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Items: 45

1.

Tissue Clearing and Light Sheet Microscopy: Imaging the Unsectioned Adult Zebra Finch Brain at Cellular Resolution.

Rocha MD, Düring DN, Bethge P, Voigt FF, Hildebrand S, Helmchen F, Pfeifer A, Hahnloser RHR, Gahr M.

Front Neuroanat. 2019 Feb 14;13:13. doi: 10.3389/fnana.2019.00013. eCollection 2019.

2.

Expansion Light Sheet Microscopy Resolves Subcellular Structures in Large Portions of the Songbird Brain.

Düring DN, Rocha MD, Dittrich F, Gahr M, Hahnloser RHR.

Front Neuroanat. 2019 Jan 31;13:2. doi: 10.3389/fnana.2019.00002. eCollection 2019.

3.

Excitatory and inhibitory synapse reorganization immediately after critical sensory experience in a vocal learner.

Huang Z, Khaled HG, Kirschmann M, Gobes SM, Hahnloser RH.

Elife. 2018 Oct 25;7. pii: e37571. doi: 10.7554/eLife.37571.

4.

Learning auditory discriminations from observation is efficient but less robust than learning from experience.

Narula G, Herbst JA, Rychen J, Hahnloser RHR.

Nat Commun. 2018 Aug 13;9(1):3218. doi: 10.1038/s41467-018-05422-y.

5.

Author Correction: Deep sleep maintains learning efficiency of the human brain.

Fattinger S, de Beukelaar TT, Ruddy KL, Volk C, Heyse NC, Herbst JA, Hahnloser RHR, Wenderoth N, Huber R.

Nat Commun. 2018 May 25;9:16182. doi: 10.1038/ncomms16182.

6.

Songbirds work around computational complexity by learning song vocabulary independently of sequence.

Lipkind D, Zai AT, Hanuschkin A, Marcus GF, Tchernichovski O, Hahnloser RHR.

Nat Commun. 2017 Nov 1;8(1):1247. doi: 10.1038/s41467-017-01436-0.

7.

Deep sleep maintains learning efficiency of the human brain.

Fattinger S, de Beukelaar TT, Ruddy KL, Volk C, Heyse NC, Herbst JA, Hahnloser RHR, Wenderoth N, Huber R.

Nat Commun. 2017 May 22;8:15405. doi: 10.1038/ncomms15405. Erratum in: Nat Commun. 2018 May 25;9:16182.

8.

A Bayesian Account of Vocal Adaptation to Pitch-Shifted Auditory Feedback.

Hahnloser RH, Narula G.

PLoS One. 2017 Jan 30;12(1):e0169795. doi: 10.1371/journal.pone.0169795. eCollection 2017.

9.

A lightweight feedback-controlled microdrive for chronic neural recordings.

Jovalekic A, Cavé-Lopez S, Canopoli A, Ondracek JM, Nager A, Vyssotski AL, Hahnloser RH.

J Neural Eng. 2017 Apr;14(2):026006. doi: 10.1088/1741-2552/aa5848. Epub 2017 Jan 10.

PMID:
28071593
10.

A Neural Code That Is Isometric to Vocal Output and Correlates with Its Sensory Consequences.

Vyssotski AL, Stepien AE, Keller GB, Hahnloser RH.

PLoS Biol. 2016 Oct 10;14(10):e2000317. doi: 10.1371/journal.pbio.2000317. eCollection 2016 Oct.

11.

Rhythmic Continuous-Time Coding in the Songbird Analog of Vocal Motor Cortex.

Lynch GF, Okubo TS, Hanuschkin A, Hahnloser RH, Fee MS.

Neuron. 2016 May 18;90(4):877-92. doi: 10.1016/j.neuron.2016.04.021.

12.

Linear Methods for Efficient and Fast Separation of Two Sources Recorded with a Single Microphone.

Bhargava S, Blättler F, Kollmorgen S, Liu SC, Hahnloser RH.

Neural Comput. 2015 Oct;27(10):2231-59. doi: 10.1162/NECO_a_00776. Epub 2015 Aug 27.

PMID:
26313599
13.

Reconstruction of vocal interactions in a group of small songbirds.

Anisimov VN, Herbst JA, Abramchuk AN, Latanov AV, Hahnloser RH, Vyssotski AL.

