Will brain imaging technology soon enable neuroscientists to read minds? We cannot answer this question without some understanding of the state of the art in neuroimaging. But neither can we answer this question without some understanding of the concept invoked by the term "mind reading." This article is an attempt to develop such understanding. Our analysis proceeds in two stages. In the first stage, we provide a categorical explication of mind reading. The categorical explication articulates empirical conditions that must be (...) satisfied if mind reading is to be achieved. In the second stage, we develop a metric for judging the proficiency of mind reading experiments. The conception of mind reading that emerges helps to reconcile folk psychological judgments about what mind reading must involve with the constraints imposed by empirical strategies for achieving it. (shrink)

Functional decomposition is an important goal in the life sciences, and is central to mechanistic explanation and explanatory reduction. A growing literature in philosophy of science, however, has challenged decomposition-based notions of explanation. ‘Holists’ posit that complex systems exhibit context-sensitivity, dynamic interaction, and network dependence, and that these properties undermine decomposition. They then infer from the failure of decomposition to the failure of mechanistic explanation and reduction. I argue that complexity, so construed, is only incompatible with one notion of decomposition, (...) which I call ‘atomism’, and not with decomposition writ large. Atomism posits that function ascriptions must be made to parts with minimal reference to the surrounding system. Complexity does indeed falsify atomism, but I contend that there is a weaker, ‘contextualist’ notion of decomposition that is fully compatible with the properties that holists cite. Contextualism suggests that the function of parts can shift with external context, and that interactions with other parts might help determine their context-appropriate functions. This still admits of functional decomposition within a given context. I will give examples based on the notion of oscillatory multiplexing in systems neuroscience. If contextualism is feasible, then holist inferences are faulty—one cannot infer from the presence of complexity to the failure of decomposition, mechanism, and reductionism. (shrink)

I will begin by proposing a taxonomy of taxonomic positions regarding the mind–brain: localism, globalism, revisionism, and contextualism, and will go on to focus on the last position. Although some versions of contextualism have been defended by various researchers, they largely limit themselves to a version of neural contextualism: different brain regions perform different functions in different neural contexts. I will defend what I call “environmental-etiological contextualism,” according to which the psychological functions carried out by various neural regions can only (...) be identified and individuated against an environmental context or with reference to a causal history. While this idea may seem innocuous enough, it has important implications for a structure-to-function mapping in the mind and brain sciences. It entails that the same neural structures can subserve different psychological functions in different contexts, leading to crosscutting psycho-neural mappings. I will try to illustrate how this can occur with reference to recent research on episodic memory. (shrink)

Cognitive ontology has become a popular topic in philosophy, cognitive psychology, and cognitive neuroscience. At its center is the question of which cognitive capacities should be included in the ontology of cognitive psychology and cognitive neuroscience. One common strategy for answering this question is to look at brain structures and determine the cognitive capacities for which they are responsible. Some authors interpret this strategy as a search for neural mechanisms, as understood by the so-called new mechanistic approach. In this article, (...) I will show that this new mechanistic answer is confronted with what I call the triviality problem. A discussion of this problem will show that one cannot derive a meaningful cognitive ontology from neural mechanisms alone. Nonetheless, neural mechanisms play a crucial role in the discovery of a cognitive ontology because they are epistemic proxies for best systematizations. (shrink)

