Levels of Analysis in Cognitive Science

Eigenfeatures are created by the principal component approach (PCA) used on objects described by a low-level code (i.e., pixels, Gabor jets). We suggest that eigenfeatures act like the flexible features described by Schyns et al. They are particularly suited for face processing and give rise to class-specific effects such as the other-race effect. The PCA approach can be modified to accommodate top-down constraints.

Explanations of psychological regularities in terms of biological regularities are undoubtedly appealing for many reasons. In addition, the scientific methodology that searches for such explanations certainly has merit. Nonetheless, the history of neuroscience, psychology, and computer science over the last one hundred years, indicates that such explanations are difficult to find and that the methodology of searching for them often frustrating. Recent attempts to provide "neurally-inspired" explanations of psychological regularities embodied in the theory of parallel distributed processing, PDP, also show (...) signs of these difficulties. The more neurobiologically accurate portions of PDP are isolated from the more psychologically plausible portions, while the portions dedicated to computational analyses of neural networks tend to be isolated from both biology and psychology. Since, however, we may be sure that some day there will be some true scientific and philosophic theory of the role of neurons in mentation, we may press on in the enterprise, using what we have now as a point of departure. In this spirit, we may consider evolutionary explanations of features of our neural hardware. By pursuing evolutionary explanations via computer simulations, genetic algorithms, we have a new direction in which to proceed in our neural network theorizing. A second project we pursue is the application of a neural network studied in PDP computer science, the Boltzmann machine, to psychological phenomena. Here the psychological phenomena are those found in human decision making under risk and captured in Kahneman and Tversky's prospect theory. (shrink)

This paper attempts to establish a systems-semiotic framework explaining creativity in the design process, where the design process is considered to have as its basis the cognitive process. The design process is considered as the interaction between two or more cognitive systems resulting in a purposeful and ongoing transformation of their already complex representational structures and the production of newer ones, in order to fulfill an ill-defined goal. Creativity is considered as the result of an emergence of organizational complexity in (...) each cognitive system participating in the design process, while it is trying to purposefully incorporate new constraints in its meaning structures. The meanings generated in each system are identified as the contingent and anticipatory content of its representations, and where self-organization is the dominant process in which they are continuously involved. Furthermore, Peircean semiotic processes appear to provide the functionality needed by the emergent representational structures in order to complete the cycle of a creative design process. Creativity originates in the abductive stage of the semiotic process, the fallible nature of which is maintained in the proposed framework by the fact that the respective emergent representations can be misfits. The nodal points of the framework are identified and analyzed showing that a cognitive system needs the whole interactive anticipatory cycle in order to engage in a creative design process. (shrink)

Mind and Matter is conceived as an interdisciplinary journal, aimed at an educated readership interested in all aspects of mind-matter research from the perspectives of the sciences and humanities. It is devoted to the publication of empirical, theoretical, and conceptual research and the discussion of its results. The main subject areas of the journal are -- neuroscience, cognitive science, behavioral science -- physical approaches, mathematical modeling, data analysis -- philosophy of science, philosophy of mind, applied metaphysics --cultural and social studies, (...) history of ideas. (shrink)

The notion of levels has been widely used in discussions of cognitive science, especially in discussions of the relation of connectionism to symbolic modeling of cognition. I argue that many of the notions of levels employed are problematic for this purpose, and develop an alternative notion grounded in the framework of mechanistic explanation. By considering the source of the analogies underlying both symbolic modeling and connectionist modeling, I argue that neither is likely to provide an adequate analysis of processes at (...) the level at which cognitive theories attempt to function: One is drawn from too low a level, the other from too high a level. If there is a distinctly cognitive level, then we still need to determine what are the basic organizational principles at that level. (shrink)

This paper argues that, while there is a difference between personal and sub-personal explanation, claims of autonomy should be treated with scepticism. It distinguishes between horizontal and vertical explanatory relations that might hold between facts at the personal and facts at the sub-personal level. Noting that many philosophers are prepared to accept vertical explanatory relations between the two levels, I argue for the stronger claim that, in the case of at least three central personal level phenomena, the demands of explanatory (...) adequacy require postulating horizontal explanatory relations. (shrink)

