Mental Maps1

It’s often hypothesized that the structure of mental representation is map‐like rather than language‐like. The possibility arises as a counterexample to the argument from the best explanation of productivity and systematicity to the language of thought hypothesis—the hypothesis that mental structure is compositional and recursive. In this paper, I argue that the analogy with maps does not undermine the argument, because maps and language have the same kind of compositional and recursive structure.     

Natural deduction in connectionist systems

The relation between logic and thought has long been controversial, but has recently influenced theorizing about the nature of mental processes in cognitive science. One prominent tradition argues that to explain the systematicity of thought we must posit syntactically structured representations inside the cognitive system which can be operated upon by structure sensitive rules similar to those employed in systems of natural deduction. I have argued elsewhere that the systematicity of human thought might better be explained as resulting from the fact that we have learned natural languages which are themselves syntactically structured. According to this view, symbols of natural language are external to the cognitive processing system and what the cognitive system must learn to do is produce and comprehend such symbols. In this paper I pursue that idea by arguing that ability in natural deduction itself may rely on pattern recognition abilities that enable us to operate on external symbols rather than encodings of rules that might be applied to internal representations. To support this suggestion, I present a series of experiments with connectionist networks that have been trained to construct simple natural deductions in sentential logic. These networks not only succeed in reconstructing the derivations on which they have been trained, but in constructing new derivations that are only similar to the ones on which they have been trained.     

Connectionist representation,semantic compositionality,and the instability of concept structure

Summary In the present paper connectionist approaches to the problem of internal representation and the nature of concepts are discussed. In the first part the concept of representation that underlies connectionist modeling is made explicit. It is argued that the connectionist view of representation relies on a correlational theory of semantic content- i.e., the covariation between internal and external states is taken as the basis for ascribing meaning to internal states. The problems and virtues of such a correlational approach to internal representation are addressed. The second part of the paper is concerned with whether connectionism is capable of accounting for the apparent productivity and systematicity of language and thought. There is an evaluation of the recent arguments of Fodor and Pylyshyn, who claim that systematicity can only be explained if one conceives of mental representations as structured symbols composed of context-free constituents. There is a review of empirical evidence that strongly suggests that concepts are not fixed memory structures and that the meaning of constituent symbols varies, depending on the context in which they are embedded. On the basis of this review it is concluded that the meaning of a complex expression is not computed from the context-free meanings of the constituents, and that strong compositionality, as endorsed by Fodor and Pylyshyn (1988), seems implausible as a process theory for the comprehension of complex concepts. Instead, the hypothesis is endorsed that constraint satisfaction in distributed connectionist networks may allow for an alternative account of weak compositionality compatible with the context sensitivity of meaning. In the final section, it is argued that neither mere implementation of a language of thought in connectionist networks nor radical elimination of symbol systems seems to be a fruitful research strategy, but that it might be more useful to discuss how connectionist systems can develop the capacity to use external symbol systems like language or logic without instantiating symbol systems themselves.     

Representations in language processing: why comprehension is not “brute-causal”

I defend a claim, central to much work in psycholinguistics, that constructing mental representations of syntactic structures is a necessary step in language comprehension. Call such representations “mental phrase markers” (MPMs). Several theorists in psycholinguistics, AI, and philosophy have cast doubt on the usefulness of positing MPMs (Devitt, 2006; Rohde, 2002; Schank & Birnbaum, 1984). I examine their proposals and argue that they face major empirical and conceptual difficulties. My conclusions tell against the broader skepticism that persists in philosophy—e.g., in the embodied cognition literature (Hutto & Myin, 2012)—about the usefulness of positing mental representations in psychological models. Using my discussion of sentence parsing as a case study, I propose several conditions on an appropriate appeal to mental representations. Finally, I point out that the familiar arguments from productivity, systematicity, and inferential coherence suffice to establish that MPMs themselves have a constituent structure of a sort that resembles that of public-language sentences. This supports the idea that computational operations defined over MPMs are sensitive to their syntactic structure.     

