Vladimir Litvak
Wellcome Trust Centre for Neuroimaging
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Featured researches published by Vladimir Litvak.
Science | 2011
Mélanie Boly; Marta I. Garrido; Olivia Gosseries; Marie Aurélie Bruno; Pierre Boveroux; Caroline Schnakers; Marcello Massimini; Vladimir Litvak; Steven Laureys; K. J. Friston
Discerning the neural correlates of (un)consciousness sheds light on the mechanisms underlying vegetative states. Frontoparietal cortex is involved in the explicit processing (awareness) of stimuli. Frontoparietal activation has also been found in studies of subliminal stimulus processing. We hypothesized that an impairment of top-down processes, involved in recurrent neuronal message-passing and the generation of long-latency electrophysiological responses, might provide a more reliable correlate of consciousness in severely brain-damaged patients, than frontoparietal responses. We measured effective connectivity during a mismatch negativity paradigm and found that the only significant difference between patients in a vegetative state and controls was an impairment of backward connectivity from frontal to temporal cortices. This result emphasizes the importance of top-down projections in recurrent processing that involve high-order associative cortices for conscious perception.
Computational Intelligence and Neuroscience | 2011
Vladimir Litvak; Jérémie Mattout; Stefan J. Kiebel; Christophe Phillips; Richard N. Henson; James M. Kilner; Gareth R. Barnes; Robert Oostenveld; Jean Daunizeau; Guillaume Flandin; William D. Penny; K. J. Friston
SPM is a free and open source software written in MATLAB (The MathWorks, Inc.). In addition to standard M/EEG preprocessing, we presently offer three main analysis tools: (i) statistical analysis of scalp-maps, time-frequency images, and volumetric 3D source reconstruction images based on the general linear model, with correction for multiple comparisons using random field theory; (ii) Bayesian M/EEG source reconstruction, including support for group studies, simultaneous EEG and MEG, and fMRI priors; (iii) dynamic causal modelling (DCM), an approach combining neural modelling with data analysis for which there are several variants dealing with evoked responses, steady state responses (power spectra and cross-spectra), induced responses, and phase coupling. SPM8 is integrated with the FieldTrip toolbox , making it possible for users to combine a variety of standard analysis methods with new schemes implemented in SPM and build custom analysis tools using powerful graphical user interface (GUI) and batching tools.
NeuroImage | 2013
Joachim Gross; Sylvain Baillet; Gareth R. Barnes; Richard N. Henson; Arjan Hillebrand; Ole Nørregaard Jensen; Karim Jerbi; Vladimir Litvak; Burkhard Maess; Robert Oostenveld; Lauri Parkkonen; Jason R. Taylor; Virginie van Wassenhove; Michael Wibral; Jan-Mathijs Schoffelen
Magnetoencephalographic (MEG) recordings are a rich source of information about the neural dynamics underlying cognitive processes in the brain, with excellent temporal and good spatial resolution. In recent years there have been considerable advances in MEG hardware developments and methods. Sophisticated analysis techniques are now routinely applied and continuously improved, leading to fascinating insights into the intricate dynamics of neural processes. However, the rapidly increasing level of complexity of the different steps in a MEG study make it difficult for novices, and sometimes even for experts, to stay aware of possible limitations and caveats. Furthermore, the complexity of MEG data acquisition and data analysis requires special attention when describing MEG studies in publications, in order to facilitate interpretation and reproduction of the results. This manuscript aims at making recommendations for a number of important data acquisition and data analysis steps and suggests details that should be specified in manuscripts reporting MEG studies. These recommendations will hopefully serve as guidelines that help to strengthen the position of the MEG research community within the field of neuroscience, and may foster discussion in order to further enhance the quality and impact of MEG research.
