Caries Detection with Near-Infrared Transillumination Using Deep Learning

F. Casalegno; T. Newton; R. Daher; M. Abdelaziz; A. Lodi-Rizzini et al. 

Journal of Dental Research. 2019-08-26.  p. 0022034519871884. DOI : 10.1177/0022034519871884.

A null model of the mouse whole-neocortex micro-connectome

M. W. Reimann; M. Geyaert; Y. Shi; H. Lu; H. Markram et al. 

Nature Communications. 2019-08-29. Vol. 10, p. 3903. DOI : 10.1038/s41467-019-11630-x.

Objective Morphological Classification of Neocortical Pyramidal Cells

L. Kanari; S. Ramaswamy; Y. Shi; S. Morand; J. Meystre et al. 

Cerebral Cortex. 2019-04-01. Vol. 29, num. 4, p. 1719-1735. DOI : 10.1093/cercor/bhy339.

Cortical reliability amid noise and chaos

M. Nolte; M. W. Reimann; J. G. King; H. Markram; E. B. Muller 

Nature Communications. 2019-08-22. Vol. 10, p. 3792. DOI : 10.1038/s41467-019-11633-8.

A Kinetic Map of the Homomeric Voltage-Gated Potassium Channel (Kv) Family

R. Ranjan; E. Logette; M. Marani; M. Herzog; V. Tache et al. 

Frontiers in Cellular Neuroscience. 2019-08-20. Vol. 13, p. 358. DOI : 10.3389/fncel.2019.00358.

Calculated Drude weight and optical gap across the metal-insulator transition in the RVO3 series (R = Sr, Ca, La, Y)

S. Domenech; H. P. Martins; E. B. Guedes; R. J. Ochekoski Mossanek; M. Abbate 

European Physical Journal B. 2019-08-01. Vol. 92, num. 8, p. 169. DOI : 10.1140/epjb/e2019-100187-3.

A Derived Positional Mapping of Inhibitory Subtypes in the Somatosensory Cortex

D. Keller; J. Meystre; R. V. Veettil; O. Burri; R. Guiet et al. 

Frontiers In Neuroanatomy. 2019-08-06. Vol. 13, p. 78. DOI : 10.3389/fnana.2019.00078.

Individual differences in sensory sensitivity: Further lessons from an Autism model

M. R. Favre; H. Markram; K. Markram 

Cognitive Neuroscience. 2019-03-30. Vol. 10, num. 3, p. 171-173. DOI : 10.1080/17588928.2019.1592143.

A Brief History of Simulation Neuroscience

X. Fan; H. Markram 

Frontiers In Neuroinformatics. 2019-05-07. Vol. 13, p. 32. DOI : 10.3389/fninf.2019.00032.

Cellular, Synaptic and Network Effects of Acetylcholine in the Neocortex

C. Colangelo; P. Shichkova; D. Keller; H. Markram; S. Ramaswamy 

Frontiers In Neural Circuits. 2019-04-12. Vol. 13, p. 24. DOI : 10.3389/fncir.2019.00024.

Experimentally-constrained biophysical models of tonic and burst firing modes in thalamocortical neurons

E. Iavarone; J. Yi; Y. Shi; B-J. Zandt; C. O’Reilly et al. 

PLoS Computational Biology. 2019-05-16. Vol. 15, num. 5, p. e1006753. DOI : 10.1371/journal.pcbi.1006753.

A Cell Atlas for the Mouse Brain (vol 12, 84, 2018)

C. Ero; M-O. Gewaltig; D. Keller; H. Markram 

Frontiers In Neuroinformatics. 2019-02-19. Vol. 13, p. 7. DOI : 10.3389/fninf.2019.00007.


A Process for Digitizing and Simulating Biologically Realistic Oligocellular Networks Demonstrated for the Neuro-Glio-Vascular Ensemble

J. S. Coggan; C. Cali; D. Keller; M. Agus; D. Boges et al. 

Frontiers In Neuroscience. 2018-09-25. Vol. 12, p. 664. DOI : 10.3389/fnins.2018.00664.

Data-Driven Modeling of Cholinergic Modulation of Neural Microcircuits: Bridging Neurons, Synapses and Network Activity

S. Ramaswamy; C. Colangelo; H. Markram 

Frontiers In Neural Circuits. 2018-10-09. Vol. 12, p. 77. DOI : 10.3389/fncir.2018.00077.

The physiological variability of channel density in hippocampal CA1 pyramidal cells and interneurons explored using a unified data-driven modeling workflow

R. Migliore; C. A. Lupascu; L. L. Bologna; A. Romani; J-D. Courcol et al. 

Plos Computational Biology. 2018-09-01. Vol. 14, num. 9, p. e1006423. DOI : 10.1371/journal.pcbi.1006423.

A Cell Atlas for the Mouse Brain

C. Eroe; M-O. Gewaltig; D. Keller; H. Markram 

Frontiers In Neuroinformatics. 2018-11-28. Vol. 12, p. 84. DOI : 10.3389/fninf.2018.00084.

Cell Densities in the Mouse Brain: A Systematic Review

D. Keller; C. Ero; H. Markram 

Frontiers In Neuroanatomy. 2018-10-23. Vol. 12, p. 83. DOI : 10.3389/fnana.2018.00083.

NeuroMorphoVis: a collaborative framework for analysis and visualization of neuronal morphology skeletons reconstructed from microscopy stacks

M. Abdellah; J. Hernando; S. Eilemann; S. Lapere; N. Antille et al. 

BIOINFORMATICS. 2018. Vol. 34, num. 13, p. 574-582. DOI : 10.1093/bioinformatics/bty231.

A Topological Representation of Branching Neuronal Morphologies

L. Kanari; P. Dlotko; M. Scolamiero; R. Levi; J. Shillcock et al. 

NEUROINFORMATICS. 2018. Vol. 16, num. 1, p. 3-13. DOI : 10.1007/s12021-017-9341-1.


Timed Synaptic Inhibition Shapes NMDA Spikes, Influencing Local Dendritic Processing and Global I/O Properties of Cortical Neurons

M. Doron; G. Chindemi; E. Muller; H. Markram; I. Segev 

Cell Reports. 2017. Vol. 21, num. 6, p. 1550-1561. DOI : 10.1016/j.celrep.2017.10.035.

