A citation-based method for searching scientific literature

J F Medina, M D Mauk. Nat Neurosci 2000
Times Cited: 216







List of co-cited articles
1210 articles co-cited >1



Times Cited
  Times     Co-cited
Similarity


A theory of cerebellar cortex.
D Marr. J Physiol 1969
54

Distributed synergistic plasticity and cerebellar learning.
Zhenyu Gao, Boeke J van Beugen, Chris I De Zeeuw. Nat Rev Neurosci 2012
304
29

Internal models in the cerebellum.
D M Wolpert, R C Miall, M Kawato. Trends Cogn Sci 1998
22

Precise control of movement kinematics by optogenetic inhibition of Purkinje cell activity.
Shane A Heiney, Jinsook Kim, George J Augustine, Javier F Medina. J Neurosci 2014
135
22

Timing mechanisms in the cerebellum: testing predictions of a large-scale computer simulation.
J F Medina, K S Garcia, W L Nores, N M Taylor, M D Mauk. J Neurosci 2000
199
21

Timing and plasticity in the cerebellum: focus on the granular layer.
Egidio D'Angelo, Chris I De Zeeuw. Trends Neurosci 2009
210
21

Acquisition, extinction, and reacquisition of a cerebellar cortical memory trace.
Dan-Anders Jirenhed, Fredrik Bengtsson, Germund Hesslow. J Neurosci 2007
197
21

The cerebellar microcircuit as an adaptive filter: experimental and computational evidence.
Paul Dean, John Porrill, Carl-Fredrik Ekerot, Henrik Jörntell. Nat Rev Neurosci 2010
214
19



Mechanisms of cerebellar learning suggested by eyelid conditioning.
J F Medina, W L Nores, T Ohyama, M D Mauk. Curr Opin Neurobiol 2000
136
17


Network structure within the cerebellar input layer enables lossless sparse encoding.
Guy Billings, Eugenio Piasini, Andrea Lőrincz, Zoltan Nusser, R Angus Silver. Neuron 2014
69
23



Distributed cerebellar plasticity implements adaptable gain control in a manipulation task: a closed-loop robotic simulation.
Jesús A Garrido, Niceto R Luque, Egidio D'Angelo, Eduardo Ros. Front Neural Circuits 2013
40
37

Evolving Models of Pavlovian Conditioning: Cerebellar Cortical Dynamics in Awake Behaving Mice.
Michiel M ten Brinke, Henk-Jan Boele, Jochen K Spanke, Jan-Willem Potters, Katja Kornysheva, Peer Wulff, Anna C H G IJpelaar, Sebastiaan K E Koekkoek, Chris I De Zeeuw. Cell Rep 2015
115
15



High-fidelity transmission of sensory information by single cerebellar mossy fibre boutons.
Ede A Rancz, Taro Ishikawa, Ian Duguid, Paul Chadderton, Séverine Mahon, Michael Häusser. Nature 2007
202
14

Memory trace and timing mechanism localized to cerebellar Purkinje cells.
Fredrik Johansson, Dan-Anders Jirenhed, Anders Rasmussen, Riccardo Zucca, Germund Hesslow. Proc Natl Acad Sci U S A 2014
82
17

The contribution of single synapses to sensory representation in vivo.
Alexander Arenz, R Angus Silver, Andreas T Schaefer, Troy W Margrie. Science 2008
140
13




The neural basis of temporal processing.
Michael D Mauk, Dean V Buonomano. Annu Rev Neurosci 2004
534
13



A temporal basis for predicting the sensory consequences of motor commands in an electric fish.
Ann Kennedy, Greg Wayne, Patrick Kaifosh, Karina Alviña, L F Abbott, Nathaniel B Sawtell. Nat Neurosci 2014
83
14

Cerebellum-dependent learning: the role of multiple plasticity mechanisms.
Edward S Boyden, Akira Katoh, Jennifer L Raymond. Annu Rev Neurosci 2004
291
12


Convergence of pontine and proprioceptive streams onto multimodal cerebellar granule cells.
Cheng-Chiu Huang, Ken Sugino, Yasuyuki Shima, Caiying Guo, Suxia Bai, Brett D Mensh, Sacha B Nelson, Adam W Hantman. Elife 2013
134
12

Learning-induced plasticity in deep cerebellar nucleus.
Tatsuya Ohyama, William L Nores, Javier F Medina, Frank A Riusech, Michael D Mauk. J Neurosci 2006
103
11


The cerebellum as a liquid state machine.
Tadashi Yamazaki, Shigeru Tanaka. Neural Netw 2007
68
16



Tonic inhibition enhances fidelity of sensory information transmission in the cerebellar cortex.
Ian Duguid, Tiago Branco, Michael London, Paul Chadderton, Michael Häusser. J Neurosci 2012
99
11

Granule cell ascending axon excitatory synapses onto Golgi cells implement a potent feedback circuit in the cerebellar granular layer.
Elisabetta Cesana, Katarzyna Pietrajtis, Céline Bidoret, Philippe Isope, Egidio D'Angelo, Stéphane Dieudonné, Lia Forti. J Neurosci 2013
41
26

Reevaluating the role of LTD in cerebellar motor learning.
Martijn Schonewille, Zhenyu Gao, Henk-Jan Boele, Maria F Vinueza Veloz, Wardell E Amerika, Antonia A M Simek, Marcel T De Jeu, Jordan P Steinberg, Kogo Takamiya, Freek E Hoebeek,[...]. Neuron 2011
210
11

Integration of quanta in cerebellar granule cells during sensory processing.
Paul Chadderton, Troy W Margrie, Michael Häusser. Nature 2004
495
11

Excitatory Cerebellar Nucleocortical Circuit Provides Internal Amplification during Associative Conditioning.
Zhenyu Gao, Martina Proietti-Onori, Zhanmin Lin, Michiel M Ten Brinke, Henk-Jan Boele, Jan-Willem Potters, Tom J H Ruigrok, Freek E Hoebeek, Chris I De Zeeuw. Neuron 2016
83
13

Encoding of action by the Purkinje cells of the cerebellum.
David J Herzfeld, Yoshiko Kojima, Robijanto Soetedjo, Reza Shadmehr. Nature 2015
138
11

Modeling the Cerebellar Microcircuit: New Strategies for a Long-Standing Issue.
Egidio D'Angelo, Alberto Antonietti, Stefano Casali, Claudia Casellato, Jesus A Garrido, Niceto Rafael Luque, Lisa Mapelli, Stefano Masoli, Alessandra Pedrocchi, Francesca Prestori,[...]. Front Cell Neurosci 2016
32
34

Neural modeling of an internal clock.
Tadashi Yamazaki, Shigeru Tanaka. Neural Comput 2005
38
26


The cerebellum: a neuronal learning machine?
J L Raymond, S G Lisberger, M D Mauk. Science 1996
449
10


Sensory prediction or motor control? Application of marr-albus type models of cerebellar function to classical conditioning.
Nathan F Lepora, John Porrill, Christopher H Yeo, Paul Dean. Front Comput Neurosci 2010
37
27

Spatiotemporal firing patterns in the cerebellum.
Chris I De Zeeuw, Freek E Hoebeek, Laurens W J Bosman, Martijn Schonewille, Laurens Witter, Sebastiaan K Koekkoek. Nat Rev Neurosci 2011
247
10


Co-cited is the co-citation frequency, indicating how many articles cite the article together with the query article. Similarity is the co-citation as percentage of the times cited of the query article or the article in the search results, whichever is the lowest. These numbers are calculated for the last 100 citations when articles are cited more than 100 times.