Publications

Highlights

Morphology, physiology and synaptic connectivity of local interneurons in the mouse somatosensory thalamus
“Morphology, physiology and synaptic connectivity of local interneurons in the mouse somatosensory thalamus”, Jane Simko and Henry Markram, The Journal of Physiology, November 2021

2025

Higher-order interactions in neuronal function: From genes to ionic currents in biophysical models

M. Reva; A. Arnaudon; M. Zbili; A. Makkeh; H. Markram et al. 

Proceedings of the National Academy of Sciences. 2025. Vol. 122, num. 40. DOI : 10.1073/pnas.2500048122.

N-glycosylation modulates the inactivation kinetics of the Kv3.4 ion channel

R. Ranjan; E. Logette; M. Herzog; V. Buchillier; E. Scantamburlo et al. 

iScience. 2025. Vol. 28, num. 9, p. 113409. DOI : 10.1016/j.isci.2025.113409.

Biophysical modeling of thalamic reticular nucleus subpopulations and their differential contribution to spindle dynamics

P. Litvak; N. D. Hartley; R. Kast; G. Feng; Z. Fu et al. 

iScience. 2025. Vol. 28, num. 9, p. 113393. DOI : 10.1016/j.isci.2025.113393.

Of mice and men: Dendritic architecture differentiates human from mouse neuronal networks

L. Kanari; Y. Shi; A. Arnaudon; N. Barros-Zulaica; R. Benavides-Piccione et al. 

iScience. 2025. Vol. 28, num. 7, p. 112928. DOI : 10.1016/j.isci.2025.112928.

A multiscale electro-metabolic model of a rat neocortical circuit reveals the impact of ageing on central cortical layers

S. Farina; A. Cattabiani; D. Mandge; P. Shichkova; J. B. Isbister et al. 

PLOS Computational Biology. 2025. Vol. 21, num. 5. DOI : 10.1371/journal.pcbi.1013070.

Seizure and redox rescue in a model of glucose transport deficiency

J. S. Coggan; P. Shichkova; H. Markram; D. Keller 

PLoS Computational Biology. 2025. Vol. 21, num. 4, p. e1012959. DOI : 10.1371/journal.pcbi.1012959.

Computational Generation of Long-range Axonal Morphologies

A. Berchet; R. Petkantchin; H. Markram; L. Kanari 

NEUROINFORMATICS. 2025. Vol. 23, num. 1. DOI : 10.1007/s12021-024-09696-0.

2024

Cell density quantification of high resolution Nissl images of the juvenile rat brain

J. Meystre; J. Jacquemier; O. Burri; C. Zsolnai; N. Frank et al. 

Frontiers In Neuroanatomy. 2024. Vol. 18, p. 1463632. DOI : 10.3389/fnana.2024.1463632.

Nissl_3, Raw images for Machine learning for histological annotation and quantification of cortical layers.

J. Meystre 

2024.

Nissl_5, Raw images for Machine learning for histological annotation and quantification of cortical layers

J. Meystre 

2024.

Nissl_2, Raw images for Machine learning for histological annotation and quantification of cortical layers.

J. Meystre 

2024.

Nissl_4, Raw images for Machine learning for histological annotation and quantification of cortical layers.

J. Meystre 

2024.

Fear learning induces synaptic potentiation between engram neurons in the rat lateral amygdala

M. Abatis; R. Perin; R. Niu; E. van den Burg; C. Hegoburu et al. 

Nature Neuroscience. 2024. DOI : 10.1038/s41593-024-01676-6.

Nissl_1, Raw images for Machine learning for histological annotation and quantification of cortical layers

J. Meystre 

2024.

Supplementary files for Machine learning for histological annotation and quantification of cortical layers

J. Meystre; O. Burri 

2024.

Nissl_6, Raw images for Machine learning for histological annotation and quantification of cortical layers

J. Meystre 

2024.

