The Human Brain Project (HBP) is a massive interdisciplinary project involving hundreds of researchers across more than eighty institutions that seeks to leverage cutting edge information and communication technologies to create a multi-level brain simulation platform (BSP). My worry is that some brain models running on the BSP will be persons. If this is right then not only will the in silico experiments the HBP envisions being carried on the BSP be unethical the mere termination of (...) certain brain models running on the BSP will be unethical. To assess the possible personhood of certain brain simulations I consider John Searle’s critique of strong AI. In arguing that Searle’s critique fails I conclude that the HBP must tread carefully and devise strict rules on how research using the BSP ought to proceed. (shrink)

Modelling and simulations have gained a leading position in contemporary attempts to describe, explain, and quantitatively predict the human brain's operations. Computer models are highly sophisticated tools developed to achieve an integrated knowledge of the brain with the aim of overcoming the actual fragmentation resulting from different neuroscientific approaches. In this paper we investigate plausibility of simulation technologies for emulation of consciousness and the potential clinical impact of large-scale brain simulation on the assessment and care (...) of disorders of consciousness, e.g. Coma, Vegetative State/Unresponsive Wakefulness Syndrome, Minimally Conscious State.Notwithstanding their technical limitations, we suggest that simulation technologies may offer new solutions to old practical problems, particularly in clinical contexts. We take DOCs as an illustrative case, arguing that the simulation of neural correlates of consciousness is potentially useful for improving treatments of patients with DOCs. (shrink)

The claim defended in the paper is that the mechanistic account of explanation can easily embrace idealization in big-scale brain simulations, and that only causally relevant detail should be present in explanatory models. The claim is illustrated with two methodologically different models: Blue Brain, used for particular simulations of the cortical column in hybrid models, and Eliasmith’s SPAUN model that is both biologically realistic and able to explain eight different tasks. By drawing on the mechanistic theory of computational (...) explanation, I argue that large-scale simulations require that the explanandum phenomenon is identified; otherwise, the explanatory value of such explanations is difficult to establish, and testing the model empirically by comparing its behavior with the explanandum remains practically impossible. The completeness of the explanation, and hence of the explanatory value of the explanatory model, is to be assessed vis-à-vis the explanandum phenomenon, which is not to be conflated with raw observational data and may be idealized. I argue that idealizations, which include building models of a single phenomenon displayed by multi-functional mechanisms, lumping together multiple factors in a single causal variable, simplifying the causal structure of the mechanisms, and multi-model integration, are indispensable for complex systems such as brains; otherwise, the model may be as complex as the explanandum phenomenon, which would make it prone to so-called Bonini paradox. I conclude by enumerating dimensions of empirical validation of explanatory models according to new mechanism, which are given in a form of a “checklist” for a modeler. (shrink)

The advancement of computing technology makes it possible to build extremely accurate digital reconstructions of brain circuits. Are such unprecedented levels of biological accuracy essential for brain simulations to play the roles they are expected to play in neuroscientific research? The main goal of this paper is to clarify this question by distinguishing between various roles played by large-scale simulations in contemporary neuroscience, and by reflecting about what makes a simulation biologically accurate. It is argued that large-scale (...) simulations may play model-oriented and prediction-oriented roles in brain research, and that the concept of biological accuracy can be interpreted as related to the plausibility of the theoretical model implemented in the simulation system, to the accuracy of the computer implementation, and to the level of details of the implemented model. Building on these observations and distinctions, it is argued that biological accuracy is not essential for a computer simulation to play the epistemic roles it is expected to play in brain research. (shrink)

