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ORCIDDean V. Buonomano
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Journal Articles
- 2022
[j9]Shanglin Zhou
, Sotiris C. Masmanidis, Dean V. Buonomano:
Encoding time in neural dynamic regimes with distinct computational tradeoffs. PLoS Comput. Biol. 18(3) (2022)- 2018
- [j8]N. F. Hardy, Dean V. Buonomano:
Encoding Time in Feedforward Trajectories of a Recurrent Neural Network Model. Neural Comput. 30(2) (2018) - 2012
- [j7]Tyler P. Lee, Dean V. Buonomano:
Unsupervised Formation of Vocalization-Sensitive Neurons: A Cortical Model Based on Short-Term and Homeostatic Plasticity. Neural Comput. 24(10): 2579-2603 (2012) - 2002
- [j6]Uma R. Karmarkar, Mark T. Najarian, Dean V. Buonomano:
Mechanisms and significance of spike-timing dependent plasticity. Biol. Cybern. 87(5-6): 373-382 (2002) - 1999
- [j5]Dean V. Buonomano, Michael Merzenich:
A Neural Network Modell of Temporal Code Generation and Position Invariant Pattern Recognition. Neural Comput. 11(1): 103-116 (1999) - 1994
- [j4]Dean V. Buonomano, Michael D. Mauk:
Neural Network Model of the Cerebellum: Temporal Discrimination and the Timing of Motor Responses. Neural Comput. 6(1): 38-55 (1994) - [j3]Jennifer L. Raymond, Douglas A. Baxter, Dean V. Buonomano, John H. Byrne:
Response to letter by Gaudiano et al. Neural Networks 7(2): 406-407 (1994) - 1992
- [j2]Jennifer L. Raymond, Douglas A. Baxter, Dean V. Buonomano, John H. Byrne:
A learning rule based on empirically-derived activity-dependent neuromodulation supports operant conditioning in a small network. Neural Networks 5(5): 789-803 (1992) - 1990
- [j1]Dean V. Buonomano, Douglas A. Baxter, John H. Byrne:
Small networks of empirically derived adaptive elements simulate some higher-order features of classical conditioning. Neural Networks 3(5): 507-523 (1990)
Coauthor Index
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