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Henry Markram

Publications and source records attributed to Henry Markram.

At least 19 recordsLinked to original sources
PubMed2006

Heterogeneity in the pyramidal network of the medial prefrontal cortex.

The prefrontal cortex is specially adapted to generate persistent activity that outlasts stimuli and is resistant to distractors, presumed to be the basis of working memory. The pyramidal network that supports this activity is unknown. Multineuron patch-clamp recordings in the ferret medial prefrontal cortex showed a heterogeneity of synapses interconnecting distinct subnetworks of different pyramidal cells. One subnetwork was similar to the pyramidal network commonly found in primary sensory areas, consisting of accommodating pyramidal cells interconnected with depressing synapses. The other subnetwork contained complex pyramidal cells with dual apical dendrites displaying nonaccommodating discharge patterns; these cells were hyper-reciprocally connected with facilitating synapses displaying pronounced synaptic augmentation and post-tetanic potentiation. These cellular, synaptic and network properties could amplify recurrent interactions between pyramidal neurons and support persistent activity in the prefrontal cortex.

Animals↗
PubMed2006

The blue brain project.

IBM's Blue Gene supercomputer allows a quantum leap in the level of detail at which the brain can be modelled. I argue that the time is right to begin assimilating the wealth of data that has been accumulated over the past century and start building biologically accurate models of the brain from first principles to aid our understanding of brain function and dysfunction.

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PubMed2005

Fading memory and kernel properties of generic cortical microcircuit models.

It is quite difficult to construct circuits of spiking neurons that can carry out complex computational tasks. On the other hand even randomly connected circuits of spiking neurons can in principle be used for complex computational tasks such as time-warp invariant speech recognition. This is possible because such circuits have an inherent tendency to integrate incoming information in such a way that simple linear readouts can be trained to transform the current circuit activity into the target output for a very large number of computational tasks. Consequently we propose to analyze circuits of spiking neurons in terms of their roles as analog fading memory and non-linear kernels, rather than as implementations of specific computational operations and algorithms. This article is a sequel to [W. Maass, T. Natschläger, H. Markram, Real-time computing without stable states: a new framework for neural computation based on perturbations, Neural Comput. 14 (11) (2002) 2531-2560, Online available as #130 from: ], and contains new results about the performance of generic neural microcircuit models for the recognition of speech that is subject to linear and non-linear time-warps, as well as for computations on time-varying firing rates. These computations rely, apart from general properties of generic neural microcircuit models, just on capabilities of simple linear readouts trained by linear regression. This article also provides detailed data on the fading memory property of generic neural microcircuit models, and a quick review of other new results on the computational power of such circuits of spiking neurons.

Action Potentials↗
PubMed2005

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

Neocortical neurones can be classified according to several independent criteria: morphological, physiological, and molecular expression (neuropeptides (NPs) and/or calcium-binding proteins (CaBPs)). While it has been suggested that particular NPs and CaBPs characterize certain anatomical subtypes of neurones, there is also considerable overlap in their expression, and little is known about simultaneous expression of multiple NPs and CaBPs in morphologically characterized neocortical neurones. Here we determined the gene expression profiles of calbindin (CB), parvalbumin (PV), calretinin (CR), neuropeptide Y (NPY), vasoactive intestinal peptide (VIP), somatostatin (SOM) and cholecystokinin (CCK) in 268 morphologically identified neurones located in layers 2-6 in the juvenile rat somatosensory neocortex. We used patch-clamp electrodes to label neurones with biocytin and harvest the cytoplasm to perform single-cell RT-multiplex PCR. Quality threshold clustering, an unsupervised algorithm that clustered neurones according to their entire profile of expressed genes, revealed seven distinct clusters. Surprisingly, each cluster preferentially contained one anatomical class. Artificial neural networks using softmax regression predicted anatomical types at nearly optimal statistical levels. Classification tree-splitting (CART), a simple binary neuropeptide decision tree algorithm, revealed the manner in which expression of the multiple mRNAs relates to different anatomical classes. Pruning the CART tree revealed the key predictors of anatomical class (in order of importance: SOM, PV, VIP, and NPY). We reveal here, for the first time, a strong relationship between specific combinations of NP and CaBP gene expressions and the anatomical class of neocortical neurones.

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PubMed2005

The neocortical microcircuit as a tabula rasa.