With the advent of powerful parallel computers, efforts have commenced to simulate complete mammalian brains. However, so far none of these efforts has produced outcomes close to explaining even the behavioral complexities of animals. In this article, we suggest four challenges that ground this shortcoming. First, we discuss the connection between hypothesis testing and simulations. Typically, efforts to simulate complete mammalian brains lack a clear hypothesis. Second, we treat complications related to a lack of parameter constraints for large-scale simulations. To (...) demonstrate the severity of this issue, we review work on two small-scale neural systems, the crustacean stomatogastric ganglion and the Caenorhabditis elegans nervous system. Both of these small nervous systems are very thoroughly, but not completely understood, mainly due to issues with variable and plastic parameters. Third, we discuss the hierarchical structure of neural systems as a principled obstacle to whole-brain simulations. Different organizational levels imply qualitative differences not only in structure, but in choice and appropriateness of investigative technique and perspective. The challenge of reconciling different levels also undergirds the challenge of simulating and hypothesis testing, as modeling a system is not the same thing as simulating it. Fourth, we point out that animal brains are information processing systems tailored very specifically for the ecological niches the respective animals live in. (shrink)

Despite the impressive amount of financial resources invested in carrying out large-scale brain simulations, it is controversial what the payoffs are of pursuing this project. The present paper argues that in some cases, from designing, building, and running a large-scale neural simulation, scientists acquire useful knowledge about the computational performance of the simulating system, rather than about the neurobiological system represented in the simulation. What this means, why it is not a trivial lesson, and how it advances (...) the literature on the epistemology of computer simulation are the three preoccupations addressed by the paper. (shrink)

In this paper, I discuss the relationship between bodily experiences in dreams and the sleeping, physical body. I question the popular view that dreaming is a naturally and frequently occurring real-world example of cranial envatment. This view states that dreams are functionally disembodied states: in a majority of dreams, phenomenal experience, including the phenomenology of embodied selfhood, unfolds completely independently of external and peripheral stimuli and outward movement. I advance an alternative and more empirically plausible view of dreams as weakly (...) phenomenally-functionally embodied states. The view predicts that bodily experiences in dreams can be placed on a continuum with bodily illusions in wakefulness. It also acknowledges that there is a high degree of variation across dreams and different sleep stages in the degree of causal coupling between dream imagery, sensory input, and outward motor activity. Furthermore, I use the example of movement sensations in dreams and their relation to outward muscular activity to develop a predictive processing account. I propose that movement sensations in dreams are associated with a basic and developmentally early kind of bodily self-sampling. This account, which affords a central role to active inference, can then be broadened to explain other aspects of self- and world-simulation in dreams. Dreams are world-simulations centered on the self, and important aspects of both self- and world-simulation in dreams are closely linked to bodily self-sampling, including muscular activity, illusory own-body perception, and vestibular orienting in sleep. This is consistent with cognitive accounts of dream generation, in which long-term beliefs and expectations, as well as waking concerns and memories play an important role. What I add to this picture is an emphasis on the real-body basis of dream imagery. This offers a novel perspective on the formation of dream imagery and suggests new lines of research. (shrink)

Despite the impressive amount of financial resources recently invested in carrying out large-scale brain simulations, it is controversial what the pay-offs are of pursuing this project. One idea is that from designing, building, and running a large-scale neural simulation, scientists acquire knowledge about the computational performance of the simulating system, rather than about the neurobiological system represented in the simulation. It has been claimed that this knowledge may usher in a new era of neuromorphic, cognitive computing systems. (...) This study elucidates this claim and argues that the main challenge this era is facing is not the lack of biological realism. The challenge lies in identifying general neurocomputational principles for the design of artificial systems, which could display the robust flexibility characteristic of biological intelligence. (shrink)

Prediction draws on both simulation and theory. I ask how simulation is defined, and what the roles of simulation and theory are, respectively. Simulation is flexible in structure and resources. Often simulation and theory are combined in prediction. The function of simulation consists of representing a situation that is relevantly like the target situation with regards to the feature predicted.

What psychological and philosophical significance should we attach to recent efforts at computer simulations of human cognitive capacities? In answering this question, I find it useful to distinguish what I will call "strong" AI from "weak" or "cautious" AI. According to weak AI, the principal value of the computer in the study of the mind is that it gives us a very powerful tool. For example, it enables us to formulate and test hypotheses in a more rigorous and precise fashion. (...) But according to strong AI, the computer is not merely a tool in the study of the mind; rather, the appropriately programmed computer really is a mind, in the sense that computers given the right programs can be literally said to. (shrink)