Experiments in cognitive neuroscience build a setup whose set of controlled stimuli and rules elicits a cognitive process in a participant. This setup requires researchers to decide the value of quite a few parameters along several dimensions. We call ‘’contextual factors’’ the parameters often assumed not to change the cognitive process elicited and are free to vary across the experiment’s repetitions. Against this assumption, empirical evidence shows that many of these contextual factors can significantly influence cognitive performance. Nevertheless, it is (...) not entirely clear what it means for a cognitive phenomenon to be context-sensitive and how to identify context-sensitivity experimentally. We claim that a phenomenon can be context-sensitive either because it is only triggered within a specific context or because different contexts change its manifestation conditions. Assessing which of these forms of context-sensitivity is present in a given phenomenon requires a criterion for individuating it across contextual variations. We argue that some inter-level experiments that, within the mechanistic approach to explanation, are required to identify relations of constitutive relevance between a phenomenon and a mechanism, are also necessary for individuating the phenomenon across its contextual variations. We articulate a criterion according to which behavioral variations across contexts indicate different phenomena if and only if the mechanistic activities, components and/or organizational properties recruited in each context are different. We support this approach by showing how it is applied in paradigmatic studies addressing cognitive performance differences resulting from contextual variations of task features, such as stimulus type and response modality. Finally, we address the challenge that a form of context-sensitivity possessed by the so-called ‘multifunctional mechanisms’ is incompatible with our proposal because it entails that the same mechanism can be recruited in different contexts to produce different phenomena. We examine key cases of multifunctionality and argue that they are consistent with our proposal because a single mechanism can have different components, activities and/or organizational properties in different contexts. Thus, these modifications may not affect the identity of a mechanism, and they could explain how it produced different phenomena in those contexts. (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)

Theories in cognitive science, and especially cognitive neuroscience, often claim that parts of cognitive systems are reused for different cognitive functions. Philosophical analysis of this concept, however, is rare. Here, I first provide a set of criteria for an analysis of reuse, and then I analyse reuse in terms of the functions of subsystems. I also discuss how cognitive systems execute cognitive functions, the relation between learning and reuse, and how to differentiate reuse from related concepts like multi-use, redundancy, and (...) duplication of parts. Finally, I illustrate how my account captures the reuse of dynamical subsystems as unveiled by recent research in cognitive neurobiology. This recent research suggests two different evolutionary justifications for reuse claims. _1_ Introduction _2_ Criteria for Analyses of Reuse _3_ Use and Reuse _4_ The Reuse of Dynamical Systems in Cognitive Systems _5_ Conclusion. (shrink)

In this paper, I argue that looking at the concept of neural function through the lens of cognition alone risks cognitive myopia: it leads neuroscientists to focus only on mechanisms with cognitive functions that process behaviorally relevant information when conceptualizing “neural function”. Cognitive myopia tempts researchers to neglect neural mechanisms with noncognitive functions which do not process behaviorally relevant information but maintain and repair neural and other systems of the body. Cognitive myopia similarly affects philosophy of neuroscience because scholars overlook (...) noncognitive functions when analyzing issues surrounding e.g., functional decomposition or the multifunctionality of neural structures. I argue that we can overcome cognitive myopia by adopting a patchwork approach that articulates cognitive and noncognitive “patches” of the concept of neural function. Cognitive patches describe mechanisms with causally specific effects on cognition and behavior which are likely operative in transforming sensory or other inputs into motor outputs. Noncognitive patches describe mechanisms that lack such specific effects; these mechanisms are enabling conditions for cognitive functions to occur. I use these distinctions to characterize two noncognitive functions at the mesoscale of neural circuits: subsistence functions like breathing are implemented by central pattern generators and are necessary to maintain the life of the organism. Infrastructural functions like gain control are implemented by canonical microcircuits and prevent neural system damage while cognitive processing occurs. By adding conceptual patches that describe these functions, a patchwork approach can overcome cognitive myopia and help us explain how the brain’s capacities as an information processing device are constrained by its ability to maintain and repair itself as a physiological apparatus. (shrink)

Since cognitive neuroscience aims at giving an integrated account of mind and brain, its ontology should include both neural and cognitive entities and specify their relations. According to what we call the standard ontological framework of cognitive neuroscience, the aim of cognitive neuroscience should be to establish one-to-one mappings between neural and cognitive entities. Where such entities do not yet closely align, this can be achieved by reforming the cognitive ontology, the neural ontology, or both. In order to assess the (...) limits and the possibilities of the SOFCN, we will examine a paradigmatic case study: the concept of Broca’s area, which indicates an alleged mapping between the left inferofrontal gyrus and the production of language. We review evidence showing that such a mapping does not hold, thus calling into question either the status of Broca’s area or the validity of the SOFCN. We then propose some strategies for addressing the issue and suggest that it may be solved within the SOFCN by adopting both of the following strategies: first, more accurately defining the relevant neural structures and second, switching the focus of neural ontology from structures to events, individuated by a where conjoint with a how. (shrink)