The neocortex has a high capacity for plasticity. To understand the full scope of this capacity, it is essential to know how neurons choose particular partners to form synaptic connections. By using multineuron whole-cell recordings and confocal microscopy we found that axons of layer V neocortical pyramidal neurons do not preferentially project toward the dendrites of particular neighboring pyramidal neurons; instead, axons promiscuously touch all neighboring dendrites without any bias. Functional synaptic coupling of a small fraction of these neurons is, however, correlated with the existence of synaptic boutons at existing touch sites. These data provide the first direct experimental evidence for a tabula rasa-like structural matrix between neocortical pyramidal neurons and suggests that pre- and postsynaptic interactions shape the conversion between touches and synapses to form specific functional microcircuits. These data also indicate that the local neocortical microcircuit has the potential to be differently rewired without the need for remodeling axonal or dendritic arbors.

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PubMed2005

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

The synaptic drive from neuronal populations varies considerably over short time scales. Such changes in the pre-synaptic rate trigger many temporal processes absent under steady-state conditions. This paper examines the differential impact of pyramidal cell population bursts on post-synaptic pyramidal cells receiving depressing synapses, and on a class of interneuron that receives facilitating synapses. In experiment a significant shift of the order of one hundred milliseconds is seen between the response of these two cell classes to the same population burst. It is demonstrated here that such a temporal differentiation of the response can be explained by the synaptic and membrane properties without recourse to elaborate cortical wiring schemes. Experimental data is first used to construct models of the two types of dynamic synaptic response. A population-based approach is then followed to examine analytically the temporal synaptic filtering effects of the population burst for the two post-synaptic targets. The peak-to-peak delays seen in experiment can be captured by the model for experimentally realistic parameter ranges. It is further shown that the temporal separation of the response is communicated in the outgoing action potentials of the two post-synaptic cells: pyramidal cells fire at the beginning of the burst and the class of interneuron receiving facilitating synapses fires at the end of the burst. The functional role of such delays in the temporal organisation of activity in the cortical microcircuit is discussed.

Action Potentials↗
PubMed2005

Microcircuits in action--from CPGs to neocortex.

To understand the interface between global brain function and molecular neuroscience--that is, the microcircuit level--a major challenge. Such understanding is prerequisite if we are to account for neural function in cellular terms. Very few vertebrate microcircuits are yet understood because their analysis is demanding technically. In this review of the TINS Microcircuits Special Feature, we attempt to shed light on the problem by comparing the operation of four types of microcircuit, to identify common molecular and cellular components. Central pattern generator (CPG) networks underlying rhythmic movements and hippocampal microcircuits that generate gamma and theta rhythms are compared with the neocortical microcircuits used in cognitive tasks and a cerebellar network. The long-term goal is to identify the components of a molecular and synaptic tool kit for the design of different microcircuits.

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PubMed2005

Synaptic pathways in neural microcircuits.

The functions performed by different neural microcircuits depend on the anatomical and physiological properties of the various synaptic pathways connecting neurons. Neural microcircuits across various species and brain regions are similar in terms of their repertoire of neurotransmitters, their synaptic kinetics, their short-term and long-term plasticity, and the target-specificity of their synaptic connections. However, microcircuits can be fundamentally different in terms of the precise recurrent design used to achieve a specific functionality. In this review, which is part of the TINS Microcircuits Special Feature, we compare the connectivity designs in spinal, hippocampal, neocortical and cerebellar microcircuits, and discuss the different computational challenges that each microcircuit faces.

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PubMed2005

NEOBASE: databasing the neocortical microcircuit.

Mammals adapt to a rapidly changing world because of the sophisticated perceptual and cognitive function enabled by the neocortex. The neocortex, which has expanded to constitute nearly 80% of the human brain seems to have arisen from repeated duplication of a stereotypical template of neurons and synaptic circuits with subtle specializations in different brain regions and species. Determining the design and function of this microcircuitry is therefore of paramount importance to understanding normal and abnormal higher brain function. Recent advances in recording synaptically-coupled neurons has allowed rapid dissection of the neocortical microcircuitry thus yielding a massive amount of quantitative anatomical, electrical and gene expression data on the neurons and the synaptic circuits that connect the neurons. Due to the availability of the above mentioned data, it has now become imperative to database the neurons of the microcircuit and their synaptic connections. The NEOBASE project, aims to archive the neocortical microcircuit data in a manner that facilitates development of advanced data mining applications, statistical and bioinformatics analyses tools, custom microcircuit builders, and visualization and simulation applications. The database architecture is based on ROOT, a software environment that allows the construction of an object oriented database with numerous relational capabilities. The proposed architecture allows construction of a database that closely mimics the architecture of the real microcircuit, which facilitates the interface with virtually any application, allows for data format evolution, and aims for full interoperability with other databases. NEOBASE will provide an important resource and research tool for studying the microcircuit basis of normal and abnormal neocortical function. The database will be available to local as well as remote users using Grid based tools and technologies.