Representations gone mental

Many philosophers and psychologists have attempted to elucidate the nature of mental representation by appealing to notions like isomorphism or abstract structural resemblance. The ‘structural representations’ that these theorists champion are said to count as representations by virtue of functioning as internal models of distal systems. In his 2007 book, Representation Reconsidered, William Ramsey endorses the structural conception of mental representation, but uses it to develop a novel argument against representationalism, the widespread view that cognition essentially involves the manipulation of mental representations. Ramsey argues that although theories within the ‘classical’ tradition of cognitive science once posited structural representations, these theories are being superseded by newer theories, within the tradition of connectionism and cognitive neuroscience, which rarely if ever appeal to structural representations. Instead, these theories seem to be explaining cognition by invoking so-called ‘receptor representations’, which, Ramsey claims, aren’t genuine representations at all—despite being called representations, these mechanisms function more as triggers or causal relays than as genuine stand-ins for distal systems. I argue that when the notions of structural and receptor representation are properly explicated, there turns out to be no distinction between them. There only appears to be a distinction between receptor and structural representations because the latter are tacitly conflated with the ‘mental models’ ostensibly involved in offline cognitive processes such as episodic memory and mental imagery. While structural representations might count as genuine representations, they aren’t distinctively mental representations, for they can be found in all sorts of non-intentional systems such as plants. Thus to explain the kinds of offline cognitive capacities that have motivated talk of mental models, we must develop richer conceptions of mental representation than those provided by the notions of structural and receptor representation.     

Towards structural systematicity in distributed,statically bound visual representations

The problem of representing the spatial structure of images, which arises in visual object processing, is commonly described using terminology borrowed from propositional theories of cognition, notably, the concept of compositionality. The classical propositional stance mandates representations composed of symbols, which stand for atomic or composite entities and enter into arbitrarily nested relationships. We argue that the main desiderata of a representational system—productivity and systematicity—can (indeed, for a number of reasons, should) be achieved without recourse to the classical, proposition‐like compositionality. We show how this can be done, by describing a systematic and productive model of the representation of visual structure, which relies on static rather than dynamic binding and uses coarsely coded rather than atomic shape primitives.     

Learning the systematic transformation of holographic reduced representations

Holographic Reduced Representation is a representational scheme which allows for the representation of variable-sized structures in a distributed manner. It has been shown that these compositional structures can be transformed holistically. However, in order to do so, the transformation vector was constructed by hand. In this paper we present two methods of learning the holistic transformation of Holographic Reduced Representations from examples. We show that the acquired knowledge can be generalised to structures containing unseen elements and to structures more complex than the training examples. These generalisations require a degree of systematicity which to our knowledge has not yet been achieved by other comparable methods.     

Keeping it Real: Intentional Inexistents,Fineness‐of‐Grain,and the Dilemma for Extrinsic Higher‐Order Representational Theories

According to the standard argument from targetless higher‐order representations, the possibility of such representations presents a dilemma for higher‐order theorists. In this article I argue that there are two theoretically well‐motivated replies to the standard argument. Consequently, the standard argument against higher‐order theories fails. I then go on to argue that while certain versions of higher‐order theory can adequately respond to the standard argument, they both, nevertheless, fail to explain the fineness‐of‐grain that phenomenally conscious experience appears to have.     

What Differentiates Declarative and Procedural Memories: Reply to Cohen,Poldrack, and Eichenbaum (1997)

Cohen, Poldrack, and Eichenbaum (1997; hereafter CPE) offer an account of the nature of individual items in memory and how they relate to one another. They argue that there are two separate memory systems, procedural and declarative (Cohen & Eichenbaum, 1993; Cohen & Squire, 1980). These systems differ in their neuroanatomic substrates, in their operating characteristics, and in the nature of the representations they use. CPE argue that representations in the declarative memory system are compositional, meaning that declarative representations may be composed of other declarative representations. Declarative memories are also flexible, meaning they can be accessed in contexts that differ from those in which they were encoded. Procedural memories, on the other hand, are neither compositional nor flexible. I will argue that there is not sufficient reason to argue that procedural and declarative memories have these distinct characteristics. Both procedural and declarative memories are arguably compositional, and both can appear flexible or inflexible, depending on testing conditions.     