On the Structure of Cortical Microcircuits Inferred from Small Sample Sizes

M. Vegue; R. Perin; A. Roxin 

Journal Of Neuroscience. 2017. Vol. 37, num. 35, p. 8498-8510. DOI : 10.1523/Jneurosci.0984-17.2017.

Reconstruction and visualization of large-scale volumetric models of neocortical circuits for physically-plausible in silico optical studies

M. Abdellah; J. Hernando; N. Antille; S. Eilemann; H. Markram et al. 

Bmc Bioinformatics. 2017. Vol. 18, p. 402. DOI : 10.1186/s12859-017-1788-4.

Morphological Diversity Strongly Constrains Synaptic Connectivity and Plasticity

M. W. Reimann; A-L. Horlemann; S. Ramaswamy; E. B. Muller; H. Markram 

Cerebral Cortex. 2017. Vol. 27, num. 9, p. 4570-4585. DOI : 10.1093/cercor/bhx150.

Modeling the metabolic response of astrocytes to neuronal activity

J. Coggan; D. Keller; C. Cal; H. Lehvaslaiho; F. Schurmann et al. 

2017. 13th European Meeting on Glial Cells in Health and Disease, Edinburgh, SCOTLAND, JUL 08-11, 2017. p. E280-E280.

Cliques of Neurons Bound into Cavities Provide a Missing Link between Structure and Function

M. W. Reimann; M. Nolte; M. Scolamiero; K. Turner; R. Perin et al. 

Frontiers In Computational Neuroscience. 2017. Vol. 11, p. 48. DOI : 10.3389/fncom.2017.00048.

Rich cell-type-specific network topology in neocortical microcircuitry

E. Gal; M. London; A. Globerson; S. Ramaswamy; M. W. Reimann et al. 

Nature Neuroscience. 2017. Vol. 20, num. 7, p. 1004-+. DOI : 10.1038/nn.4576.

Bio-physically plausible visualization of highly scattering fluorescent neocortical models for in silico experimentation

M. Abdellah; A. Bilgili; S. Eilemann; J. Shillcock; H. Markram et al. 

Bmc Bioinformatics. 2017. Vol. 18, p. 62. DOI : 10.1186/s12859-016-1444-4.


Distributor of neurons in a neocortical column

G. Khazen; H. Markram; F. Schürmann; M. Telefont 



Single-cell RT-PCR, a technique to decipher the electrical, anatomical, and genetic determinants of neuronal diversity

M. Toledo-Rodriguez; H. Markram 

Methods in molecular biology (Clifton, N.J.). 2014. Vol. 1183, p. 143-58. DOI : 10.1007/978-1-4939-1096-0_8.

The death of Cajal and the end of scientific romanticism and individualism

J. Defelipe; E. Garrido; H. Markram 

Trends In Neurosciences. 2014. Vol. 37, num. 10, p. 525-527. DOI : 10.1016/j.tins.2014.08.002.

Dampened neural activity and abolition of epileptic-like activity in cortical slices by active ingredients of spices

M. Pezzoli; A. Elhamdani; S. Camacho; J. Meystre; S. M. Gonzalez et al. 

Scientific Reports. 2014. Vol. 4, p. 6825. DOI : 10.1038/srep06825.

Synaptic and cellular organization of layer 1 of the developing rat somatosensory cortex

S. Muralidhar; Y. Wang; H. Markram 

Frontiers In Neuroanatomy. 2014. Vol. 7, p. 52. DOI : 10.3389/fnana.2013.00052.

OCTOPUS: Efficient Query Execution on Dynamic Mesh Datasets

F. Tauheed; T. Heinis; F. Schürmann; H. Markram; A. Ailamaki 

2014. 30st International Conference on Data Engineering (ICDE ’14), Chicago, USA, April, 2014.


Correction: Effective Stimuli for Constructing Reliable Neuron Models

S. Druckmann; T. K. Berger; F. Schuermann; S. Hill; H. Markram et al. 

PLoS Computational Biology. 2013. Vol. 9, num. 6. DOI : 10.1371/annotation/c002fbe1-712c-4608-9747-f1185f0b7cf4.

Seven challenges for neuroscience

H. Markram 

Functional neurology. 2013. Vol. 28, num. 3, p. 145-51. DOI : 10.11138/FNeur/2013.28.3.145.

A computer-assisted multi-electrode patch-clamp system

R. Perin; H. Markram 

Journal of visualized experiments : JoVE. 2013. num. 80, p. e50630. DOI : 10.3791/50630.

A Hierarchical Structure of Cortical Interneuron Electrical Diversity Revealed by Automated Statistical Analysis

S. Druckmann; S. Hill; F. Schuermann; H. Markram; I. Segev 

Cerebral Cortex. 2013. Vol. 23, num. 12, p. 2994-3006. DOI : 10.1093/cercor/bhs290.

Nlgn4 knockout induces network hypo-excitability in juvenile mouse somatosensory cortex in vitro

V. Delattre; D. La Mendola; J. Meystre; H. Markram; K. Markram 

Scientific Reports. 2013. Vol. 3, p. 2897. DOI : 10.1038/srep02897.

General developmental health in the VPA-rat model of autism

M. R. Favre; T. R. Barkat; D. Lamendola; G. Khazen; H. Markram et al. 

Frontiers In Behavioral Neuroscience. 2013. Vol. 7. DOI : 10.3389/fnbeh.2013.00088.

A Biophysically Detailed Model of Neocortical Local Field Potentials Predicts the Critical Role of Active Membrane Currents

M. W. Reimann; C. A. Anastassiou; R. Perin; S. L. Hill; H. Markram et al. 

Neuron. 2013. Vol. 79, num. 2, p. 375-390. DOI : 10.1016/j.neuron.2013.05.023.

Neuroscience thinks big (and collaboratively)

E. R. Kandel; H. Markram; P. M. Matthews; R. Yuste; C. Koch 

Nature Reviews Neuroscience. 2013. Vol. 14, num. 9, p. 659-664. DOI : 10.1038/nrn3578.

Preserving axosomatic spiking features despite diverse dendritic morphology

E. Hay; F. Schuermann; H. Markram; I. Segev 

Journal Of Neurophysiology. 2013. Vol. 109, num. 12, p. 2972-2981. DOI : 10.1152/jn.00048.2013.