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PubMed2004

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

Whole-cell patch-clamp recordings followed by histochemical staining and single-cell RT-PCR were obtained from 180 Martinotti interneurones located in layers II to VI of the somatosensory cortex of Wistar rats (P13-P16) in order to examine their anatomical, electrophysiological and molecular properties. Martinotti cells (MCs) mostly displayed ovoid-shaped somata, bitufted dendritic morphologies, and axons with characteristic spiny boutons projecting to layer I and spreading horizontally across neighbouring columns more than 1 mm. Electron microscopic examination of MC boutons revealed that all synapses were symmetrical and most synapses (71%) were formed onto dendritic shafts. MCs were found to contact tuft, apical and basal dendrites in multiple neocortical layers: layer II/III MCs targeted mostly layer I and to a lesser degree layer II/III; layer IV MCs targeted mostly layer IV and to a lesser degree layer I; layer V and VI MCs targeted mostly layer IV and layer I and to a lesser degree the layer in which their somata was located. MCs typically displayed spike train accommodation (90%; n = 127) in response to depolarizing somatic current injections, but some displayed non-accommodating (8%) and a few displayed irregular spiking responses (2%). Some accommodating and irregular spiking MCs also responded initially with bursts (17%). Accommodating responses were found in all layers, non-accommodating mostly in upper layers and bursting mostly in layer V. Single-cell multiplex RT-PCR performed on 63 MCs located throughout layers II-VI, revealed that all MCs were somatostatin (SOM) positive, and negative for parvalbumin (PV) as well as vasoactive intestinal peptide (VIP). Calbindin (CB), calretinin (CR), neuropeptide Y (NPY) and cholecystokinin (CCK) were co- expressed with SOM in some MCs. Some layer-specific trends seem to exist. Finally, 24 accommodating MCs were examined for the expression of 26 ion channel genes. The ion channels with the highest expression in these MCs were (from highest to lowest); Cabeta1, Kv3.3, HCN4, Cabeta4, Kv3.2, Kv3.1, Kv2.1, HCN3, Caalpha1G, Kv3.4, Kv4.2, Kv1.1 and HCN2. In summary, this study provides the first detailed analysis of the anatomical, electrophysiological and molecular properties of Martinotti cells located in different neocortical layers. It is proposed that MCs are crucial interneurones for feedback inhibition in and between neocortical layers and columns.

Action Potentials↗
PubMed2004

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

The computational power of the neocortex arises from interactions of multiple neurons, which display a wide range of electrical properties. The gene expression profiles underlying this phenotypic diversity are unknown. To explore this relationship, we combined whole-cell electrical recordings with single-cell multiplex RT-PCR of rat (p13-16) neocortical neurons to obtain cDNA libraries of 26 ion channels (including voltage activated potassium channels, Kv1.1/2/4/6, Kvbeta1/2, Kv2.1/2, Kv3.1/2/3/4, Kv4.2/3; sodium/potassium permeable hyperpolarization activated channels, HCN1/2/3/4; the calcium activated potassium channel, SK2; voltage activated calcium channels, Caalpha1A/B/G/I, Cabeta1/3/4), three calcium binding proteins (calbindin, parvalbumin and calretinin) and GAPDH. We found a previously unreported clustering of ion channel genes around the three calcium-binding proteins. We further determined that cells similar in their expression patterns were also similar in their electrical properties. Subsequent regression modeling with statistical resampling yielded a set of coefficients that reliably predicted electrical properties from the expression profile of individual neurons. This is the first report of a consistent relationship between the co-expression of a large profile of ion channel and calcium binding protein genes and the electrical phenotype of individual neocortical neurons.

