2020

Causality in cognitive neuroscience: concepts, challenges, and distributional robustness

Weichwald, Sebastian, Peters, Jonas

Understand

While probabilistic models describe the dependence structure between observed variables, causal models go one step further: they predict, for example, how cognitive functions are affected by external interventions that perturb neuronal activity.

In this review and perspective article, we introduce the concept of causality in the context of cognitive neuroscience and review existing methods for inferring causal relationships from data.
Causal inference is an ambitious task that is particularly challenging in cognitive neuroscience.
We discuss two difficulties in more detail: the scarcity of interventional data and the challenge of finding the right variables.

Built on

“The Probability Approach in Econometrics”
T. Haavelmo · 1944
Earlier work this paper cites.
“Analyse générale des liaisons stochastiques”
G. Darmois · 1953
Earlier work this paper cites.
“The Direction of Time”
H. Reichenbach · 1956
Earlier work this paper cites.
“Tests of equality between sets of coefficients in two linear regressions”
G.. Chow · 1960
Earlier work this paper cites.
“Linear combinations of independent random variables and the normal distribution law”
V.. Skitovič · 1962
Earlier work this paper cites.
“Investigating Causal Relations by Econometric Models and Cross-spectral Methods”
C… Granger · 1969
Earlier work this paper cites.
“Econometric policy evaluation: A critique”
R. Lucas · 1976
Earlier work this paper cites.
“Autonomy”
J. Aldrich · 1989
Earlier work this paper cites.
“Structural Equations with Latent Variables”
Kenneth Bollen · 1989
Earlier work this paper cites.
“Independence properties of directed markov fields”
S.. Lauritzen, A.. Dawid, B.. Larsen and H.-G. Leimer · 1990
Earlier work this paper cites.
“Equivalence and Synthesis of Causal Models”
Thomas Verma and Judea Pearl · 1990
Earlier work this paper cites.
“R.A. Fisher and the development of statistics - a view in his centerary year”
Denis Conniffe · 1991
Earlier work this paper cites.
“Graphical Models”
S. Lauritzen · 1996
Earlier work this paper cites.
“Causation, Prediction, and Search”
Peter Spirtes, Clark Glymour and Richard Scheines · 2001
Earlier work this paper cites.
“Optimal structure identification with greedy search”
D.. Chickering · 2002
Earlier work this paper cites.
“A Distribution-Free Theory of Nonparametric Regression”
L. Györfi, M. Kohler, A. Krzyżak and H. Walk · 2002
Earlier work this paper cites.
“Neural correlates of consciousness in humans”
Geraint Rees, Gabriel Kreiman and Christof Koch · 2002
Earlier work this paper cites.
“Learning sparse nonparametric DAGs” (to appear)
Original
Xun Zheng et al · 2002
Earlier work this paper cites.
“Two Theorems on Invariance and Causality”
N. Cartwright · 2003
Earlier work this paper cites.
“Dynamic causal modelling”
K.. Friston, L. Harrison and W. Penny · 2003
Earlier work this paper cites.
“Causal Inference of Ambiguous Manipulations”
Peter Spirtes and Richard Scheines · 2004
Earlier work this paper cites.
“Deep Brain Stimulation for Treatment-Resistant Depression”
Helen Mayberg et al · 2005
Earlier work this paper cites.
“Making Things Happen: A Theory of Causal Explanation”
James Woodward · 2005
Earlier work this paper cites.
“Electric Fields of the Brain”
P.. Nunez and R. Srinivasan · 2006
Earlier work this paper cites.
“Learning the structure of linear latent variable models”
Ricardo Silva, Richard Scheine, Clark Glymour and Peter Spirtes · 2006
Earlier work this paper cites.
“Exact Bayesian structure learning from uncertain interventions”
D. Eaton and K.. Murphy · 2007
Earlier work this paper cites.
“The Cholesterol Wars”
Daniel Steinberg · 2007
Earlier work this paper cites.
“Causality in Economics and Econometrics”
K.. Hoover · 2008
Earlier work this paper cites.
“Nonlinear causal discovery with additive noise models”
Patrik Hoyer et al · 2008
Earlier work this paper cites.
“What we can do and what we cannot do with fMRI”
Nikos Logothetis · 2008
Earlier work this paper cites.
“Kernel-Granger causality and the analysis of dynamical networks”
D. Marinazzo, M. Pellicoro and S. Stramaglia · 2008
Earlier work this paper cites.
“Transcranial direct current stimulation: State of the art 2008”
Michael. Nitsche et al · 2008
Earlier work this paper cites.
“Causality, invariance and policy”
N. Cartwright · 2009
Earlier work this paper cites.
“The history, development and impact of computed imaging in neurological diagnosis and neurosurgery: CT, MRI, and DTI”
Aaron Filler · 2009
Earlier work this paper cites.
“Causality”
Judea Pearl · 2009
Earlier work this paper cites.
“On the Identifiability of the Post-Nonlinear Causal Model”
K. Zhang and A. Hyvärinen · 2009
Earlier work this paper cites.
“Global and local fMRI signals driven by neurons defined optogenetically by type and wiring”
Jin Lee et al · 2010
Earlier work this paper cites.
“Six problems for causal inference from fMRI”
J Ramsey et al · 2010
Earlier work this paper cites.
“Cholesterol and Beyond”
A Truswell · 2010
Earlier work this paper cites.
“Nonlinear connectivity by Granger causality”
Daniele Marinazzo, Wei Liao, Huafu Chen and Sebastiano Stramaglia · 2011
Earlier work this paper cites.
“Functional network organization of the human brain”
Jonathan Power et al · 2011
Earlier work this paper cites.
“Network modelling methods for FMRI”
Stephen Smith et al · 2011
Earlier work this paper cites.
“Effective connectivity: influence, causality and biophysical modeling”
Pedro Valdes-Sosa, Alard Roebroeck, Jean Daunizeau and Karl Friston · 2011
Earlier work this paper cites.

