Abstract
Duhem’s problem arises especially in scientific contexts where the tools and procedures of measurement and analysis are numerous and complex. Several philosophers of cognitive science have cited its manifestations in fMRI as grounds for skepticism regarding the epistemic value of neuroimaging. To address these Duhemian arguments for skepticism, I offer an alternative approach based on Deborah Mayo’s error-statistical account in which Duhem's problem is more fruitfully approached in terms of error probabilities. This is illustrated in examples such as the use of probabilistic brain atlases, comparison of different preprocessing protocols with respect to their error characteristics, and statistical modeling of fMRI data. These examples demonstrate the ways in which we can better understand and formulate the general methodological problem and direct the way toward alternative approaches to neuroimaging in philosophy of cognitive science, in which we can be more balanced and productive in our scrutiny of the epistemic value of neuroimaging studies.
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Notes
For an in-depth error-statistical discussion of what we can learn from fMRI and its theoretical significance for cognitive science, please see Aktunc, 2011; forthcoming).
References
Aktunc, M. Emrah. 2011. “Experimental Knowledge in Cognitive Neuroscience: Evidence, Errors, and Inference.” PhD Diss., Virginia Polytechnic Institute and State University.
Aktunc, M. Emrah. forthcoming. “Severe Tests in Neuroimaging: What We Can Learn and How We Can Learn It.” Philosophy of Science.
Baier, B., H.O. Karnath, M. Dieterich, F. Birklein, C. Heinze, and N.G. Muller. 2010. Keeping memory clear and stable—the contribution of human basal ganglia and prefrontal cortex to working memory. The Journal of Neuroscience 30: 9788–9792.
Bogen, J. (2010) “Theory and Observation in Science.” The Stanford Encyclopedia of Philosophy (Spring 2010 Edition), Edward N. Zalta (ed.), URL = <http://plato.stanford.edu/archives/spr2010/entries/science-theory-observation/>.
Duhem, P. (1906/1991). The Aim And Structure of Physical Theory. [Translated from the French by Philip P. Wiener] Princeton, NJ: Princeton University Press.
Duncan, D.E. 2009. Looking at stress—and God—in the human brain. Waukesha: Discover Magazine.
Fransson, P., K.D. Merboldt, K.M. Petersson, M. Ingvar, and J. Frahm. 2002. On the effects of spatial filtering—a comparative fMRI study of episodic memory encoding at high and Low resolution. NeuroImage 16: 977–984.
Huettel, S.A., A.W. Song, and G. McCarthy. 2004. Functional magnetic resonance imaging. Sunderland: Sinauer Associates, Inc. Publishers.
Huettel, S.A., A.W. Song, and G. McCarthy. 2008. Functional magnetic resonance imaging, 2nd ed. Sunderland: Sinauer Associates, Inc. Publishers.
LaConte, S., J. Anderson, S. Muley, J. Ashe, S. Frutiger, K. Rehm, L.K. Hansen, E. Yacoub, X. Hu, D. Rottenberg, and S. Strother. 2003. The evaluation of preprocessing choices in single-subject BOLD fMRI using NPAIRS performance metrics. NeuroImage 18: 10–27.
Lazar, N.A. 2008. The statistical analysis of functional MRI data. New York: Springer.
Mayo, D. 1996. Error and the growth of experimental knowledge. Chicago: The University of Chicago Press.
Mayo, D. 1997. Duhem’s problem, the Bayesian Way, and error statistics, or ‘What’s belief Got to Do with It?’”. Philosophy of Science 64(2): 222–244.
Mayo, D. 2005. Evidence as passing severe tests: highly probable versus highly probed hypotheses. In Scientific evidence: philosophical theories & applications, ed. P. Achinstein. Baltimore: The Johns Hopkins University Press.
Mayo, D., and A. Spanos. 2004. Methodology in practice: statistical misspecification testing. Philosophy of Science 71: 1007–1025.
Mayo, D., and A. Spanos. 2010. Error and inference: recent exchanges on experimental reasoning, reliability, and the objectivity of science. New York: Cambridge University Press.
Mayo, D., and A. Spanos. 2011. Error statistics. In The handbook of philosophy of science, Volume7: philosophy of statistics, ed. Prasanta S. Bandyopadhyay and Malcolm Forster. Amsterdam: Elsevier Publishers.
Mazziotta, J.C., A.W. Toga, A. Evans, P. Fox, and J. Lancaster. 1995. (The international consortium of brain mapping, ICBM). A probabilistic atlas of the human brain: theory and rationale for its development. NeuroImage 2: 89–101.
Petersson, K.M., T.E. Nichols, J.B. Poline, and A.P. Holmes. 1999. Statistical limitations in functional neuroimaging I. Non-inferential methods and statistical models. Philosophical Transactions of the Royal Society of London 354: 1239–1260.
Provost, J.S., M. Petrides, and O. Monchi. 2010. Dissociating the role of the caudate nucleus and dorsolateral prefrontal cortex in the monitoring of events within human working memory. European Journal of Neuroscience 32: 873–880.
Roskies, A. 2008. Neuroimaging and inferential distance. Neuroethics 1: 19–30.
Roskies, A. 2010. Neuroimaging and inferential distance. In Foundational issues in human brain mapping, ed. S.J. Hanson and M. Bunzl. Cambridge: The MIT Press.
Shattuck, D.W., M. Mirza, V. Adisetiyo, C. Hojatkashani, G. Salamon, K.L. Narr, R.A. Poldrack, R.M. Bilder, and A.W. Toga. 2007. Construction of a 3D probabilistic atlas of human cortical structures. NeuroImage 39(3): 1064–1080.
Spanos, A. 1998. Probability theory and statistical inference: econometric modeling with observational data. Cambridge: Cambridge University Press.
Strother, S.C., J. Anderson, L.K. Hansen, U. Kjems, R. Kustra, J. Sidtis, S. Frutiger, S. Muley, S. LaConte, and D. Rottenberg. 2002. The quantitative evaluation of functional neuroimaging experiments: the NPAIRS data analysis framework. NeuroImage 15: 747–771.
Talairach, J., and P. Tournoux. 1988. Co-planar stereotaxic atlas of the human brain. New York: Thieme Medical Publishers.
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Aktunç, M.E. Tackling Duhemian Problems: An Alternative to Skepticism of Neuroimaging in Philosophy of Cognitive Science. Rev.Phil.Psych. 5, 449–464 (2014). https://doi.org/10.1007/s13164-014-0186-3
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DOI: https://doi.org/10.1007/s13164-014-0186-3