Nat Methods. 2014 Nov;11(11):1135-7. doi: 10.1038/nmeth.3114. Epub 2014 Sep 28.

PMID:
25262206
14.

A higher sensory brain region is involved in reversing reinforcement-induced vocal changes in a songbird.

Canopoli A, Herbst JA, Hahnloser RH.

J Neurosci. 2014 May 14;34(20):7018-26. doi: 10.1523/JNEUROSCI.0266-14.2014.

15.

Evidence for a causal inverse model in an avian cortico-basal ganglia circuit.

Giret N, Kornfeld J, Ganguli S, Hahnloser RH.

Proc Natl Acad Sci U S A. 2014 Apr 22;111(16):6063-8. doi: 10.1073/pnas.1317087111. Epub 2014 Apr 7.

16.

Dynamic alignment models for neural coding.

Kollmorgen S, Hahnloser RH.

PLoS Comput Biol. 2014 Mar 13;10(3):e1003508. doi: 10.1371/journal.pcbi.1003508. eCollection 2014 Mar.

17.

Activity in a premotor cortical nucleus of zebra finches is locally organized and exhibits auditory selectivity in neurons but not in glia.

Graber MH, Helmchen F, Hahnloser RH.

PLoS One. 2013 Dec 3;8(12):e81177. doi: 10.1371/journal.pone.0081177. eCollection 2013.

18.

A Hebbian learning rule gives rise to mirror neurons and links them to control theoretic inverse models.

Hanuschkin A, Ganguli S, Hahnloser RH.

Front Neural Circuits. 2013 Jun 19;7:106. doi: 10.3389/fncir.2013.00106. eCollection 2013.

19.

At the interface of the auditory and vocal motor systems: NIf and its role in vocal processing, production and learning.

Lewandowski B, Vyssotski A, Hahnloser RH, Schmidt M.

J Physiol Paris. 2013 Jun;107(3):178-92. doi: 10.1016/j.jphysparis.2013.04.001. Epub 2013 Apr 17. Review.

20.

An efficient coding hypothesis links sparsity and selectivity of neural responses.

Blättler F, Hahnloser RH.

PLoS One. 2011;6(10):e25506. doi: 10.1371/journal.pone.0025506. Epub 2011 Oct 13.

21.

Regulation of learned vocal behavior by an auditory motor cortical nucleus in juvenile zebra finches.

Naie K, Hahnloser RH.

J Neurophysiol. 2011 Jul;106(1):291-300. doi: 10.1152/jn.01035.2010. Epub 2011 Apr 27.

22.

Projection neuron circuits resolved using correlative array tomography.

Oberti D, Kirschmann MA, Hahnloser RH.

Front Neurosci. 2011 Apr 12;5:50. doi: 10.3389/fnins.2011.00050. eCollection 2011.

23.

Correlative microscopy of densely labeled projection neurons using neural tracers.

Oberti D, Kirschmann MA, Hahnloser RH.

Front Neuroanat. 2010 Jun 14;4:24. doi: 10.3389/fnana.2010.00024. eCollection 2010.

24.

Auditory representations and memory in birdsong learning.

Hahnloser RH, Kotowicz A.

Curr Opin Neurobiol. 2010 Jun;20(3):332-9. doi: 10.1016/j.conb.2010.02.011. Epub 2010 Mar 20. Review.

PMID:
20307967
25.

Spike-time-dependent plasticity and heterosynaptic competition organize networks to produce long scale-free sequences of neural activity.

Fiete IR, Senn W, Wang CZ, Hahnloser RH.

Neuron. 2010 Feb 25;65(4):563-76. doi: 10.1016/j.neuron.2010.02.003.

26.

Perceptron learning rule derived from spike-frequency adaptation and spike-time-dependent plasticity.

D'Souza P, Liu SC, Hahnloser RH.

Proc Natl Acad Sci U S A. 2010 Mar 9;107(10):4722-7. doi: 10.1073/pnas.0909394107. Epub 2010 Feb 18.

27.

Neural processing of auditory feedback during vocal practice in a songbird.

Keller GB, Hahnloser RH.

Nature. 2009 Jan 8;457(7226):187-90. doi: 10.1038/nature07467. Epub 2008 Nov 12.

PMID:
19005471
28.