2023

Transcriptional maintenance of cortical somatostatin interneuron subtype identity during migration

H. Munguba; K. Nikouei; H. Hochgerner; P. Oberst; A. Kouznetsova et al. 

Neuron. 2023. Vol. 111, num. 22. DOI : 10.1016/j.neuron.2023.07.018.

Neuronal growth on high-aspect-ratio diamond nanopillar arrays for biosensing applications

E. Losero; S. Jagannath; M. Pezzoli; V. Goblot; H. Babashah et al. 

Scientific Reports. 2023. Vol. 13, num. 1. DOI : 10.1038/s41598-023-32235-x.

2022

A calcium-based plasticity model for predicting long-term potentiation and depression in the neocortex

G. Chindemi; M. Abdellah; O. Amsalem; R. Benavides-Piccione; V. Delattre et al. 

Nature Communications. 2022. Vol. 13, num. 1, p. 3038. DOI : 10.1038/s41467-022-30214-w.

2021

Homeostatic regulation of axonal Kv1.1 channels accounts for both synaptic and intrinsic modifications in the hippocampal CA3 circuit

M. Zbili; S. Rama; M-J. Benitez; L. Fronzaroli-Molinieres; A. Bialowas et al. 

Proceedings Of The National Academy Of Sciences Of The United States Of America (PNAS). 2021. Vol. 118, num. 47, p. e2110601118. DOI : 10.1073/pnas.2110601118j1of12.

Morphology, physiology and synaptic connectivity of local interneurons in the mouse somatosensory thalamus

J. Simko; H. Markram 

Journal Of Physiology. 2021. Vol. 599, num. 22, p. 5085 – 5101. DOI : 10.1113/JP281711.

Temporal stability of stimulus representation increases along rodent visual cortical hierarchies

E. Piasini; L. Soltuzu; P. Muratore; R. Caramellino; K. Vinken et al. 

Nature Communications. 2021. Vol. 12, num. 1, p. 4448. DOI : 10.1038/s41467-021-24456-3.

Cellpose training data and scripts from “Machine learning for histological annotation and quantification of cortical layers”

J. Jacquemier; J. Meystre; O. Burri 

2021.

Rodent somatosensory thalamocortical circuitry: Neurons, synapses, and connectivity

C. O’Reilly; E. Iavarone; J. Yi; S. L. Hill 

Neuroscience And Biobehavioral Reviews. 2021. Vol. 126, p. 213 – 235. DOI : 10.1016/j.neubiorev.2021.03.015.

Engram cell connectivity: an evolving substrate for information storage

T. J. Ryan; C. O-d. San Luis; M. Pezzoli; S. Sen 

Current Opinion In Neurobiology. 2021. Vol. 67, p. 215 – 225. DOI : 10.1016/j.conb.2021.01.006.

Thalamic microcircuitry: neurons, synapses, and circuit motifs in receptive field structure and sensory processing

J. Yi / H. Markram; S. L. Hill (Dir.)  

Lausanne, EPFL, 2021. 

2020

GABA-mediated tonic inhibition differentially modulates gain in functional subtypes of cortical interneurons

A. Bryson; R. J. Hatch; B-J. Zandt; C. Rossert; S. F. Berkovic et al. 

Proceedings Of The National Academy Of Sciences Of The United States Of America (PNAS). 2020. Vol. 117, num. 6, p. 3192 – 3202. DOI : 10.1073/pnas.1906369117.

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

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

2020. 64th Annual Meeting of the Biophysical-Society, San Diego, CA, Feb 15-19, 2020. p. 108A – 108A. DOI : 10.1016/j.bpj.2019.11.739.

Impact of higher order network structure on emergent cortical activity

M. Nolte; E. Gal; H. Markram; M. W. Reimann 

Network Neuroscience. 2020. Vol. 4, num. 1, p. 292 – 314. DOI : 10.1162/netn_a_00124.