In recent years, a number of research projects have been proposed whose goal is to build large-scale simulations of brain mechanisms at unprecedented levels of biological accuracy. Here it is argued that the roles these simulations are expected to play in neuroscientific research go beyond the “synthetic method” extensively adopted in Artificial Intelligence and biorobotics. In addition we show that, over and above the common goal of simulating brain mechanisms, these projects pursue various modelling ambitions that can be (...) sharply distinguished from one another, and that correspond to conceptually different interpretations of the notion of “biological accuracy”. They include the ambition to reach extremely deep levels in the mechanistic decomposition hierarchy, to simulate networks composed of extremely large numbers of neural units, to build systems able to generate rich behavioural repertoires, to simulate “complex” neuron models, to implement the “best” theories available on brain structure and function. Some questions will be raised concerning the significance of each of these modelling ambitions with respect to the various roles played by simulations in the study of the brain. (shrink)

A number of research projects have recently taken up the challenge of formulating large-scale models of brain mechanisms at unprecedented levels of detail. These research enterprises have raised lively debates in the press and in the scientific and philosophical literature, some of them revolving around the question whether the incorporation of so many details in a theoretical model and in a computer simulations of it is really needed for the model to be explanatory. Is there a “right” level of (...) detail? In this article I analyse the claim, made by two leading neuroscientists, according to which the content of the why-question addressed and the amount of computational resources available constrains the choice of the most appropriate level of detail in brain modelling. Based on the recent philosophical literature on scientific explanation, I distinguish between two kinds of details, called here mechanistic decomposition and property details, and argue that the nature of the why-question provides only partial constraints to the choice of the most appropriate level of detail under the two interpretations of the term considered here. (shrink)

Recent application of theories of embodied or grounded cognition to the recognition and interpretation of facial expression of emotion has led to an explosion of research in psychology and the neurosciences. However, despite the accelerating number of reported findings, it remains unclear how the many component processes of emotion and their neural mechanisms actually support embodied simulation. Equally unclear is what triggers the use of embodied simulation versus perceptual or conceptual strategies in determining meaning. The present article integrates (...) behavioral research from social psychology with recent research in neurosciences in order to provide coherence to the extant and future research on this topic. The roles of several of the brain's reward systems, and the amygdala, somatosensory cortices, and motor centers are examined. These are then linked to behavioral and brain research on facial mimicry and eye gaze. Articulation of the mediators and moderators of facial mimicry and gaze are particularly useful in guiding interpretation of relevant findings from neurosciences. Finally, a model of the processing of the smile, the most complex of the facial expressions, is presented as a means to illustrate how to advance the application of theories of embodied cognition in the study of facial expression of emotion. (shrink)

Nick Bostrom’s recently patched ‘‘simulation argument’’ (Bostrom in Philos Q 53:243–255, 2003; Bos- trom and Kulczycki in Analysis 71:54–61, 2011) purports to demonstrate the probability that we ‘‘live’’ now in an ‘‘ancestor simulation’’—that is as a simulation of a period prior to that in which a civilization more advanced than our own—‘‘post-human’’—becomes able to simulate such a state of affairs as ours. As such simulations under consid- eration resemble ‘‘brains in vats’’ (BIVs) and may appear open to (...) similar objections, the paper begins by reviewing objections to BIV-type proposals, specifically those due a presumed mad envatter. In counter example, we explore the motivating rationale behind current work in the development of psychologically realistic social simula- tions. Further concerns about rendering human cognition in a computational medium are confronted through review of current dynamic systems models of cognitive agency. In these models, aspects of the human condition are repro- duced that may in other forms be considered incomputable, i.e., political voice, predictive planning, and consciousness. The paper then argues that simulations afford a unique potential to secure a post-human future, and may be nec- essary for a pre-post-human civilization like our own to achieve and to maintain a post-human situation. Long-s- tanding philosophical interest in tools of this nature for Aristotle’s ‘‘statesman’’ and more recently for E.O. Wilson in the 1990s is observed. Self-extinction-level threats from State and individual levels of organization are compared, and a likely dependence on large-scale psychologically realistic simulations to get past self-extinction-level threats is projected. In the end, Bostrom’s basic argument for the conviction that we exist now in a simulation is reaffirmed. (shrink)