An asymmetry between the demands at the computational and algorithmic levels of description furnishes the illusion that the abstract profile at the computational level can be multiply realized, and that something is actually being shared at the algorithmic one. A disembodied rendering of the situation lays the stress upon the different ways in which an algorithm can be implemented. However, from an embodied approach, things look rather different. The relevant pairing, I shall argue, is not between implementation and algorithm, but (...) rather between algorithm and computation. The autonomy of psychology is a result of the failure to appreciate this point. (shrink)

This paper is concerned with the modeling of neural systems regarded as information processing entities. I investigate the various dynamic regimes that are accessible in neural networks considered as nonlinear adaptive dynamic systems. The possibilities of obtaining steady, oscillatory or chaotic regimes are illustrated with different neural network models. Some aspects of the dependence of the dynamic regimes upon the synaptic couplings are examined. I emphasize the role that the various regimes may play to support information processing abilities. I present (...) an example where controlled transient evolutions in a neural network, are used to model the regulation of motor activities by the cerebellar cortex. (shrink)

I reply to my critics in respect of my work on expertise. I define the 'core' of the multidisciplinary 'expertise studies'. I argue that those who have taken the work seriously could resolve their problems by paying more attention to the core. Each could have made good use of an aspect of the core.

Cognitive science is the interdisciplinary study of minds and intelligent behavior in human beings and animals. The challenge of integrating a study of the mind with a scientific world view has only recently attracted sustained effort. In this course, we will examine the various scientific methodologies that have been brought to bear to uncover the nature of the mind. We will critically assess the data and theoretical results that define contemporary cognitive science. Beyond the results of experiments and the theories (...) that are based on them, cognitive science proposes that there is an underlying framework that unifies the diverse methodologies we appeal to. We seek to understand this foundation. (shrink)

Arguments, claims, and discussions about the “level of description” of a theory are ubiquitous in cognitive science. Such talk is typically expressed more precisely in terms of the granularity of the theory, or in terms of Marr’s three levels. I argue that these ways of understanding levels of description are insufficient to capture the range of different types of theoretical commitments that one can have in cognitive science. When we understand these commitments as points in a multi-dimensional space, we find (...) that we must also reconsider our understanding of intertheoretic relations. In particular, we should understand cognitive theories as constraining one another, rather than reducing to one another. (shrink)

Starting from Dennett's distinction between personal and sub-personal levels of description, I consider the relationships amongst three levels: the personal level, the level of information-processing mechanisms, and the level of neurobiology. I defend a conception of the relationship between the personal level and the sub-personal level of information-processing mechanisms as interaction without reduction . Even given a nonreductionist conception of persons, philosophical theorizing sometimes supports downward inferences from the personal to the sub-personal level. An example of a downward inference is (...) provided and an objection is considered. (shrink)

Until recently, the notions of function and multiple realization were supposed to save the autonomy of psychological explanations. Furthermore, the concept of supervenience presumably allows both dependence of mind on brain and non-reducibility of mind to brain, reconciling materialism with an independent explanatory role for mental and functional concepts and explanations. Eliminativism is often seen as the main or only alternative to such autonomy. It gladly accepts abandoning or thoroughly reconstructing the psychological level, and considers reduction if successful as equivalent (...) with elimination. In comparison with the philosophy of mind, the philosophy of biology has developed more subtle and complex ideas about functions, laws, and reductive explanation than the stark dichotomy of autonomy or elimination. It has been argued that biology is a patchwork of local laws, each with different explanatory interests and more or less limited scope. This points to a pluralistic, domain-specific and multi-level view of explanations in biology. Explanatory pluralism has been proposed as an alternative to eliminativism on the one hand and methodological dualism on the other hand. It holds that theories at different levels of description, like psychology and neuroscience, can co-evolve, and mutually influence each other, without the higher-level theory being replaced by, or reduced to, the lower-level one. Such ideas seem to tally with the pluralistic character of biological explanation. In biological psychology, explanatory pluralism would lead us to expect many local and non-reductive interactions between biological, neurophysiological, psychological and evolutionary explanations of mind and behavior. This idea is illustrated by an example from behavioral genetics, where genetics, physiology and psychology constitute distinct but interrelated levels of explanation. Accounting for such a complex patchwork of related explanations seems to require a more sophisticated and precise way of looking at levels than the existing ideas on (reductive and non-reductive) explanation in the philosophy of mind. (shrink)