2019

Inferring and validating mechanistic models of neural microcircuits based on spike-train data

J. Ladenbauer; S. McKenzie; D. F. English; O. Hagens; S. Ostojic 

Nature Communications. 2019. Vol. 10, p. 4933. DOI : 10.1038/s41467-019-12572-0.

Estimating the Readily-Releasable Vesicle Pool Size at Synaptic Connections in the Neocortex

N. Barros-Zulaica; J. Rahmon; G. Chindemi; R. Perin; H. Markram et al. 

Frontiers In Synaptic Neuroscience. 2019. Vol. 11, p. 29. DOI : 10.3389/fnsyn.2019.00029.

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. Vol. 10, p. 3903. DOI : 10.1038/s41467-019-11630-x.

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.  p. 0022034519871884. DOI : 10.1177/0022034519871884.

Cortical reliability amid noise and chaos

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

Nature Communications. 2019. 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. Vol. 13, p. 358. DOI : 10.3389/fncel.2019.00358.

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. Vol. 13, p. 78. DOI : 10.3389/fnana.2019.00078.

A Text Mining Pipeline Using Active and Deep Learning Aimed at Curating Information in Computational Neuroscience

M. Shardlow; M. Ju; M. Li; C. O’Reilly; E. Iavarone et al. 

Neuroinformatics. 2019. Vol. 17, num. 3, p. 391 – 406. DOI : 10.1007/s12021-018-9404-y.

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. Vol. 15, num. 5, p. e1006753. DOI : 10.1371/journal.pcbi.1006753.

A Brief History of Simulation Neuroscience

X. Fan; H. Markram 

Frontiers In Neuroinformatics. 2019. 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. Vol. 13, p. 24. DOI : 10.3389/fncir.2019.00024.

Objective Morphological Classification of Neocortical Pyramidal Cells

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

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

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

M. R. Favre; H. Markram; K. Markram 

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

Corrigendum: A Cell Atlas for the Mouse Brain

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

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

Untangling emergent cortical dynamics: neurons from networks, noise from chaos

M. C. Nolte / H. Markram; E. B. Muller (Dir.)  

Lausanne, EPFL, 2019. 

In Silico Voltage-Sensitive Dye Imaging: A Model-Based Approach for Bridging Scales of Cortical Activity

T. H. Newton / H. Markram (Dir.)  

Lausanne, EPFL, 2019. 

2018

A Cell Atlas for the Mouse Brain

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

Frontiers In Neuroinformatics. 2018. 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. Vol. 12, p. 83. DOI : 10.3389/fnana.2018.00083.

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. Vol. 12, p. 77. DOI : 10.3389/fncir.2018.00077.

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. Vol. 12, p. 664. DOI : 10.3389/fnins.2018.00664.

Data-driven reconstruction of a point neuron mouse brain

C. Erö / H. Markram; M-O. Gewaltig (Dir.)  

Lausanne, EPFL, 2018. 

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.

Genetic identification of brain cell types underlying schizophrenia

N. Skene; J. Bryois; T. Bakken; G. Breen; J. Crowley et al. 

Nature Genetics. 2018. Vol. 50, num. 6, p. 825 – 833. DOI : 10.1038/s41588-018-0129-5.

Dynamical response properties of neocortical neurons to conductance-driven time-varying inputs

D. Linaro; I. Biro; M. Giugliano 

European Journal of Neuroscience. 2018. Vol. 47, num. 1, p. 17 – 32. DOI : 10.1111/ejn.13761.

2017

The Crossed Projection to the Striatum in Two Species of Monkey and in Humans: Behavioral and Evolutionary Significance

G. M. Innocenti; T. B. Dyrby; K. W. Andersen; E. M. Rouiller; R. Caminiti 

Cerebral Cortex. 2017. Vol. 27, num. 6, p. 3217 – 3230. DOI : 10.1093/cercor/bhw161.