Computing the size and number of neuronal clusters in local circuits

R. Perin; M. Telefont; H. Markram 

Frontiers In Neuroanatomy. 2013. Vol. 7, p. 1. DOI : 10.3389/fnana.2013.00001.

Matched Pre- and Post-Synaptic Changes Underlie Synaptic Plasticity over Long Time Scales

A. Loebel; J-V. Le Be; M. J. E. Richardson; H. Markram; A. V. M. Herz 

Journal Of Neuroscience. 2013. Vol. 33, num. 15, p. 6257-6266. DOI : 10.1523/Jneurosci.3740-12.2013.

One minute with … Henry Markram

J. Griggs; H. Markram 

New Scientist. 2013. Vol. 217, num. 2903, p. 29-29.

New insights into the classification and nomenclature of cortical GABAergic interneurons

J. Defelipe; P. L. Lopez-Cruz; R. Benavides-Piccione; C. Bielza; P. Larranaga et al. 

Nature Reviews Neuroscience. 2013. Vol. 14, num. 3, p. 202-216. DOI : 10.1038/nrn3444.


Structural to functional synaptic conversion

M. Reimann; H. Markram; F. Schürmann; E. B. Muller; S. Hill et al. 

US9165244; US2014108315.


Physically-based in silico light sheet microscopy for visualizing fluorescent brain models

M. Abdellah; A. Bilgili; S. Eilemann; H. Markram; F. Schürmann 

BMC bioinformatics. 2015. Vol. 16, num. Suppl 11, p. S8. DOI : 10.1186/1471-2105-16-S11-S8.

The neocortical microcircuit collaboration portal: a resource for rat somatosensory cortex

S. Ramaswamy; J-D. Courcol; M. Abdellah; S. R. Adaszewski; N. Antille et al. 

Frontiers In Neural Circuits. 2015. Vol. 9, p. 44. DOI : 10.3389/fncir.2015.00044.

An algorithm to predict the connectome of neural microcircuits

M. W. Reimann; J. G. King; E. B. Muller; S. Ramaswamy; H. Markram 

Frontiers In Computational Neuroscience. 2015. Vol. 9, p. 120. DOI : 10.3389/fncom.2015.00120.

Reconstruction and Simulation of Neocortical Microcircuitry

H. Markram; E. Muller; S. Ramaswamy; M. W. Reimann; M. Abdellah et al. 

Cell. 2015. Vol. 163, num. 2, p. 456-492. DOI : 10.1016/j.cell.2015.09.029.

Anatomy and physiology of the thick-tufted layer 5 pyramidal neuron

S. Ramaswamy; H. Markram 

Frontiers In Cellular Neuroscience. 2015. Vol. 9, p. 233. DOI : 10.3389/fncel.2015.00233.

An Exclusion Zone for Ca2+ Channels around Docked Vesicles Explains Release Control by Multiple Channels at a CNS Synapse

D. Keller; N. Babai; O. Kochubey; Y. Han; H. Markram et al. 

PLoS computational biology. 2015. Vol. 11, num. 5, p. e1004253. DOI : 10.1371/journal.pcbi.1004253.

Network-timing-dependent plasticity

V. Delattre; D. Keller; M. Perich; H. Markram; E. B. Muller 

Frontiers in cellular neuroscience. 2015. Vol. 9, p. 220. DOI : 10.3389/fncel.2015.00220.

Predictable enriched environment prevents development of hyper-emotionality in the VPA rat model of autism

M. R. Favre; D. La Mendola; J. Meystre; D. Christodoulou; M. Cochrane et al. 

Frontiers in Neuroscience. 2015. Vol. 9, num. 127, p. 127. DOI : 10.3389/fnins.2015.00127.

Cell-type- and activity-dependent extracellular correlates of intracellular spiking

C. Anastassiou; R. d. C. Perin; G. Buzsaki; H. Markram; C. Koch 

Journal of Neurophysiology. 2015. Vol. 114, num. 1, p. 608-23. DOI : 10.1152/jn.00628.2014.

A versatile clearing agent for multi-modal brain imaging

I. Costantini; J-P. Ghobril; A. P. Di Giovanna; A. L. A. Mascaro; L. Silvestri et al. 

Scientific Reports. 2015. Vol. 5, num. 9808, p. 1-9. DOI : 10.1038/srep09808.

The future of human cerebral cartography: a novel approach

R. Frackowiak; H. Markram 

Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences. 2015. Vol. 370, num. 1668, p. 20-32. DOI : 10.1098/rstb.2014.0171.

Anti-Obesity and Anti-Hyperglycemic Effects of Cinnamaldehyde via altered Ghrelin Secretion and Functional impact on Food Intake and Gastric Emptying

S. Camacho; S. Michlig; C. De Senarclens-Bezencon; J. Meylan; J. Meystre et al. 

Scientific Reports. 2015. Vol. 5, p. 7919. DOI : 10.1038/srep07919.


From Neuron Biophysics to Orientation Selectivity in Electrically Coupled Networks of Neocortical L2/3 Large Basket Cells

O. Amsalem; W. Van Geit; E. Muller; H. Markram; I. Segev 

Cerebral Cortex. 2016. Vol. 26, num. 8, p. 3655-3668. DOI : 10.1093/cercor/bhw166.

Tight Coupling of Astrocyte pH Dynamics to Epileptiform Activity Revealed by Genetically Encoded pH Sensors

J. V. Raimondo; H. Tomes; A. Irkle; L. Kay; L. Kellaway et al. 

Journal Of Neuroscience. 2016. Vol. 36, num. 26, p. 7002-7013. DOI : 10.1523/Jneurosci.0664-16.2016.

BluePyOpt: Leveraging Open Source Software and Cloud Infrastructure to Optimise Model Parameters in Neuroscience

W. Van Geit; M. Gevaert; G. Chindemi; C. Roessert; J-D. Courcol et al. 

Frontiers In Neuroinformatics. 2016. Vol. 10, p. 17. DOI : 10.3389/fninf.2016.00017.


Organizing neural networks

H. Markram; R. d. C. Perin; T. Berger 

DK2531959; EP2531959; US2015363689; CN102859538; US2012323833; EP2531959; WO2011095342.


Encoding and decoding of information

H. Markram 

CN104901702; CN102648582; US8941512; JP2014209794; US2012313798; US8253607; CN102648582; EP2460276; US2012119926; KR20120046760; US8159373; WO2011012614; US2011025532; WO2011012158; WO2011012614.


