. We do so with electrophysiological recordings and optogenetic manipulations combined with behavioral analysis. We look into the local processing of movement preparation and generation in the motor cortex as well as higher order structures, e.g. prefrontal cortex.

The goal is to create a better understanding of how neural subpopulations and pathways within and across brain areas influence motor behavior. In order to address these scientific aims we are constantly working on improving the existing techniques. We currently focus on the design of new optoelectronic probes and targeting strategies. Apart from advancing our basic knowledge about the neural mechanisms of movements, our results might help improving the design of new prosthetic devices and understanding of disorders in which the normal production of movements is disrupted.

Current News

New Article Published in Animals

Ensuring proper pain relief in laboratory animals is vital for their welfare and for obtaining accurate scientific results. We retrospectively examined the effects of carprofen as post-operative analgesia in Sprague Dawley rats following stereotactic surgery.

New Article Published in bioRxiv

In this study, we employed an action-preparation task in rats, combined with bidirectional optogenetic interventions, opto-fMRI, single unit electrophysiology and local field potential synchrony measurements across PFC subsections. Our findings support a clear and simple model of action inhibition within the prefrontal network.

New Article Published in Transactions on Machine Learning Research

In this paper we propose the novel class of hierarchical inverse Q-learning (HIQL) algorithms, which extend the fixed-reward inverse Q-learning (IQL) framework from Kalweit et al. (2020) to solve multiintention IRL problems. We applied HIQL in a real mice decision-making dataset from a dynamic two-armed bandit task (De La Crompe et al., 2023), and mathematically characterized exploitation and exploration behavior of animals during value-based decision-making.

Open Positions

Internal World Models: How does AI view the world
Merry Christmas from the Robot Learning Lab – 2023
FreiDOG Dance @ BrainWorlds Freiburg-Oxford Workshop
IMBIT Opening
Make thinking visible
Research Unit 5159

Farewell to Carola Haas who retired recently from her professorship. Carola, your years on the BrainLinks-BrainTools steering board brought vision, dedication, and impact. Thank you for everything—your legacy will continue to inspire us! @IMBIT_UniFR @UniFreiburg @Uniklinik_Fr

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