Neurogenic Radial Glia-like Cells in Meninges Migrate and Differentiate into Functionally Integrated Neurons in the Neonatal Cortex

F. Bifari; I. Decimo; A. Pino; E. Llorens-Bobadilla; S. Zhao et al. 

Cell Stem Cell. 2017. Vol. 20, num. 3, p. 360 – 373.e7. DOI : 10.1016/j.stem.2016.10.020.

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.

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.

All-diamond functional surface micro-electrode arrays for brain-slice neural analysis

F. Vahidpour; L. Curley; I. Biro; M. Mcdonald; D. Croux et al. 

Physica Status Solidi (a). 2017. Vol. 214, num. 2, p. 1532347. DOI : 10.1002/pssa.201532347.

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.

Diamond microelectrode arrays for in vitro neuronal recordings

M. Mcdonald; A. Monaco; F. Vahidpour; K. Haenen; M. Giugliano et al. 

Mrs Communications. 2017. Vol. 7, num. 3, p. 683 – 690. DOI : 10.1557/mrc.2017.62.

On the Structure of Cortical Microcircuits Inferred from Small Sample Sizes

M. Vegue; R. Perin; A. Roxin 

The Journal of neuroscience. 2017. Vol. 37, num. 35, p. 8498 – 8510. DOI : 10.1523/Jneurosci.0984-17.2017.

2016

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.

Enhanced Sensitivity to Rapid Input Fluctuations by Nonlinear Threshold Dynamics in Neocortical Pyramidal Neurons

S. Mensi; O. Hagens; W. Gerstner; C. Pozzorini 

Plos Computational Biology. 2016. Vol. 12, p. e1004761. DOI : 10.1371/journal.pcbi.1004761.

Brief wide-field photostimuli evoke and modulate oscillatory reverberating activity in cortical networks

R. Pulizzi; G. Musumeci; C. Van Den Haute; S. Van De Vijver; V. Baekelandt et al. 

Scientific Reports. 2016. Vol. 6, p. 24701. DOI : 10.1038/srep24701.

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. 

The Journal of neuroscience. 2016. Vol. 36, num. 26, p. 7002 – 7013. DOI : 10.1523/Jneurosci.0664-16.2016.

2015

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.

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.

Comments on the paper by Horowitz et al. (2014)

G. M. Innocenti; R. Caminiti; F. Aboitiz 

Brain Structure & Function. 2015. Vol. 220, num. 3, p. 1789 – 1790. DOI : 10.1007/s00429-014-0974-7.

Organization and evolution of parieto-frontal processing streams in macaque monkeys and humans

R. Caminiti; G. M. Innocenti; A. Battaglia-Mayer 

Neuroscience And Biobehavioral Reviews. 2015. Vol. 56, p. 73 – 96. DOI : 10.1016/j.neubiorev.2015.06.014.

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.

Duration of Purkinje cell complex spikes increases with their firing frequency

P. Warnaar; J. Couto; M. Negrello; M. Junker; A. Smilgin et al. 

Frontiers In Cellular Neuroscience. 2015. Vol. 9, p. 122. DOI : 10.3389/fncel.2015.00122.

Carbon-based smart nanomaterials in biomedicine and neuroengineering (vol 5, pg 1849, 2014)

A. M. Monaco; M. Giugliano 

Beilstein Journal Of Nanotechnology. 2015. Vol. 6, p. 499 – 499. DOI : 10.3762/bjnano.6.51.

Large Volume Imaging of Rodent Brain Anatomy with Emphasis on Selective Plane Illumination Microscopy

J. P. Ghobril / H. Markram; F. S. Pavone (Dir.)  

Lausanne, EPFL, 2015. 

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.

Adaptation of short-term plasticity parameters via error-driven learning may explain the correlation between activity-dependent synaptic properties, connectivity motifs and target specificity

U. Esposito; M. Giugliano; E. Vasilaki 

Frontiers In Computational Neuroscience. 2015. Vol. 8, p. 175. DOI : 10.3389/fncom.2014.00175.

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.

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.

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.

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.