Ephaptic coupling of cortical neurons

C. A. Anastassiou; R. Perin; H. Markram; C. Koch 

Nature neuroscience. 2011. Vol. 14, num. 2, p. 217-23. DOI : 10.1038/nn.2727.

Morphological development of thick-tufted layer v pyramidal cells in the rat somatosensory cortex

S. Romand; Y. Wang; M. Toledo-Rodriguez; H. Markram 

Frontiers in neuroanatomy. 2011. Vol. 5, p. 5. DOI : 10.3389/fnana.2011.00005.

A synaptic organizing principle for cortical neuronal groups

R. Perin; T. K. Berger; H. Markram 

Proceedings of the National Academy of Sciences of the United States of America. 2011. Vol. 108, num. 13, p. 5419-24. DOI : 10.1073/pnas.1016051108.

Innate neural assemblies for lego memory

H. Markram; R. Perin 

Frontiers in neural circuits. 2011. Vol. 5, p. 6. DOI : 10.3389/fncir.2011.00006.

Models of neocortical layer 5b pyramidal cells capturing a wide range of dendritic and perisomatic active properties

E. Hay; S. Hill; F. Schürmann; H. Markram; I. Segev 

PLoS computational biology. 2011. Vol. 7, num. 7, p. e1002107. DOI : 10.1371/journal.pcbi.1002107.

Channelpedia: an integrative and interactive database for ion channels

R. Ranjan; G. Khazen; L. Gambazzi; S. Ramaswamy; S. L. Hill et al. 

Frontiers in neuroinformatics. 2011. Vol. 5, p. 36. DOI : 10.3389/fninf.2011.00036.

Introducing the Human Brain Project

H. Markram; K. Meier; T. Lippert; S. Grillner; R. Frackowiak et al. 

2011. 2nd European Future Technologies Conference and Exhibition (FET), Budapest, HUNGARY, May 04-06, 2011. p. 39-42. DOI : 10.1016/j.procs.2011.12.015.

Effective Stimuli for Constructing Reliable Neuron Models

S. Druckmann; T. K. Berger; F. Schuermann; S. Hill; H. Markram et al. 

Plos Computational Biology. 2011. Vol. 7, num. 8, p. e1002133. DOI : 10.1371/journal.pcbi.1002133.

Newsmaker interview: Heny Markram Blue Brain founder responds to critics, clarifies his goals

G. Miller; H. Markram 

Science. 2011. Vol. 334, num. 6057, p. 748-749.

Frontiers research : seek, share & create

H. Markram; K. Markram 

Common knowledge : the challenge of transdisciplinarity; Lausanne, Switzerland: EPFL Press, 2011. p. 145-162.

A history of spike-timing-dependent plasticity

H. Markram; W. Gerstner; P. J. Sjöström 

Frontiers in Synaptic Neuroscience. 2011. Vol. 3, num. 4, p. 1-24. DOI : 10.3389/fnsyn.2011.00004.


Method for in-vitro monitoring of neuronal disorders and use thereof

M. Giugliano; R. Luthi-carter; H. Markram; L. Gambazzi; O. Goekce 

EP2591356; US2013109048; WO2012004778.


A neuron membrane mesh representation for visualization of electrophysiological simulations

S. Lasserre; J. Hernando; S. Hill; F. Schürmann; P. d. M. Anasagasti et al. 

IEEE transactions on visualization and computer graphics. 2012. Vol. 18, num. 2, p. 214-27. DOI : 10.1109/TVCG.2011.55.

Intrinsic morphological diversity of thick-tufted layer 5 pyramidal neurons ensures robust and invariant properties of in silico synaptic connections

S. Ramaswamy; S. L. Hill; J. G. King; F. Schürmann; Y. Wang et al. 

The Journal of physiology. 2012. Vol. 590, num. Pt 4, p. 737-52. DOI : 10.1113/jphysiol.2011.219576.

Combinatorial expression rules of ion channel genes in juvenile rat (Rattus norvegicus) neocortical neurons

G. Khazen; S. L. Hill; F. Schürmann; H. Markram 

PloS One. 2012. Vol. 7, num. 4, p. e34786. DOI : 10.1371/journal.pone.0034786.

The human brain project

H. Markram 

Scientific American. 2012. Vol. 306, num. 6, p. 50-5.

Spike-timing-dependent plasticity: a comprehensive overview

H. Markram; W. Gerstner; P. J. Sjöström 

Frontiers in synaptic neuroscience. 2012. Vol. 4, p. 2. DOI : 10.3389/fnsyn.2012.00002.

Statistical connectivity provides a sufficient foundation for specific functional connectivity in neocortical neural microcircuits

S. L. Hill; Y. Wang; I. Riachi; F. Schürmann; H. Markram 

Proceedings of the National Academy of Sciences of the United States of America. 2012. Vol. 109, num. 42, p. E2885-94. DOI : 10.1073/pnas.1202128109.

Short-term ionic plasticity at GABAergic synapses

J. V. Raimondo; H. Markram; C. J. Akerman 

Frontiers in synaptic neuroscience. 2012. Vol. 4, p. 5. DOI : 10.3389/fnsyn.2012.00005.

The neocortical column

J. DeFelipe; H. Markram; K. S. Rockland 

Frontiers In Neuroanatomy. 2012. Vol. 6, p. 22. DOI : 10.3389/fnana.2012.00022.

SCOUT: Prefetching for Latent Structure Following Queries

F. Tauheed; T. Heinis; F. Schürmann; H. Markram; A. Ailamaki 

2012. 38th International Conference on Very Large Databases (VLDB ’12), Istanbul, Turkey, August, 2012.

Accelerating Range Queries For Brain Simulations

F. Tauheed; L. Biveinis; T. Heinis; F. Schürmann; H. Markram et al. 

2012. 28th International Conference on Data Engineering (ICDE ’12), Washington DC, USA, March, 2012. DOI : 10.1109/Icde.2012.56.


Presynaptic cholinergic action in the hippocampus

M. Segal; V. Greenberger; H. Markram 

EXS. 1989. Vol. 57, p. 88-96.


Electrophysiological characteristics of cholinergic and non-cholinergic neurons in the rat medial septum-diagonal band complex

H. Markram; M. Segal 

Brain research. 1990. Vol. 513, num. 1, p. 171-4.