I present a new argument that we are much more likely to be living in a computer simulation than in the ground-level of reality. (Similar arguments can be marshalled for the view that we are more likely to be Boltzmann brains than ordinary people, but I focus on the case of simulations.) I explain how this argument overcomes some objections to Bostrom’s classic argument for the same conclusion. I also consider to what extent the argument depends upon an internalist (...) conception of evidence, and I refute the common line of thought that finding many simulations being run—or running them ourselves—must increase the odds that we are in a simulation. GPI Working Paper No. 16-2021. (shrink)

The goal of computational cognitive neuroscience is to understand how the brain embodies the mind by using biologically based computational models comprised of networks of neuronlike units. This text, based on a course taught by Randall O'Reilly and Yuko Munakata over the past several years, provides an in-depth introduction to the main ideas in the field. The neural units in the simulations use equations based directly on the ion channels that govern the behavior of real neurons and the neural (...) networks incorporate anatomical and physiological properties of the neocortex. Thus the text provides the student with knowledge of the basic biology of the brain as well as the computational skills needed to simulate large-scale cognitive phenomena. (shrink)

This paper examines the causal basis of our ability to attribute emotions to music, developing and synthesizing the existing arousal, resemblance and persona theories of musical expressivity to do so. The principal claim is that music hijacks the simulation mechanism of the brain, a mechanism which has evolved to detect one's own and other people's emotions.

This paper contributes to an ongoing debate regarding the cognitive processes involved when one person predicts a target person's behavior and/or attributes a mental state to that target person. According to simulation theory, a person typically performs these tasks by employing some part of her brain as a simulation of what is going on in a corresponding part of the brain of the target person. I propose a general intuitive analysis of what 'simulation' means. (...) class='Hi'>Simulation is a particular way of using one process to acquire knowledge about another process. What distinguishes simulation from other ways of acquiring knowledge is that simulation requires, for its non-accidental success, that the simulating process reflect significant aspects of the simulated process. This conceptual work is of independent philosophical interest, but it also enables me to argue for two conclusions that are of great significance to the debate about mental simulation theory. First, I argue that, in order to stake a non-trivial claim, simulation theory must hold that mental simulation involves what I call concretely similar processes. Second, I argue for the surprising conclusion that a significant class of cases that simulation theorists have claimed as intuitive cases of simulation do not actually involve simulation, after all. I close by sketching an alternative account that might handle these problematic cases. (shrink)

Context: W. R. Ashby’s work on homeostasis as the basic mechanism underlying all kinds of physiological as well as cognitive functions has aroused renewed interest in cognitive science and related disciplines. Researchers have successfully incorporated some of Ashby’s technical results, such as ultrastability, into modern frameworks (e.g., CTRNN networks). Problem: The recovery of Ashby’s technical contributions has left in the background Ashby’s far more controversial non-technical views, according to which homeostatic adaptation to the environment governs all aspects of all forms (...) of life. This thesis entails that life is fundamentally “heteronomous” and it is conceptually at odds with the autopoiesis framework adopted by Ashby’s recent defenders as well as with the primacy of autonomy in human life that most of the Western philosophical tradition upholds. The paper argues that the use of computer simulations focused on the more conceptual aspects of Ashby’s thought may help us recover, extend and consequently assess an overall view of life as heteronomy. Method: The paper discusses some computer simulations of Ashby’s original electro-mechanical device (the homeostat) that implement his techniques (double-feedback loops and random parameter-switching). Results: First simulation results show that even though Ashby’s claims about homeostatic adaptivity need to be slightly weakened, his overall results are confirmed, thereby suggesting that an extension to virtual robots engaged in minimal cognitive tasks may be successful. Implications: The paper shows that a fuller incorporation of Ashby’s original results into recent cognitive science research may trigger a philosophical and technical reevaluation of the traditional distinction between heteronomous and autonomous behavior. Constructivist content: The research outlined in the paper supports an extended constructionist perspective in which agency as autonomy plays a more limited role. (shrink)

