Neuroscience has become increasingly reliant on multi-subject research in addition to studies of unusual single patients. This research has brought with it a challenge: how are data from different human brains to be combined? The dominant strategy for aggregating data across brains is what I call the ‘cartographic approach’, which involves mapping data from individuals to a spatial template. Here I characterize the cartographic approach and argue that one of its key steps, registration, should be carried out in a way (...) that is sensitive to the target of investigation. Because registration aims to align homologous brain locations, but not all homologous locations can be simultaneously aligned, a multiplicity of registration methods is required to meet the needs of researchers investigating different phenomena. I call this position ‘registration pluralism’. Registration pluralism has potential implications for neuroscientific practice, three of which I discuss here. This work shows the importance of reflecting more carefully on data aggregation methods, especially in light of the substantial individual differences that exist between brains. (shrink)

The dominant assumption about the causal architecture of the mind is, that it is composed of a stable set of components that contribute independently to relevant observables that are employed to measure cognitive activity. This view has been called component-dominant dynamics. An alternative has been proposed, according to which the different components are not independent, but fundamentally interdependent, and are not stable basic properties of the mind, but rather an emergent feature of the mind given a particular task context. This (...) view has been called interaction-dominant dynamics. In this paper, we review evidence for interaction-dominant dynamics as the causal architecture of the mind. We point out, that such an architecture is consistent with problems of convergence in research on the level of results and theorizing. Moreover, we point out that if interaction-dominant dynamics as the causal architecture of the mind were to be true, this would naturally lead to problems with generalization and replicability in sciences of the mind and brain, and would probably warrant changes in the scientific practice with regard to study-design and data analysis. (shrink)

Driven by an appreciation of the field’s early stage of development, I apply the concept of exploratory experimentation, originally put forward in the late 90s philosophy of biology, to current research in cognitive neuroscience. I concentrate on functional magnetic resonance imaging and how this wide-spread technique is used, from experimental design to data analysis. I claim that, although subject to certain significant modifications with respect to the concept’s original rendering, the exploratory character of neuroimaging experiments can be appreciated considering their (...) goals, centered on the stabilization of experimental systems for phenomenological description, and the relevance of their methodological facet. Although I do not claim that there is a specific kind of experiment that one can single out as definitely exploratory, exploration can be seen as a general trait imbuing fMRI-based experimentation. (shrink)

Brain damage may doubly dissociate cognitive modules, but the practice of revealing dissociations is predicated on modularity being true (T. Shallice, 1988). This article questions the utility of assuming modularity, as it examines a paradigmatic double dissociation of reading modules. Reading modules illustrate two general problems. First, modularity fails to converge on a fixed set of exclusionary criteria that define pure cases. As a consequence, competing modular theories force perennial quests for purer cases, which simply perpetuates growth in the list (...) of exclusionary criteria. The first problem leads, in part, to the second problem. Modularity fails to converge on a fixed set of pure cases. The second failure perpetuates unending fractionation into more modules. (shrink)

Van Orden and Paap argue that subtractive functional neuroimaging is fundamentally flawed, unfalsifiable, and cannot bear upon the nature of mind. In this they are mistaken, although their criticisms interestingly illuminate the scientific problems we confront in investigating the material basis of mind. Here, I consider the criticisms of Van Orden and Paap and discuss where they are mistaken and where justified. I then consider the picture of imaging science that Van Orden and Paap seem to espouse and sketch an (...) alternative picture that is more realistic, more interesting, and consistent with the deliverances and the weaknesses of neuroimaging techniques. Finally, I identify three assumptions that I do think neuroimaging is wedded to and briefly discuss their implications. (shrink)

Brain images are used both as scientific evidence and to illustrate the results of neuroimaging experiments. These images are apt to be viewed as photographs of brain activity, and in so viewing them people are prone to assume that they share the evidential characteristics of photographs. Photographs are epistemically compelling, and have a number of characteristics that underlie what I call their inferential proximity. Here I explore the aptness of the photography analogy, and argue that although neuroimaging does bear important (...) similarities to photography, the details of the generation and analysis of neuroimages significantly complicate the relation of the image to the data. Neuroimages are not inferentially proximate, but their seeming so increases the potential for misinterpretation. This suggests caution in appealing to such images in the public domain. (shrink)

Brain damage may doubly dissociate cognitive modules, but the practice of revealing dissociations is predicated on modularity being true (T. Shallice, 1988). This article questions the utility of assuming modularity, as it examines a paradigmatic double dissociation of reading modules. Reading modules illustrate two general problems. First, modularity fails to converge on a fixed set of exclusionary criteria that define pure cases. As a consequence, competing modular theories force perennial quests for purer cases, which simply perpetuates growth in the list (...) of exclusionary criteria. The first problem leads, in part, to the second problem. Modularity fails to converge on a fixed set of pure cases. The second failure perpetuates unending fractionation into more modules. (shrink)