Acetylcholine potentiates responses to N-methyl-D-aspartate in the rat hippocampus

H. Markram; M. Segal 

Neuroscience letters. 1990. Vol. 113, num. 1, p. 62-5.

Regional changes in NGF receptor immunohistochemical labeling in the septum of the aged rat

H. Markram; M. Segal 

Neurobiology of aging. 1990. Vol. 11, num. 4, p. 481-4.

Long-lasting facilitation of excitatory postsynaptic potentials in the rat hippocampus by acetylcholine

H. Markram; M. Segal 

The Journal of physiology. 1990. Vol. 427, p. 381-93.


Actions of norepinephrine in the rat hippocampus

M. Segal; H. Markram; G. Richter-Levin 

Progress in brain research. 1991. Vol. 88, p. 323-30. DOI : 10.1016/S0079-6123(08)63819-4.

Calcimycin potentiates responses of rat hippocampal neurons to N-methyl-D-aspartate

H. Markram; M. Segal 

Brain research. 1991. Vol. 540, num. 1-2, p. 322-4.


The inositol 1,4,5-trisphosphate pathway mediates cholinergic potentiation of rat hippocampal neuronal responses to NMDA

H. Markram; M. Segal 

The Journal of physiology. 1992. Vol. 447, p. 513-33.

Spontaneous recovery of deficits in spatial memory and cholinergic potentiation of NMDA in CA1 neurons during chronic lithium treatment

G. Richter-Levin; H. Markram; M. Segal 

Hippocampus. 1992. Vol. 2, num. 3, p. 279-86. DOI : 10.1002/hipo.450020307.

Activation of protein kinase C suppresses responses to NMDA in rat CA1 hippocampal neurones

H. Markram; M. Segal 

The Journal of physiology. 1992. Vol. 457, p. 491-501.


Calcium transients in dendrites of neocortical neurons evoked by single subthreshold excitatory postsynaptic potentials via low-voltage-activated calcium channels

H. Markram; B. Sakmann 

Proceedings of the National Academy of Sciences of the United States of America. 1994. Vol. 91, num. 11, p. 5207-11.


Dendritic calcium transients evoked by single back-propagating action potentials in rat neocortical pyramidal neurons

H. Markram; P. J. Helm; B. Sakmann 

The Journal of physiology. 1995. Vol. 485 ( Pt 1), p. 1-20.


Redistribution of synaptic efficacy: a mechanism to generate infinite synaptic input diversity from a homogeneous population of neurons without changing absolute synaptic efficacies

H. Markram; M. Tsodyks 

Journal of physiology, Paris. 1996. Vol. 90, num. 3-4, p. 229-32.

Frequency and dendritic distribution of autapses established by layer 5 pyramidal neurons in the developing rat neocortex: comparison with synaptic innervation of adjacent neurons of the same class

J. Lübke; H. Markram; M. Frotscher; B. Sakmann 

The Journal of neuroscience : the official journal of the Society for Neuroscience. 1996. Vol. 16, num. 10, p. 3209-18.

Redistribution of synaptic efficacy between neocortical pyramidal neurons

H. Markram; M. Tsodyks 

Nature. 1996. Vol. 382, num. 6594, p. 807-10. DOI : 10.1038/382807a0.


Regulation of synaptic efficacy by coincidence of postsynaptic APs and EPSPs

H. Markram; J. Lübke; M. Frotscher; B. Sakmann 

Science (New York, N.Y.). 1997. Vol. 275, num. 5297, p. 213-5.

The neural code between neocortical pyramidal neurons depends on neurotransmitter release probability

M. V. Tsodyks; H. Markram 

Proceedings of the National Academy of Sciences of the United States of America. 1997. Vol. 94, num. 2, p. 719-23.

Physiology and anatomy of synaptic connections between thick tufted pyramidal neurones in the developing rat neocortex

H. Markram; J. Lübke; M. Frotscher; A. Roth; B. Sakmann 

The Journal of physiology. 1997. Vol. 500, num. 2, p. 409-40. DOI : 10.1113/jphysiol.1997.sp022031.

A network of tufted layer 5 pyramidal neurons

H. Markram 

Cerebral cortex (New York, N.Y. : 1991). 1997. Vol. 7, num. 6, p. 523-33.

Neural codes: firing rates and beyond

W. Gerstner; A. K. Kreiter; H. Markram; A. V. M. Herz 

Proc. Natl. Acad. Sci. USA. 1997. Vol. 94, num. 24, p. 12740-12741. DOI : 10.1073/pnas.94.24.12740.


Differential signaling via the same axon of neocortical pyramidal neurons

H. Markram; Y. Wang; M. Tsodyks 

Proceedings of the National Academy of Sciences of the United States of America. 1998. Vol. 95, num. 9, p. 5323-8.

Neural networks with dynamic synapses

M. Tsodyks; K. Pawelzik; H. Markram 

Neural computation. 1998. Vol. 10, num. 4, p. 821-35.

Competitive calcium binding: implications for dendritic calcium signaling

H. Markram; A. Roth; F. Helmchen 

Journal of computational neuroscience. 1998. Vol. 5, num. 3, p. 331-48.

Potential for multiple mechanisms, phenomena and algorithms for synaptic plasticity at single synapses

H. Markram; D. Pikus; A. Gupta; M. Tsodyks 

Neuropharmacology. 1998. Vol. 37, num. 4-5, p. 489-500.

Information processing with frequency-dependent synaptic connections

H. Markram; A. Gupta; A. Uziel; Y. Wang; M. Tsodyks 

Neurobiology of learning and memory. 1998. Vol. 70, num. 1-2, p. 101-12. DOI : 10.1006/nlme.1998.3841.


Anatomical and functional differentiation of glutamatergic synaptic innervation in the neocortex

Y. Wang; A. Gupta; H. Markram 

Journal of physiology, Paris. 1999. Vol. 93, num. 4, p. 305-17.


Synchrony generation in recurrent networks with frequency-dependent synapses

M. Tsodyks; A. Uziel; H. Markram 

The Journal of neuroscience : the official journal of the Society for Neuroscience. 2000. Vol. 20, num. 1, p. RC50.

Organizing principles for a diversity of GABAergic interneurons and synapses in the neocortex

A. Gupta; Y. Wang; H. Markram 

Science (New York, N.Y.). 2000. Vol. 287, num. 5451, p. 273-8.


