On network derivation, classification, and visualization: a response to Habeck and Moeller.

In the decade and a half since Biswal's fortuitous discovery of spontaneous correlations in functional imaging data, the field of functional connectivity (FC) has seen exponential growth resulting in the identification of widely-replicated intrinsic networks and the innovation of novel analytic methods with the promise of diagnostic application. As such a young field undergoing rapid change, we have yet to converge upon a desired and needed set of standards. In this issue, Habeck and Moeller begin a dialogue for developing best practices by providing four criticisms with respect to FC estimation methods, interpretation of FC networks, assessment of FC network features in classifying sub-populations, and network visualization. Here, we respond to Habeck and Moeller and provide our own perspective on the concerns raised in the hope that the neuroimaging field will benefit from this discussion.

[1]  Peter Hall,et al.  Bounds on the Rate of Convergence of Moments in the Central Limit Theorem , 1982 .

[2]  L. Sachs.  Angewandte Statistik : Anwendung statistischer Methoden , 1984 .

[3]  Edward Rolf Tufte,et al.  The visual display of quantitative information , 1985 .

[4]  Daniel B. Carr,et al.  The Visual Display of Quantitative Information , 1987 .

[5]  Gerald E. Jones.  How to Lie with Charts , 1995 .

[6]  S. Paradiso,et al.  "Cognitive dysmetria" as an integrative theory of schizophrenia: a dysfunction in cortical-subcortical-cerebellar circuitry? , 1998, Schizophrenia bulletin.

[7]  M. Greicius,et al.  Default-mode network activity distinguishes Alzheimer's disease from healthy aging: Evidence from functional MRI , 2004, Proc. Natl. Acad. Sci. USA.

[8]  Maurizio Corbetta,et al.  The human brain is intrinsically organized into dynamic, anticorrelated functional networks. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[9]  S. Rombouts,et al.  Consistent resting-state networks across healthy subjects , 2006, Proceedings of the National Academy of Sciences.

[10]  Godfrey D Pearlson,et al.  Simulated Driving and Brain Imaging: Combining Behavior, Brain Activity, and Virtual Reality , 2006, CNS Spectrums.

[11]  Norihiro Sadato,et al.  Frontoparietal network involved in successful retrieval from episodic memory. Spatial and temporal analyses using fMRI and ERP. , 2006, Cerebral cortex.

[12]  Hengl Tomislav,et al.  Maps are Not What They Seem: Representing Uncertainty in Soil-property Maps , 2006 .

[13]  J Fiehler,et al.  Age-Dependent Normal Values of T2* and T2′ in Brain Parenchyma , 2008, American Journal of Neuroradiology.

[14]  V. Calhoun,et al.  Modulation of temporally coherent brain networks estimated using ICA at rest and during cognitive tasks , 2008, Human brain mapping.

[15]  Alan D. Castel,et al.  Seeing is believing: The effect of brain images on judgments of scientific reasoning , 2008, Cognition.

[16]  V. Calhoun,et al.  Temporal lobe and “default” hemodynamic brain modes discriminate between schizophrenia and bipolar disorder , 2008, Human brain mapping.

[17]  Kenneth Hugdahl,et al.  Prediction of human errors by maladaptive changes in event-related brain networks , 2008, Proceedings of the National Academy of Sciences.

[18]  Stephen M Smith,et al.  Correspondence of the brain's functional architecture during activation and rest , 2009, Proceedings of the National Academy of Sciences.

[19]  B. Biswal,et al.  The resting brain: unconstrained yet reliable. , 2009, Cerebral cortex.

[20]  Michael Bach,et al.  A primer on common statistical errors in clinical ophthalmology , 2010, Documenta Ophthalmologica.

[21]  Archana Venkataraman,et al.  Intrinsic functional connectivity as a tool for human connectomics: theory, properties, and optimization. , 2010, Journal of neurophysiology.

[22]  Xi-Nian Zuo,et al.  Reliable intrinsic connectivity networks: Test–retest evaluation using ICA and dual regression approach , 2010, NeuroImage.

[23]  Christian Windischberger,et al.  Toward discovery science of human brain function , 2010, Proceedings of the National Academy of Sciences.

[24]  Rex E. Jung,et al.  A Baseline for the Multivariate Comparison of Resting-State Networks , 2011, Front. Syst. Neurosci..