Multivariate pattern analysis, or MVPA, has become one of the most popular analytic methods in cognitive neuroscience. Since its inception, MVPA has been heralded as offering much more than regular univariate analyses, for—we are told—it not only can tell us which brain regions are engaged while processing particular stimuli, but also which patterns of neural activity represent the categories the stimuli are selected from. We disagree, and in the current paper we offer four conceptual challenges to the use of MVPA (...) to make claims about neural representation. Our view is that the use of MVPA to make claims about neural representation is problematic. (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)

Stawarczyk, Bezdek, and Zacks offer neuroscience evidence for a midline default network core, which appears to coordinate internal, top‐down mentation with externally‐triggered, bottom‐up attention in a push‐pull relationship. The network may enable the flexible pursuance of thoughts tuned into or detached from the current environment.

Some skeptics question the very possibility of moral bioenhancement by arguing that if we lack a widely acceptable notion of morality, we will not be able to accept the use of a biotechnological technique as a tool for moral bioenhancement. I will examine this skepticism and argue that the assessment of moral bioenhancement does not require such a notion of morality. In particular, I will demonstrate that this skepticism can be neutralized in the case of recent neurofeedback techniques. This goal (...) will be accomplished in four steps. First, I will draw an outline of the skepticism against the possibility of moral bioenhancement and point out that a long-lasting dispute among moral philosophers nourishes this skepticism. Second, I will survey recent neurofeedback techniques and outline their three features: the variety of the target human faculties, such as emotion, cognition, and behavior; the flexibility or personalizability of the target brain state; and the nonclinical application of neurofeedback techniques. Third, I will argue that, by virtue of these three unique features, neurofeedback techniques can be a tool for moral bioenhancement without adopting any specific notion of morality. Fourth, I will examine the advantages and threats that neurofeedback-based moral enhancement may have. Finally, I will conclude that neurofeedback-based moral enhancement can become a new and promising tool for moral bioenhancement and requires further ethical investigations on its unique features. (shrink)

The authors' commentary on Bruno Latour's "Technology is society made durable" provides the reader with an opportunity to become acquainted with actor-network theory.

In this paper, I summarize an emerging debate in the cognitive sciences over the right taxonomy for understanding cognition – the right theory of and vocabulary for describing the structure of the mind – and the proper role of neuroscientific evidence in specifying this taxonomy. In part because the discussion clearly entails a deep reconsideration of the supposed autonomy of psychology from neuroscience, this is a debate in which philosophers should be interested, with which they should be familiar, and to (...) which they should contribute. Here, I outline some of the positions being advocated, and reflect on some of the possible implications of this work both for scientific and folk psychology. (shrink)

The remember/know procedure is the most widely used method to investigate recollection and familiarity. It uses trial-by-trial reports to determine how much recollection and familiarity contribute to different kinds of recognition. Few other methods provide information about individual memory judgements and no alternative allows such direct indications of recollection and familiarity influences. Here we review how the RK procedure has been and should be used to help resolve theoretical disagreements about the processing and neural bases of components of recognition memory. (...) Emphasis is placed on procedural weaknesses and a possible confound of recollection and familiarity with recognition memory strength. Recommendations are made about how to minimise these problems including using modified versions of the procedure. The proposals here are important for improving behavioural and lesion research, and vital for brain imaging work. (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)

In this paper, our goal is to survey some of the legal contexts within which violence risk assessment already plays a prominent role, explore whether developments in neuroscience could potentially be used to improve our ability to predict violence, and discuss whether neuropredictive models of violence create any unique legal or moral problems above and beyond the well worn problems already associated with prediction more generally. In Violence Risk Assessment and the Law, we briefly examine the role currently played by (...) predictions of violence in three high stakes legal contexts: capital sentencing, civil commitment hearings, and sexual predator statutes. In Clinical vs. Actuarial Violence Risk Assessment, we briefly examine the distinction between traditional clinical methods of predicting violence and more recently developed actuarial methods, exemplified by the Classification of Violence Risk software created by John Monahan and colleagues as part of the MacArthur Study of Mental Disorder and Violence [1]. In The Neural Correlates of Psychopathy, we explore what neuroscience currently tells us about the neural correlates of violence, using the recent neuroscientific research on psychopathy as our focus. We also discuss some recent advances in both data collection and data analysis that we believe will play an important role when it comes to future neuroscientific research on violence. In The Potential Promise of Neuroprediction, we discuss whether neuroscience could potentially be used to improve our ability to predict future violence. Finally, in The Potential Perils of Neuroprediction, we explore some potential evidentiary, constitutional, and moral issues that may arise in the context of the neuroprediction of violence. (shrink)

Cognitive Science, Volume 46, Issue 3, March 2022.