Nature Immunology | 2009
Vladimir Litvak; Stephen A. Ramsey; Alistair G. Rust; Kathleen A. Kennedy; Aaron E. Lampano; Matti Nykter; Ilya Shmulevich; Alan Aderem
The innate immune system is like a double-edged sword: it is absolutely required for host defense against infection, but when uncontrolled, it can trigger a plethora of inflammatory diseases. Here we use systems-biology approaches to predict and confirm the existence of a gene-regulatory network involving dynamic interaction among the transcription factors NF-κB, C/EBPδ and ATF3 that controls inflammatory responses. We mathematically modeled transcriptional regulation of the genes encoding interleukin 6 and C/EBPδ and experimentally confirmed the prediction that the combination of an initiator (NF-κB), an amplifier (C/EBPδ) and an attenuator (ATF3) forms a regulatory circuit that discriminates between transient and persistent Toll-like receptor 4–induced signals. Our results suggest a mechanism that enables the innate immune system to detect the duration of infection and to respond appropriately.
Brain | 2011
Vladimir Litvak; Ashwani Jha; Alexandre Eusebio; Robert Oostenveld; Thomas Foltynie; Patricia Limousin; Ludvic Zrinzo; Marwan Hariz; K. J. Friston; Peter Brown
Both phenotype and treatment response vary in patients with Parkinsons disease. Anatomical and functional imaging studies suggest that individual symptoms may represent malfunction of different segregated networks running in parallel through the basal ganglia. In this study, we use a newly described, electrophysiological method to describe cortico-subthalamic networks in humans. We performed combined magnetoencephalographic and subthalamic local field potential recordings in thirteen patients with Parkinsons disease at rest. Two spatially and spectrally separated networks were identified. A temporoparietal-brainstem network was coherent with the subthalamic nucleus in the alpha (7-13 Hz) band, whilst a predominantly frontal network was coherent in the beta (15-35 Hz) band. Dopaminergic medication modulated the resting beta network, by increasing beta coherence between the subthalamic region and prefrontal cortex. Subthalamic activity was predominantly led by activity in the cortex in both frequency bands. The cortical topography and frequencies involved in the alpha and beta networks suggest that these networks may be involved in attentional and executive, particularly motor planning, processes, respectively.
Experimental Neurology | 2007
Chiung Chu Chen; Vladimir Litvak; Thomas P. Gilbertson; Andrea A. Kühn; Chin Song Lu; Shih Tseng Lee; Chon Haw Tsai; Stephen Tisch; Patricia Limousin; Marwan Hariz; Peter Brown
Excessive synchronization of neuronal activity at around 20 Hz is a common finding in the basal ganglia of patients with untreated Parkinsons disease (PD). Correlative evidence suggests, but does not prove, that this spontaneous activity may contribute to slowness of movement in this condition. Here we investigate whether externally imposed synchronization through direct stimulation of the region of the subthalamic nucleus at 20 Hz can slow motor performance in a simple unimanual tapping task and whether this effect is frequency selective. Tapping rates were recorded on 42 sides in 22 patients with PD after overnight withdrawal of medication. Tapping was performed without stimulation and during bilateral stimulation at 20 Hz, 50 Hz and 130 Hz. We found that tapping rates were slowed by 8.2+/-3.2% (p=0.014) during 20-Hz stimulation in subjects with relatively preserved baseline function in the task. This effect was frequency selective. The current data provide proof of the principle that excessive beta synchrony within the basal ganglia-cortical loop may contribute to the slowing of movements in Parkinsons disease.
PLOS Computational Biology | 2008
Stephen A. Ramsey; Sandy L. Klemm; Kathleen A. Kennedy; Vesteinn Thorsson; Bin Li; Mark Gilchrist; Elizabeth S. Gold; Carrie D. Johnson; Vladimir Litvak; Garnet Navarro; Jared C. Roach; Carrie M. Rosenberger; Alistair G. Rust; Natalya Yudkovsky; Alan Aderem; Ilya Shmulevich
Macrophages are versatile immune cells that can detect a variety of pathogen-associated molecular patterns through their Toll-like receptors (TLRs). In response to microbial challenge, the TLR-stimulated macrophage undergoes an activation program controlled by a dynamically inducible transcriptional regulatory network. Mapping a complex mammalian transcriptional network poses significant challenges and requires the integration of multiple experimental data types. In this work, we inferred a transcriptional network underlying TLR-stimulated murine macrophage activation. Microarray-based expression profiling and transcription factor binding site motif scanning were used to infer a network of associations between transcription factor genes and clusters of co-expressed target genes. The time-lagged correlation was used to analyze temporal expression data in order to identify potential causal influences in the network. A novel statistical test was developed to assess the significance of the time-lagged correlation. Several associations in the resulting inferred network were validated using targeted ChIP-on-chip experiments. The network incorporates known regulators and gives insight into the transcriptional control of macrophage activation. Our analysis identified a novel regulator (TGIF1) that may have a role in macrophage activation.
