Colin Klein

Since its introduction, multivariate pattern analysis, or ‘neural decoding’, has transformed the field of cognitive neuroscience. Underlying its influence is a crucial inference, which we call the decoder’s dictum: if information can be decoded from patterns of neural activity, then this provides strong evidence about what information those patterns represent. Although the dictum is a widely held and well-motivated principle in decoding research, it has received scant philosophical attention. We critically evaluate the dictum, arguing that it is false: decodability is a poor guide for revealing the content of neural representations. However, we also suggest how the dictum can be improved on, in order to better justify inferences about neural representation using MVPA. 1Introduction 2A Brief Primer on Neural Decoding: Methods, Application, and Interpretation 2.1What is multivariate pattern analysis? 2.2The informational benefits of multivariate pattern analysis 3Why the Decoder’s Dictum Is False 3.1We don’t know what information is decoded 3.2The theoretical basis for the dictum 3.3Undermining the theoretical basis 4Objections and Replies 4.1Does anyone really believe the dictum? 4.2Good decoding is not enough 4.3Predicting behaviour is not enough 5Moving beyond the Dictum 6Conclusion

Maura Tumulty has raised two objections to my imperative account of pain.1 First, she argues that there is a disanalogy between pains and other imperative sensations like itch, hunger, and thirst. Suppose (with Hall) one thinks that an itch says “Scratch here!”2 Scratch the itch, and it dutifully disappears. Not so with pain. The pain of a broken ankle has the content ‘Do not put weight on that ankle!’ Yet the coddled ankle still throbs: obeying the imperative does not extinguish it. Second, Tumulty argues that the imperative account cannot handle certain pains, particularly pains of the deep viscera. On my account, pains proscribe against taking action with the painful body part. Yet some pains are associated with body parts over which we have no control. Kidney stones cause intense pain, but I cannot (voluntarily) control my kidney. What action, then, could that pain possibly proscribe? Lacking such a story, it is hard to say (as I do) that pains are exhausted by their imperative content.

At present, the science of consciousness is structured around the search for the neural correlates of consciousness. One of the alleged advantages of the NCCs framework is its metaphysical neutrality—the fact that it begs no contested questions with respect to debates about the fundamental nature of consciousness. Here, we argue that even if the NCC framework is metaphysically neutral, it is structurally committed, for it presupposes a certain model—what we call the Lite-Brite model—of consciousness. This, we argue, represents a serious liability for the NCC framework for the plausibility of the Lite-Brite model is very much an open question, and the science of consciousness would be better served by a framework that does not presuppose it. Drawing on interventionist ideas in the philosophy of science, we suggest that the Difference-Maker framework can provide just such an alternative. Instead of searching for the neural correlates of consciousness, we ought to be searching for the difference makers of consciousness. We detail how a shift to searching DMCs will change both the practice of consciousness science and the interpretation of existing results.

In a target article that appeared in this journal, Thomas Stoffregen 2000 questions the possibility of ecological event perception research. This paper describes an experiments performed to examine the perception of the disappearance of gap-crossing affordances, a variety of event as defined by Chemero 2000. We found that subjects reliably perceive both gap-crossing affordances and the disappearance of gap-crossing affordances. Our findings provide empirical evidence in favor of understanding events as changes in the layout of affordances, shoring up event perception research in ecological psychology.

Amputation of a limb can result in the persistent hallucination that the limb is still present [Ramachandran and Hirstein, 1998]. Distressingly, these socalled ‘phantom limbs’ are often quite painful. Of a friend whose arm had been amputated due to gas gangrene, W.K. Livingston writes: I once asked him why the sense of tenseness in the hand was so frequently emphasized among his complaints. He asked me to clench my fingers over my thumb, flex my wrist, and raise the arm into a hammerlock position and hold it there. He kept me in this position as long as I could stand it. At the end of five minutes I was perspiring freely, my hand and arm felt unbearably cramped, and I quit. But you can take your hand down, he said. (quoted in [Melzack, 1973] 53) In addition to the obvious medical issues, phantom limb pain also presents philosophical problems. Here’s a thorny one: are phantom limb pains hallucinations of pain?

Neuroimaging studies of the resting state continue to gather philosophical and scientific attention. Most discussions assume an identification between resting-state activity and activity in the so-called default mode network. I argue we should resist this identification, structuring my discussion around a dilemma first posed by Morcom and Fletcher. I offer an alternative view of rest as a state dominated by long-term processes and show how interaction effects might thereby let rest shed light on short-term changes in activation

Contrastive neuroimaging is often taken to provide evidence about the localization of cognitive functions. After canvassing some problems with this approach, I offer an alternative: neuroimaging gives evidence about regions of the brain that bear difference-making relationships to psychological processes of interest. I distinguish between the specificity and what I call the systematicity of a difference-making relationship, and I show how at least some neuroimaging experiments can give evidence for systematic difference-making.