The distinction between personal level explanations and subpersonal ones has been subject to much debate in philosophy. We understand it as one between explanations that focus on an agent’s interaction with its environment, and explanations that focus on the physical or computational enabling conditions of such an interaction. The distinction, understood this way, is necessary for a complete account of any agent, rational or not, biological or artificial. In particular, we review some recent research in Artificial Life that pretends to (...) do completely without the distinction, while using agent-centered concepts all the way. It is argued that the rejection of agent level explanations in favour of mechanistic ones is due to an unmotivated need to choose among representationalism and eliminativism. The dilemma is a false one if the possibility of a radical form of externalism is considered. (shrink)

The distinction between personal level explanations and subpersonal ones has been subject to much debate in philosophy. We understand it as one between explanations that focus on an agent’s interaction with its environment, and explanations that focus on the physical or computational enabling conditions of such an interaction. The distinction, understood this way, is necessary for a complete account of any agent, rational or not, biological or artificial. In particular, we review some recent research in Artificial Life that pretends to (...) do completely without the distinction, while using agent-centred concepts all the way. It is argued that the rejection of agent level explanations in favour of mechanistic ones is due to an unmotivated need to choose among representationalism and eliminativism. The dilemma is a false one if the possibility of a radical form of externalism is considered. (shrink)

The vivid terms, "Top-down" and "Bottom-up" have become popular in several different contexts in cognitive science. My task today is to sort out some different meanings and comment on the relations between them, and their implications for cognitive science.

In this paper, I claim that the personal/subpersonal distinction is first and foremost a distinction between two kinds of psychological theory or explanation: it is only in this form that we can understand why the distinction was first introduced, and how it continues to earn its keep. I go on to examine the different ontological commitments that might lead us from the primary distinction between personal and subpersonal explanations to a derivative distinction between personal and subpersonal states. I argue that (...) on one of the most common metaphysical interpretations of the explanatory distinction, talk of a distinction between personal and subpersonal states simply makes no sense. When people insist on applying the personal/subpersonal terminology to psychological states, I allow that they are often making a genuine distinction, but one that it is best understood in terms of Stich's (1978) distinction between doxastic and subdoxastic states. I end the paper by considering some other common misinterpretations of the personal/subpersonal distinction, such as those involving consciousness, normativity, or autonomy. (shrink)

One question of the bounds of cognition is that of which things have it. A scientifically relevant debate on this question must explain the persistent and selective use of psychological predicates to report findings throughout biology: for example, that neurons prefer, fruit flies and plants decide, and bacteria communicate linguistically. This paper argues that these claims should enjoy default literal interpretation. An epistemic consequence is that these findings can contribute directly to understanding the nature of psychological capacities.

Do accounts of scientific theory formation and revision have implications for theories of everyday cognition? We maintain that failing to distinguish between importantly different types of theories of scientific inference has led to fundamental misunderstandings of the relationship between science and everyday cognition. In this article, we focus on one influential manifestation of this phenomenon which is found in Fodor's well-known critique of theories of cognitive architecture. We argue that in developing his critique, Fodor confounds a variety of distinct claims (...) about the holistic nature of scientific inference. Having done so, we outline more promising relations that hold between theories of scientific inference and ordinary cognition. (shrink)

This paper attempts in the first instance to clarify the application of the personal/sub-personal distinction to psychoanalysis and to indicate how this issue is related to that of psychoanalysis" epistemology. It is argued that psychoanalysis may be regarded either as a form of personal psychology, or as a form of jointly personal and sub-personal psychology, but not as a form of sub-personal psychology. It is further argued that psychoanalysis indicates a problem with the personal/sub-personal distinction itself as understood by Dennett (...) A revised view of the distinction, which is argued to reflect its true metaphysical significance, is proposed. (shrink)

