Philipp HAUEIS

Beyond cognitive myopia: a patchwork approach to neural function

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 see only mechanisms with cognitive functions that process behaviorally relevant information when studying neural systems. Cognitive myopia leads to a neglect of 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 neglect noncognitive functions when analyzing research strategies like functional decomposition or approaches to 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 characterize two noncognitive functions at the mesoscale of neural circuits: subsistence functions like breathing are implemented by central pattern generators and are necessary to sustain 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.

Marco NATHAN

The Mind-Body Problem 3.0

It is commonplace to consider the mind-body problem as a longstanding question that has framed discussions of the nature of mental states ever since Descartes molded the debate into its current form. This essay undermines this presupposition by identifying some quantum shifts in the main issue at stake. The questions driving 20th century philosophy of mind are evidently not the same questions troubling Descartes. More controversially, contemporary scientic research has moved away from theoretical discussions that were central to psychology and neuroscience just a few decades ago. It is time to reframe the issue in more contemporary terms.

Charles RATHKOPF

Neural Reuse and the Human Nature

This article explores the question of whether a distinction can be drawn on empirical grounds between those properties of human neural architecture that are due to evolution, and those that are due to cultural acquisition. After a discussion of the theory of neural reuse, it is argued that such a distinction is unlikely to be forthcoming. The developmental relationship between the fusiform face area and the visual world form area is discussed as a central example of the intertwined nature of evolved and acquired neural architectural properties. Finally, a brief argument is given that these results concerning neural architecture carry an interesting implication about the open-ended character of human nature.

Edouard MACHERY

The Amodal Brain and the Offloading Hypothesis

In this article, I argue that a growing body of evidence shows that concepts are amodal and I provide a novel interpretation of the body of evidence that was taken to support neo-empiricist theories of concepts: the offloading hypothesis in the 1990s and 2000s.

Colin KLEIN

From Station to Station: notes towards a quantitative
approach to cognitive ontology

Daniel C. BURNSTON

Getting over Atomism: Functional Decomposition in Complex Neural Systems

Functional decomposition is an important goal in the life sciences, and is central to mechanistic explanation and explanatory reduction.  Many theorists in philosophy of biology and neuroscience, however, think that it is misguided.  “Holists” of this sort posit that biological systems exhibit properties of context-sensitivity, dynamic interaction, and network dependence that are at odds with decomposition.  They then infer from the failure of decomposition to the failure of mechanistic explanation and reduction.  I argue that these properties of complexity are only incompatible with one way of construing decomposition, which I call “atomism,” and not with decomposition writ large.  On atomistic views, parts of a system must have their functions intrinsically, and thus we can never make reference to system variables when describing the function of parts.  I ague, conversely, that all that decomposition requires is that for each phenomenon of interest, we can articulate differential contributions to that phenomenon by the parts involved.  This view admits that the function of each individual part can vary with context, and that interactions with other parts might help determine their context-appropriate functions.  I will give examples based on the notion of oscillatory multiplexing in systems neuroscience.  If I am right that complexity is compatible with decomposition, then holist inferences are faulty – one cannot infer from the presence of complexity to the failure of decomposition, mechanism, and reductionism.   
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Alfredo VERNAZZANI

The structure of sensorimotor explanation

The sensorimotor theory of vision and visual consciousness is often described as a radical alternative to the computational and connectionist orthodoxy in the study of visual perception. However, it is far from clear whether the theory represents a significant departure from orthodox approaches or whether it is an enrichment of it. In this study, I tackle this issue by focusing on the explanatory structure of the sensorimotor theory. I argue that the standard formulation of the theory subscribes to the same theses of the dynamical hypothesis and that it affords covering-law explanations. This however exposes the theory to the mere description worry and generates a puzzle about the role of representations. I then argue that the  sensorimotor theory is compatible with a mechanistic framework, and show how this can overcome the mere description worry and solve the problem of the explanatory role of representations. By doing so, it will be shown that the theory should be understood as an enrichment of the orthodoxy, rather than an alternative.​

Felipe DE BRIGARD

Cognitive systems and the changing brain

The notion of cognitive system is widely used in explanations in cognitive psychology and neuroscience. Traditional approaches define cognitive systems in an agent-relative way, that is, via top-down functional decomposition that assumes a cognitive agent as starting point. The extended cognition movement challenged that approach by questioning the primacy of the notion of cognitive agent. In response, [Adams, F., and K. Aizawa. 2001. The Bounds of Cognition. Oxford, UK: Wiley-Blackwell.] suggested that to have a clear understanding of what a cognitive system is we may need to solve “the demarcation challenge”: the problem of identifying a reliable way to determine which mechanisms that are causally responsible for the production of a certain cognitive process constitute a cognitive system responsible for such process and which ones do not. Recently, [Rupert, R. 2009. Cognitive Systems and the Extended Mind. Oxford: Oxford University Press.] offered a solution based on the idea that the mechanisms that constitute a cognitive system are integrated in a particular sense. In this paper I critically review Rupert’s solution and argue against it. Additionally, I argue that a successful account of cognitive system must accommodate the fact that the neural mechanisms causally responsible for the production of a cognitive process are diachronically dynamic and yet functionally stable. At the end, I offer a suggestion as to how to accommodate this diachronic dynamicity without losing functional stability. I conclude by drawing some implications for the discussion on cognitive ontologies.​

