During our festive Christmas celebration, we reflected on an exciting year of scientific discoveries. The evening was filled with punch, nice food, stories, and papersongs. Live music was, of course, a must-have addition to the party.
The Optophysiology Lab wishes you a Merry Christmas and a good start to the year 2025.
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.
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.
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.
How do brains—biological or artificial—respond and adapt to an ever-changing environment? In a recent meeting, experts from various fields of neuroscience and artificial intelligence met to discuss internal world models in brains and machines, arguing for an interdisciplinary approach to gain deeper insights into the underlying mechanisms.
In this study, we introduce the architecture, the integrated building blocks, and the post-CMOS processes required to realize a NeuroBus , and we characterize the prototyped direct digitizing neural recorder front-end as well as polyimide-based ECoG brain interface.
In this study, we introduce a novel class of Latent (Markov) Variable Inverse Q-learning algorithms for characterizing animal behavior during complex decision-making tasks.
To study behavioral flexibility in freely-moving mice, we developed a versatile, low-cost, open-source behavioral setup, called FreiBox, allowing us to investigate the neuronal correlates of licking-based behavioral flexibility.
This study proposes an unitary concept that, leveraging a cross-species definition of prefrontal regions, explains how prefrontal ensembles adaptively regulate and efficiently coordinate multiple processes in distinct cognitive behaviors.
This study provides mechanistic insights into the interactions between the rostral forelimb area (RFA) and the caudal forelimb area (CFA). Specifically, we provide evidence for a differential impact of RFA on CFA depending on the task phase and the targeted CFA layers.