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Items: 1 to 50 of 55

1.

The Neural Basis of Timing: Distributed Mechanisms for Diverse Functions.

Paton JJ, Buonomano DV.

Neuron. 2018 May 16;98(4):687-705. doi: 10.1016/j.neuron.2018.03.045. Review.

PMID:
29772201
2.

Encoding sensory and motor patterns as time-invariant trajectories in recurrent neural networks.

Goudar V, Buonomano DV.

Elife. 2018 Mar 14;7. pii: e31134. doi: 10.7554/eLife.31134.

3.

Encoding Time in Feedforward Trajectories of a Recurrent Neural Network Model.

Hardy NF, Buonomano DV.

Neural Comput. 2018 Feb;30(2):378-396. doi: 10.1162/neco_a_01041. Epub 2017 Nov 21.

PMID:
29162002
4.

Differential Encoding of Time by Prefrontal and Striatal Network Dynamics.

Bakhurin KI, Goudar V, Shobe JL, Claar LD, Buonomano DV, Masmanidis SC.

J Neurosci. 2017 Jan 25;37(4):854-870. doi: 10.1523/JNEUROSCI.1789-16.2016.

5.

Neurocomputational Models of Interval and Pattern Timing.

Hardy NF, Buonomano DV.

Curr Opin Behav Sci. 2016 Apr;8:250-257. Epub 2016 Feb 12.

6.

Temporal Interval Learning in Cortical Cultures Is Encoded in Intrinsic Network Dynamics.

Goel A, Buonomano DV.

Neuron. 2016 Jul 20;91(2):320-7. doi: 10.1016/j.neuron.2016.05.042. Epub 2016 Jun 23.

7.

Time in Cortical Circuits.

Finnerty GT, Shadlen MN, Jazayeri M, Nobre AC, Buonomano DV.

J Neurosci. 2015 Oct 14;35(41):13912-6. doi: 10.1523/JNEUROSCI.2654-15.2015. Review.

8.

Neural coding: time contraction and dilation in the striatum.

Motanis H, Buonomano DV.

Curr Biol. 2015 May 4;25(9):R374-6. doi: 10.1016/j.cub.2015.02.057.

9.

Multifocal fluorescence microscope for fast optical recordings of neuronal action potentials.

Shtrahman M, Aharoni DB, Hardy NF, Buonomano DV, Arisaka K, Otis TS.

Biophys J. 2015 Feb 3;108(3):520-9. doi: 10.1016/j.bpj.2014.12.005.

10.

Neural dynamics based timing in the subsecond to seconds range.

Buonomano DV.

Adv Exp Med Biol. 2014;829:101-17. doi: 10.1007/978-1-4939-1782-2_6. Review.

PMID:
25358707
11.

A model of order-selectivity based on dynamic changes in the balance of excitation and inhibition produced by short-term synaptic plasticity.

Goudar V, Buonomano DV.

J Neurophysiol. 2015 Jan 15;113(2):509-23. doi: 10.1152/jn.00568.2014. Epub 2014 Oct 22.

12.

Useful dynamic regimes emerge in recurrent networks.

Goudar V, Buonomano DV.

Nat Neurosci. 2014 Apr;17(4):487-9. doi: 10.1038/nn.3679. No abstract available.

PMID:
24671063
13.

Timing as an intrinsic property of neural networks: evidence from in vivo and in vitro experiments.

Goel A, Buonomano DV.

Philos Trans R Soc Lond B Biol Sci. 2014 Jan 20;369(1637):20120460. doi: 10.1098/rstb.2012.0460. Print 2014 Mar 5. Review.

14.

Robust timing and motor patterns by taming chaos in recurrent neural networks.

Laje R, Buonomano DV.

Nat Neurosci. 2013 Jul;16(7):925-33. doi: 10.1038/nn.3405. Epub 2013 May 26.

15.

Chronic electrical stimulation homeostatically decreases spontaneous activity, but paradoxically increases evoked network activity.

Goel A, Buonomano DV.

J Neurophysiol. 2013 Apr;109(7):1824-36. doi: 10.1152/jn.00612.2012. Epub 2013 Jan 16.

16.

Unsupervised formation of vocalization-sensitive neurons: a cortical model based on short-term and homeostatic plasticity.

Lee TP, Buonomano DV.

Neural Comput. 2012 Oct;24(10):2579-603. doi: 10.1162/NECO_a_00345. Epub 2012 Jul 30.

PMID:
22845822
17.

Developmental shift of short-term synaptic plasticity in cortical organotypic slices.

Chen WX, Buonomano DV.

Neuroscience. 2012 Jun 28;213:38-46. doi: 10.1016/j.neuroscience.2012.04.018. Epub 2012 Apr 19.

18.

Learning of temporal motor patterns: an analysis of continuous versus reset timing.

Laje R, Cheng K, Buonomano DV.

Front Integr Neurosci. 2011 Oct 13;5:61. doi: 10.3389/fnint.2011.00061. eCollection 2011.

19.

A novel learning rule for long-term plasticity of short-term synaptic plasticity enhances temporal processing.

Carvalho TP, Buonomano DV.

Front Integr Neurosci. 2011 May 30;5:20. doi: 10.3389/fnint.2011.00020. eCollection 2011.