Colour Discrimination And Monitoring Theories of Consciousness

According to the monitoring theory of consciousness, a mental state is conscious in virtue of being represented in the right way by a monitoring state. David Rosenthal, William Lycan, and Uriah Kriegel have developed three different influential versions of this theory. In order to explain colour experiences, each of these authors combines his version of the monitoring theory of consciousness with a specific account of colour representation. Even though Rosenthal, Lycan, and Kriegel disagree on the specifics, they all hold that colours are represented by a single type of mental state. The main goal of this paper is to show that a more complex account of colour representation is needed for the monitoring theory of consciousness to do justice to the phenomenology of colour experiences. In particular, I will argue that the fine-grained character of colour experience—that is, the fact that perceivers can become conscious of small differences between colours—requires that colour representation be construed in terms of two different types of mental states, namely sensory states that represent appearance properties and colour representations that represent physical colours.     

Understanding the glue of narrative structure: Children's on- and off-line inferences about characters’ goals

Because characters’ goals play a key role in the structure of narratives, the ability to make inferences about goals is essential to narrative comprehension. Despite their importance, no previous studies have examined the process by which children make these goal inferences. In the current study, we examined 6- and 8-year-old children's goal inference making processes through think-aloud protocols. We also examined the product of comprehension, the mental representation of text, through free recall and comprehension questions. The results revealed that children of both ages regularly made appropriate goal inferences while listening to narratives. In addition, the number of goal inferences predicted children's recall of the stories. Thus, children as young as 6 years old are sensitive to the vital role of characters’ goals in narrative structure, and they can engage in sophisticated cognitive processing while they listen to narratives to form coherent mental representations of them.     

Biologically Plausible,Human‐Scale Knowledge Representation

Several approaches to implementing symbol‐like representations in neurally plausible models have been proposed. These approaches include binding through synchrony (Shastri & Ajjanagadde, 1993 ), “mesh” binding (van der Velde & de Kamps, 2006 ), and conjunctive binding (Smolensky, 1990 ). Recent theoretical work has suggested that most of these methods will not scale well, that is, that they cannot encode structured representations using any of the tens of thousands of terms in the adult lexicon without making implausible resource assumptions. Here, we empirically demonstrate that the biologically plausible structured representations employed in the Semantic Pointer Architecture (SPA) approach to modeling cognition (Eliasmith, 2013 ) do scale appropriately. Specifically, we construct a spiking neural network of about 2.5 million neurons that employs semantic pointers to successfully encode and decode the main lexical relations in WordNet, which has over 100,000 terms. In addition, we show that the same representations can be employed to construct recursively structured sentences consisting of arbitrary WordNet concepts, while preserving the original lexical structure. We argue that these results suggest that semantic pointers are uniquely well‐suited to providing a biologically plausible account of the structured representations that underwrite human cognition.     

Mental rotation is not easily cognitively penetrable

When participants take part in mental imagery experiments, are they using their “tacit knowledge” of perception to mimic what they believe should occur in the corresponding perceptual task? Two experiments were conducted to examine whether such an account can be applied to mental imagery in general. These experiments both examined tasks that required participants to “mentally rotate” stimuli. In Experiment 1, instructions led participants to believe that they could reorient shapes in one step or avoid reorienting the shapes altogether. Regardless of instruction type, response times increased linearly with increasing rotation angles. In Experiment 2, participants first observed novel objects rotating at different speeds, and then performed a mental rotation task with those objects. The speed of perceptually demonstrated rotation did not affect the speed of mental rotation. We argue that tacit knowledge cannot explain mental imagery results in general, and that in particular the mental rotation effect reflects the nature of the underlying internal representation and processes that transform it, rather than participants’ pre-existing knowledge.     

Visible embodiment: Gestures as simulated action

Spontaneous gestures that accompany speech are related to both verbal and spatial processes. We argue that gestures emerge from perceptual and motor simulations that underlie embodied language and mental imagery. We first review current thinking about embodied cognition, embodied language, and embodied mental imagery. We then provide evidence that gestures stem from spatial representations and mental images. We then propose the gestures-as-simulated-action framework to explain how gestures might arise from an embodied cognitive system. Finally, we compare this framework with other current models of gesture production, and we briefly outline predictions that derive from the framework.     

