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Published in The Journal of the Acoustical Society of America, 2020
An auditory model combining a periphery model with a binaural excitatory-inhibitory interaction stage to account for lateralization of high-frequency sounds across over 1000 amplitude-modulated stimuli
Recommended citation: Klug, J., Schmors, L., Ashida, G., & Dietz, M. (2020). "Neural rate difference model can account for lateralization of high-frequency stimuli." The Journal of the Acoustical Society of America, 148(2), 678–691.
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Published in Molecular Psychiatry, 2023
Combining two-photon calcium imaging, electrophysiology and neurotransmitter biosensors to reveal how lateral habenula neuronal ensembles encode cue-punishment associations through opposing excitatory and inhibitory plasticity
Recommended citation: Congiu, M., Mondoloni, S., Zouridis, I. S., Schmors, L., Lecca, S., Lalive, A. L., Ginggen, K., Deng, F., Berens, P., Paolicelli, R. C., Li, Y., Burgalossi, A., & Mameli, M. (2023). "Plasticity of neuronal dynamics in the lateral habenula for cue-punishment associative learning." Molecular Psychiatry, 28, 5118–5127.
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Published in European Journal of Neuroscience, 2024
In vivo characterization of lateral habenula neuronal diversity and their role in aversion processing and behavioral state modulation
Recommended citation: Zouridis, I. S., Schmors, L., Lecca, S., Congiu, M., Mameli, M., Berens, P., Monteiro, F., Preston-Ferrer, P., & Burgalossi, A. (2024). "Aversion Encoding and Behavioral State Modulation of Physiologically Defined Cell Types in the Lateral Habenula." European Journal of Neuroscience.
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Published in iScience, 2025
Quantitative analysis of how corticothalamic feedback and behavioral state modulate visual thalamus responses depending on stimulus context
Recommended citation: Schmors, L., Kotkat, A. H., Bauer, Y., Huang, Z., Crombie, D., Meyerolbersleben, L. S., Sokoloski, S., Berens, P., & Busse, L. (2025). "Effects of corticothalamic feedback depend on visual responsiveness and stimulus type." iScience, 28(6), 112481.
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Published in The Thirty-ninth Annual Conference on Neural Information Processing Systems (NeurIPS), 2025
A novel framework for visualizing neural time-series data using contrastive learning
Recommended citation: Schmors, L., et al. (2025). "TRACE: Time-series Representation through Averaging and Contrastive Embeddings." NeurIPS 2025.
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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