20.

Population clocks: motor timing with neural dynamics.

Buonomano DV, Laje R.

Trends Cogn Sci. 2010 Dec;14(12):520-7. doi: 10.1016/j.tics.2010.09.002.

21.

Neural dynamics of in vitro cortical networks reflects experienced temporal patterns.

Johnson HA, Goel A, Buonomano DV.

Nat Neurosci. 2010 Aug;13(8):917-9. doi: 10.1038/nn.2579. Epub 2010 Jun 13.

22.

Embedding multiple trajectories in simulated recurrent neural networks in a self-organizing manner.

Liu JK, Buonomano DV.

J Neurosci. 2009 Oct 21;29(42):13172-81. doi: 10.1523/JNEUROSCI.2358-09.2009.

23.

Harnessing chaos in recurrent neural networks.

Buonomano DV.

Neuron. 2009 Aug 27;63(4):423-5. doi: 10.1016/j.neuron.2009.08.003. Review.

24.

Influence of the interstimulus interval on temporal processing and learning: testing the state-dependent network model.

Buonomano DV, Bramen J, Khodadadifar M.

Philos Trans R Soc Lond B Biol Sci. 2009 Jul 12;364(1525):1865-73. doi: 10.1098/rstb.2009.0019. Review.

25.

Differential effects of excitatory and inhibitory plasticity on synaptically driven neuronal input-output functions.

Carvalho TP, Buonomano DV.

Neuron. 2009 Mar 12;61(5):774-85. doi: 10.1016/j.neuron.2009.01.013.

26.

State-dependent computations: spatiotemporal processing in cortical networks.

Buonomano DV, Maass W.

Nat Rev Neurosci. 2009 Feb;10(2):113-25. doi: 10.1038/nrn2558. Epub 2009 Jan 15. Review.

PMID:
19145235
27.

A method for chronic stimulation of cortical organotypic cultures using implanted electrodes.

Johnson HA, Buonomano DV.

J Neurosci Methods. 2009 Jan 30;176(2):136-43. doi: 10.1016/j.jneumeth.2008.08.037. Epub 2008 Sep 13.

PMID:
18835297
28.

Distortions of subjective time perception within and across senses.

van Wassenhove V, Buonomano DV, Shimojo S, Shams L.

PLoS One. 2008 Jan 16;3(1):e1437. doi: 10.1371/journal.pone.0001437.

29.

The biology of time across different scales.

Buonomano DV.

Nat Chem Biol. 2007 Oct;3(10):594-7. No abstract available.

PMID:
17876310
30.
31.

Timing in the absence of clocks: encoding time in neural network states.

Karmarkar UR, Buonomano DV.

Neuron. 2007 Feb 1;53(3):427-38.

32.

Different forms of homeostatic plasticity are engaged with distinct temporal profiles.

Karmarkar UR, Buonomano DV.

Eur J Neurosci. 2006 Mar;23(6):1575-84.

PMID:
16553621
33.
34.

A technique for repeated recordings in cortical organotypic slices.

Dong HW, Buonomano DV.

J Neurosci Methods. 2005 Jul 15;146(1):69-75. Epub 2005 Feb 25.

PMID:
15935222
35.
36.

The neural basis of temporal processing.

Mauk MD, Buonomano DV.

Annu Rev Neurosci. 2004;27:307-40. Review.

PMID:
15217335
37.

Timing of neural responses in cortical organotypic slices.

Buonomano DV.

Proc Natl Acad Sci U S A. 2003 Apr 15;100(8):4897-902. Epub 2003 Mar 31.

38.

Temporal specificity of perceptual learning in an auditory discrimination task.

Karmarkar UR, Buonomano DV.

Learn Mem. 2003 Mar-Apr;10(2):141-7.

39.
40.

Mechanisms and significance of spike-timing dependent plasticity.

Karmarkar UR, Najarian MT, Buonomano DV.

Biol Cybern. 2002 Dec;87(5-6):373-82.

PMID:
12461627
41.

A model of spike-timing dependent plasticity: one or two coincidence detectors?

Karmarkar UR, Buonomano DV.

J Neurophysiol. 2002 Jul;88(1):507-13.

42.

How do we tell time?

Buonomano DV, Karmarkar UR.

Neuroscientist. 2002 Feb;8(1):42-51. Review.

PMID:
11843098
43.
45.

A neural network model of temporal code generation and position-invariant pattern recognition.

Buonomano DV, Merzenich M.

Neural Comput. 1999 Jan 1;11(1):103-16.

PMID:
9950725
47.

Cortical plasticity: from synapses to maps.

Buonomano DV, Merzenich MM.

Annu Rev Neurosci. 1998;21:149-86. Review.

PMID:
9530495
48.

Context-sensitive synaptic plasticity and temporal-to-spatial transformations in hippocampal slices.

Buonomano DV, Hickmott PW, Merzenich MM.

Proc Natl Acad Sci U S A. 1997 Sep 16;94(19):10403-8.

49.

Learning and generalization of auditory temporal-interval discrimination in humans.

Wright BA, Buonomano DV, Mahncke HW, Merzenich MM.

J Neurosci. 1997 May 15;17(10):3956-63.

50.

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