Recent developments in technologically enabled social cognition call for a rethinking of many aspects of human cognition. According to the hypothesis of extended cognition, we must revise our psychological categories by eliminating allegedly superficial distinctions between internal cognition and external processes. As an alternative to this proposal, I outline a hypothesis of outsourced cognition which seeks to respect distinctions that are operative in both folk psychology and the social and cognitive sciences. According to this hypothesis, the cognitive states and processes (...) of the individual are substantially and explanatorily distinct from the relevant external states and processes. In consequence, the individual remains a cognitive unit that is both central and indispensable in the explanations of cognitive science. As a case study, I consider the epistemology of testimony. I will argue that important epistemological categories may be preserved by adopting the hypothesis of outsourced cognition over the hypothesis of extended cognition. Moreover, I will argue that the outsourced cognition hypothesis deepens the problems that beset an extended epistemology of testimony. (shrink)

In approaching the question of whether groups of people can have cognitive capacities that are fundamentally different than the cognitive capacities of the individuals within the group, we lay out a Multiple, Interactive Levels of Cognitive Systems (MILCS) framework. The goal of MILCS is to explain the kinds of cognitive processes typically studied by cognitive scientists, such as perception, attention, memory, categorization, decision making, problem solving, and judgment. Rather than focusing on high-level constructs such as modules in an information processing (...) flow diagram or internal representations, MILCS focuses on mechanisms that allow systems to engage in flexible, adaptive behavior. Examples of these mechanisms are network structure-process pairs that: combine data from perception with top-down theories, achieve consistency and consensus through information exchange, selectively attend to information globally assessed as relevant, and develop specialized units from originally homogeneous networks through competition among the units. Two such systems are considered in some detail -- lateral inhibition within a network for selecting from a candidate set the option that is most attractive, and a diffusion process for accumulating evidence to reach a generally rapid and accurate decision. These system descriptions are aptly applied at multiple levels, including within and across people. These systems provide accounts that unify cognitive processes across multiple levels, can be expressed in a common vocabulary provided by network science, are inductively powerful yet appropriately constrained, and are applicable to a large number of superficially diverse cognitive systems. Given that people are typically highly motivated to participate in strong groups, cognitively resourceful people will tend to form groups that effectively employ cognitive systems at higher levels than the individuals. The impressive cognitive capacities of individual people do not eliminate the need to talk about group cognition. Instead, smart people generally form smart groups. (shrink)

In fMRI research, the goal of correcting for multiple comparisons is to identify areas of activity that reflect true effects, and thus would be expected to replicate in future studies. Finding an appropriate balance between trying to minimize false positives (Type I error) while not being too stringent and omitting true effects (Type II error) can be challenging. Furthermore, the advantages and disadvantages of these types of errors may differ for different areas of study. In many areas of social neuroscience (...) that involve complex processes and considerable individual differences, such as the study of moral judgment, effects are typically smaller and statistical power weaker, leading to the suggestion that less stringent corrections that allow for more sensitivity may be beneficial, but also result in more false positives. Using moral judgment fMRI data, we evaluated four commonly used methods for multiple comparison correction implemented in SPM12 by examining which method produced the most precise overlap with results from a meta-analysis of relevant studies and with results from nonparametric permutation analyses. We found that voxel-wise thresholding with family-wise error correction based on Random Field Theory provides a more precise overlap (i.e., without omitting too few regions or encompassing too many additional regions) than either clusterwise thresholding, Bonferroni correction, or false discovery rate correction methods. (shrink)

The new paradigm in the psychology of reasoning draws on Bayesian formal frameworks, and some advocates of the new paradigm think of these formal frameworks as providing a computational-level theory of rational human inference. I argue that Bayesian theories should not be seen as providing a computational-level theory of rational human inference, where by “Bayesian theories” I mean theories that claim that all rational credal states are probabilistically coherent and that rational adjustments of degrees of belief in the light of (...) new evidence must be in accordance with some sort of conditionalization. The problems with the view I am criticizing can best be seen when we look at chains of inferences, rather than single-step inferences. Chains of inferences have been neglected almost entirely within the new paradigm. (shrink)

