Componential Granger causality, and its application to identifying the source and mechanisms of the top-down biased activation that controls attention to affective vs sensory processing

NeuroImage

Volumn 59, Issue 2, 2012, Pages 1846-1858

  Ge, Tian ^a   Feng, Jianfeng ^a,b   Grabenhorst, Fabian ^c   Rolls, Edmund T ^b,d  

^a FUDAN UNIVERSITY   (China)

^b UNIVERSITY OF WARWICK   (United Kingdom)

^c UNIVERSITY OF CAMBRIDGE   (United Kingdom)

^d UNIVERSITY OF OXFORD   (United Kingdom)

Author keywords

Affect; Biased activation theory of attention; Biased competition; Causal networks; Connectivity; Dorsolateral prefrontal cortex; Emotion; FMRI; Functional networks; Granger causality; Intensity; Neuroimaging; Orbitofrontal cortex; Pleasantness; PPI; Primary taste cortex; Reward; Selective attention; Taste; Value

Indexed keywords

ADULT; AFFECT; ANTERIOR DORSOLATERAL PREFRONTAL CORTEX; ARTICLE; BRAIN FUNCTION; COMPONENTIAL GRANGER CAUSALITY; CONTROLLED STUDY; COVARIANCE; FEMALE; FUNCTIONAL MAGNETIC RESONANCE IMAGING; HUMAN; HUMAN EXPERIMENT; INSULA; INTERMETHOD COMPARISON; MALE; NORMAL HUMAN; ORBITAL CORTEX; POSTERIOR DORSOLATERAL PREFRONTAL CORTEX; PREFRONTAL CORTEX; PRIORITY JOURNAL; SELECTIVE ATTENTION; SENSORY CORTEX; SENSORY STIMULATION; STIMULUS RESPONSE; TASTE; TIME SERIES ANALYSIS; VARIANCE;

ADULT; AFFECT; ALGORITHMS; ATTENTION; BRAIN; FEEDBACK, PHYSIOLOGICAL; FEMALE; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MALE; PLEASURE; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; TASTE; YOUNG ADULT;

EID: 83055194458     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2011.08.047     Document Type: Article

References (73)