An algorithm for modifying neurotransmitter release probability based on pre- and postsynaptic spike timing

W. Senn; H. Markram; M. Tsodyks 

Neural computation. 2001. Vol. 13, num. 1, p. 35-67.


Fully implicit parallel simulation of single neurons

M. L. Hines; H. Markram; F. Schürmann 

Journal of computational neuroscience. 2008. Vol. 25, num. 3, p. 439-48. DOI : 10.1007/s10827-008-0087-5.

Slow oscillations in neural networks with facilitating synapses

O. Melamed; O. Barak; G. Silberberg; H. Markram; M. Tsodyks 

Journal of computational neuroscience. 2008. Vol. 25, num. 2, p. 308-16. DOI : 10.1007/s10827-008-0080-z.

Hyper-connectivity and hyper-plasticity in the medial prefrontal cortex in the valproic Acid animal model of autism

T. Rinaldi; C. Perrodin; H. Markram 

Frontiers in neural circuits. 2008. Vol. 2, p. 4. DOI : 10.3389/neuro.04.004.2008.

Evaluating automated parameter constraining procedures of neuron models by experimental and surrogate data

S. Druckmann; T. K. Berger; S. Hill; F. Schürmann; H. Markram et al. 

Biological cybernetics. 2008. Vol. 99, num. 4-5, p. 371-9. DOI : 10.1007/s00422-008-0269-2.

Minimal Hodgkin-Huxley type models for different classes of cortical and thalamic neurons

M. Pospischil; M. Toledo-Rodriguez; C. Monier; Z. Piwkowska; T. Bal et al. 

Biological cybernetics. 2008. Vol. 99, num. 4-5, p. 427-41. DOI : 10.1007/s00422-008-0263-8.

Fixing the location and dimensions of functional neocortical columns

H. Markram 

HFSP journal. 2008. Vol. 2, num. 3, p. 132-5. DOI : 10.2976/1.2919545.

Multisensory integration of dynamic voices and faces in the monkey brain

C. Perrodin; C. I. Petkov; N. K. Logothetis; H. Markram 


Hyperconnectivity of Local Neocortical Microcircuitry Induced by Prenatal Exposure to Valproic Acid

T. Rinaldi; G. Silberberg; H. Markram 

Cereb Cortex. 2008. Vol. 18, num. 4, p. 763-70. DOI : 10.1093/cercor/bhm117.

Inferring connection proximity in networks of electrically coupled cells by subthreshold frequency response analysis

C. Cali; T. K. Berger; M. Pignatelli; A. Carleton; H. Markram et al. 

J Comput Neurosci. 2008. Vol. 24, num. 3, p. 330-345. DOI : 10.1007/s10827-007-0058-2.

Abnormal fear conditioning and amygdala processing in an animal model of autism

K. Markram; T. Rinaldi; D. La Mendola; C. Sandi; H. Markram 

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology. 2008. Vol. 33, num. 4, p. 901-12. DOI : 10.1038/sj.npp.1301453.

Identifying, tabulating, and analyzing contacts between branched neuron morphologies

J. Kozloski; K. Sfyrakis; S. Hill; F. Schürmann; C. Peck et al. 

IBM Journal of Research and Development. 2008. Vol. 52, num. 1/2, p. 43-55.


Single-cell RT-PCR, a technique to decipher the electrical, anatomical, and genetic determinants of neuronal diversity

M. Toledo-Rodriguez; H. Markram 

Methods in molecular biology (Clifton, N.J.). 2007. Vol. 403, p. 123-39. DOI : 10.1007/978-1-59745-529-9_8.

Methods For Treating And/Or Preventing Pervasive Developmental Disorders In A Subject

H. Markram; T. Rinaldi; T. Markram; M. Rodriguez Bravo; B. Mattson et al. 

WO2007029063; WO2007029063.


Disynaptic inhibition between neocortical pyramidal cells mediated by Martinotti cells

G. Silberberg; H. Markram 

Neuron. 2007. Vol. 53, num. 5, p. 735-46. DOI : 10.1016/j.neuron.2007.02.012.

Elevated NMDA receptor levels and enhanced postsynaptic long-term potentiation induced by prenatal exposure to valproic acid

T. Rinaldi; K. Kulangara; K. Antoniello; H. Markram 

Proceedings Of The National Academy Of Sciences Of The United States Of America. 2007. Vol. 104, num. 33, p. 13501-6. DOI : 10.1073/pnas.0704391104.

Interfacing neurons with carbon nanotubes: electrical signal transfer and synaptic stimulation in cultured brain circuits

A. Mazzatenta; M. Giugliano; S. Campidelli; L. Gambazzi; L. Businaro et al. 

Journal of Neuroscience. 2007. Vol. 27, num. 26, p. 6931-6936. DOI : 10.1523/JNEUROSCI.1051-07.2007.

The intense world syndrome – an alternative hypothesis for autism

H. Markram; T. Rinaldi; K. Markram 

Front. Neurosci.. 2007. Vol. 1, num. 1, p. 77-96. DOI : 10.3389/neuro.

Bioinformatics: industrializing neuroscience

H. Markram 

Nature. 2007. Vol. 445, num. 7124, p. 160-1. DOI : 10.1038/445160a.

Morphological, electrophysiological, and synaptic properties of corticocallosal pyramidal cells in the neonatal rat neocortex

J. V. Le Be; G. Silberberg; Y. Wang; H. Markram 

Cereb Cortex. 2007. Vol. 17, num. 9, p. 2204-13. DOI : 10.1093/cercor/bhl127.

A novel multiple objective optimization framework for constraining conductance-based neuron models by experimental data

S. Druckmann; Y. Banitt; A. Gidon; F. Schürmann; H. Markram et al. 

Front. Neurosci.. 2007. Vol. 1, num. 1, p. 7-18. DOI : 10.3389/neuro.


Enhanced long-term microcircuit plasticity in the valproic Acid animal model of autism

G. T. Silva; J-V. Le Bé; I. Riachi; T. Rinaldi; K. Markram et al. 

Frontiers in synaptic neuroscience. 2009. Vol. 1, p. 1. DOI : 10.3389/neuro.19.001.2009.

