Richard H.R. Hahnloser

INI, ETH Zurich, Zürich, Zürich, Switzerland 
computational neuroscience; birdsong electrophysiology
"Richard Hahnloser"
Mean distance: 13.57 (cluster 17)
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Zai AT, Cavé-Lopez S, Rolland M, et al. (2020) Sensory substitution reveals a manipulation bias. Nature Communications. 11: 5940
Düring DN, Dittrich F, Rocha MD, et al. (2020) Fast Retrograde Access to Projection Neuron Circuits Underlying Vocal Learning in Songbirds. Cell Reports. 33: 108364
Yamahachi H, Zai AT, Tachibana RO, et al. (2020) Undirected singing rate as a non-invasive tool for welfare monitoring in isolated male zebra finches. Plos One. 15: e0236333
Kollmorgen S, Hahnloser RHR, Mante V. (2020) Nearest neighbours reveal fast and slow components of motor learning. Nature. 577: 526-530
Daliparthi VK, Tachibana RO, Cooper BG, et al. (2019) Transitioning between preparatory and precisely sequenced neuronal activity in production of a skilled behavior. Elife. 8
Rocha MD, Düring DN, Bethge P, et al. (2019) Tissue Clearing and Light Sheet Microscopy: Imaging the Unsectioned Adult Zebra Finch Brain at Cellular Resolution. Frontiers in Neuroanatomy. 13: 13
Düring DN, Rocha MD, Dittrich F, et al. (2019) Expansion Light Sheet Microscopy Resolves Subcellular Structures in Large Portions of the Songbird Brain. Frontiers in Neuroanatomy. 13: 2
Narula G, Herbst JA, Rychen J, et al. (2018) Learning auditory discriminations from observation is efficient but less robust than learning from experience. Nature Communications. 9: 3218
Fattinger S, de Beukelaar TT, Ruddy KL, et al. (2018) Author Correction: Deep sleep maintains learning efficiency of the human brain. Nature Communications. 9: 16182
Lipkind D, Zai AT, Hanuschkin A, et al. (2017) Songbirds work around computational complexity by learning song vocabulary independently of sequence. Nature Communications. 8: 1247
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