Images come in many varieties, but for evidential purposes, photographs are privileged. Recent advances in neuroimaging provide us with a new type of image that is used as scientific evidence. Brain images are epistemically compelling, in part because they are liable to be viewed as akin to photographs of brain activity. Here I consider features of photography that underlie the evidential status we accord it, and argue that neuroimaging diverges from photography in ways that seriously undermine the photographic analogy. While (...) neuroimaging remains an important source of scientific evidence, proper interpretation of brain images is much more complex than it appears. ‡This work was supported in part by a grant from the Leslie Humanities Center at Dartmouth College. I thank John Kulvicki for helpful comments, and Kim Sterelny, for making it possible for me to spend some time at the ANU with a grant from the Australian Research Council. †To contact the author, please write to: Dartmouth College, Department of Philosophy, Hanover, NH 03755; e-mail: [email protected]. (shrink)

Because physical theories typically predict numerical values, an improvement in experimental precision reduces the tolerance range and hence increases corroborability. In most psychological research, improved power of a statistical design leads to a prior probability approaching 1/2 of finding a significant difference in the theoretically predicted direction. Hence the corroboration yielded by "success" is very weak, and becomes weaker with increased precision. "Statistical significance" plays a logical role in psychology precisely the reverse of its role in physics. This problem is (...) worsened by certain unhealthy tendencies prevalent among psychologists, such as a premium placed on experimental "cuteness" and a free reliance upon ad hoc explanations to avoid refutation. (shrink)

Good research requires, among other virtues,(i) methods that yield stable experimentalobservations without arbitrary (post hoc)assumptions, (ii) logical interpretations ofthe sources of observations, and (iii) soundinferences to general causal mechanismsexplaining experimental results by placing themin larger explanatory contexts. In TheNew Phrenology , William Uttal examines theresearch tradition of localization, and findsit deficient in all three virtues, whetherbased on lesion studies or on new technologiesfor functional brain imaging. In this paper Iconsider just the arguments concerning brainimaging, especially functional MagneticResonance Imaging. I think (...) that Uttal is tooharsh in his methodological critique, butcorrect in his assessment of the conceptuallimitations of localist evidence. I proposeinstead a data-driven test for assessingrelative modularity in brain images, and showits use in a secondary analysis of fMRI datafrom the National fMRI Data Center(www.fmridc.org). Although the analysis is alimited pilot study, it offers additionalempirical challenge to localism. (shrink)

We take up two issues discussed by Chow: the claim by critics of hypothesis testing that the null hypothesis (H0) is always false, and the claim that reporting effect sizes is more appropriate than relying on statistical significance. Concerning the former, we agree with Chow's sentiment despite noting serious shortcomings in his discussion. Concerning the latter, we agree with Chow that effect size need not translate into scientific relevance, and furthermore reiterate that with small samples effect size measures cannot substitute (...) for significance. (shrink)

William Uttal's The new phrenology is a broad attack on localization in cognitive neuroscience. He argues that even though the brain is a highly differentiated organ, "high level cognitive functions" should not be localized in specific brain regions. First, he argues that psychological processes are not well-defined. Second, he criticizes the methods used to localize psychological processes, including imaging technology: he argues that variation among individuals compromises localization, and that the statistical methods used to construct activation maps are flawed. Neither (...) criticism is compelling. First, as we illustrate, there are behavioral measures which offer at least weak constraints on psychological attribution. Second, though imaging does face methodological difficulties associated with variation among individuals, these are broadly acknowledged; moreover, his specific criticisms of the imaging work, and in particular of fMRI, misrepresent the methodology. In concluding, we suggest a way of framing the issues that might allow us to resolve differences between localizationist models and more distributed models empirically. (shrink)

Statistical significance testing has its problems, but so do the alternatives that are proposed; and the alternatives may be both more cumbersome and less informative. Significance tests remain legitimate aspects of the rhetoric of scientific persuasion.

There is a bias in neuroscience toward localizing and modularizing brain functions. Single cell recording, imaging studies, and the study of neurological deficits all feed into the Gallian view that different brain areas do different things and the things being done are confined to particular processing streams. At the same time, there is a growing sentiment that brains probably don’t work like that after all; it is better to conceive of them as fundamentally distributed units, multi‐tasking at every level. This (...) sentiment, however, is much less congenial to the tried‐and‐true experimental protocols available today and to theorizing about the brain in general. This essay examines the tension between current experimental methods and large-scale views of the brain. We argue that this disconnection between experiment and what really are guiding theoretical metaphors seriously impedes progress in neuroscience. (shrink)

There is a bias in neuroscience toward localizing and modularizing brain functions. Single cell recording, imaging studies, and the study of neurological deficits all feed into the Gallian view that different brain areas do different things and the things being done are confined to particular processing streams. At the same time, there is a growing sentiment that brains probably don’t work like that after all; it is better to conceive of them as fundamentally distributed units, multi‐tasking at every level. This (...) sentiment, however, is much less congenial to the tried‐and‐true experimental protocols available today and to theorizing about the brain in general. This essay examines the tension between current experimental methods and large-scale views of the brain. We argue that this disconnection between experiment and what really are guiding theoretical metaphors seriously impedes progress in neuroscience. (shrink)

fMRI is a tool to study brain function noninvasively that can reliably identify sites of neural involvement for a given task. However, to what extent can fMRI signals be related to measures obtained in electrophysiology? Can the blood-oxygen-level-dependent signal be interpreted as spatially pooled spiking activity? Here we combine knowledge from neurovascular coupling, functional imaging and neurophysiology to discuss whether fMRI has succeeded in demonstrating one of the most established functional properties in the visual brain, namely directional selectivity in the (...) motion-processing region V5/ MT+. We also discuss differences of fMRI and electrophysiology in their sensitivity to distinct physiological processes. We conclude that fMRI constitutes a complement, not a poor-resolution substitute, to invasive techniques, and that it deserves interpretations that acknowledge its stand as a separate signal. (shrink)