By the late 1990s, several converging trends in economics, psychology, and neuroscience had set the stage for the birth of a new scientific field known as “neuroeconomics”. Without the availability of an extensive variety of experimental designs for dealing with individual and social decision-making provided by experimental economics and psychology, many neuroeconomics studies could not have been developed. At the same time, without the significant progress made in neuroscience for grasping and understanding brain functioning, neuroeconomics would have never seen the (...) light of day. The paper is an overview of the main significant advances in the knowledge of brain functioning by neuroscience that have contributed to the emergence of neuroeconomics and its rise over the past two decades. These advances are grouped over three non-independent topics referred to as the “emo-rational” brain, “social” brain, and “computational” brain. For each topic, it emphasizes findings considered as critical to the birth and development of neuroeconomics while highlighting some of prominent questions about which knowledge should be improved by future research. In parallel, it shows that the boundaries between neuroeconomics and several recent sub-fields of cognitive neuroscience, such as affective, social, and more generally, decision neuroscience, are rather porous. (shrink)

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. (shrink)

Current neuroimaging techniques with high spatial resolution constrain participant motion so that many natural tasks cannot be carried out. The aim of this paper is to show how a time-locked correlation-analysis of cerebral blood flow velocity (CBFV) lateralization data, obtained with functional TransCranial Doppler (fTCD) ultrasound, can be used to infer cerebral activation patterns across tasks. In a first experiment we demonstrate that the proposed analysis method results in data that are comparable with the standard Lateralization Index (LI) for within-task (...) comparisons of CBFV patterns, recorded during cued word generation (CWG) at two difficulty levels. In the main experiment we demonstrate that the proposed analysis method shows correlated blood-flow patterns for two different cognitive tasks that are known to draw on common brain areas, CWG, and Music Synthesis. We show that CBFV patterns for Music and CWG are correlated only for participants with prior musical training. CBFV patterns for tasks that draw on distinct brain areas, the Tower of London and CWG, are not correlated. The proposed methodology extends conventional fTCD analysis by including temporal information in the analysis of cerebral blood-flow patterns to provide a robust, non-invasive method to infer whether common brain areas are used in different cognitive tasks. It complements conventional high resolution imaging techniques. (shrink)

Romantic love is universally observed in human communities, and the manner in which a person chooses a long-term romantic partner has been a central question in studies on close relationships. Numerous empirical psychological studies have demonstrated that facial attractiveness greatly impacts initial romantic attraction. This close link was further investigated by neuroimaging studies showing that both viewing attractive faces and having romantic thoughts recruit the reward system. However, it remains unclear how our brains integrate perceived facial attractiveness into initial romantic (...) attraction. In addition, it remains unclear how our brains shape a persistent attraction to a particular person through interactions; this persistent attraction is hypothesized to contribute to a long-term relationship. After reviewing related studies, I introduce methodologies that could help address these questions. (shrink)

Studies of consciousness have traditionally been based mainly upon the perceptual domains of consciousness. However, there is another side of consciousness, represented by various types of intrinsic conscious experiences. Even though intrinsic experiences can represent up to 50% of our conscious experiences, they are still largely neglected in conscious studies. We assume there are two reasons for this. First, the field of intrinsic conscious experiences is methodologically far more problematic than any other. Second, specific paradigms for capturing the correlates of (...) intrinsic conscious experiences are almost nonexistent. Nevertheless, we expect the intrinsic side of consciousness to soon take its place in conscious studies, but first new experimental paradigms will have to be devised, which would be of a similar design to the paradigms used in studies of perceptual consciousness. In this hypothesis and theory article, we propose such a hypothetical paradigm, presenting the exploratory data of our proof-of-concept study, discussing its use, and addressing its shortcomings and their possible remediation. (shrink)

Neurons repeatedly exposed to similar perceptual experiences fire together and wire together to form ‘meaning kernels’ of concepts. Pulvermueller argues that abstract concepts may be devoid of meaning kernels, because the perceptual experiences that construct abstract concepts are subject to great variation and share few common features. Abstract concept are therefore grounded in the brain through features that belong to ‘meaning halos’, rather than to ‘meaning kernels’.

À la fin des années 1990, plusieurs tendances convergentes en économie, psychologie et neuroscience ont préparé le terrain pour la naissance d’un nouveau champ scientifique qualifié de « neuroéconomie ». Comme pour toute discipline émergente – pensons par exemple à l’économie mathématique, l’économétrie ou l’économie expérimentale en d’autres temps – la neuroéconomie est plutôt controversée en économie. Elle soulève un grand nombre de questions d’ordre empirique, méthodologique et philosophiques donnant lieu à des débats et controverses que l’article identifie et discute (...) à travers trois questions majeures relatives aux connaissances produites : Sont-elles fiables? Sont-elles scientifiquement légitimes? Sont-elles utiles pour les économistes? Sans prétendre à l’exhaustivité, ce cadre analytique permet de comprendre l’essence des principales critiques adressées à la neuroéconomie. Dans le même temps, l’article éclaire la nature des réponses susceptibles d’être apportées à ces critiques au vu des progrès conceptuels et empiriques qu’a connus ce champ de recherche depuis son émergence et à la lumière du tournant apparu dans l’agenda de la neuroéconomie au cours de la dernière décennie. JEL Codes : A12, B41, C51, C81, C9, D03, D87. (shrink)

On the basis of a new criterion for a property to be perceivable–a property is perceivable iff it is not only given immediately and non-volitionally, but also grasped via a holistic form of attention–in this paper we will claim that not only facial properties, but other high-order properties located in a hierarchy of high-order properties, notably gender and racial properties, are perceivable as well. Such claims will be both theoretically and empirically justified.

