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Douglas A. Baxter
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2020 – today
- 2022
- [j19]Yili Zhang, Paul Smolen, Cristina M. Alberini, Douglas A. Baxter, John H. Byrne:
Computational analysis of memory consolidation following inhibitory avoidance (IA) training in adult and infant rats: Critical roles of CaMKIIα and MeCP2. PLoS Comput. Biol. 18(6) (2022) - 2021
- [j18]Paul Smolen, Marcelo A. Wood, Douglas A. Baxter, John H. Byrne:
Modeling suggests combined-drug treatments for disorders impairing synaptic plasticity via shared signaling pathways. J. Comput. Neurosci. 49(1): 37-56 (2021) - 2020
- [j17]Paul Smolen, Douglas A. Baxter, John H. Byrne:
Comparing Theories for the Maintenance of Late LTP and Long-Term Memory: Computational Analysis of the Roles of Kinase Feedback Pathways and Synaptic Reactivation. Frontiers Comput. Neurosci. 14: 569349 (2020)
2010 – 2019
- 2014
- [j16]Yili Zhang, Paul Smolen, Douglas A. Baxter, John H. Byrne:
Computational Analyses of Synergism in Small Molecular Network Motifs. PLoS Comput. Biol. 10(3) (2014) - 2012
- [j15]Paul Smolen, Douglas A. Baxter, John H. Byrne:
Molecular Constraints on Synaptic Tagging and Maintenance of Long-Term Potentiation: A Predictive Model. PLoS Comput. Biol. 8(8) (2012)
2000 – 2009
- 2007
- [j14]Douglas A. Baxter, John H. Byrne:
Short-term plasticity in a computational model of the tail-withdrawal circuit in Aplysia. Neurocomputing 70(10-12): 1993-1999 (2007) - 2006
- [j13]Yidao Cai, Mark Flynn, Douglas A. Baxter, Terry Crow:
Role of A-type K+ channels in spike broadening observed in soma and axon of Hermissenda type-B photoreceptors: A simulation study. J. Comput. Neurosci. 21(1): 89-99 (2006) - [c1]Enrico Cataldo, John H. Byrne, Douglas A. Baxter:
Computational Model of a Central Pattern Generator. CMSB 2006: 242-256 - 2005
- [j12]Randall D. Hayes, John H. Byrne, Steven J. Cox, Douglas A. Baxter:
Estimation of single-neuron model parameters from spike train data. Neurocomputing 65-66: 517-529 (2005) - [j11]Enrico Cataldo, Marcello Brunelli, John H. Byrne, Evyatar Av-Ron, Yidao Cai, Douglas A. Baxter:
Computational Model of Touch Sensory Cells (T Cells) of the Leech: Role of the Afterhyperpolarization (AHP) in Activity-Dependent Conduction Failure. J. Comput. Neurosci. 18(1): 5-24 (2005) - [j10]David B. Pettigrew, Paul Smolen, Douglas A. Baxter, John H. Byrne:
Dynamic Properties of Regulatory Motifs Associated with Induction of Three Temporal Domains of Memory in Aplysia. J. Comput. Neurosci. 18(2): 163-181 (2005) - 2004
- [j9]Chuan Luo, John W. Clark Jr., Carmen C. Canavier, Douglas A. Baxter, John H. Byrne:
Multimodal behavior in a four neuron ring circuit: mode switching. IEEE Trans. Biomed. Eng. 51(2): 205-218 (2004) - 2003
- [j8]Mark Flynn, Yidao Cai, Douglas A. Baxter, Terry Crow:
A Computational Study of the Role of Spike Broadening in Synaptic Facilitation of Hermissenda. J. Comput. Neurosci. 15(1): 29-41 (2003) - [j7]Yidao Cai, Douglas A. Baxter, Terry Crow:
Computational Study of Enhanced Excitability in Hermissenda: Membrane Conductances Modulated by 5-HT. J. Comput. Neurosci. 15(1): 105-121 (2003)
1990 – 1999
- 1999
- [j6]Carmen C. Canavier, Douglas A. Baxter, John W. Clark Jr., John H. Byrne:
Control of multistability in ring circuits of oscillators. Biol. Cybern. 80(2): 87-102 (1999) - 1997
- [j5]Carmen C. Canavier, Robert J. Butera, R. O. Dror, Douglas A. Baxter, John W. Clark Jr., John H. Byrne:
Phase response characteristics of model neurons determine which patterns are expressed in a ring circuit model of gait generation. Biol. Cybern. 77(6): 367-380 (1997) - 1995
- [j4]Robert J. Butera, John W. Clark Jr., Carmen C. Canavier, Douglas A. Baxter, John H. Byrne:
Analysis of the effects of modulatory agents on a modeled bursting neuron: Dynamic interactions between voltage and calcium dependent systems. J. Comput. Neurosci. 2(1): 19-44 (1995) - 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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