Functional holography of complex networks activity—From cultures to the human brain

Baruchi, Itay; Towle, Vernon L.; Ben‐Jacob, Eshel

doi:10.1002/cplx.20065

Cited by 19 publications

(29 citation statements)

References 18 publications

(22 reference statements)

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“…In order to facilitate the process, we built a software visualization package (Functional Holography Analysis). This analysis, developed from a previously reported approach applied to EEG signals [29, 30] and networks in culture [31], helped not only to reveal functional clusters within brain regions but also to determine their anatomical distribution. Details of the software can be accessed at http://sites.google.com/site/funcholoappl/.…”

Section: Methodsmentioning

confidence: 99%

Loss of Intrinsic Organization of Cerebellar Networks in Spinocerebellar Ataxia Type 1: Correlates with Disease Severity and Duration

et al. 2010

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The spinocerebellar ataxias (SCAs) are a genetically heterogeneous group of cerebellar degenerative disorders, characterized by progressive gait unsteadiness, hand incoordination, and dysarthria. The mutational mechanism in SCA1, a dominantly inherited form of SCA, consists of an expanded trinucleotide CAG repeat. In SCA1, there is loss of Purkinje cells, neuronal loss in dentate nucleus, olives, and pontine nuclei. In the present study, we sought to apply intrinsic functional connectivity analysis combined with diffusion tensor imaging to define the state of cerebellar connectivity in SCA1. Our results on the intrinsic functional connectivity in lateral cerebellum and thalamus showed progressive organizational changes in SCA1 noted as a progressive increase in the absolute value of the correlation coefficients. In the lateral cerebellum, the anatomical organization of functional clusters seen as parasagittal bands in controls is lost, changing to a patchy appearance in SCA1. Lastly, only fractional anisotropy in the superior peduncle and changes in functional organization in thalamus showed a linear dependence to duration and severity of disease. The present pilot work represents an initial effort describing connectivity biomarkers of disease progression in SCA1. The functional changes detected with intrinsic functional analysis and diffusion tensor imaging suggest that disease progression can be analyzed as a disconnection syndrome.

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Section: Methodsmentioning

confidence: 99%

Loss of Intrinsic Organization of Cerebellar Networks in Spinocerebellar Ataxia Type 1: Correlates with Disease Severity and Duration

et al. 2010

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“…2A we show the correlation matrix representing for the ROIs voxels of a single subject. We note that the correlation matrix can be associated with an N − 1 dimensional space of correlations, or the "correlation space" (Baruchi et al, 2004(Baruchi et al, , 2006. We note that the correlation space does not represent a real space in the sense that the eigenvectors do not create an orthogonal mathematical space.…”

Section: Voxel Correlationsmentioning

confidence: 99%

“…To retrieve information that might be lost during the dimension reduction, we link each pair of voxels by lines color-coded according to the correlations between them (Baruchi et al, 2004(Baruchi et al, , 2006Madi et al, 2008). The result is a holographic representation (Fig.…”

Section: Dimension-reduction and Construction Of The Holographic Netwmentioning

confidence: 99%

“…The motivation for this is to capture mutual or relative effects between several voxels, via normalization of the correlations between every pair of voxels according to their correlations with all the other pairs in the matrix. The affinity transformation represents a collective property of all channels, and can help to capture hidden collective motifs related to functional connectivity in the network behaviors (Baruchi et al, 2004(Baruchi et al, , 2006. There are many different metrics for this kind of normalization, however we chose to calculate the affinity matrix using the meta-correlations matrix MC(i,j), which is the Pearson's correlation between the rows of the reordered correlation matrix of any two components (i) and (j) as described in Eq.…”

Section: Collective Normalizationmentioning

confidence: 99%

“…Here we used the PCA dimensionreduction algorithm to extract the maximal relevant information embedded in the voxel correlation matrices, but other algorithms may also be used. Using the PCA algorithm, the relevant information is presented in a 3-dimensional PCA space (Baruchi et al, 2004(Baruchi et al, , 2006) whose axes are the three leading PCA principal vectors. Each voxel is placed in this space according to its three eigenvalues for the three leading principal vectors.…”

Section: Dimension-reduction and Construction Of The Holographic Netwmentioning

confidence: 99%

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Revealing voxel correlation cliques by functional holography analysis of fMRI

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Robust decentralized adaptive synchronization of general complex networks with coupling delayed and uncertainties

Jing

Fan

et al. 2013

Complexity

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The problem of robust decentralized adaptive synchronization of general complex networks with coupling delayed and uncertainties is investigated in this article. It is only assumed that the upper normal bound of uncertain inner and outer coupling matrices is positive but its concrete structure is not also required to be known. The time‐varying coupling delay is a any nonnegative continuous and bounded function and not require its derivative to be less than one, that is, general time‐varying coupling delays and uncertainties. For such a class of uncertain complex networks, a new synchronization scheme is presented by a class of continuous memoryless robust decentralized adaptive synchronization controllers. It is also shown that the synchronization error dynamics of uncertain complex networks can be guaranteed as uniformly exponentially convergent toward a ball that can be as small as desired. Finally, numerical simulations are provided to demonstrate the effectiveness and robustness of proposed complex networks synchronization schemes. © 2013 Wiley Periodicals, Inc. Complexity 19: 10–26, 2014

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Functional holography of complex networks activity—From cultures to the human brain

Abstract: A functional holography (FH) approach is introduced for analyzing the complex activity of biological networks in the space of functional correlations. Although the activity is often recorded from part of the nodes only

Cited by 19 publications

References 18 publications

Loss of Intrinsic Organization of Cerebellar Networks in Spinocerebellar Ataxia Type 1: Correlates with Disease Severity and Duration

Loss of Intrinsic Organization of Cerebellar Networks in Spinocerebellar Ataxia Type 1: Correlates with Disease Severity and Duration

Revealing voxel correlation cliques by functional holography analysis of fMRI

Robust decentralized adaptive synchronization of general complex networks with coupling delayed and uncertainties

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