Functional localization has historically been one of the primary goals of neuroscience. There is still debate, however, about whether it is possible, and if so what kind of theories succeed at localization. I argue for a contextualist approach to localization. Most theorists assume that widespread contextual variability in function is fundamentally incompatible with functional decomposition in the brain, because contextualist accounts will fail to be generalizable and projectable. I argue that this assumption is misplaced. A properly articulated contextualism can ground (...) successful theories of localization even without positing completely generalizable accounts. Via a case study from perceptual neuroscience, I suggest that there is strong evidence for contextual variation in the function of perceptual brain areas. I then outline a version of contextualism that is empirically adequate with respect to this data, and claim that it can still distinguish brain areas from each other according to their functional properties. Finally, I claim that the view does not fail the norms for good theory in the way that anticontextualists suppose. It is true that, on a contextualist view, we will not have theories that are completely generalizable and predictive. We can, however, have successful partial generalizations that structure ongoing investigation and lead to novel functional insight, and this success is sufficient to ground the project of functional localization. (shrink)

Will brain imaging technology soon enable neuroscientists to read minds? We cannot answer this question without some understanding of the state of the art in neuroimaging. But neither can we answer this question without some understanding of the concept invoked by the term “mind reading.” This article is an attempt to develop such understanding. Our analysis proceeds in two stages. In the first stage, we provide a categorical explication of mind reading. The categorical explication articulates empirical conditions that must be (...) satisfied if mind reading is to be achieved. In the second stage, we develop a metric for judging the proficiency of mind reading experiments. The conception of mind reading that emerges helps to reconcile folk psychological judgments about what mind reading must involve with the constraints imposed by empirical strategies for achieving it. (shrink)

Burt formulates her critique at a general level of abstraction that highlights the methodological deficiencies of sociogenomics without also calling attention to precisely the same deficiencies in the social science model she seeks to defend against its encroachments. What might have been a methodological bulwark against the excesses of sociogenomics is instead a one-sided critique that merely renews its charter.

Functional localization is a central aim of cognitive neuroscience. But the nature and extent of functional localization in the human brain have been subjects of fierce theoretical debate since the 19th Century. In this essay, I first examine how concepts of functional localization have changed over time. I then analyze contemporary challenges to functional localization drawing from research on neural reuse, neural degeneracy, and the context-dependence of neural functions. I explore the consequences of these challenges for topics in philosophy of (...) science and philosophy of mind including localizationist versus anti-localizationist approaches to cognitive neuroscience, multiple realizability, reverse inference in functional neuroimaging, and the modularity of mind. (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)

The neural reuse framework developed primarily by Michael Anderson proposes that brain regions are involved in multiple and diverse cognitive tasks and that brain regions flexibly and dynamically interact in different combinations to carry out cognitive functioning. We argue that the evidence cited by Anderson and others falls short of supporting the fundamental principles of neural reuse. We map out this problem and provide solutions by drawing on recent advances in network neuroscience, and we argue that methods employed in network (...) neuroscience provide the means to fully engage in a research program operating under the principles of neural reuse. (shrink)

Theories in cognitive science, and especially cognitive neuroscience, often claim that parts of cognitive systems are reused for different cognitive functions. Philosophical analysis of this concept, however, is rare. Here, I first provide a set of criteria for an analysis of reuse, and then I analyse reuse in terms of the functions of subsystems. I also discuss how cognitive systems execute cognitive functions, the relation between learning and reuse, and how to differentiate reuse from related concepts like multi-use, redundancy, and (...) duplication of parts. Finally, I illustrate how my account captures the reuse of dynamical subsystems as unveiled by recent research in cognitive neurobiology. This recent research suggests two different evolutionary justifications for reuse claims. (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)