Carl CRAVER

Mutual Manipulability Redux

In a recent article, Baumgartner and Gebharter (2016) claim that the mutual manipulability, as I articulate it, is incompatible with Woodward’s interventionism and, with added rhetorical flourish, that this incompatibility “reduces the mechanistic paradigm to absurdity” (743). This incompatibility turns on the detailed requirements of Woodward’s interventionism as applied to constitutive relations, in which the behavior of the whole supervenes on the details about the parts, their properties, their interactions and their organization. Given this supervenience relationship, one cannot intervene into the behavior of the mechanism, it is claimed, without changing the behavior of at least some of the parts.  As a consequence of this fact, it is impossible to intervene, in Woodward’s technical sense, on the behavior of the mechanism as a whole with respect to the component parts. Baumgartner and Gebharter’s ornate reconstructions make it clear that the original formulation of mutual manipulability, and in particular the diagrams accompanying its initial presentation, were misleading. It is telling in particular that Baumgartner and Gebharter, despite their obvious care in reconstructing my views, fail to reconstruct the view I had in mind. Because their criticisms have now spawned a literature of its own, which literature has also failed to hit on the solution I intended to present, it is perhaps appropriate that I explain why I find Baumgartner and Gebharter’s reconstructions untrue to the original intentions and why the intended view faces none of the objections that they lodge against the account. The result will hopefully be a more satisfactory account of what constitutive relevance is and its relationship to mutual manipulability, levels, interlevel causation, and reduction.  I describe mutual manipulability as a criterion for establishing that a given part X or its properties, activities, or organization φ lies causally between the inputs to and outputs from the behavior of the mechanism as a whole. Analyzing the structure of interlevel experiments along these lines yields the result that mutual manipulability is, in fact, a conjunction of mundane interventionist counterfactuals that test for different aspects of the constitutive relevance relationship as it holds between mechanistic levels of organization in multilevel explanations. 

David K. KAPLAN

Modelling Bayesian Computation in the Brain: Unification, Explanation, and Constraints

Colombo and Hartmann (2017) recently argue that Bayesian modelling in neuroscience can not only unify a diverse range of behavioural phenomena under a common mathematical framework, but can also place useful constraints on both mechanism discovery and confirmation among competing mechanistic models. After reviewing some reasons for decoupling unification and explanation, we raise two challenges for their view. First, although they attempt to distance themselves from the view that Bayesian models provide mechanistic explanations, to the extent that a given model successfully constrains the search space for possible mechanisms, it will convey at least some mechanistic information and therefore automatically qualify as a partial or incomplete mechanistic explanation. Second, according to their view, one widely used strategy to guide and constrain mechanism discovery involves assuming a mapping between features of a behaviorally confirmed Bayesian model and features of the neural mechanisms underlying the behavior. Using their own example of multisensory integration, we discuss how competing mechanistic models can be consistent with all available behavioral data and yet be inconsistent with each other. This tension reveals that there are too many degrees of freedom in the mapping relationship between models of behavioral phenomena and neural mechanisms, and points to the role that other background assumptions play including  about the appropriate level at which the neural model should be specified (e.g., individual neuron or population level) and localization-assumptions about where in the system the underlying mechanism might occur. These considerations highlight the need for a more refined account of modelling constraints in neuroscience.
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Mazvita CHIRIMUUTA

Charting the Heraclitean Brain: 
Perspectivism and Simplification in Models of the Motor Cortex

The mainstream theory of the motor cortex is a computational and representational one, but it has been called into question because of an unresolved dispute over whether neurons in this region represent patterns of muscle activation or other movement parameters such as limb velocity. Some neuroscientists have recently argued that the representational theory should be replaced with a dynamical systems one. Here I argue that both of these scientific perspectives are responses to the challenge of constructing relatively simple models of the brain, a system which is extremely complex in the ‘Heraclitean’ sense that its structure and functions are continually changing with experience, and never precisely re-occur. Because each of these perspectives employs different assumptions in order to make the task of modelling the brain tractable, they result in different, and apparently inconsistent ‘pictures’ of what the brain/mind is like—either an information processor analogous to a computer, or a non-representational dynamical system. I discuss proposals to reconcile these perspectives, and consider whether any non-perspectival insights about the nature of the brain/mind can be derived from these models.
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Lena KÄSTNER

On the Mechanistic Triad:
How Do Producing, Underlying and Maintaining Mechanisms Connect?

Recent discussions about different kinds, types, or readings of mechanisms tend to run metaphysical questions together with questions about discovery and explanation. The current paper sets out to disentangle these issues and to show how explanations describing mechanisms that produce, underlie, and maintain their phenomena can be fruitfully integrated. I argue that scientists emphasize different aspects of mechanisms depending on their purposes. The different research questions they ask depending on what kind of phenomenon they seek to explain guide mechanism discovery. The development of mechanistic explanations is thus shaped by the explanandum: there exists an important conceptual tie between the kind of phenomenon scientists seek to explain and which kinds of metaphysical relations they emphasize in their explanations: to explain how an end product or result is generated, scientists will usually search for mechanism that produced it; to explain a process, they will typically search for the mechanism underlying it; and to explain how a system’s stable state or continuous behavior is maintained, they search for the mechanism maintaining it. In this paper, I show how recognizing these different projects and understanding their connections fuels explanatory integration.

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