Brain Connectivity

Brain Mapping identifies regions where experimental effect sizes are significantly non-zero (orange). Brain connectivity then explains activity in a set of regions using (eg. differential equation) models with directed connections. For Brain Mapping the parameters of interest are regional activities and for Brain Connectivity they are directed pathways (blue). Both approaches can be applied to data from fMRI or M/EEG. For fMRI this requires Bayesian inversion of a forward model describing a temporal convolution, and for M/EEG a forward model describing a spatial mapping.

Dynamic Causal Modelling
Clinical Applications

  • N. Ramnani, T.E.J. Behrens, W.D. Penny, and P.M. Matthews. New approaches for exploring anatomic and functional connectivity in the human brain. Biological Psychiatry, 2004, 56(9), 613-619.

  • W.D. Penny, K.E. Stephan, A. Mechelli, and K.J. Friston. Modelling Functional Integration: A Comparison of Structural Equation and Dynamic Causal and Models. NeuroImage, 23:264-274, 2004. Note: Supplement 1.

  • Dynamic Causal Models

    Dynamic Causal Modeling (DCM) is a Bayesian estimation framework for fitting differential equation models of neuronal activity to brain imaging data. Model comparison in this context allows researchers to formally compare different theories about the architectures of the large-scale neural networks that mediate human perception, cognition and action, using non-invasive brain imaging data. In the figure below the red traces indicate time series of neuronal activity that result when the modulatory connection from u2 is activated. This is a mathematical model of gain control effects mediated eg. by neuromodulators.

  • W. Penny (2011). Comparing Dynamic Causal Models using AIC, BIC and Free Energy. Neuroimage Available online 27 July 2011.

  • W Penny, K Stephan, J. Daunizeau, M. Rosa, K. Frsiton, T. Schofield and A Leff. Comparing Families of Dynamic Causal Models. PLoS Computational Biology, Mar 2010, 6(3), e1000709.

  • W.D. Penny, K.E. Stephan, A. Mechelli, and K.J. Friston. Comparing Dynamic Causal Models. NeuroImage, 22(3):1157-1172, 2004.

  • K Stephan, W Penny, R Moran, H den Ouden, J Daunizeau and K Friston. Ten simple rules for dynamic causal modeling. Neuroimage, Feb 15 2010, 49(4):3099-109.

  • K.E. Stephan, L.M. Harrison, S.J. Kiebel, O. David, W.D. Penny, and K.J. Friston. Dynamic causal models of neural system dynamics: current state and future extensions. Journal of Biosciences, 32:411-416, 2007.

  • K.E. Stephan, J.C. Marshall, W.D. Penny, K.J. Friston, and G.R. Fink. Interhemispheric integration of visual processing during task-driven lateralization. Journal of Neuroscience, 27:3512-3522, 2007.

  • K.E. Stephan, W.D. Penny, J.C. Marshall, G.R. Fink, and K.J. Friston. Investigating the functional role of Callosal connections with Dynamic Causal Models. Ann. N.Y. Acad. Sci., 1064:16-36, 2005.

  • K.E. Stephan, L. Harrison, W.D. Penny, and K.J. Friston. Biophysical models of fMRI responses. Current Opinion in Neurobiology, 14(5):629-635, 2004.

  • K.J. Friston, L. Harrison, and W.D. Penny. Dynamic Causal Modelling. NeuroImage, 19(4):1273-1302, 2003.

  • Clinical Applications

    Collaborations with Alex Leff's group have involved the application of Dynamic Causal Models (for MEG/EEG) in studying recovery of language function after brain injury (eg. due to stroke). Work with Klaas Stephan's group aims to fractionate schizophrenic groups into sub-categories with distinct brain connectivity fingerprints.

  • T. Schofield and W. Penny and K. Stephan and J. Crinion and A. Thompson and C. Price and A. Leff (2012). Changes in auditory feedback connections determine the severity of speech processing deficits after stroke. Journal of Neuroscience 32(12):4260-4270.

  • Z. Woodhead, W. Penny, G. Barnes, H. Crewes, R. Wise, C. Price and A. Leff (2013). Reading therapy strengthens top-down connectivity in patients with pure alexia. Brain. 136, 2579-2591.

  • S. Teki, G. Barnes, W. Penny, P. Iverson, Z. Woodhead, T. Griffiths and A. Leff (2013). The right hemisphere supports but does not replace left hemisphere auditory function in patients with persisting aphasia. Brain. 136, 1901-12.

  • Z. Woodhead, G. Barnes, W. Penny, R. Moran, S. Teki, C. Price and A. Leff (2012). Reading front to back: MEG evidence for early feedback effects during word recognition. Cerebral Cortex doi: 10.1093/cercor/bhs365.

  • K. Brodersen, L. Deserno, F. Schlagenhauf, Z. Lin, W. Penny, J. Buhmann and K. Stephan (2014). Dissecting psychiatric spectrum disorders by generative embedding. Neuroimage: Clinical, 4, 98-111 ,