Fictional Models and Fictional Representations

Scientific models consist of fictitious elements and assumptions. Various attempts have been made to answer the question of how a model, which is sometimes viewed as a fiction, can explain or predict the target phenomenon adequately. I examine two accounts (the counterfactual dependency view and the idealization view) of models-as-fictions which are aiming at disentangling the myth of representing the reality by fictional models. I argue that both views have their own weaknesses in spite of many virtues. I propose to re-evaluate the problems of representation from a novel perspective in which some of the model representations can be regarded as fictional representations. I argue that this type of model representation is credible despite being a fictional representation of the reality.     

The non-abstractness of mental representations

An argument is made that formal abstract mental representations are lacking because they fail to accommodate the contribution of the medium. The importance of the medium is singled out and several respects in which it resists formal characterization noted. Specifically, it is pointed out that the medium can always be relevant, that the aspects by which it is made so are not in principle demarcated or constrained, and that they cannot be restricted a priori at the time of encoding. The examination of several ways by which specifications of medium could be incorporated into mental representations suggests that to obtain a full account of the medium one has to abandon some basic characteristics of mental representations. Conversely, maintaining the concept of mental representation in its standard sense leaves the medium, and with it some fundamental properties of human cognition, outside of one's scientific account. This conclusion serves as the basis for more general comments regarding the study of mind.     

Facing the mirror: A relativist account of immune nonconceptual self-representations

There is a consensus among philosophers that some “I”-thoughts are immune to error through misidentification. In some recent papers, this property has been formulated in the following deflationist way: an “I”-thought is immune to error through misidentification when it can misrepresent the mental or bodily property self-ascribed but cannot misrepresent the subject (if any) possessing that property. However, it has been put forward that the range of mental and bodily states that are immune in that limited sense cannot include nonconceptual forms of self-representation. In this paper, I claim the opposite. I argue in favor of a theoretical framework inspired by semantic relativism that solves the problem of immune nonconceptual self-representations. In order to do so, I refute an argument against the relativist account which is based on the existence of shared representations. This argument, I contend, rests on a confusion between two conditions to which a relativist may appeal when considering whether a certain mental content is relative to the self: a strong invariance condition and a weak invariance condition. I then argue that even if we acknowledge the existence of shared representations, the weak invariance condition is still satisfied, and consequently the relativist framework can make sense of INSRs. I argue that this weak invariance condition is satisfied by a representational function that self-relativizes certain representations. I then provide an empirical instance of such a function by discussing some of the recent literature on motor representations and the sense of agency. In the last part of the paper, I answer several potential objections. These potential objections lead me to distinguish two fundamental kinds of error relative to the self: error through misidentification and error through misapplication. This distinction allows me to answer a fundamental question raised by the very idea of de facto immunity to error through misidentification.     

Images of numbers, or "When 98 is upper left and 6 sky blue".

Some people declare that they possess a personal visual representation of numbers: some automatically "see" the numbers they are confronted with in a precise location in a structured mental space, others "associate" specific colours with given numbers. Such visuo-spatial representations of numbers were first described by Galton in 1880 but have since received little attention from psychologists. It is the aim of this article to describe these mental representations and discuss their role in number processing. The authors first review Galton's observations, and then present their own. Finally, they discuss the relevance of these visuo-spatial representations in relation to contemporary debates on number representation and calculation.     

Integrating structure and meaning: a distributed model of analogical mapping

In this paper we present Drama , a distributed model of analogical mapping that integrates semantic and structural constraints on constructing analogies. Specifically, Drama uses holographic reduced representations (Plate, 1994), a distributed representation scheme, to model the effects of structure and meaning on human performance of analogical mapping. Drama is compared to three symbolic models of analogy (SME, Copycat, and ACME) and one partially distributed model (LISA). We describe Drama's performance on a number of example analogies and assess the model in terms of neurological and psychological plausibility. We argue that Drama's successes are due largely to integrating structural and semantic constraints throughout the mapping process. We also claim that Drama is an existence proof of using distributed representations to model high-level cognitive phenomena.