Action Potentials↗
PubMed2004

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

It is well established that sensory stimulation results in the activity of multiple functional columns in the neocortex. The manner in which neurones within each column are active in relation to each other is, however, not known. Multiple whole-cell recordings in activated neocortical slices from rat revealed diverse correlation profiles of excitatory synaptic input to different types of neurones. The specific correlation profile between any two neurones could be predicted by the settings of synaptic depression and facilitation at the input synapses. Simulations further showed that patterned activity is essential for synaptic dynamics to impose the temporal dispersion of excitatory input. We propose that synaptic dynamics choreograph neuronal activity within the neocortical microcircuit in a context-dependent manner.

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PubMed2004

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

Structural and functional diversity of GABAergic interneurons has become increasingly central in our understanding of the elemental steps of information processing in the brain. The use of different molecular, electrophysiological and anatomical techniques has provided a wealth of new information regarding GABAergic interneurons over the past decade but it has also led to confusion regarding the number of subtypes of GABAergic interneurons. Combinatorial approaches that also consider multiple parameters seem now to offer renewed hope for finally clarifying the structural diversity of GABAergic interneurons. New molecular techniques have become a powerful tool for exposing the functional diversity of GABAergic neurons at the cellular, microcircuit and systems levels. This article reviews literature regarding molecular tools that have been used, or that appear promising for future attempts, to classify GABAergic interneurons. Some important limitations will also be indicated.

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PubMed2004

Interneurons of the neocortical inhibitory system.

Mammals adapt to a rapidly changing world because of the sophisticated cognitive functions that are supported by the neocortex. The neocortex, which forms almost 80% of the human brain, seems to have arisen from repeated duplication of a stereotypical microcircuit template with subtle specializations for different brain regions and species. The quest to unravel the blueprint of this template started more than a century ago and has revealed an immensely intricate design. The largest obstacle is the daunting variety of inhibitory interneurons that are found in the circuit. This review focuses on the organizing principles that govern the diversity of inhibitory interneurons and their circuits.

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PubMed2003

Deriving physical connectivity from neuronal morphology.

A model is presented that allows prediction of the probability for the formation of appositions between the axons and dendrites of any two neurons based only on their morphological statistics and relative separation. Statistics of axonal and dendritic morphologies of single neurons are obtained from 3D reconstructions of biocytin-filled cells, and a statistical representation of the same cell type is obtained by averaging across neurons according to the model. A simple mathematical formulation is applied to the axonal and dendritic statistical representations to yield the probability for close appositions. The model is validated by a mathematical proof and by comparison of predicted appositions made by layer 5 pyramidal neurons in the rat somatosensory cortex with real anatomical data. The model could be useful for studying microcircuit connectivity and for designing artificial neural networks.

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PubMed2003

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

Temporal integration of information and prediction of future sensory inputs are assumed to be important computational tasks of generic cortical microcircuits. It has remained open how cortical microcircuits could possibly achieve this, especially since they consist--in contrast to most neural network models--of neurons and synapses with heterogeneous dynamic responses. It turns out, however, that the diversity of computational units increases the capability of microcircuit models for temporal integration. Furthermore the prediction of future input may be rather easy for such circuits since it suffices to train the readouts from such microcircuits. In this article we show that very simple readouts from a generic recurrently connected circuit of integrate-and-fire neurons with diverse dynamic synapses can be trained in an unsupervised manner to predict movements of different objects, that move within an unlimited number of combinations of speed, angle, and offset over a simulated sensory field. The autonomously trained microcircuit model is also able to compute the direction of motion, which is a computationally difficult problem ('aperture problem') since it requires disambiguation of local sensory readings through the context of other sensory readings at the current and preceding moments. Furthermore the same circuit can be trained simultaneously in a supervised manner to also report the shape and velocity of the moving object. Finally it is shown that the trained neural circuit supports novelty detection and the generation of 'imagined movements'. Altogether the results of this article suggest that it is not necessary to construct specific and biologically unrealistic neural circuit models for specific sensory processing tasks, since 'found' generic cortical microcircuit models in combination with very simple perceptron-like readouts can easily be trained to solve such computational tasks.

Action Potentials↗
PubMed2002

Stereotypy in neocortical microcircuits.

A central debate regarding neocortical function concerns the degree to which the underlying microcircuitry is stereotypically organized. Stereotypy reflects invariance in structure and function, as a result of common genetic templates and environmental conditions, whereas uniqueness can be caused by genetic variations, differences in environmental conditions as well as random processes. Stereotypy is an appealing concept because it provides strong support for determinism in the formation of neuronal microcircuits and in the relationship between their specific structure and function.

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