Dr. Anna Liley (Research engineer)
Bobby Tromm (Research engineer)
Axelle Piguet (Data scientist)
Eleni Moysiadou (Research assistant)
Loussineh Keshishian (M.Sc. thesis - Sorbonne University)
Pierre Boulet (M.Sc. thesis - CY-Tech)
Enia Ardid (M.Sc. intern - Paris-Saclay, Complutense)
Morgan Tarpenning (Undergraduate intern - Stanford University)
Martin Gazançon (Undergraduate intern - University College London)
Kathaleen Mallard (Undergraduate intern - Stanford University)
Naomi Checoury Taub (Undergraduate intern - Stanford University)
Nikolas is a tenured researcher (chargé de recherche) at the French National Institute of Health and Medical Research (INSERM) and team leader at the Paris Brain Institute (Institut du Cerveau - ICM), where he leads the Neuronal Circuits & Brain Dynamics team, supported by the European Research Council (ERC) Starting Grant.
Nikolas studied Applied Mathematics and Physics at the National Technical University of Athens.
He has always been fascinated by the complexity of the brain, so he decided to shift his focus to Neuroscience, and joined the Neurasmus Master’s program in Neuroscience in Berlin and Bordeaux, where he worked with Cyril Herry on the neuronal circuits of fear behavior.
During his Ph.D., he worked with Anton Sirota at the Ludwig Maximilian University of Munich, where he investigated the role of breathing in entraining neuronal dynamics and engaged in the large-scale characterization of the oscillatory architecture of memory circuits.
As an EMBO & MSCA postdoctoral fellow in the group of Andreas Lüthi at the Friedrich Miescher Institute for Biomedical Research (FMI) in Basel, and later as SNF Ambizione team leader at the FMI, he used a combination of modern neurotechnologies to unravel the role of neuromodulators in coordinating the activity of the amygdala during behavior.
In 2024, Nikolas joined the French National Institute of Health and Medical Research and the Paris Brain Institute, with the support of the ATIP-Avenir, Ambizione, and ERC Starting grants.
Irene studied Biotechnology at the University of Zaragoza. Her curiosity about how the brain processes information led her to pursue a Master's degree in Neuroscience at the Autonomous University of Madrid, where she became fascinated by the dialogue between neurons and astrocytes as a fundamental component of the modulation of plasticity in the brain.
Following this scientific interest, during her Master’s thesis she started working on astrocyte-neuron interactions with Gertrudis Perea at the Cajal Institute, CSIC.
For her Ph.D. she joined the emerging laboratory of Marta Navarrete, where she developed a project based on the implementation of novel molecular tools aimed at dissecting astrocytic functional heterogeneity in mice circuits of the nucleus accumbens.
Her research demonstrated the existence of functionally specific astrocyte subsets, defined as astrocytic ensembles, associated with behavior. During this period, Irene completed an EMBO-funded internship with Prof. George Malliaras at the University of Cambridge and joined the Young Researchers Committee of the Spanish Society of Neuroscience (SENC) as an active organizer of the SENC mentoring programme.
She joined our team in 2025.
Javier studied Biochemistry and Biomedical Sciences at the University of Valencia. Following an interest on understanding how circuits emerge from the orchestrated activity of neurons, he earned a Master’s degree in Neuroscience at the Universidad Miguel Hernández de Elche, researching texture discrimination under the supervision of Miguel Maravall.
He obtained his PhD at the Bioengineering Institute of Elche, in the Visual Neuroprosthetics lab led by Eduardo Fernández. Here, he recorded populations of neurons of rats’ visual cortex and explored the temporal structure of their activity in the context of interval timing.
He then joined the group of Ramón Reig at the Instituto de Neurociencias, where he was lately awarded a Margarita Salas fellowship. He investigated the slow wave activity to understand the communication of cortical and striatal circuits, using a combination of data science and computational modelling techniques.
In 2025, he joined the Neuronal Circuits & Brain Dynamics team led by Nikolas Karalis at the Paris Brain Institute.
Pierre is a research engineer in our team. He holds a Master’s degree in Cognitive Psychology from Université Paris-Cité, where he graduated in 2024. During his master’s program, Pierre developed a strong interest in working at the intersection of cognitive psychology, neuroscience, and computational methods, which led him to pursue a research internship in Daniel Bendor’s laboratory at University College London (UCL). There, he immersed himself in the fascinating world of systems neuroscience, investigating the mechanisms underlying representational drift in the hippocampus.
After completing his Master’s degree, Pierre joined Nikolas Karalis’ team at the Paris Brain Institute, where he is currently studying how spatial information is replayed across different subfields of the hippocampus. His research combines electrophysiological data analysis with virtual reality paradigms to uncover the neural dynamics underlying memory processes.
Pierre is deeply fascinated by the complex interplay of diverse neuronal networks and how their coordinated activity enables sophisticated information representation, processing, and memorization. Outside the lab, Pierre enjoys exploring personal projects, such as visualizing complex human networks and emotional interactions.
Pierre studied applied mathematics and computer science in CY-Tech (ex EISTI), Cergy, France.
He has always been fascinated by the human brain’s capacity to exhibit a wide variety of complex behaviors, ranging from emotions to learning and creativity.
These interests lead him to our lab where he first joined as an intern then got integrated as a research engineer.
His work consists in implementing different machine learning and signal processing tools in order to understand how different combinations of neuromodulation levels can dynamically change the computational properties of neural circuits.