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Then

“Recovery of non-linear cause-effect relationships from linearly mixed neuroimaging data”
Sebastian Weichwald, Arthur Gretton, Bernhard Schölkopf and Moritz Grosse-Wentrup · 2016
Later among the works it cites.
“MERLiN: Mixture Effect Recovery in Linear Networks”
Sebastian Weichwald, Moritz Grosse-Wentrup and Arthur Gretton · 2016
Later among the works it cites.
“Whole-Brain Neural Dynamics of Probabilistic Reward Prediction”
Dominik Bach, Mkael Symmonds, Gareth Barnes and Raymond Dolan · 2017
Later among the works it cites.
“Transcranial electrical stimulation”
Sven Bestmann and Vincent Walsh · 2017
Later among the works it cites.
“Causal mapping of emotion networks in the human brain: Framework and initial findings”
Julien Dubois et al · 2017
Later among the works it cites.
“When the Map Is Better Than the Territory”
Erik. Hoel · 2017
Later among the works it cites.
“Discovery of causal models that contain latent variables through Bayesian scoring of independence constraints”
Fattaneh Jabbari, Joseph Ramsey, Peter Spirtes and Gregory Cooper · 2017
Later among the works it cites.
“From connectome to cognition: The search for mechanism in human functional brain networks”
Ravi Mill, Takuya Ito and Michael Cole · 2017
Later among the works it cites.
“Elements of Causal Inference”
J. Peters, D. Janzing and B. Schölkopf · 2017
Later among the works it cites.
“Causal Consistency of Structural Equation Models”
Rubenstein \& Weichwald andothers · 2017
Later among the works it cites.
“Assessing and tuning brain decoders: Cross-validation, caveats, and guidelines” Individual Subject Prediction
Gaël Varoquaux et al · 2017
Later among the works it cites.
“Causal Discovery from Nonstationary/Heterogeneous Data: Skeleton Estimation and Orientation Determination”
K. Zhang et al · 2017
Later among the works it cites.
“An Upper Bound for Random Measurement Error in Causal Discovery”
T. Blom, A. Klimovskaia, S. Magliacane and J.. Mooij · 2018
Later among the works it cites.
“Theoretical Aspects of Cyclic Structural Causal Models”
Original
Stephan Bongers, Jonas Peters, Bernhard Schölkopf and Joris Mooij · 2018
Later among the works it cites.
“Invariant Causal Prediction in the Presence of Latent Variables”
Original
R. Christiansen and J. Peters · 2018
Later among the works it cites.
“Structural causal models for macro-variables in time-series”
Original
Dominik Janzing, Paul Rubenstein and Bernhard Schölkopf · 2018
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“The lure of causal statements: Rampant mis-inference of causality in estimated connectivity”
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“Invariant Causal Prediction for Sequential Data”
N. Pfister, P. Bühlmann and J. Peters · 2018
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“The new mind readers: What neuroimaging can and cannot reveal about our thoughts”
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“Anchor regression: heterogeneous data meets causality”
Original
Dominik Rothenhäusler, Nicolai Meinshausen, Peter Bühlmann and Jonas Peters · 2018
Later among the works it cites.
“Atlases of cognition with large-scale human brain mapping”
