Micah Richert

Salk Institute for Biological Studies, La Jolla, CA, United States 
"Micah Richert"
Mean distance: 14.04 (cluster 29)


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Bart Krekelberg grad student Salk Institute
Thomas D. Albright grad student 2008 UCSD
 (Classical and surround receptive field structure in cortical area MT as revealed by reverse correlation.)
Jeffrey L. Krichmar post-doc UC Irvine
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Beyeler M, Richert M, Dutt ND, et al. (2014) Efficient spiking neural network model of pattern motion selectivity in visual cortex. Neuroinformatics. 12: 435-54
Richert M, Albright TD, Krekelberg B. (2013) The complex structure of receptive fields in the middle temporal area. Frontiers in Systems Neuroscience. 7: 2
Richert M, Szatmary B, Izhikevich E. (2013) Self-tuning spike-timing dependent plasticity curves to simplify models and improve learning Bmc Neuroscience. 14
Meier PM, Richert M, Nageswaran JM, et al. (2013) Temporally evolving surround suppression helps decoding in a spiking model of motion processing Bmc Neuroscience. 14
Petre C, Richert M, Szatmary B, et al. (2013) Beyond inhibition: lateral modulation of plasticity of feedforward synapses in a spiking model of V1 Bmc Neuroscience. 14
Richert M, Nageswaran JM, Sokol S, et al. (2013) A spiking model of superior colliculus for bottom-up saliency Bmc Neuroscience. 14
Piekniewski F, Richert M, Fisher D, et al. (2013) Balanced excitation and inhibition in a spiking model of V1 Bmc Neuroscience. 14
Izhikevich EM, Piekniewski F, Nageswaran J, et al. (2013) Spontaneous emergence of simple and complex receptive fields in a spiking model of V1 Bmc Neuroscience. 14
Carlson KD, Richert M, Dutt N, et al. (2013) Biologically plausible models of homeostasis and STDP: Stability and learning in spiking neural networks Proceedings of the International Joint Conference On Neural Networks
Richert M, Nageswaran JM, Dutt N, et al. (2011) An efficient simulation environment for modeling large-scale cortical processing. Frontiers in Neuroinformatics. 5: 19
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