1. Bar M. The proactive brain: using analogies and associations to generate predictions. Trends Cogn. Sci. 2007, 11:280-289.
2. Beck D.M., Kastner S. Top-down and bottom-up mechanisms in biasing competition in the human brain. Vision Res. 2009, 49:1154-1165.
3. Bengtsson S.L., Haynes J.D., Sakai K., Buckley M.J., Passingham R.E. The representation of abstract task rules in the human prefrontal cortex. Cereb. Cortex 2009, 19:1929-1936.
4. Bressler S.L., Menon V. Large-scale brain networks in cognition: emerging methods and principles. Trends Cogn. Sci. 2010, 14:277-290.
5. Bressler S.L., Seth A.K. Wiener-Granger Causality: A well established methodology. NeuroImage 2011, 58:323-329.
6. Bressler S.L., Tang W., Sylvester C.M., Shulman G.L., Corbetta M. Top-down control of human visual cortex by frontal and parietal cortex in anticipatory visual spatial attention. J. Neurosci. 2008, 28:10056-10061.
7. Collins D.L., Neelin P., Peters T.M., Evans A.C. Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space. J. Comput. Assist. Tomogr. 1994, 18:192-205.
8. Corbetta M., Shulman G.L. Control of goal-directed and stimulus-driven attention in the brain. Nat. Rev. Neurosci. 2002, 3:201-215.
9. de Araujo I.E.T., Kringelbach M.L., Rolls E.T., Hobden P. The representation of umami taste in the human brain. J. Neurophysiol. 2003, 90:313-319.
10. de Araujo I.E.T., Kringelbach M.L., Rolls E.T., McGlone F. Human cortical responses to water in the mouth, and the effects of thirst. J. Neurophysiol. 2003, 90:1865-1876.
11. de Araujo I.E.T., Rolls E.T., Kringelbach M.L., McGlone F., Phillips N. Taste-olfactory convergence, and the representation of the pleasantness of flavour, in the human brain. Eur. J. Neurosci. 2003, 18:2059-2068.
12. Deco G., Rolls E.T. Attention, short-term memory, and action selection: a unifying theory. Prog. Neurobiol. 2005, 76:236-256.
13. Deco G., Rolls E.T. Neurodynamics of biased competition and co-operation for attention: a model with spiking neurons. J. Neurophysiol. 2005, 94:295-313.
14. Deshpande G., Hu X., Lacey S., Stilla R., Sathian K. Object familiarity modulates effective connectivity during haptic shape perception. Neuroimage 2010, 49:1991-2000.
15. Deshpande G., Sathian K., Hu X. Effect of hemodynamic variability on Granger causality analysis of fMRI. Neuroimage 2010, 52:884-896.
16. Desimone R., Duncan J. Neural mechanisms of selective visual attention. Annu. Rev. Neurosci. 1995, 18:193-222.
17. Ding M., Chen Y., Bressler S.L. Granger causality: basic theory and application to neuroscience. Handbook of Time Series Snalysis 2006, 437-460. Wiley, Weinheim. B. Schelter, M. Winterhalder, J. Timmer (Eds.).
18. Downar J., Crawley A.P., Mikulis D.J., Davis K.D. A multimodal cortical network for the detection of changes in the sensory environment. Nat. Neurosci. 2000, 3:277-283.
19. Friston K. Hierarchical models in the brain. PLoS Comput. Biol. 2008, 4:e1000211.
20. Friston K.J., Buechel C., Fink G.R., Morris J., Rolls E.T., Dolan R.J. Psychophysiological and modulatory interactions in neuroimaging. Neuroimage 1997, 6:218-229.
21. Friston K.J., Glaser D.E., Henson R.N., Kiebel S., Phillips C., Ashburner J. Classical and Bayesian inference in neuroimaging: applications. Neuroimage 2002, 16:484-512.
22. Ge T., Kendrick K.M., Feng J. A novel extended Granger Causal Model approach demonstrates brain hemispheric differences during face recognition learning. PLoS Comput. Biol. 2009, 5:e1000570.
23. Genovese C.R., Lazar N.A., Nichols T. Thresholding of statistical maps in functional neuroimaging using the false discovery rate. Neuroimage 2002, 15:870-878.
24. Geweke J. Measurement of linear-dependence and feedback between multiple time-series. J. Am. Stat. Assoc. 1982, 77:304-313.
25. Geweke J.F. Measures of conditional linear-dependence and feedback between time-series. J. Am. Stat. Assoc. 1984, 79:907-915.
26. Gitelman D.R., Penny W.D., Ashburner J., Friston K.J. Modeling regional and psychophysiologic interactions in fMRI: the importance of hemodynamic deconvolution. Neuroimage 2003, 19:200-207.
