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Simon Laughlin, Ph.D. (ANU)

Affiliations: 
Zoology University of Cambridge, Cambridge, England, United Kingdom 
Area:
Visual system, energy efficiency, neural circuit design, natural image statistics, information theory, noise constraints, optimal coding
Website:
http://www.zoo.cam.ac.uk/zoostaff/laughlin/
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"Simon Laughlin"
Mean distance: 12.89 (cluster 39)
 
SNBCP

Parents

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Randolf Menzel grad student 1971-1973 Neurobiology Australian National University
 (A bold new perspective)
G. Adrian Horridge grad student 1970-1974 ANU
 (A formative experience)

Collaborators

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Roger C. Hardie collaborator Cambridge
Holger Krapp collaborator Cambridge
Matti Weckstrom collaborator University of Oulu
John A. White collaborator Cambridge
Peter Sterling collaborator 1999- Cambridge
Gordon L. Fain collaborator 2008- Cambridge
Doekele G. Stavenga collaborator 1975-1976 Neurobiology Australian National University
 (applied information theory to vision)
Allan W. Snyder collaborator 1971-1984 Applied Mathematics, Australian National University
David Attwell collaborator 1999-2003 Cambridge
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Publications

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Heras FJ, Anderson J, Laughlin SB, et al. (2017) Voltage-dependent K(+) channels improve the energy efficiency of signalling in blowfly photoreceptors. Journal of the Royal Society, Interface. 14
Heras FJ, Laughlin SB. (2017) Optimizing the use of a sensor resource for opponent polarization coding. Peerj. 5: e2772
Heras FJ, Laughlin SB, Niven JE. (2016) Shunt peaking in neural membranes. Journal of the Royal Society, Interface. 13
Sterling P, Laughlin S. (2015) Principles of neural design Principles of Neural Design. 1-542
Sengupta B, Laughlin SB, Niven JE. (2014) Consequences of converting graded to action potentials upon neural information coding and energy efficiency. Plos Computational Biology. 10: e1003439
Sengupta B, Laughlin SB, Niven JE. (2013) Balanced excitatory and inhibitory synaptic currents promote efficient coding and metabolic efficiency. Plos Computational Biology. 9: e1003263
Sengupta B, Faisal AA, Laughlin SB, et al. (2013) The effect of cell size and channel density on neuronal information encoding and energy efficiency. Journal of Cerebral Blood Flow and Metabolism : Official Journal of the International Society of Cerebral Blood Flow and Metabolism. 33: 1465-73
Stemmler M, Sengupta B, Laughlin S, et al. (2011) Energetically optimal action potentials Advances in Neural Information Processing Systems 24: 25th Annual Conference On Neural Information Processing Systems 2011, Nips 2011
Weckström M, Laughlin S. (2010) Extracellular potentials modify the transfer of information at photoreceptor output synapses in the blowfly compound eye. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 30: 9557-66
Sengupta B, Stemmler M, Laughlin SB, et al. (2010) Action potential energy efficiency varies among neuron types in vertebrates and invertebrates. Plos Computational Biology. 6: e1000840
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