In the 1980s and 1990s, there was a major theoretical debate in the memory domain regarding the multiple memory systems and processing modes frameworks. The components of processing framework argued for a middle ground: Instead of neatly divided memory systems or processing modes, this framework proposed the existence of numerous processing components that are recruited in different combinations by memory tasks and yield complex patterns of associations and dissociations. Because behavioral evidence was not sufficient to decide among these three frameworks, (...) the debate was largely abandoned. However, functional neuroimaging evidence accumulated during the last two decades resolves the stalemate, because this evidence is more consistent with the components framework than with the other two frameworks. For example, functional neuroimaging evidence shows that brain regions attributed to one memory system can contribute to tasks associated with other memory systems and that brain regions attributed to the same processing mode (perceptual or conceptual) can be dissociated from each other. Functional neuroimaging evidence suggests that memory processes are supported by transient interactions between a few regions called process-specific alliances. These conceptual developments are an example of how functional neuroimaging can contribute to theoretical debates in cognitive psychology. (shrink)

We outline a framework of multilevel neurocognitive mechanisms that incorporates representation and computation. We argue that paradigmatic explanations in cognitive neuroscience fit this framework and thus that cognitive neuroscience constitutes a revolutionary break from traditional cognitive science. Whereas traditional cognitive scientific explanations were supposed to be distinct and autonomous from mechanistic explanations, neurocognitive explanations aim to be mechanistic through and through. Neurocognitive explanations aim to integrate computational and representational functions and structures across multiple levels of organization in order to explain (...) cognition. To a large extent, practicing cognitive neuroscientists have already accepted this shift, but philosophical theory has not fully acknowledged and appreciated its significance. As a result, the explanatory framework underlying cognitive neuroscience has remained largely implicit. We explicate this framework and demonstrate its contrast with previous approaches. (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.

Several developments for diverse scientific goals, mostly in physics and physiology, had to take place, which eventually gave us fMRI as one of the central research paradigms of contemporary cognitive neuroscience. This technique stands on solid foundations established by the physics of magnetic resonance and the physiology of hemodynamics and is complimented by computational and statistical techniques. I argue, and support using concrete examples, that these foundations give rise to a productive theory-ladenness in fMRI, which enables researchers to identify and (...) control for the types of methodological and inferential errors. Consequently, this makes it possible for researchers to represent and investigate cognitive phenomena in terms of hemodynamic data and for experimental knowledge to grow independently of large scale theories of cognition. (shrink)

Most animals have mental states of one sort or another, but few species share our capacity for self-awareness. We are aware of our own mental states via introspection, and we are aware of the mental states of our fellow human beings on the basis of what they do and say. This chapter is not concerned with these traditional forms of mind-reading—forms whose origins predate the beginnings of recorded history—but with the prospects of a rather different and significantly more recent form (...) of ‘mind-reading’: the capacity to reliably ascribe mental states to a creature on the basis of information derived from information about their brain states. (shrink)

Functional neuroimaging is sometimes criticized as showing only where in the brain things happen, not how they happen, and thus being unable to inform us about questions of mental and neural representation. Novel analytical methods increasingly make clear that imaging can give us access to constructs of interest to psychology. In this paper I argue that neuroimaging can give us an important, if limited, window into the large-scale structure of neural representation. I describe Representational Similarity Analysis, increasingly used in neuroimaging (...) studies, and lay out desiderata for representations in general. In that context I discuss what RSA can and cannot tell us about neural representation. I compare RSA with fMRI to a different experimental paradigm which has been embraced as being indicative of representation in psychology, and argue that it compares favorably. (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)

Brain-imaging technologies have posed the problem of breaching our brain privacy. Until the invention of those technologies, many of us entertained the idea that nothing can threaten our mental privacy, as long as we kept it, for each of us has private access to his or her own mind but no access to any other. Yet, philosophically, the issue of private, mental accessibility appears to be quite unsettled, as there are still many philosophers who reject the idea of private, mental (...) accessibility. I have attempted to refute such rejections and to establish this idea on firmer grounds. My arguments in this paper show that brain imaging allows no access to our mind and that mind privacy is quite different from brain privacy, as the latter can be breached by brain imaging, whereas the former cannot. A reduction of the mind to the body inescapably fails, as there is a categorial difference between mind and body or brain, which is compatible with their inseparability. Brain imaging cannot enable one to “read” the mind or to breach our mental privacy. There is no external access to one’s mind. Each of us has exclusive access to his or her own mind. (shrink)

In recent years, neuroscience has begun to transform itself into a “big data” enterprise with the importation of computational and statistical techniques from machine learning and informatics. In addition to their translational applications such as brain-computer interfaces and early diagnosis of neuropathology, these tools promise to advance new solutions to longstanding theoretical quandaries. Here I critically assess whether these promises will pay off, focusing on the application of multivariate pattern analysis (MVPA) to the problem of reverse inference. I argue that (...) MVPA does not inherently provide a new answer to classical worries about reverse inference, and that the method faces pervasive interpretive problems of its own. Further, the epistemic setting of MVPA and other decoding methods contributes to a potentially worrisome shift towards prediction and away from explanation in fundamental neuroscience. (shrink)

Several developments for diverse scientific goals, mostly in physics and physiology, had to take place, which eventually gave us fMRI as one of the central research paradigms of contemporary cognitive neuroscience. This technique stands on solid foundations established by the physics of magnetic resonance and the physiology of hemodynamics and is complimented by computational and statistical techniques. I argue, and support using concrete examples, that these foundations give rise to a productive theory-ladenness in fMRI, which enables researchers to identify and (...) control for the types of methodological and inferential errors. Consequently, this makes it possible for researchers to represent and investigate cognitive phenomena in terms of hemodynamic data and for experimental knowledge to grow independently of large scale theories of cognition. (shrink)