27. Gottfried J.A., O'Doherty J., Dolan R.J. Appetitive and aversive olfactory learning in humans studied using event-related functional magnetic resonance imaging. J. Neurosci. 2002, 22:10829-10837.
28. Gottfried J.A., Winston J.S., Dolan R.J. Dissociable codes of odor quality and odorant structure in human piriform cortex. Neuron 2006, 49:467-479.
29. Grabenhorst F., Rolls E.T. Selective attention to affective value alters how the brain processes taste stimuli. Eur. J. Neurosci. 2008, 27:723-729.
30. Grabenhorst F., Rolls E.T. Attentional modulation of affective vs sensory processing: functional connectivity and a top-down biased activation theory of selective attention. J. Neurophysiol. 2010, 104:1649-1660.
31. Grabenhorst F., Rolls E.T. Value, pleasure, and choice in the ventral prefrontal cortex. Trends Cogn. Sci. 2011, 15:56-67.
32. Grabenhorst F., Rolls E.T., Bilderbeck A. How cognition modulates affective responses to taste and flavor: top down influences on the orbitofrontal and pregenual cingulate cortices. Cereb. Cortex 2008, 18:1549-1559.
33. Grabenhorst F., Rolls E.T., Parris B.A., D'Souza A. How the brain represents the reward value of fat in the mouth. Cereb. Cortex 2010, 20:1082-1091.
34. Granger C.W.J. Investigating causal relations by econometric models and cross-spectral methods. Econometrica 1969, 37:424-438.
35. Green W.H. Econometric Analysis 2002, Prentice Hall, Upper Saddle River, NJ. 5 ed.
36. Guo S.X., Ladroue C., Feng J.F. Granger causality: theory and applications. Frontiers in Computational and Systems Biology 2010, 83-111. Springer-Verlag. J.F. Feng, W.J. Fu, F.Z. Sun (Eds.).
37. Haase L., Cerf-Ducastel B., Murphy C. Cortical activation in response to pure taste stimuli during the physiological states of hunger and satiety. Neuroimage 2009, 44:1008-1021.
38. Henson R. Analysis of fMRI time series. Human Brain Function 2003, Academic Press, London. J. Ashburner, K. Friston, W. Penny (Eds.).
39. Hwang K., Velanova K., Luna B. Strengthening of top-down frontal cognitive control networks underlying the development of inhibitory control: a functional magnetic resonance imaging effective connectivity study. J. Neurosci. 2010, 30:15535-15545.
40. Jiao Q., Lu G., Zhang Z., Zhong Y., Wang Z., Guo Y., Li K., Ding M., Liu Y. Granger causal influence predicts BOLD activity levels in the default mode network. Hum. Brain Mapp. 2011, 32:154-161.
41. Kampen N.G.v. Stochastic Processes in Physics and Chemistry 1992, Elsevier, Amsterdam.
42. Kanwisher N., Wojciulik E. Visual attention: insights from brain imaging. Nat. Rev. Neurosci. 2000, 1:91-100.
43. Kiebel S.J., Poline J.B., Friston K.J., Holmes A.P., Worsley K.J. Robust smoothness estimation in statistical parametric maps using standardized residuals from the general linear model. NeuroImage 1999, 10:756-766.
44. Klein J.C., Rushworth M.F., Behrens T.E., Mackay C.E., de Crespigny A.J., D'Arceuil H., Johansen-Berg H. Topography of connections between human prefrontal cortex and mediodorsal thalamus studied with diffusion tractography. Neuroimage 2010, 51:555-564.
45. Kouneiher F., Charron S., Koechlin E. Motivation and cognitive control in the human prefrontal cortex. Nat. Neurosci. 2009, 12:939-945.
46. Kringelbach M.L., O'Doherty J., Rolls E.T., Andrews C. Activation of the human orbitofrontal cortex to a liquid food stimulus is correlated with its subjective pleasantness. Cereb. Cortex 2003, 13:1064-1071.
47. Luo Q., Ge T., Feng J. Granger causality with signal-dependent noise. Neuroimage 2011, 57:1422-1429.
48. McCabe C., Rolls E.T. Umami: a delicious flavor formed by convergence of taste and olfactory pathways in the human brain. Eur. J. Neurosci. 2007, 25:1855-1864.
49. Mechelli A., Price C.J., Friston K.J., Ishai A. Where bottom-up meets top-down: neuronal interactions during perception and imagery. Cereb. Cortex 2004, 14:1256-1265.