Automated High-Throughput Characterization of Single Neurons by Means of Simplified Spiking Models

C. A. Pozzorini; S. Mensi; O. Hagens; R. Naud; C. Koch et al. 

Plos Computational Biology. 2015. Vol. 11, num. 4, p. e1004275. DOI : 10.1371/journal.pcbi.1004275.

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.

2014

The In-Silico Neocortical Microcircuit : From Structure to Dynamics

M. Reimann / H. Markram; S. Hill (Dir.)  

Lausanne, EPFL, 2014. 

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.

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.

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.

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

M. Toledo-Rodriguez; H. Markram 

Patch-Clamp Methods and Protocols; Springer, 2014. p. 143 – 158.

Scalable Exploration of Spatial Data in Large-Scale Scientific Simulations

F. Tauheed / A. Ailamaki; H. Markram (Dir.)  

Lausanne, EPFL, 2014. 

2013

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.

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.

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, p. 88. DOI : 10.3389/fnbeh.2013.00088.

One minute with … Henry Markram

J. Griggs; H. Markram 

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

Network Activity and Plasticity

V. Delattre / H. Markram (Dir.)  

Lausanne, EPFL, 2013. 

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 

The Journal of neuroscience. 2013. Vol. 33, num. 15, p. 6257 – 6266. DOI : 10.1523/Jneurosci.3740-12.2013.

Hyper-emotional neurophysiology in a rat model of autism

M. R. Favre / H. Markram; K. Markram (Dir.)  

Lausanne, EPFL, 2013. 

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.

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.

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.

Synaptic and Cellular Organization of Layer 1 of the Developing Rat Somatosensory Cortex

S. Muralidhar / H. Markram (Dir.)  

Lausanne, EPFL, 2013. 

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.

2012

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.

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 (PNAS). 2012. Vol. 109, num. 42, p. E2885 – 94. DOI : 10.1073/pnas.1202128109.

The neocortical column

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

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

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.

The human brain project

H. Markram 

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

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.

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.

2011

Organizing neural networks

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

US11900237; US2023394280; US2022121907; US11126911; US2019354841; US10387767; US10373048; KR101816329; DK2531959; EP2531959; CN102859538; JP5844286; US2015363689; JP2013519140; CN102859538; US2012323833; EP2531959; KR20120123698; WO2011095342.

2011.

Engineering Neuron Models : from Ion Channels to Electrical Behavior

R. Ranjan / H. Markram (Dir.)  

Lausanne, EPFL, 2011. 

Augmenting cognition

 

Lausanne: EPFL Press, 2011.

Encoding and decoding of information

H. Markram 

ES2823253; EP3771103; EP2460276; CN104901702; KR101734596; JP5848414; CN104901702; CN102648582; US8941512; JP2014209794; JP5587412; JP2013500660; US2012313798; US8253607; CN102648582; EP2460276; US2012119926; KR20120046760; US8159373; WO2011012614; WO2011012158; WO2011012614; US2011025532.

2011.

Predictive Engineering the Membrane Composition of Neocortical Neurons

G. Khazen / H. Markram (Dir.)  

Lausanne, EPFL, 2011. 

Emergent Properties of in silico Synaptic Transmission in a Model of the Rat Neocortical Column

S. Ramaswamy / H. Markram; S. L. Hill (Dir.)  

Lausanne, EPFL, 2011. 

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.

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.

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.

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. DOI : 10.1126/science.334.6057.748.

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.

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.

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.

Frontiers research : seek, share & create

H. Markram; K. Markram 

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

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.

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 (PNAS). 2011. Vol. 108, num. 13, p. 5419 – 24. DOI : 10.1073/pnas.1016051108.

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.

A Pipeline Based Approach for Experimental Neuroscience Data Management

M. A. Jan / H. Markram; F. Schürmann (Dir.)  

Lausanne, EPFL, 2011. 

2010

Emergent Connectivity Principles in the Neocortex

I. Riachi / H. Markram (Dir.)  

Lausanne, EPFL, 2010. 