David Marr provided an influential account of levels of description in classical cognitive science. In this paper we contrast Marr'ent with some alternatives that are suggested by the recent emergence of connectionism. Marr's account is interesting and important both because of the levels of description it distinguishes, and because of the way his presentation reflects some of the most basic, foundational, assumptions of classical AI-style cognitive science . Thus, by focusing on levels of description, one can sharpen foundational differences between (...) classicism and potential non-classical conceptions of mentality that might emerge under the rubric of connectionism. (shrink)

The debate between Classicism and Connectionism can be properly characterized as a debate concerning the appropriate levels of analysis for psychological theorizing. Classicists maintain that the level of analysis defined by the Classical architecture is the level of analysis at which psychological theorizing should reside. This level is called the symbolic level. On the other hand, Connectionists claim that the proper level of analysis for cognitive modeling is at the subsymbolic level which is considered a level lower than the symbolic (...) level. This thesis argues that both Classicism and Connectionism characterized in the above way are single-level approaches. It is argued in this thesis that Classicism is wrong in denying the cognitive relevancy of the lower-level theorizing; and some forms of Connectionism should be rejected because they underestimate the theoretical significance of the higher-level modeling. ;The concept of level is widely employed by philosophers and cognitive scientists, but has not received sufficient analysis. This thesis offers a general theory of levels, and evaluates Classicism and Connectionism on the basis of this general theory of levels. Basically this thesis argues that a cognitive system should be regarded as a system organized into a hierarchy of levels of organization. Different levels of organization may demand different levels of analysis. This thesis argues that each level of analysis enjoys a degree of autonomy, i.e., it is not totally reducible to the lower-level analysis. The traditional dichotomy of the cognitive and the implementational levels is too simplistic and overlooks the complexity of a cognitive system. Not all levels of organization of a system are cognitively relevant. But much empirical evidence has shown that many levels of organization are either strongly relevant or at least weakly relevant to cognitive modeling. It would be theoretically more plausible and fruitful to adopt a multi-level approach which takes many levels of analysis seriously in cognitive modeling. A very general picture of a multi-level approach to the mind is depicted in this thesis. (shrink)

Introduction: the neuroscientific turn in political science The observation that brains and political orders are interdependent is almost trivial. Obviously, political orders require brain processes in order to emerge and to remain in place, as these processes enable action and cognition. Conversely, every since Aristotle coined man as “by nature a political animal” (Aristotle, Pol.: 1252a 3; cf. Eth. Nic.: 1097b 11), this also suggests that the political engagements of this animal has likely consequences for its natural development, including the (...) development of its psychological functions. Given these mutual interdependencies, it is remarkable that only since the 1960s, the more general domain of ‘biopolitics’ has attracted attention though first particularly in the form of behavioral politics (Alford and Hibbing). Since then biopolitics has gained in interest, so much so that different subdomains can be identified. Indeed, a 2008 review of the field of biopolitics identified five ‘headings’ of it: “(1) the case for a ‘more biologically oriented political science’, (2) ‘biologically related’ public policy issues, (3) physiological measures of political attitudes and behaviour, (4) the influence of physiological factors on actual political behaviour, and (5) the manner in which our species’ evolutionary history has left homo sapiens genetically endowed with certain social and political behavioural tendencies” (Somit and Peterson 43). Striking is how the relation between biology and politics is taken here in a rather unidirectional way, emphasizing particularly the decisive power of biology upon politics. The reverse relation is not mentioned specifically, reflecting the field of biopolitics, perhaps until quite recently. This absence of studies of political influences on our biology may have to do with the difficulty in investigating such influences. Empirical studies in biopolitics have two foci, broadly speaking: genetics and the brain, both of which have turned out to be complex and dynamic phenomena (Alford and Hibbing). Yet the studies of genetics and brain processes have made much progress in the last few decades, thanks to the development of research instruments - like fMRI brain scanners and TMS brain stimulation instruments - and of computational tools for data analysis and the simulation of explanatory models. For the field of biopolitics it is particularly relevant that within cognitive neuroscience the study of social and political issues has witnessed an increasing interest of researchers even more recently. Indeed, aware of the enabling and mediating role of the brain regarding those issues, a truly ‘neuroscientific turn’ can be observed in the social sciences, testified for example by the emergence of the field of ‘neuropolitics’ (Connolly; Vandervalk). Developing a systematic neuropolitics or biopolitics in general is a difficult challenge because of the wealth of causal influences on and interdependencies between biological, brain, cognitive and socio-political factors. Taking a somewhat more abstract perspective, this paper focuses on the process of emerging complexity in adaptive systems, enabling those to conduct ever more complex processes. Yet, parallel to that development can be observed that such systems, or organisms, are also capable in reducing the complexity of the information they are to process. Once they’re capable of developing and adjusting such compressed and complex representations of information, those systems or organisms can handle more information faster and more efficient and adaptive, yielding important benefits to the organism in navigating its environment (Halford, Wilson and Phillips). Before focusing on the role of narrative as a cognitive strategy for such a reduction of informational complexity, I will discuss the development of stable structures and increasing complexity in dynamic systems. Such a more general perspective prepares our discussion of the structures of both narratives and politics and in doing so contributes to the explanation of their interaction. (shrink)