50. Nitschke J.B., Dixon G.E., Sarinopoulos I., Short S.J., Cohen J.D., Smith E.E., Kosslyn S.M., Rose R.M., Davidson R.J. Altering expectancy dampens neural response to aversive taste in primary taste cortex. Nat. Neurosci. 2006, 9:435-442.
51. O'Doherty J., Rolls E.T., Francis S., Bowtell R., McGlone F. The representation of pleasant and aversive taste in the human brain. J. Neurophysiol. 2001, 85:1315-1321.
52. O'Doherty J.P., Dayan P., Friston K., Critchley H., Dolan R.J. Temporal difference models and reward-related learning in the human brain. Neuron 2003, 38:329-337.
53. O'Doherty J.P., Buchanan T.W., Seymour B., Dolan R.J. Predictive neural coding of reward preference involves dissociable responses in human ventral midbrain and ventral striatum. Neuron 2006, 49:157-166.
54. Renart A., Parga N., Rolls E.T. Backprojections in the cerebral cortex: implications for memory storage. Neural Comput. 1999, 11:1349-1388.
55. Rolls E.T. Memory, Attention, and Decision-Making: A Unifying Computational Neuroscience Approach 2008, Oxford University Press, Oxford.
56. Rolls E.T., Deco G. Computational Neuroscience of Vision 2002, Oxford University Press, Oxford.
57. Rolls E.T., Grabenhorst F. The orbitofrontal cortex and beyond: from affect to decision-making. Prog. Neurobiol. 2008, 86:216-244.
58. Rolls E.T., Kringelbach M.L., de Araujo I.E.T. Different representations of pleasant and unpleasant odors in the human brain. Eur. J. Neurosci. 2003, 18:695-703.
59. Rolls E.T., Grabenhorst F., Margot C., da Silva M.A.A.P., Velazco M.I. Selective attention to affective value alters how the brain processes olfactory stimuli. J. Cogn. Neurosci. 2008, 20:1815-1826.
60. Rossi A.F., Pessoa L., Desimone R., Ungerleider L.G. The prefrontal cortex and the executive control of attention. Exp. Brain Res. 2009, 192:489-497.
61. Sakai K., Passingham R.E. Prefrontal interactions reflect future task operations. Nat. Neurosci. 2003, 6:75-81.
62. Sakai K., Passingham R.E. Prefrontal set activity predicts rule-specific neural processing during subsequent cognitive performance. J. Neurosci. 2006, 26:1211-1218.
63. Schippers M.B., Keysers C. Mapping the flow of information within the putative mirror neuron system during gesture observation. Neuroimage 2011, 57:37-44.
64. Schippers M.B., Roebroeck A., Renken R., Nanetti L., Keysers C. Mapping the information flow from one brain to another during gestural communication. Proc. Natl. Acad. Sci. U.S.A. 2010, 107:9388-9393.
65. Schippers M.B., Renken R., Keysers C. The effect of intra- and inter-subject variability of hemodynamic responses on group level Granger causality analyses. Neuroimage 2011, 57:22-36.
66. Schoenfeld M.A., Neuer G., Tempelmann C., Schussler K., Noesselt T., Hopf J.M., Heinze H.J. Functional magnetic resonance tomography correlates of taste perception in the human primary taste cortex. Neuroscience 2004, 127:347-353.
67. Sims C.A. Money, income, and causality. Am. Econ. Rev. 1972, 62:540-552.
68. Small D.M., Gregory M.D., Mak Y.E., Gitelman D., Mesulam M.M., Parrish T. Dissociation of neural representation of intensity and affective valuation in human gustation. Neuron 2003, 39:701-711.
69. Veldhuizen M.G., Bender G., Constable R.T., Small D.M. Trying to detect taste in a tasteless solution: modulation of early gustatory cortex by attention to taste. Chem. Senses 2007, 32:569-581.
70. Wiener N. The theory of prediction. Modern Mathematics for Engineers 1956, McGraw-Hill, New York. E. Beckenbach (Ed.).
71. Wilson J.L., Jenkinson M., Araujo I.E.T., Kringelbach M.L., Rolls E.T., Jezzard P. Fast, fully automated global and local magnetic field optimisation for fMRI of the human brain. Neuroimage 2002, 17:967-976.
72. Yacubian J., Glascher J., Schroeder K., Sommer T., Braus D.F., Buchel C. Dissociable systems for gain- and loss-related value predictions and errors of prediction in the human brain. J. Neurosci. 2006, 26:9530-9537.
73. Zou C.L., Feng J.F. Granger causality vs. dynamic Bayesian network inference: a comparative study. BMC Bioinformatics 2009, 10:122.