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.

Emergent Dynamics in Neocortical Microcircuits

R. d. C. Perin / H. Markram (Dir.)  

Lausanne, EPFL, 2010. 

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.

Impact of Carbon-Nanotube Substrate Coating in Neuronal Networks

L. Gambazzi / H. Markram (Dir.)  

Lausanne, EPFL, 2010. 

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.

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.

Properties of neocortical microcircuits

T. Berger / H. Markram (Dir.)  

Lausanne, EPFL, 2009. 

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.

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.

Structure and function of the olfactory bulb microcircuit

M. Pignatelli / H. Markram; A. Carleton (Dir.)  

Lausanne, EPFL, 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.

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.

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.

2008

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 – 316. DOI : 10.1007/s10827-008-0080-z.

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.

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.

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.

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.

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. DOI : 10.1147/rd.521.0043.

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.

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.

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.

2007

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.01.1.1.001.2007.

Industrializing neuroscience

H. Markram 

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

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.

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.

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.01.1.1.006.2007.

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

T. Rinaldi; G. Silberberg; H. Markram 

Cereb Cortex. 2007. Vol. 18, num. 4, p. 763 – 70. DOI : 10.1093/cercor/bhm117.

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. 

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

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.

Amygdala upregulation of NCAM polysialylation induced by auditory fear conditioning is not required for memory formation, but plays a role in fear extinction

K. Markram; M. A. Lopez Fernandez; D. N. Abrous; C. Sandi 

Neurobiol Learn Mem. 2007. Vol. 87, num. 4, p. 573 – 82. DOI : 10.1016/j.nlm.2006.11.007.

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 (PNAS). 2007. Vol. 104, num. 33, p. 13501 – 6. DOI : 10.1073/pnas.0704391104.

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

M. Toledo-Rodriguez; H. Markram 

Patch-Clamp Methods and Protocols; Springer, 2007. p. 123 – 139.

Structure and dynamics of the neocortical microcircuit connectivity

J-V. Le Bé / H. Markram (Dir.)  

Lausanne, EPFL, 2007. 

2006

The blue brain project

H. Markram 

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

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 (PNAS). 2006. Vol. 103, num. 35, p. 13214 – 9. DOI : 10.1073/pnas.0604691103.

Dynamical principles for neuroscience and intelligent biomimetic devices

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

2006. EPFL LATSIS Symposium 2006.

Altered neocortical microcircuitry in the valproic acid rat model of autism

T. Rinaldi / H. Markram (Dir.)  

Lausanne, EPFL, 2006. 

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.

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.

Un nouveau mécanisme de mémoire : connexions et déconnexions de neurones dans le néocortex de jeunes rats [A new mechanism for memory: neuronal networks rewiring in the young rat neocortex]

J. V. Le Be; H. Markram 

médecine/sciences. 2006. Vol. 22, num. 12, p. 1031 – 1033. DOI : 10.1051/medsci/200622121031.

2005

Synaptic plasticity at the cerebellum input stage: mechanisms and functional implications

E. D’Angelo 

Arch Ital Biol. 2005. Vol. 143, num. 2, p. 143 – 56.

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.

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 (PNAS). 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.

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.

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.

NEOBASE: databasing the neocortical microcircuit

A. J. Muhammad; H. Markram 

2005. Healthgrid 2005, Oxford, UK, 7-9 April 2005. p. 167 – 77.

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.

2004

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.

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.

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.

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.

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.

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.

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.

Computational Models for Generic Cortical Microcircuits

W. Maass; T. Natschläger; H. Markram 

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

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.

Interneuron Heterogeneity in the Neocortex

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

Excitatory-Inhibitory Balance: Synapses, Circuits, Systems; Kluwer Academic Publishing, 2004. p. 149 – 172.

2003

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

R. Legenstein; H. Markram; W. Maass 

Reviews in the Neurosciences. 2003. Vol. 14, num. 1-2, p. 5 – 19. DOI : 10.1515/REVNEURO.2003.14.1-2.5.