This article presents and discusses one of the most prominent inferential strategies currently employed in cognitive neuropsychology, namely, reverse inference. Simply put, this is the practice of inferring, in the context of experimental tasks, the engagement of cognitive processes from locations or patterns of neural activation. This technique is notoriously controversial because, critics argue, it presupposes the problematic assumption that neural areas are functionally selective. We proceed as follows. We begin by introducing the basic structure of traditional “location-based” reverse inference (...) and discuss the influential lack of selectivity objection. Next, we rehearse various ways of responding to this challenge and provide some reasons for cautious optimism. The second part of the essay presents a more recent development: “pattern-decoding reverse inference”. This inferential strategy, we maintain, provides an even more convincing response to the lack of selectivity charge. Due to this and other methodological advantages, it is now a prominent component in the toolbox of cognitive neuropsychology. Finally, we conclude by drawing some implications for philosophy of science and philosophy of mind. (shrink)

In this essay, we examine the use of resting state fMRI data for psychological inferences. We argue that resting state studies hold the paired promises of discovering novel functional brain networks, and of avoiding some of the limitations of task-based fMRI. However, we argue that the very features of experimental design that enable resting state fMRI to support exploratory science also generate a novel confound. We argue that seemingly key features of resting state functional connectivity networks may be artefacts resulting (...) from sampling a ‘mixture distribution’ of diverse brain networks active at different times during the scan. We explore the consequences of this ‘mixture view’ for attempts to theorize about the cognitive or psychological functions of resting state networks, as well as the value of exploratory experiments. (shrink)

In contemporary human brain mapping, it is commonly assumed that the “mind is what the brain does”. Based on that assumption, task-based imaging studies of the last three decades measured differences in brain activity that are thought to reflect the exercise of human mental capacities (e.g., perception, attention, memory). With the advancement of resting state studies, tractography and graph theory in the last decade, however, it became possible to study human brain connectivity without relying on cognitive tasks or constructs. It (...) therefore is currently an open question whether the assumption that “the mind is what the brain does” is an indispensable working hypothesis in human brain mapping. This paper argues that the hypothesis is, in fact, dispensable. If it is dropped, researchers can “meet the brain on its own terms” by searching for new, more adequate concepts to describe human brain organization. Neuroscientists can establish such concepts by conducting exploratory experiments that do not test particular cognitive hypotheses. The paper provides a systematic account of exploratory neuroscientific research that would allow researchers to form new concepts and formulate general principles of brain connectivity, and to combine connectivity studies with manipulation methods to identify neural entities in the brain. These research strategies would be most fruitful if applied to the mesoscopic scale of neuronal assemblies, since the organizational principles at this scale are currently largely unknown. This could help researchers to link microscopic and macroscopic evidence to provide a more comprehensive understanding of the human brain. The paper concludes by comparing this account of exploratory neuroscientific experiments to recent proposals for large-scale, discovery-based studies of human brain connectivity. (shrink)

Since the mid‐1980s, psychologists and neuroscientists have used brain imaging to test hypotheses about human thought processes and their neural instantiation. In just three decades, functional neuroimaging has been transformed from a crude clinical tool to a widely used research method for understanding the human brain and mind. Such rapidly achieved success is bound to evoke skepticism. A degree of skepticism toward new methods and ideas is both inevitable and useful in any field. It is especially valuable in a science (...) as young as cognitive neuroscience and its even younger siblings, social and affective neuroscience. Healthy skepticism encourages us to check our assumptions, recognize the limitations of our methods, and proceed thoughtfully. Skepticism itself, however, also must be examined.In this article, I review the most commonly voiced criticisms of functional neuroimaging. In the spirit of healthy skepticism, I will critically examine these criticisms themselves. Each contains at least a kernel of truth, although I will argue that in some cases the kernel has been overextended in ways that are inaccurate or misleading. (shrink)

Neuroscience research examining sex/gender differences aims to explain behavioral differences between men and women in terms of differences in their brains. Historically, this research has used ad hoc methods and has been conducted explicitly in order to show that prevailing gender roles were dictated by biology. I examine contemporary fMRI research on sex/gender differences in emotion processing and argue that it, too, both uses problematic methods and, in doing so, reinforces gender stereotypes.

Much of cognitive science is committed to the modular approach to the study of cognition. The core of this approach consists of a pair of assumptions - the anatomical and the functional modularity assumptions - which motivate two kinds of inference: the anatomical and the functional modularity inferences. The legitimacy of both of these inferences has been strongly challenged, a situation that has had surprisingly little impact on most theorizing in the field. Following the introduction of an important, yet rarely (...) made, distinction between two functional concepts - the distinction between cognitive working and cognitive role - this paper analyses these kinds of inference, and refocuses the attention on new aspects of their main limitations. It is argued that both the anatomical and functional modularity inferences can, and do, operate in three distinct modes in contemporary cognitive science, and that seeing this is essential to understanding both the power and the limitations of these methodological tools. (shrink)