I have developed transcendental arguments to refute several versions of Nick Bostrom’s simulation hypothesis. I called some of these arguments the SIM-style argument. In this paper, I have four main aims. First, I employ the SIM-style argument to remedy a defect in Hilary Putnam’s Brain-in-vat argument. Second, I show that the most radical skepticism, which Tim Button called the nightmarish Cartesian skepticism, can be refuted by the SIM-style argument or by another transcendental argument I develop here. Third, I (...) compare my approach to radical skepticisms with Donald Davidson’s, as it is often regarded as an exemplar of transcendental arguments. Fourth, I explain how the prominent objections, mainly developed by Barry Stroud, to transcendental arguments can incur two undesirable results: psychologism and Kantian skepticism. (shrink)

There is much disagreement about how extensive a role theoretical mind-reading, behavior-reading, and simulation each have and need to have in our knowing and understanding other minds, and how each method is implemented in the brain, but less discussion of the epistemological question what it is about the products of these methods that makes them count as knowledge or understanding. This question has become especially salient recently as some have the intuition that mirror neurons can bring understanding of (...) another's action despite involving no higher-order processing, whereas most epistemologists writing about understanding think that it requires reflective access to one's grounds, which is closer to the intuitions of other commenters on mirror neurons. I offer a definition of what it is that makes something understanding that is compelling independently of the context of cognition of other minds, and use it to show two things: 1) that theoretical mind-reading and simulation bring understanding in virtue of the same epistemic feature, and 2) why the kind of motor representation without propositional attitudes that is done by mirror neurons is sufficient for action understanding. I further suggest that more attention should be paid to the potential disadvantages of a simulative method of knowing. Though it can be more efficient in some cases, it can also bring vulnerability, wear and tear on one's personal equipment, and unintended mimicry. (shrink)

Summary Embodied simulation, a basic functional mechanism of our brain, and its neural underpinnings are discussed and connected to intersubjectivity and the reception of human cultural artefacts, like visual arts and film. Embodied simulation provides a unified account of both non-verbal and verbal aspects of interpersonal relations that likely play an important role in shaping not only the self and his/her relation to others, but also shared cultural practices. Embodied simulation sheds new light on aesthetic experience (...) and is proposed as a key element for the dialogue between neuroscience and the humanities within the biocultural paradigm. (shrink)

I reply to some recent comments by Brian Weatherson on my 'simulation argument'. I clarify some interpretational matters, and address issues relating to epistemological externalism, the difference from traditional brain-in-a-vat arguments, and a challenge based on 'grue'-like predicates.

Recently, a number of neuroscientists and philosophers have taken the so-called predictive coding approach to support a form of radical neuro-representationalism, according to which the content of our conscious experiences is a neural construct, a brain-generated simulation. There is remarkable similarity between this account and ideas found in and developed by German neo-Kantians in the mid-nineteenth century. Some of the neo-Kantians eventually came to have doubts about the cogency and internal consistency of the representationalist framework they were operating (...) within. In this paper, I will first argue that some of these concerns ought to be taken seriously by contemporary proponents of predictive coding. After having done so, I will turn to phenomenology. As we shall see, Husserl’s endorsement of transcendental idealism was partially motivated by his rejection of representationalism and phenomenalism and by his attempt to safeguard the objectivity of the world of experience. This confronts us with an intriguing question. Which position is best able to accommodate our natural inclination for realism: Contemporary neuro-representationalism or Husserl’s transcendental idealism? (shrink)

The “Human Brain Project” (HBP) is a large-scale European neuroscience and information communication technology (ICT) project that has been a matter of heated controversy since its inception. With its aim to simulate the entire human brain with the help of supercomputing technologies, the HBP plans to fundamentally change neuroscientific research practice, medical diagnosis, and eventually the use of computers itself. Its controversial nature and its potential impacts render the HBP a subject of crucial importance for critical studies of (...) science and society. In this paper, we provide a critical exploratory analysis of the potential mid- to long-term impacts the HBP and its ICT infrastructure could be expected to have, provided its agenda will indeed be implemented and executed to a substantive degree. We analyse how the HBP aspires to change current neuroscientific practice, what impact its novel infrastructures could have on research culture, medical practice and the use of ICT, and how, given a certain degree of successful execution of the project’s aims, potential clinical and methodological applications could even transform society beyond scientific practice. Furthermore, we sketch the possibility that research such as that projected by the HBP may eventually transform our everyday world, even beyond the scope of the HBP’s explicit agenda, and beyond the isolated ‘application’ of some novel technological device. Finally, we point towards trajectories for further philosophical, historical and sociological research on the HBP that our exploratory analysis might help to inspire. Our analysis will yield important insights regardless of the actual success of the HBP. What we drive at, for the most part, is the broader dynamics of scientific and technological development of which the HBP agenda is merely one particularly striking exemplification. (shrink)