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.

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.

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.

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.

2002

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.

Stereotypy in neocortical microcircuits

G. Silberberg; A. Gupta; H. Markram 

Trends in Neurosciences. 2002. Vol. 25, num. 5, p. 227 – 230. DOI : 10.1016/S0166-2236(02)02151-3.

Coding of temporal information by activity-dependent synapses

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

Journal of Neurophysiology. 2002. Vol. 87, num. 1, p. 140 – 148. DOI : 10.1152/jn.00258.2001.

Spike frequency adaptation and neocortical rhythms

G. Fuhrmann; H. Markram; M. Tsodyks 

Journal of Neurophysiology. 2002. Vol. 88, num. 2, p. 761 – 770. DOI : 10.1152/jn.2002.88.2.761.

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.

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

T. Natschläger; W. Maass; H. Markram 

TELEMATIK. 2002. Vol. 8, num. 1, p. 39 – 43.

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. DOI : 10.1007/3-540-36181-2_28.

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.

2001

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.

2000

Synchrony generation in recurrent networks with frequency-dependent synapses

M. Tsodyks; A. Uziel; H. Markram 

Journal of Neuroscience. 2000. Vol. 20, num. 1, p. RC50. DOI : 10.1523/JNEUROSCI.20-01-j0003.2000.

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

A. Gupta; Y. Wang; H. Markram 

Science. 2000. Vol. 287, num. 5451, p. 273 – 278. DOI : 10.1126/science.287.5451.273.

1999

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 – 317. DOI : 10.1016/S0928-4257(00)80059-5.

1998

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 (PNAS). 1998. Vol. 95, num. 9, p. 5323 – 5328. DOI : 10.1073/pnas.95.9.5323.

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.

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 – 348. DOI : 10.1023/A:1008891229546.

Neural networks with dynamic synapses

M. Tsodyks; K. Pawelzik; H. Markram 

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

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.

1997

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 (PNAS). 1997. Vol. 94, num. 2, p. 719 – 723. DOI : 10.1073/pnas.94.2.719.

A network of tufted layer 5 pyramidal neurons

H. Markram 

Cerebral Cortex. 1997. Vol. 7, num. 6, p. 523 – 533. DOI : 10.1093/cercor/7.6.523.

Neural codes: firing rates and beyond

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

Proceedings Of The National Academy Of Sciences Of The United States Of America (PNAS). 1997. Vol. 94, num. 24, p. 12740 – 12741. DOI : 10.1073/pnas.94.24.12740.

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.

Regulation of synaptic efficacy by coincidence of postsynaptic APs and EPSPs

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

Science. 1997. Vol. 275, num. 5297, p. 213 – 215. DOI : 10.1126/science.275.5297.213.

1996

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. 1996. Vol. 16, num. 10, p. 3209 – 18. DOI : 10.1523/JNEUROSCI.16-10-03209.1996.

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. DOI : 10.1016/S0928-4257(97)81429-5.

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.

1995

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, num. 1, p. 1 – 20. DOI : 10.1113/jphysiol.1995.sp020708.

1994

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 (PNAS). 1994. Vol. 91, num. 11, p. 5207 – 5211. DOI : 10.1073/pnas.91.11.5207.

1992

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. DOI : 10.1113/jphysiol.1992.sp019389.

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.

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 – 533. DOI : 10.1113/jphysiol.1992.sp019015.

1991

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 – 324. DOI : 10.1016/0006-8993(91)90529-5.

1990

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 – 484. DOI : 10.1016/0197-4580(90)90017-T.

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. DOI : 10.1113/jphysiol.1990.sp018177.

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 – 174. DOI : 10.1016/0006-8993(90)91106-Q.

1989

Presynaptic cholinergic action in the hippocampus

M. Segal; V. Greenberger; H. Markram 

EXS. 1989. Vol. 57, p. 88 – 96.