Tracing the route to path analysis in neuroimaging

This article provides a personal perspective of the adoption of path analysis (structural equation modeling) to neuroimaging. The paper covers the motivation stemming from the need to merge functional measures with neuroanatomy and early innovations in its application. The use of path analysis as a means to test directional hypotheses about networks is presented along with the development of the complementary method, partial least squares. A method is useful when it provides insights that were previously inaccessible, and reflecting this, the paper concludes with a synopsis of the theoretical developments that arose for the routine use of methods like path analysis.

[1]  Karl J. Friston,et al.  Investigating the Functional Role of Callosal Connections with Dynamic Causal Models , 2005, Annals of the New York Academy of Sciences.

[2]  Leslie G. Ungerleider,et al.  Changes in limbic and prefrontal functional interactions in a working memory task for faces. , 1996, Cerebral cortex.

[3]  Karl J. Friston Functional and effective connectivity in neuroimaging: A synthesis , 1994 .

[4]  Barry Horwitz,et al.  The pattern of functional coupling of brain regions in the awake rat , 1986, Brain Research.

[5]  Steven L. Bressler,et al.  The Role of Neural Context in Large-Scale Neurocognitive Network Operations , 2007 .

[6]  Rainer Goebel,et al.  Investigating directed cortical interactions in time-resolved fMRI data using vector autoregressive modeling and Granger causality mapping. , 2003, Magnetic resonance imaging.

[7]  Olaf Sporns,et al.  Complex network measures of brain connectivity: Uses and interpretations , 2010, NeuroImage.

[8]  Fred L. Bookstein,et al.  The enduring effects of prenatal alcohol exposure on child development: Birth through seven years, a partial least squares solution. , 1993 .

[9]  R. Cabeza,et al.  Analysis of neural interactions explains the activation of occipital cortex by an auditory stimulus. , 1998, Journal of neurophysiology.

[10]  A. R. McIntosh,et al.  Movement and novelty of a square wave display affect 2-deoxyglucose uptake in the rat visual system , 1989, Behavioural Brain Research.

[11]  Olaf Sporns,et al.  The small world of the cerebral cortex , 2007, Neuroinformatics.

[12]  O. Sporns,et al.  Complex brain networks: graph theoretical analysis of structural and functional systems , 2009, Nature Reviews Neuroscience.

[13]  E. Tulving,et al.  Network Analysis of Positron Emission Tomography Regional Cerebral Blood Flow Data: Ensemble Inhibition during Episodic Memory Retrieval , 1996, The Journal of Neuroscience.

[14]  F. Bookstein,et al.  Neurobehavioral effects of prenatal alcohol: Part II. Partial least squares analysis. , 1989, Neurotoxicology and teratology.

[15]  Leslie G. Ungerleider,et al.  Network analysis of cortical visual pathways mapped with PET , 1994, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[16]  Karl J. Friston,et al.  Dynamic causal modeling for EEG and MEG , 2009, Human brain mapping.

[17]  A. McIntosh,et al.  Structural modeling of functional neural pathways mapped with 2-deoxyglucose: effects of acoustic startle habituation on the auditory system , 1991, Brain Research.

[18]  K J Friston,et al.  The predictive value of changes in effective connectivity for human learning. , 1999, Science.

[19]  O. Sporns,et al.  Dynamical consequences of lesions in cortical networks , 2008, Human brain mapping.

[20]  D. Willshaw,et al.  The cingulate as a catalyst region for global dysfunction: a dynamical modelling paradigm. , 2006, Cerebral cortex.

[21]  Mark W. Woolrich,et al.  Network modelling methods for FMRI , 2011, NeuroImage.

[22]  Karl J. Friston,et al.  Dynamic causal modelling , 2003, NeuroImage.

[23]  A. Meyer-Lindenberg,et al.  Interindividual differences in functional interactions among prefrontal, parietal and parahippocampal regions during working memory. , 2003, Cerebral cortex.

[24]  Rainer Goebel,et al.  Mapping directed influence over the brain using Granger causality and fMRI , 2005, NeuroImage.

[25]  Anthony Randal McIntosh,et al.  Contexts and catalysts , 2007, Neuroinformatics.

[26]  Kewei Chen,et al.  Identification and validation of effective connectivity networks in functional magnetic resonance imaging using switching linear dynamic systems , 2010, NeuroImage.

[27]  B Horwitz,et al.  Intercorrelations of Glucose Metabolic Rates between Brain Regions: Application to Healthy Males in a State of Reduced Sensory Input , 1984, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[28]  G L Shulman,et al.  INAUGURAL ARTICLE by a Recently Elected Academy Member:A default mode of brain function , 2001 .

[29]  A. McIntosh,et al.  Understanding Neural Interactions in Learning and Memory Using Functional Neuroimaging , 1998, Annals of the New York Academy of Sciences.

[30]  M. Corbetta,et al.  Common Blood Flow Changes across Visual Tasks: II. Decreases in Cerebral Cortex , 1997, Journal of Cognitive Neuroscience.

[31]  A. McIntosh,et al.  Functional Connectivity of the Medial Temporal Lobe Relates to Learning and Awareness , 2003, The Journal of Neuroscience.

[32]  M. N. Rajah,et al.  Interactions of prefrontal cortex in relation to awareness in sensory learning. , 1999, Science.

[33]  Anthony Randal McIntosh,et al.  Partial least squares analysis of neuroimaging data: applications and advances , 2004, NeuroImage.

[34]  A. McIntosh,et al.  Mapping cognition to the brain through neural interactions. , 1999, Memory.

[35]  Karl J. Friston,et al.  Modelling functional integration: a comparison of structural equation and dynamic causal models , 2004, NeuroImage.

[36]  Natasa Kovacevic,et al.  Neuroanatomical differences between mouse strains as shown by high-resolution 3D MRI , 2006, NeuroImage.

[37]  Viktor K. Jirsa,et al.  Handbook of Brain Connectivity , 2007 .

[38]  Natasa Kovacevic,et al.  Extracting Message Inter-Departure Time Distributions from the Human Electroencephalogram , 2011, PLoS Comput. Biol..

[39]  F. Gonzalez-Lima,et al.  Structural equation modeling and its application to network analysis in functional brain imaging , 1994 .

[40]  Barry Horwitz,et al.  Functional Neural Systems Analyzed by Use of Interregional Correlations of Glucose Metabolism , 1989 .

[41]  J V Haxby,et al.  Network analysis of PET-mapped visual pathways in Alzheimer type dementia. , 1995, Neuroreport.

[42]  A. R. McIntosh,et al.  Spatiotemporal analysis of event-related fMRI data using partial least squares , 2004, NeuroImage.

[43]  A. McIntosh,et al.  Spatiotemporal analysis of experimental differences in event-related potential data with partial least squares. , 2001, Psychophysiology.