A Component-Based Extension Framework for Large-Scale Parallel Simulations in NEURON

J. G. King; M. Hines; S. Hill; P. H. Goodman; H. Markram et al. 

Frontiers in neuroinformatics. 2009. Vol. 3, p. 10. DOI : 10.3389/neuro.11.010.2009.

Multiquantal release underlies the distribution of synaptic efficacies in the neocortex

A. Loebel; G. Silberberg; D. Helbig; H. Markram; M. Tsodyks et al. 

Frontiers in computational neuroscience. 2009. Vol. 3, p. 27. DOI : 10.3389/neuro.10.027.2009.

Carbon nanotubes might improve neuronal performance by favouring electrical shortcuts

G. Cellot; E. Cilia; S. Cipollone; V. Rancic; A. Sucapane et al. 

Nature Nanotechnology. 2009. Vol. 4, p. 126-133. DOI : 10.1038/NNANO.2008.374.

Frequency-dependent disynaptic inhibition in the pyramidal network: a ubiquitous pathway in the developing rat neocortex

T. K. Berger; R. Perin; G. Silberberg; H. Markram 

Journal Of Physiology-London. 2009. Vol. 587, p. 5411-5425. DOI : 10.1113/jphysiol.2009.176552.

Substrate arrays of iridium oxide microelectrodes for in-vitro neuronal interfacing

S. Gawad; M. Giugliano; M. O. Heuschkel; B. Wessling; H. Markram et al. 

Frontiers in Neuroengineering. 2009. Vol. 2, p. 1.1-1.7. DOI : 10.3389/neuro.16.001.2009.


The intense world theory – a unifying theory of the neurobiology of autism

K. Markram; H. Markram 

Frontiers in human neuroscience. 2010. Vol. 4, p. 224. DOI : 10.3389/fnhum.2010.00224.

Brief Bursts Self-Inhibit and Correlate the Pyramidal Network

T. K. Berger; G. Silberberg; R. Perin; H. Markram 

Plos Biology. 2010. Vol. 8, num. 9, p. e1000473. DOI : 10.1371/journal.pbio.1000473.

Diminished activity-dependent brain-derived neurotrophic factor expression underlies cortical neuron microcircuit hypoconnectivity resulting from exposure to mutant huntingtin fragments

L. Gambazzi; O. Gokce; T. Seredenina; E. Katsyuba; H. Runne et al. 

The Journal of pharmacology and experimental therapeutics. 2010. Vol. 335, num. 1, p. 13-22. DOI : 10.1124/jpet.110.167551.

Emergent Dynamics in Neocortical Microcircuits

R. d. C. Perin / H. Markram (Dir.)  

Lausanne, EPFL, 2010. 


The blue brain project

H. Markram 

Nat Rev Neurosci. 2006. Vol. 7, num. 2, p. 153-60. DOI : 10.1038/nrn1848.

Heterogeneity in the pyramidal network of the medial prefrontal cortex

Y. Wang; H. Markram; P. H. Goodman; T. K. Berger; J. Ma et al. 

Nat Neurosci. 2006. Vol. 9, num. 4, p. 534-42. DOI : 10.1038/nn1670.

Parallel network simulations with NEURON

M. Migliore; C. Cannia; W. W. Lytton; H. Markram; M. L. Hines 

J Comput Neurosci. 2006. Vol. 21, num. 2, p. 119-29. DOI : 10.1007/s10827-006-7949-5.

Spontaneous and evoked synaptic rewiring in the neonatal neocortex

J. V. Le Be; H. Markram 

Proceedings Of The National Academy Of Sciences Of The United States Of America. 2006. Vol. 103, num. 35, p. 13214-9. DOI : 10.1073/pnas.0604691103.

[A new mechanism for memory: neuronal networks rewiring in the young rat neocortex]

J. V. Le Be; H. Markram 

Med Sci (Paris). 2006. Vol. 22, num. 12, p. 1031-3. DOI : 10.1051/medsci/200622121031.

Dynamical principles for neuroscience and intelligent biomimetic devices

A. Ijspeert; J. Buchli; A. Selverston; M. Rabinovich; M. Hasler et al. 

Lausanne: EPFL, 2006.


Synaptic pathways in neural microcircuits

G. Silberberg; S. Grillner; F. E. LeBeau; R. Maex; H. Markram 

Trends Neurosci. 2005. Vol. 28, num. 10, p. 541-51. DOI : 10.1016/j.tins.2005.08.004.

Microcircuits in action–from CPGs to neocortex

S. Grillner; H. Markram; E. De Schutter; G. Silberberg; F. E. LeBeau 

Trends Neurosci. 2005. Vol. 28, num. 10, p. 525-33. DOI : 10.1016/j.tins.2005.08.003.

Neuropeptide and calcium-binding protein gene expression profiles predict neuronal anatomical type in the juvenile rat

M. Toledo-Rodriguez; P. Goodman; M. Illic; C. Wu; H. Markram 

J Physiol. 2005. Vol. 567, num. Pt 2, p. 401-13. DOI : 10.1113/jphysiol.2005.089250.

NEOBASE: databasing the neocortical microcircuit

A. J. Muhammad; H. Markram 

Stud Health Technol Inform. 2005. Vol. 112, p. 167-77.

The neocortical microcircuit as a tabula rasa

N. Kalisman; G. Silberberg; H. Markram 

Proceedings Of The National Academy Of Sciences Of The United States Of America. 2005. Vol. 102, num. 3, p. 880-5. DOI : 10.1073/pnas.0407088102.

The Neocortical Microcircuit Database (NMDB)

H. Markram; X. Luo; G. Silberberg; M. Toledo-Rodriguez; A. Gupta 

Databasing the Brain: From Data to Knowledge (Neuroinformatics); Wiley Press, 2005. p. 327-342.

Subthreshold cross-correlations between cortical neurons: A reference model with static synapses

O. Melamed; G. Silberberg; H. Markram; W. Gerstner; M. J. E. Richardson 

NEUROCOMPUTING. 2005. num. 65-66, p. 685-690. DOI : 10.1016/j.neucom.2004.10.098.

Short-term-plasticity orchestrates the response of pyramidal cells and interneurons to population bursts

M. J. E. Richardson; O. Melamed; G. Silberberg; W. Gerstner; H. Markram 

Journal of Computational Neuroscience. 2005. Vol. 18, p. 323-331. DOI : 10.1007/s10827-005-0434-8.


