Karl J Friston

Publications (754) View all

• Article: Post-hoc selection of dynamic causal models.

  M J Rosa, K Friston, W Penny
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  ABSTRACT: Dynamic causal modelling (DCM) was originally proposed as a hypothesis driven procedure in which a small number of neurobiologically motivated models are compared. Model comparison in this context usually proceeds by individually fitting each model to data and then approximating the corresponding model evidence with a free energy bound. However, a recent trend has emerged for comparing very large numbers of models in a more exploratory manner. This led Friston and Penny (2011) to propose a post-hoc approximation to the model evidence, which is computed by optimising only the largest (full) model of a set of models. The evidence for any (reduced) submodel is then obtained using a generalisation of the Savage-Dickey density ratio (Dickey, 1971). The benefit of this post-hoc approach is a huge reduction in the computational time required for model fitting. This is because only a single model is fitted to data, allowing a potentially huge model space to be searched relatively quickly. In this paper, we explore the relationship between the free energy bound and post-hoc approximations to the model evidence in the context of deterministic (bilinear) dynamic causal models (DCMs) for functional magnetic resonance imaging data.
  Journal of neuroscience methods 05/2012; 208(1):66-78. · 2.30 Impact Factor
• Source

  Available from: Karl J Friston

  Article: Topological FDR for neuroimaging.

  J Chumbley, K Worsley, G Flandin, K Friston
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  ABSTRACT: In this technical note, we describe and validate a topological false discovery rate (FDR) procedure for statistical parametric mapping. This procedure is designed to deal with signal that is continuous and has, in principle, unbounded spatial support. We therefore infer on topological features of the signal, such as the existence of local maxima or peaks above some threshold. Using results from random field theory, we assign a p-value to each maximum in an SPM and identify an adaptive threshold that controls false discovery rate, using the Benjamini and Hochberg (BH) procedure (1995). This provides a natural complement to conventional family wise error (FWE) control on local maxima. We use simulations to contrast these procedures; both in terms of their relative number of discoveries and their spatial accuracy (via the distribution of the Euclidian distance between true and discovered activations). We also assessed two other procedures: cluster-wise and voxel-wise FDR procedures. Our results suggest that (a) FDR control of maxima or peaks is more sensitive than FWE control of peaks with minimal cost in terms of false-positives, (b) voxel-wise FDR is substantially less accurate than topological FWE or FDR control. Finally, we present an illustrative application using an fMRI study of visual attention.
  NeuroImage 11/2009; 49(4):3057-64. · 5.89 Impact Factor
• Source

  Available from: Karl J Friston

  Article: Dynamic Causal Models for phase coupling.

  W D Penny, V Litvak, L Fuentemilla, E Duzel, K Friston
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  ABSTRACT: This paper presents an extension of the Dynamic Causal Modelling (DCM) framework to the analysis of phase-coupled data. A weakly coupled oscillator approach is used to describe dynamic phase changes in a network of oscillators. The use of Bayesian model comparison allows one to infer the mechanisms underlying synchronization processes in the brain. For example, whether activity is driven by master-slave versus mutual entrainment mechanisms. Results are presented on synthetic data from physiological models and on MEG data from a study of visual working memory.
  Journal of neuroscience methods 08/2009; 183(1):19-30. · 2.30 Impact Factor
• Article: Short-term adaptation to a simple motor task: a physiological process preserved in multiple sclerosis.

  L Mancini, O Ciccarelli, F Manfredonia, J S Thornton, F Agosta, F Barkhof, C Beckmann, N De Stefano, C Enzinger, F Fazekas, [......], X Montalban, J Palace, C Polman, M Rocca, S Ropele, A Rovira, C Wegner, K Friston, A Thompson, T Yousry
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  ABSTRACT: Short-term adaptation indicates the attenuation of the functional MRI (fMRI) response during repeated task execution. It is considered to be a physiological process, but it is unknown whether short-term adaptation changes significantly in patients with brain disorders, such as multiple sclerosis (MS). In order to investigate short-term adaptation during a repeated right-hand tapping task in both controls and in patients with MS, we analyzed the fMRI data collected in a large cohort of controls and MS patients who were recruited into a multi-centre European fMRI study. Four fMRI runs were acquired for each of the 55 controls and 56 MS patients at baseline and 33 controls and 26 MS patients at 1-year follow-up. The externally cued (1 Hz) right hand tapping movement was limited to 3 cm amplitude by using at all sites (7 at baseline and 6 at follow-up) identically manufactured wooden frames. No significant differences in cerebral activation were found between sites. Furthermore, our results showed linear response adaptation (i.e. reduced activation) from run 1 to run 4 (over a 25 minute period) in the primary motor area (contralateral more than ipsilateral), in the supplementary motor area and in the primary sensory cortex, sensory-motor cortex and cerebellum, bilaterally. This linear activation decay was the same in both control and patient groups, did not change between baseline and 1-year follow-up and was not influenced by the modest disease progression observed over 1 year. These findings confirm that the short-term adaptation to a simple motor task is a physiological process which is preserved in MS.
  NeuroImage 01/2009; 45(2):500-11. · 5.89 Impact Factor
• Source

  Available from: Jérémie Mattout

  Article: Population-level inferences for distributed MEG source localization under multiple constraints: application to face-evoked fields.

  R N Henson, J Mattout, K D Singh, G R Barnes, A Hillebrand, K Friston
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  ABSTRACT: We address some key issues entailed by population inference about responses evoked in distributed brain systems using magnetoencephalography (MEG). In particular, we look at model selection issues at the within-subject level and feature selection issues at the between-subject level, using responses evoked by intact and scrambled faces around 170 ms (M170). We compared the face validity of subject-specific forward models and their summary statistics in terms of how estimated responses reproduced over subjects. At the within-subject level, we focused on the use of multiple constraints, or priors, for inverting distributed source models. We used restricted maximum likelihood (ReML) estimates of prior covariance components (in both sensor and source space) and show that their relative importance is conserved over subjects. At the between-subject level, we used standard anatomical normalization methods to create posterior probability maps that furnish inference about regionally specific population responses. We used these to compare different summary statistics, namely; (i) whether to test for differences between condition-specific source estimates, or whether to test the source estimate of differences between conditions, and (ii) whether to accommodate differences in source orientation by using signed or unsigned (absolute) estimates of source activity.
  NeuroImage 12/2007; 38(3):422-38. · 5.89 Impact Factor