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. (shrink)

Face perception plays a central role in social communication and is, arguably, one of the most sophisticated visual perceptual skills in humans. The organization of neural systems for face perception has stimulated intense debate. This article presents an updated model of distributed human neural systems for face perception. It opens up with a discussion of the Core System for visual analysis of faces with an emphasis on the distinction between perception of invariant features for identity recognition and changeable features for (...) recognition of facial gestures such as expression and eye gaze. The study analyses the roles of systems for the representation of emotion, for person knowledge, and for action understanding in face recognition and perception of expression and gaze. It presents systems that are of particular relevance for social communication and that are illustrative of how distributed systems are engaged by face perception. It concludes with a discussion of modularity and distributed processing in neural representation. (shrink)

Multi-voxel pattern recognition techniques combined with Hidden Markov models can be used to discover the mental states that people go through in performing a task. The combined method identifies both the mental states and how their durations vary with experimental conditions. We apply this method to a task where participants solve novel mathematical problems. We identify four states in the solution of these problems: Encoding, Planning, Solving, and Respond. The method allows us to interpret what participants are doing on individual (...) problem-solving trials. The duration of the planning state varies on a trial-to-trial basis with novelty of the problem. The duration of solution stage similarly varies with the amount of computation needed to produce a solution once a plan is devised. The response stage similarly varies with the complexity of the answer produced. In addition, we identified a number of effects that ran counter to a prior model of the task. Thus, we were able to decompose the overall problem-solving time into estimates of its components and in way that serves to guide theory. (shrink)

Clinical responses to dopamine replacement therapy for individuals with Parkinson’s disease are often difficult to predict. We characterized changes in MDS-UPDRS motor factor scores resulting from a short-duration L-Dopa response, and investigated how the inter-subject clinical differences could be predicted from motor cortical magnetoencephalography. MDS-UPDRS motor factor scores and resting-state MEG recordings were collected during SDR from twenty individuals with a PD diagnosis. We used a novel subject-specific strategy based on linear support vector machines to quantify motor cortical oscillatory frequency (...) profiles that best predicted medication state. Motor cortical profiles differed substantially across individuals and showed consistency across multiple data folds. There was a linear relationship between classification accuracy and SDR of lower limb bradykinesia, although this relationship did not persist after multiple comparison correction, suggesting that combinations of spectral power features alone are insufficient to predict clinical state. Factor score analysis of therapeutic response and novel subject-specific machine learning approaches based on subject-specific neuroimaging provide tools to predict outcomes of therapies for PD. (shrink)

Multivariate pattern analysis can reveal new information from neuroimaging data to illuminate human cognition and its disturbances. Here, we develop a methodological approach, based on multivariate statistical/machine learning and time series analysis, to discern cognitive processing stages from functional magnetic resonance imaging (fMRI) blood oxygenation level dependent (BOLD) time series. We apply this method to data recorded from a group of healthy adults whilst performing a virtual reality version of the delayed win-shift radial arm maze (RAM) task. This task has (...) been frequently used to study working memory and decision making in rodents. Using linear classifiers and multivariate test statistics in conjunction with time series bootstraps, we show that different cognitive stages of the task, as defined by the experimenter, namely, the encoding/retrieval, choice, reward and delay stages, can be statistically discriminated from the BOLD time series in brain areas relevant for decision making and working memory. Discrimination of these task stages was significantly reduced during poor behavioral performance in dorsolateral prefrontal cortex (DLPFC), but not in the primary visual cortex (V1). Experimenter-defined dissection of time series into class labels based on task structure was confirmed by an unsupervised, bottom-up approach based on Hidden Markov Models. Furthermore, we show that different groupings of recorded time points into cognitive event classes can be used to test hypotheses about the specific cognitive role of a given brain region during task execution. We found that whilst the DLPFC strongly differentiated between task stages associated with different memory loads, but not between different visual-spatial aspects, the reverse was true for V1. Our methodology illustrates how different aspects of cognitive information processing during one and the same task can be separated and attributed to specific brain regions based on information contained in multivariate patterns of voxel activity. (shrink)

Cook et al. overstate the evidence supporting their associative account of mirror neurons in humans: most studies do not address a key property, action-specificity that generalizes across the visual and motor domains. Multivariate pattern analysis of neuroimaging data can address this concern, and we illustrate how MVPA can be used to test key predictions of their account.

The continual background awareness of duration is an essential structure of consciousness, conferring temporal extension to the many objects of awareness within the evanescent sensory present. Seeking the possible neural correlates of ubiquitous temporal awareness, this article reexamines fMRI data from off-task “default mode” periods in 25 healthy subjects studied by Grady et al. , 2005). “Brain reading” using support vector machines detected information specifying elapsed time, and further analysis specified distributed networks encoding implicit time. These networks fluctuate; none are (...) continuously active during DM. However, the aggregate regions of greatest variability closely resemble the default mode network. It appears that the default mode network has an important role as a state-dependent monitor of temporality. (shrink)