This paper examines intrinsic brain networks in light of recent developments in the characterisat... more This paper examines intrinsic brain networks in light of recent developments in the characterisation of resting state fMRI timeseries--and simulations of neuronal fluctuations based upon the connectome. Its particular focus is on patterns or modes of distributed activity that underlie functional connectivity. We first demonstrate that the eigenmodes of functional connectivity--or covariance among regions or nodes--are the same as the eigenmodes of the underlying effective connectivity, provided we limit ourselves to symmetrical connections. This symmetry constraint is motivated by appealing to proximity graphs based upon multidimensional scaling. Crucially, the principal modes of functional connectivity correspond to the dynamically unstable modes of effective connectivity that decay slowly and show long term memory. Technically, these modes have small negative Lyapunov exponents that approach zero from below. Interestingly, the superposition of modes--whose exponents are sampled fr...
Data from an open label randomised controlled trial have suggested possible advantages on both mo... more Data from an open label randomised controlled trial have suggested possible advantages on both motor and non-motor measures in patients with Parkinson's disease following 12 months exposure to exenatide. Continued follow up of these same patients was performed to investigate whether these possible advantages persisted in the prolonged absence of this medication. All participants from an open label, randomised controlled trial of exenatide as a treatment for Parkinson's disease, were invited for a further follow up assessment at the UCL Institute of Neurology. This visit included all 20 individuals who had previously completed twelve months exposure to exenatide 10ug bd and the 24 individuals who had acted as randomised controls. Motor severity of PD was compared after overnight withdrawal of conventional PD medication using blinded video assessment of the MDS-UPDRS, together with several non-motor tests. This assessment was thus 24 months after their original baseline visit,...
Recently, there has been a lot of interest in characterising the connectivity of resting state br... more Recently, there has been a lot of interest in characterising the connectivity of resting state brain networks. Most of the literature uses functional connectivity to examine these intrinsic brain networks. Functional connectivity has well documented limitations because of its inherent inability to identify causal interactions. Dynamic causal modelling (DCM) is a framework that allows for the identification of the causal (directed) connections among neuronal systems--known as effective connectivity. This technical note addresses the validity of a recently proposed DCM for resting state fMRI--as measured in terms of their complex cross spectral density--referred to as spectral DCM. Spectral DCM differs from (the alternative) stochastic DCM by parameterising neuronal fluctuations using scale free (i.e., power law) forms, rendering the stochastic model of neuronal activity deterministic. Spectral DCM not only furnishes an efficient estimation of model parameters but also enables the det...
This paper examines intrinsic brain networks in light of recent developments in the characterisat... more This paper examines intrinsic brain networks in light of recent developments in the characterisation of resting state fMRI timeseries--and simulations of neuronal fluctuations based upon the connectome. Its particular focus is on patterns or modes of distributed activity that underlie functional connectivity. We first demonstrate that the eigenmodes of functional connectivity--or covariance among regions or nodes--are the same as the eigenmodes of the underlying effective connectivity, provided we limit ourselves to symmetrical connections. This symmetry constraint is motivated by appealing to proximity graphs based upon multidimensional scaling. Crucially, the principal modes of functional connectivity correspond to the dynamically unstable modes of effective connectivity that decay slowly and show long term memory. Technically, these modes have small negative Lyapunov exponents that approach zero from below. Interestingly, the superposition of modes--whose exponents are sampled fr...
Data from an open label randomised controlled trial have suggested possible advantages on both mo... more Data from an open label randomised controlled trial have suggested possible advantages on both motor and non-motor measures in patients with Parkinson's disease following 12 months exposure to exenatide. Continued follow up of these same patients was performed to investigate whether these possible advantages persisted in the prolonged absence of this medication. All participants from an open label, randomised controlled trial of exenatide as a treatment for Parkinson's disease, were invited for a further follow up assessment at the UCL Institute of Neurology. This visit included all 20 individuals who had previously completed twelve months exposure to exenatide 10ug bd and the 24 individuals who had acted as randomised controls. Motor severity of PD was compared after overnight withdrawal of conventional PD medication using blinded video assessment of the MDS-UPDRS, together with several non-motor tests. This assessment was thus 24 months after their original baseline visit,...
Recently, there has been a lot of interest in characterising the connectivity of resting state br... more Recently, there has been a lot of interest in characterising the connectivity of resting state brain networks. Most of the literature uses functional connectivity to examine these intrinsic brain networks. Functional connectivity has well documented limitations because of its inherent inability to identify causal interactions. Dynamic causal modelling (DCM) is a framework that allows for the identification of the causal (directed) connections among neuronal systems--known as effective connectivity. This technical note addresses the validity of a recently proposed DCM for resting state fMRI--as measured in terms of their complex cross spectral density--referred to as spectral DCM. Spectral DCM differs from (the alternative) stochastic DCM by parameterising neuronal fluctuations using scale free (i.e., power law) forms, rendering the stochastic model of neuronal activity deterministic. Spectral DCM not only furnishes an efficient estimation of model parameters but also enables the det...
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Papers by Joshua Kahan