Gaël Varoquaux et al · 2018
Later among the works it cites.
“Non-invasive brain stimulation: a paradigm shift in understanding brain oscillations”
Johannes Vosskuhl, Daniel Strüber and Christoph Herrmann · 2018
Later among the works it cites.
“Causal Discovery with Linear Non-Gaussian Models underMeasurement Error: Structural Identifiability Results”
K. Zhang et al · 2018
Later among the works it cites.
“Approximate Causal Abstraction”
Sander Beckers, Frederick Eberhardt and Joseph Halpern · 2019
Later among the works it cites.
“Abstracting Causal Models”
Sander Beckers and Joseph Halpern · 2019
Later among the works it cites.
“Invariant Risk Minimization”
Original
I. M. L. and D. Lopez-Paz · 2019
Later among the works it cites.
“Selecting causal brain features with a single conditional independence test per feature”
A Mastakouri, B Schölkopf and D Janzing · 2019
Later among the works it cites.
“Learning stable and predictive structures in kinetic systems”
N. Pfister, S. Bauer and J. Peters · 2019
Later among the works it cites.
“Robustifying Independent Component Analysis by Adjusting for Group-Wise Stationary Noise”
Niklas Pfister, Sebastian Weichwald, Peter Bühlmann and Bernhard Schölkopf · 2019
Later among the works it cites.
“Advancing functional connectivity research from association to causation”
Andrew Reid et al · 2019
Later among the works it cites.
“Estimating feedforward and feedback effective connections from fMRI time series: Assessments of statistical methods”
Ruben Sanchez-Romero et al · 2019
Later among the works it cites.
“Towards a Universal Taxonomy of Macro-scale Functional Human Brain Networks”
Lucina. Uddin, B.. Yeo and R. Spreng · 2019
Later among the works it cites.
“Pragmatism and Variable Transformations in Causal Modelling”, 2019
Sebastian Weichwald · 2019
Later among the works it cites.
“Inferring Causality from Noninvasive Brain Stimulation in Cognitive Neuroscience” Forthcoming
Til Bergmann and Gesa Hartwigsen · 2020
Closest in time.
“The Difficult Task of Distribution Generalization in Nonlinear Models”
Original
R. Christiansen et al · 2020
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“Transcranial alternating current stimulation attenuates BOLD adaptation and increases functional connectivity”
Kohitij Kar, Takuya Ito, Michael. Cole and Bart Krekelberg · 2020
Closest in time.
“Joint Causal Inference from Multiple Contexts”
J.. Mooij, S. Magliacane and T. Claassen · 2020
Closest in time.
“Causal models for dynamical systems”
Original
J. Peters, S. Bauer and N. Pfister · 2020
Closest in time.
“Combining Multiple Functional Connectivity Methods to Improve Causal Inferences” Forthcoming
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Closest in time.
“The Hardness of Conditional Independence Testing and the Generalised Covariance Measure”
R. Shah and J. Peters · 2020
Closest in time.
“A Linear Non-Gaussian Acyclic model for Causal Discovery”
S. Shimizu, P.. Hoyer, A. Hyvärinen and A. Kerminen · 2030
Closest in time.
“Causal Discovery with Continuous Additive Noise Models”
J. Peters, J.. Mooij, D. Janzing and B. Schölkopf · 2053
Closest in time.

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