We overview the main historical and technological elements characterising the rise, the fall and the recent renaissance of the cognitive approaches to Artificial Intelligence and provide some insights and suggestions about the future directions and challenges that, in our opinion, this discipline needs to face in the next years.

The most prominent argument for the incompatibility of free will and determinism is Peter van Inwagen’s consequence argument. In this paper, I offer a new diagnosis of what is wrong with this argument. Both proponents and critics of the argument typically accept the way it is framed and only disagree on whether the argument’s premises and the rules of inference on which it relies are true. I suggest that the argument involves a category mistake: it conflates two different levels of (...) description, namely the physical level at which we describe the state of the world from the perspective of fundamental physics and the agential level at which we describe agents and their actions. My diagnosis is based on an account of free will as a higher-level phenomenon that was developed in List (2014). I will call this account ‘compatibilist libertarianism’, for reasons that will become clear in the discussion. (shrink)

The cognitive neurosciences are based on the idea that the level of neurons or neural networks constitutes a privileged level of analysis for the explanation of mental phenomena. This paper brings to mind several arguments to the effect that this presumption is ill-conceived and unwarranted in light of what is currently understood about the physical principles underlying mental achievements. It then scrutinizes the question why such conceptions are nevertheless currently prevailing in many areas of psychology. The paper argues that corresponding (...) conceptions are rooted in four different aspects of our common-sense conception of mental phenomena and their explanation, which are illegitimately transferred to scientific enquiry. These four aspects pertain to the notion of explanation, to conceptions about which mental phenomena are singled out for enquiry, to an inductivist epistemology, and, in the wake of behavioristic conceptions, to a bias favoring investigations of input–output relations at the expense of enquiries into internal principles. To the extent that the cognitive neurosciences methodologically adhere to these tacit assumptions, they are prone to turn into a largely a-theoretical and data - driven endeavor while at the same time enhancing the prospects for receiving widespread public appreciation of their empirical findings. (shrink)

the _algorithmic_, and the _implementational_; Zenon Pylyshyn (1984) calls them the _semantic_, the _syntactic_, and the _physical_; and textbooks in cognitive psychology sometimes call them the levels of _content_, _form_, and _medium_ (e.g. Glass, Holyoak, and Santa 1979).

In Rahul Banerjee and Bikas K. Chakrabarti (eds.), Progress in Brain Research, 168: 215-246. Amsterdam: Elsevier. Electronic offprint available upon request.

Notwithstanding many similarities between Thelen et al.'s and Piaget's accounts of the A-not-B error, we argue that, in contrast to Piaget, they do not explicitly address the issue of objectivity. We suggest that this omission is partly due to the fact that Thelen et al. and Piaget's accounts are pitched at different levels of explanation.