The Journal of Neuroscience | 2003
Vladimir Litvak; Haim Sompolinsky; Idan Segev; Moshe Abeles
The capability of feedforward networks composed of multiple layers of integrate-and-fire neurons to transmit rate code was examined. Synaptic connections were made only from one layer to the next, and excitation was balanced by inhibition. When time is discrete and the synaptic potentials rise instantaneously, we show that, for random uncorrelated input to layer one, the mean rate of activity in deep layers is essentially independent of input firing rate. This implies that the input rate cannot be transmitted reliably in such feedforward networks because neurons in a given layer tend to synchronize partially with each other because of shared inputs. As a result of this synchronization, the average firing rate in deep layers will either decay to zero or reach a stable fixed point, depending on model parameters. When time is treated continuously and the synaptic potentials rise instantaneously, these effects develop slowly, and rate transmission over a limited number of layers is possible. However, the correlations among neurons at the same layer hamper reliable assessment of firing rate by averaging over 100 msec (or less). When the synaptic potentials develop gradually, as is the realistic case, transmission of rate code fails. In a network in which inhibition only balances the mean excitation but is not timed precisely with it, neurons in each layer fire together, and this volley successively propagates from layer to layer. We conclude that the transmission of rate code in feedforward networks is highly unlikely.
The Journal of Neuroscience | 2012
Vladimir Litvak; Alexandre Eusebio; Ashwani Jha; Robert Oostenveld; Gareth R. Barnes; Thomas Foltynie; Patricia Limousin; Ludvic Zrinzo; Marwan Hariz; K. J. Friston; Peter Brown
Functional neurosurgery has afforded the opportunity to assess interactions between populations of neurons in the human cerebral cortex and basal ganglia in patients with Parkinsons disease (PD). Interactions occur over a wide range of frequencies, and the functional significance of those >30 Hz is particularly unclear. Do they improve movement, and, if so, in what way? We acquired simultaneously magnetoencephalography and direct recordings from the subthalamic nucleus (STN) in 17 PD patients. We examined the effect of synchronous and sequential finger movements and of the dopamine prodrug levodopa on induced power in the contralateral primary motor cortex (M1) and STN and on the coherence between the two structures. We observed discrete peaks in M1 and STN power at 60–90 Hz and at 300–400 Hz. All these power peaks increased with movement and levodopa treatment. Only STN activity at 60–90 Hz was coherent with activity in M1. Directionality analysis showed that STN gamma activity at 60–90 Hz tended to drive gamma activity in M1. The effects of levodopa on both local and distant synchronization at 60–90 Hz correlated with the degree of improvement in bradykinesia-rigidity as did local STN activity at 300–400 Hz. Despite this, there were no effects of movement type, nor interactions between movement type and levodopa in the STN, nor in the coherence between STN and M1. We conclude that synchronization at 60–90 Hz in the basal ganglia cortical network is prokinetic but likely through a modulatory effect rather than any involvement in explicit motor processing.
NeuroImage | 2008
Vladimir Litvak; K. J. Friston
The aim of this paper is to describe a simple procedure for electromagnetic (EEG or MEG) source reconstruction, in the context of group studies. This entails a simple extension of existing source reconstiruction techniques based upon the inversion of hierarchical models. The extension ensures that evoked or induced responses are reconstructed in the same subset of sources, over subjects. Effectively, the procedure aligns the deployment of reconstructed activity over subjects and increases, substantially, the detection of differences between evoked or induced responses at the group or between-subject level.