| 2007 |
|---|
| 21 | EE | Matthieu Gilson,
David B. Grayden,
J. Leo van Hemmen,
Doreen A. Thomas,
Anthony N. Burkitt:
Spike-Timing Dependent Plasticity in Recurrently Connected Networks with Fixed External Inputs.
ICONIP (1) 2007: 102-111 |
| 20 | EE | Anthony N. Burkitt,
Matthieu Gilson,
J. Leo van Hemmen:
Spike-timing-dependent plasticity for neurons with recurrent connections.
Biological Cybernetics 96(5): 533-546 (2007) |
| 2006 |
|---|
| 19 | EE | Anthony N. Burkitt:
A Review of the Integrate-and-fire Neuron Model: I. Homogeneous Synaptic Input.
Biological Cybernetics 95(1): 1-19 (2006) |
| 18 | EE | Anthony N. Burkitt:
A review of the integrate-and-fire neuron model: II. Inhomogeneous synaptic input and network properties.
Biological Cybernetics 95(2): 97-112 (2006) |
| 2005 |
|---|
| 17 | EE | Hamish Meffin,
Anthony N. Burkitt,
David B. Grayden:
Dynamically adjustable contrast enhancement from cortical background activity.
Neurocomputing 65-66: 633-639 (2005) |
| 2004 |
|---|
| 16 | EE | Hamish Meffin,
Anthony N. Burkitt,
David B. Grayden:
An Analytical Model for the 'Large, Fluctuating Synaptic Conductance State' Typical of Neocortical Neurons In Vivo.
Journal of Computational Neuroscience 16(2): 159-175 (2004) |
| 15 | EE | Anthony N. Burkitt,
Hamish Meffin,
David B. Grayden:
Spike-Timing-Dependent Plasticity: The Relationship to Rate-Based Learning for Models with Weight Dynamics Determined by a Stable Fixed Point.
Neural Computation 16(5): 885-94 (2004) |
| 2003 |
|---|
| 14 | EE | Anthony N. Burkitt,
Hamish Meffin,
David B. Grayden:
Study of neuronal gain in a conductance-based leaky integrate-and-fire neuron model with balanced excitatory and inhibitory synaptic input.
Biological Cybernetics 89(2): 119-125 (2003) |
| 13 | EE | Anthony N. Burkitt,
J. Leo van Hemmen:
How synapses in the auditory system wax and wane: theoretical perspectives.
Biological Cybernetics 89(5): 318-332 (2003) |
| 12 | EE | Anthony N. Burkitt,
Hamish Meffin,
David B. Grayden:
Gain modulation and balanced synaptic input in a conductance-based neural model.
Neurocomputing 52-54: 221-226 (2003) |
| 2002 |
|---|
| 11 | | Levin Kuhlmann,
Anthony N. Burkitt,
Antonio Paolini,
Graeme M. Clark:
Summation of Spatiotemporal Input Patterns in Leaky Integrate-and-Fire Neurons: Application to Neurons in the Cochlear Nucleus Receiving Converging Auditory Nerve Fiber Input.
Journal of Computational Neuroscience 12(1): 55-73 (2002) |
| 10 | EE | Anthony N. Burkitt:
An information-theoretic analysis of the coding of a periodic synaptic input by integrate-and-fire neurons.
Neurocomputing 44-46: 69-74 (2002) |
| 2001 |
|---|
| 9 | EE | Anthony N. Burkitt:
Balanced neurons: analysis of leaky integrate-and-fire neurons with reversal potentials.
Biological Cybernetics 85(4): 247-255 (2001) |
| 8 | EE | Anthony N. Burkitt,
Graeme M. Clark:
Synchronization of the Neural Response to Noisy Periodic Synaptic Input.
Neural Computation 13(12): 2639-2672 (2001) |
| 2000 |
|---|
| 7 | | Anthony N. Burkitt,
Graeme M. Clark:
Calculation of Interspike Intervals for Integrate-and-Fire Neurons with Poisson Distribution of Synaptic Inputs.
Neural Computation 12(8): 1789-1820 (2000) |
| 6 | EE | Anthony N. Burkitt:
Interspike interval variability for balanced networks with reversal potentials for large numbers of inputs.
Neurocomputing 32-33: 313-321 (2000) |
| 5 | EE | Anthony N. Burkitt,
Graeme M. Clark:
Analysis of synchronization in the response of neurons to noisy periodic synaptic input.
Neurocomputing 32-33: 67-75 (2000) |
| 1999 |
|---|
| 4 | | Anthony N. Burkitt,
Graeme M. Clark:
Analysis of Integrate-and-Fire Neurons: Synchronization of Synaptic Input and Spike Output.
Neural Computation 11(4): 871-901 (1999) |
| 3 | EE | Anthony N. Burkitt,
Graeme M. Clark:
New technique for analyzing integrate and fire neurons.
Neurocomputing 26-27: 93-99 (1999) |
| 1993 |
|---|
| 2 | | Anthony N. Burkitt:
Optimised Attractor Neural Networks with External Inputs.
IWANN 1993: 167-172 |
| 1990 |
|---|
| 1 | | D. W. Heermann,
Anthony N. Burkitt:
Parallelization of the Ising model and its performance evaluation.
Parallel Computing 13(3): 345-357 (1990) |
