The activated cerebral cortex displays "high-conductance states" characterized intracellularly by intense subthreshold fluctuations, which are due to the high level of activity in the local surrounding network. Present intracellular methods to characterize this activity are limited in resolution due to the bias introduced by recording electrodes. In the present project, we plan to address these limitations by proposing a new recording paradigm based on a computer-contolled feedback with the cell. Developing and implementing this paradigm will require a tight association between mathematics, computer science, computational neuroscience and intracellular electrophysiology (in vivo and in vitro). We aim at both the conception of novel methodologies, their testing in real neurons (essentially in vitro), as well as applying these methods to intracellular recordings in primary visual cortex in vivo.
The project combines different expertises, such as mathematics, computer science, computational neuroscience and intracellular electrophysiology (in vitro and in vivo), to yield accurate and reliable methods to properly characterize high-conductance states in neurons. We plan to address several of the caveats of present recording techniques, namely 1) the impossibility to perform reliable high-resolution dynamic-clamp with sharp electrodes, which is the intracellular technique mostly used in vivo; 2) the unreliability and low time resolution of single-electrode voltage-clamp recordings in vivo; 3) the impossibility of extracting single-trial conductances from Vm activity in vivo. We propose to address these caveats with the following goals: 1. Obtain high-resolution recordings applicable to any type of electrode (sharp and patch), any type of protocol (current-clamp, voltage-clamp, dynamic-clamp) and different preparations (in vivo, in vitro, dendritic patch recordings). 2. Obtain methods to reliably extract single-trial conductances from Vm activity, as well as to "probe" the intrinsic conductances in cortical neurons. These methods will be applied to intracellular recordings during visual responses in cat V1 in vivo. 3. Obtain methods to extract correlations from Vm activity and apply these methods to intracellular recordings in vivo to measure changes in correlation in afferent activity. 4. Obtain methods to estimate spike-triggered averages from Vm activity and obtain estimates of the optimal patterns of conductances that trigger spikes in vivo. These results will be integrated into computational models to test mechanisms for selectivity. These methods will be based on a real-time feedback between a computer and the recorded neuron. This real-time feedback will be used not only to improve existing techniques, but also to extract essential information to better understand spike selectivity of cortical neurons in vivo.
We have a postdoctoral researcher position for this project and
are seeking for candidates (see Postdoc
announcement).
The goal of the FACETS project is to create a theoretical and experimental foundation for the realisation of novel computing paradigms which exploit the concepts experimentally observed in biological nervous systems. The research will be carried out by an interdisciplinary consortium, involving 16 groups of neuroscientists, computer scientists and physicists. The institutions involved represent a major fraction of the European groups working in the relevant fields. The three major lines of research will be: (a) experimental characterisation of cortical cells and networks in-vivo and in-vitro; (b) study of theoretical and computer based models of cells and networks; (c) design, construction and operation of VLSI circuits emulating the biological example. Each of the 3 lines involves studies on the level of individual computing elements (neurons) and on the network level. The continuous interaction and scientific exchange between biological experiments, computer modelling and hardware emulations within the project provides a unique research infrastructure that will in turn provide an improved insight into the computing principles of the brain. This insight may potentially contribute to an improved understanding of mental disorders in the human brain and help to develop remedies.
The FACETS consortium has several PhD and post-doc fellowships
available and is currently looking for filling these positions.
Please contact the different laboratories or see the FACETS website.
The Blue Brain Project will consist in gathering knowledge from different fields such as neuroanatomy, neurophysiology and computational neuroscience. The goal is to investigate cortical computations using an accurate software replica of neocortical microcircuits ("the Blue Column"). This sophisticate model will be run on a 8K-processor Blue Gene supercomputer build by IBM. The Blue Column will be composed of 104 morphologically complex neurons, which will be reconstructed from in vitro experiments and matched to models in order to capture their main electrical properties. The neurons will be interconnected in a 3-dimensional (3D) space with 107 -108 dynamic synapses, directly derived from morphological measurements.
In this HFSP project, our plan was to evaluate how the rhythmic activity of the brain during slow wave sleep influences synaptic transmission and plasticity at a cellular and network level in the cerebral cortex. We have addressed this general question by combining three approaches: (i) Extra-, intracellular and optical recordings in mouse primary visual and somatosensory cortex in vivo; (ii) Extra-, intracellular and optical recordings in ferret primary visual and somatosensory cortex in vitro; (iii) Computational models of morphologicallyreconstructed cortical neurons and network simulations. Optical recordings were done using voltage sensitive dye fluorescence as well as calcium indicators and a fast CCD camera. Our working hypothesis was that periods of electroencephalogram (EEG) activation (wakefulness, REM) provide ideal conditions for "priming" cortical synapses and that these synapses are later subject to long-term changes during slow-wave sleep. We have tested this hypothesis by using various paradigms in vivo, in vitro, and in models. The project provided data essential to the long-term goal of establishing firm evidence for a role of slow wave sleep in memory consolidation.
This research project led to several publications (see Publication list). In particular, we published a review article in Science.
This research project led to several publications (see Publication list).
This project (entitled "Impact of synaptic bombardment on neocortical neurons") proposed to combine computational models and intracellular recordings of neocortical pyramidal cells in vivo to quantify the total amount of sustained synaptic activity and to study how it affects the integrative properties of pyramidal cells. The long-term objective of this project was to build better representations of neuronal networks of the neocortex during intense network activity similar to the waking state. This is of great benefit for investigating information processing paradigms that involve cortical networks. Experiments and models estimated the amount of synaptic conductances tonically activated in soma and dendrites, and how this could potentially affect the basic integrative and response properties of pyramidal cells.
This research project led to numerous publications and review articles (see Publication list).
This research project led to numerous publications and one monograph (see Publication list).
Unité de Neurosciences, Information & Complexité
(UNIC)
CNRS
UPR-3293, Bat 33,
1 Avenue de la Terrasse,
91198 Gif-sur-Yvette, France.
Tel: +33-1-69-82-34-35
Fax: +33-1-69-82-34-27