Rapid interhemispheric switching during vocal production in a songbird.

Wang CZ, Herbst JA, Keller GB, Hahnloser RH.

PLoS Biol. 2008 Oct 14;6(10):e250. doi: 10.1371/journal.pbio.0060250.

29.

Spike sorting with hidden Markov models.

Herbst JA, Gammeter S, Ferrero D, Hahnloser RH.

J Neurosci Methods. 2008 Sep 15;174(1):126-34. doi: 10.1016/j.jneumeth.2008.06.011. Epub 2008 Jun 21.

PMID:
18619490
30.

Spikes and bursts in two types of thalamic projection neurons differentially shape sleep patterns and auditory responses in a songbird.

Hahnloser RH, Wang CZ, Nager A, Naie K.

J Neurosci. 2008 May 7;28(19):5040-52. doi: 10.1523/JNEUROSCI.5059-07.2008.

31.

Spike correlations in a songbird agree with a simple markov population model.

Weber AP, Hahnloser RH.

PLoS Comput Biol. 2007 Dec;3(12):e249.

32.

Cross-intensity functions and the estimate of spike-time jitter.

Hahnloser RH.

Biol Cybern. 2007 May;96(5):497-506. Epub 2007 Mar 27.

PMID:
17387506
33.

Sleep-related spike bursts in HVC are driven by the nucleus interface of the nidopallium.

Hahnloser RH, Fee MS.

J Neurophysiol. 2007 Jan;97(1):423-35. Epub 2006 Sep 27.

34.

Sleep-related neural activity in a premotor and a basal-ganglia pathway of the songbird.

Hahnloser RH, Kozhevnikov AA, Fee MS.

J Neurophysiol. 2006 Aug;96(2):794-812. Epub 2006 Feb 22.

35.

Neural mechanisms of vocal sequence generation in the songbird.

Fee MS, Kozhevnikov AA, Hahnloser RH.

Ann N Y Acad Sci. 2004 Jun;1016:153-70. Review.

PMID:
15313774
36.

Temporal sparseness of the premotor drive is important for rapid learning in a neural network model of birdsong.

Fiete IR, Hahnloser RH, Fee MS, Seung HS.

J Neurophysiol. 2004 Oct;92(4):2274-82. Epub 2004 Apr 7.

37.
38.

Stationary transmission distribution of random spike trains by dynamical synapses.

Hahnloser RH.

Phys Rev E Stat Nonlin Soft Matter Phys. 2003 Feb;67(2 Pt 1):022901. Epub 2003 Feb 10.

PMID:
12636725
39.

Permitted and forbidden sets in symmetric threshold-linear networks.

Hahnloser RH, Seung HS, Slotine JJ.

Neural Comput. 2003 Mar;15(3):621-38.

PMID:
12620160
40.

Double-ring network model of the head-direction system.

Xie X, Hahnloser RH, Seung HS.

Phys Rev E Stat Nonlin Soft Matter Phys. 2002 Oct;66(4 Pt 1):041902. Epub 2002 Oct 9.

PMID:
12443230
41.

Selectively grouping neurons in recurrent networks of lateral inhibition.

Xie X, Hahnloser RH, Seung HS.

Neural Comput. 2002 Nov;14(11):2627-46.

PMID:
12433293
42.

An ultra-sparse code underlies the generation of neural sequences in a songbird.

Hahnloser RH, Kozhevnikov AA, Fee MS.

Nature. 2002 Sep 5;419(6902):65-70. Erratum in: Nature. 2003 Jan 16;421(6920):294.

PMID:
12214232
43.

Attentional recruitment of inter-areal recurrent networks for selective gain control.

Hahnloser RH, Douglas RJ, Hepp K.

Neural Comput. 2002 Jul;14(7):1669-89.

PMID:
12079551
44.

Silicon synaptic depression.

Rasche C, Hahnloser RH.

Biol Cybern. 2001 Jan;84(1):57-62.

PMID:
11204399
45.

Digital selection and analogue amplification coexist in a cortex-inspired silicon circuit.

Hahnloser RH, Sarpeshkar R, Mahowald MA, Douglas RJ, Seung HS.

Nature. 2000 Jun 22;405(6789):947-51. Erratum in: Nature 2000 Dec 21-28;408(6815):1012.

PMID:
10879535

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