Anatomical, physiological and molecular properties of Martinotti cells in the somatosensory cortex of the juvenile rat

Y. Wang; M. Toledo-Rodriguez; A. Gupta; C. Wu; G. Silberberg et al. 

J Physiol. 2004. Vol. 561, num. Pt 1, p. 65-90. DOI : 10.1113/jphysiol.2004.073353.

Correlation maps allow neuronal electrical properties to be predicted from single-cell gene expression profiles in rat neocortex

M. Toledo-Rodriguez; B. Blumenfeld; C. Wu; J. Luo; B. Attali et al. 

Cereb Cortex. 2004. Vol. 14, num. 12, p. 1310-27. DOI : 10.1093/cercor/bhh092.

Synaptic dynamics control the timing of neuronal excitation in the activated neocortical microcircuit

G. Silberberg; C. Wu; H. Markram 

J Physiol. 2004. Vol. 556, num. Pt 1, p. 19-27. DOI : 10.1113/jphysiol.2004.060962.

Dynamics of population rate codes in ensembles of neocortical neurons

G. Silberberg; M. Bethge; H. Markram; K. Pawelzik; M. Tsodyks 

Journal of Neurophysiology. 2004. Vol. 91, num. 2, p. 704-709. DOI : 10.1152/jn.00415.2003.

Fading memory and kernel properties of generic cortical microcircuit models

W. Maass; T. Natschlager; H. Markram 

J Physiol Paris. 2004. Vol. 98, num. 4-6, p. 315-30. DOI : 10.1016/j.jphysparis.2005.09.020.

Computational Models for Generic Cortical Microcircuits

W. Maass; T. Natschläger; H. Markram 

Computational Neuroscience: A Comprehensive Approach; Chapman & Hall/CRC, 2004. p. 575-605.

Interneuron Heterogeneity in the Neocortex

A. Gupta; M. Toledo-Rodriguez; G. Silberberg; H. Markram 

Excitatory-Inhibitory Balance: Synapses, Circuits, Systems; Kluwer Academic Publishing, 2004.

Interneuron Diversity series: Molecular and genetic tools to study GABAergic interneuron diversity and function

H. Monyer; H. Markram 

Trends Neurosci. 2004. Vol. 27, num. 2, p. 90-7. DOI : 10.1016/j.tins.2003.12.008.

Interneurons of the neocortical inhibitory system

H. Markram; M. Toledo-Rodriguez; Y. Wang; A. Gupta; G. Silberberg et al. 

Nat Rev Neurosci. 2004. Vol. 5, num. 10, p. 793-807. DOI : 10.1038/nrn1519.

Coding and Learning of behavioral sequences

O. Melamed; W. Gerstner; W. Maass; M. Tsodyks; H. Markram 

Trends in Neurosciences. 2004. Vol. 27, num. 1, p. 11-14. DOI : 10.1016/j.tins.2003.10.014.


Preface to the Special Issue

J. F. Linden; H. Markram 

Cerebral Cortex. 2003. Vol. 13, num. 1, p. 1. DOI : 10.1093/cercor/13.1.1.

Deriving physical connectivity from neuronal morphology

N. Kalisman; G. Silberberg; H. Markram 

Biol Cybern. 2003. Vol. 88, num. 3, p. 210-8. DOI : 10.1007/s00422-002-0377-3.

Perspectives of the high-dimensional dynamics of neural microcircuits from the point of view of low-dimensional readouts

S. Häusler; H. Markram; W. Maass 

Complexity. 2003. Vol. 8, num. 4, p. 39-50. DOI : 10.1002/cplx.10089.

Computer models and analysis tools for neural microcircuits

T. Natschläger; H. Markram; W. Maass 

Neuroscience Databases: A Practical Guide,; Kluwer Academic Publishers, 2003. p. 123-138.

Temporal integration in recurrent microcircuits

W. Maass; H. Markram 

The Handbook of Brain Theory and Neural Networks; MIT Press, 2003. p. 1159-1163.

Input prediction and autonomous movement analysis in recurrent circuits of spiking neurons

R. Legenstein; H. Markram; W. Maass 

Rev Neurosci. 2003. Vol. 14, num. 1-2, p. 5-19.

A Model for Real-Time Computation in Generic Neural Microcircuits

W. Maass; T. Natschläger; H. Markram; S. Becker; S. Thrun et al. 

2003. NIPS 2002, Vancouver, British Columbia, December 12-14, 2002.


Anatomical, physiological, molecular and circuit properties of nest basket cells in the developing somatosensory cortex

Y. Wang; A. Gupta; M. Toledo-Rodriguez; C. Z. Wu; H. Markram 

Cereb Cortex. 2002. Vol. 12, num. 4, p. 395-410. DOI : 10.1093/cercor/12.4.395.

The “Liquid Computer”: A Novel Strategy for Real-Time Computing on Time Series

T. Natschläger; W. Maass; H. Markram 

Special Issue on Foundations of Information Processing of TELEMATIK. 2002. Vol. 8, num. 1, p. 39-43.

Real-time computing without stable states: a new framework for neural computation based on perturbations

W. Maass; T. Natschlager; H. Markram 

Neural Comput. 2002. Vol. 14, num. 11, p. 2531-60. DOI : 10.1162/089976602760407955.

Synapses as dynamic memory buffers

W. Maass; H. Markram 

Neural Networks. 2002. Vol. 15, num. 2, p. 155-161. DOI : 10.1016/S0893-6080(01)00144-7.

Coding of temporal information by activity-dependent synapses

G. Fuhrmann; I. Segev; H. Markram; M. Tsodyks 

J Neurophysiol. 2002. Vol. 87, num. 1, p. 140-8.

Spike frequency adaptation and neocortical rhythms

G. Fuhrmann; H. Markram; M. Tsodyks 

Journal of Neurophysiology. 2002. Vol. 88, num. 2, p. 761-770.

Stereotypy in neocortical microcircuits

G. Silberberg; A. Gupta; H. Markram 

Trends Neurosci. 2002. Vol. 25, num. 5, p. 227-30.

A New Approach towards Vision Suggested by Biologically Realistic Neural Microcircuit Models

W. Maass; R. A. Legenstein; H. Markram; H. H. Buelthoff; S. W. Lee et al. 

2002. Second International Workshop, BMCV 2002, Tübingen, Germany, November 22-24, 2002. p. 282-293.