Conspiracy theories play a troubling role in political discourse. Online forums provide a valuable window into everyday conspiracy theorizing, and can give a clue to the motivations and interests of those who post in such forums. Yet this online activity can be difficult to quantify and study. We describe a unique approach to studying online conspiracy theorists which used non-negative matrix factorization to create a topic model of authors' contributions to the main conspiracy forum on Reddit. This subreddit provides a large corpus of comments which spans many years and numerous authors. We show that within the forum, there are multiple sub-populations distinguishable by their loadings on different topics in the model. Further, we argue, these differences are interpretable as differences in background beliefs and motivations. The diversity of the distinct subgroups places constraints on theories of what generates conspiracy theorizing. We argue that traditional “monological” believers are only the tip of an iceberg of commenters. Neither simple irrationality nor common preoccupations can account for the observed diversity. Instead, we suggest, those who endorse conspiracies seem to be primarily brought together by epistemological concerns, and that these central concerns link an otherwise heterogenous group of individuals.

YouTube has been implicated in the transformation of users into extremists and conspiracy theorists. The alleged mechanism for this radicalizing process is YouTube’s recommender system, which is optimized to amplify and promote clips that users are likely to watch through to the end. YouTube optimizes for watch-through for economic reasons: people who watch a video through to the end are likely to then watch the next recommended video as well, which means that more advertisements can be served to them. This is a seemingly innocuous design choice, but it has a troubling side-effect. Critics of YouTube have alleged that the recommender system tends to recommend extremist content and conspiracy theories, as such videos are especially likely to capture and keep users’ attention. To date, the problem of radicalization via the YouTube recommender system has been a matter of speculation. The current study represents the first systematic, pre-registered attempt to establish whether and to what extent the recommender system tends to promote such content. We begin by contextualizing our study in the framework of technological seduction. Next, we explain our methodology. After that, we present our results, which are consistent with the radicalization hypothesis. Finally, we discuss our findings, as well as directions for future research and recommendations for users, industry, and policy-makers.

Distinguishing mechanistic components from mere causally relevant background conditions remains a difficulty for mechanistic accounts of explanation. By distinguishing resources from mechanical parts, I argue that we can more effectively draw this boundary. Further, the distinction makes obvious that there are distinctive resource explanations which are not captured by a traditional part-based mechanistic account. While this suggests a straightforward extension of the mechanistic model, I argue that incorporating resources and resource explanations requires moving beyond the purely local account of levels that some mechanists advocate.

Epidemiological models directly shape policy responses to public health crises. We argue that they also play a less obvious but important role in solving certain coordination problems and social dilemmas that arise during pandemics. This role is both ethically and epistemically valuable. However, it also gives rise to an underappreciated dilemma, as the features that make models good at solving coordination problems are often at odds with the features that make for a good scientific model. We examine and develop this dilemma in the context of the COVID-19 pandemic, and suggest extensions to other domains.

Against Maudlin, I argue that machines which merely reproduce a pre-programmed series of changes ought to be classed with Turing’s O-Machines even if they would counterfactually show Turing Machine-like activity. This can be seen on an interventionist picture of computational architectures, on which basic operations are the primitive loci for interventions. While constructions like Maudlin’s Olympia still compute, then, claims about them do not threaten philosophical arguments that depend on Turing Machine architectures and their computational equivalents

It would be nice if our definition of ‘physical’ incorporated the distinctive content of physics. Attempts at such a definition quickly run into what’s known as Hempel’s dilemma. Briefly: when we talk about ‘physics’, we refer either to current physics or to some idealized version of physics. Current physics is likely wrong and so an unsuitable basis for a definition. ‘Ideal physics’ can’t itself be cashed out except as the science which has completed an accurate survey of the physical; appeals to it to define the physical must therefore end up trivial or circular. So defining the physical in terms of physics looks like a non-starter.

Pains are subject to obvious, well-documented, and striking top-down influences. This is in stark contrast to visual perception, where the debate over cognitive penetrability tends to revolve around fairly subtle experimental effects. Several authors have recently taken up the question of whether top-down effects on pain count as cognitive penetrability, and what that might show us about traditional debates. I review some of the known mechanisms for top-down modulation of pain, and suggest that it reveals an issue with a relatively neglected part of the cognitive penetrability literature. Much of the debate inherits Pylyshyn’s stark contrast between transducers and cognition proper. His distinction grew out of his running fight with Gibson, and is far too strong to be defensible. I suggest that we might therefore view top-down influences on pain as a species of transducer calibration. This provides a novel but principled way to distinguish between several varieties of top-down effect according to their architectural features.

One challenge in explaining neural evolution is the formal equivalence of different computational architectures. If a simple architecture suffices, why should more complex neural architectures evolve? The answer must involve the intense competition for resources under which brains operate. I show how recurrent neural networks can be favored when increased complexity allows for more efficient use of existing resources. Although resource constraints alone can drive a change, recurrence shifts the landscape of what is later evolvable. Hence organisms on either side of a transition boundary may have similar cognitive capacities but very different potential for evolving new capacities.