Simulation constraints cannot help in explaining afterlife beliefs in general because belief in an afterlife is a precondition for running a simulation. Instead, an explanation may be found by examining more deeply our common-sense dualistic conception of the mind or soul.

Embodied simulation and the epistemic motivation to search for the of other people's behaviors are not necessary for specific and functional responding to, and hence processing of, human facial expressions. Rather, facial expression processing can be achieved through lower-cognitive, heuristical perceptual processing and expression of prototypical morphological musculature movement patterns that communicate discrete trustworthiness and capacity cues to conspecifics.

In the past few years, behavioural, neuroimaging and neurophysiological studies have been suggesting that Embodied Simulation represents a constitutive feature of language understanding. However, this claim is still controversial, as is the definition of Embodied Simulation. In this paper, I aim at providing a more suitable definition of Embodied Simulation. I will then apply this definition to the study of bodily metaphors. Embodied Simulation gets us attuned with our social world and it provides us with both (...) a brain and bodily disposition, which is the starting point of many cognitive processes. Exploitation of the mechanism of simulation is particularly evident in the linguistic phenomenon of metaphors. Bodily metaphors are often so successful because they exploit this mechanism of brain and bodily attunement, enacted by means of Embodied Simulation. The role of Embodied Simulation and its importance for metaphor comprehension can be explained in two points: (1) Embodied Simulation allows speakers to share a bodily attitude during communicative exchanges; (2) by means of Embodied Simulation speakers directly experience the source domain during metaphorical mapping. (shrink)

Language comprehension of action verbs recruits embodied representations in the brain that are assumed to invoke a mental simulation. This extends to abstract concepts, as well. We, therefore, argue that mental simulation works across levels of abstractness and involves higher-level schematic structures that subsume a generic structure of actions and events.

Various theorists contend that we may live in a computer simulation. David Chalmers in turn argues that the simulation hypothesis is a metaphysical hypothesis about the nature of our reality, rather than a sceptical scenario. We use recent work on consciousness to motivate new doubts about both sets of arguments. First, we argue that if either panpsychism or panqualityism is true, then the only way to live in a simulation may be as brains-in-vats, in which case it (...) is unlikely that we live in a simulation. We then argue that if panpsychism or panqualityism is true, then viable simulation hypotheses are substantially sceptical scenarios. We conclude that the nature of consciousness has wide-ranging implications for simulation arguments. (shrink)

Although many simulations draw upon only one level of abstraction, the process for generating rich simulations requires a dynamic interplay between abstract and concrete knowledge. A complete model of simulation must account for a mind and brain that can bridge the perceptual with the conceptual, the episodic with the semantic, and the concrete with the abstract.

Niedenthal et al. present a model for embodied emotion simulation and expression understanding that spans multiple brain systems. This commentary addresses the potential role of time in this model, and its implications for understanding social dysfunction.

Simulation – imagining future events – plays a role in decision-making. In Conviction Narrative Theory, people's emotional responses to their simulations inform their choices. Yet imagining one possible future also increases its plausibility and accessibility relative to other futures. We propose that the act of simulation, in addition to affective evaluation, drives people to choose in accordance with their simulations.

Understanding the role of simulation in conceptualization has become a priority for cognitive science. Barsalou makes a valuable contribution in that direction. The present commentary points to theoretical issues that need to be refined and elaborated in order to account for key aspects of meaning construction, such as negation, counterfactuals, quantification or analogy. Backstage cognition, with its elaborate bindings, blendings, and mappings, is more complex than Barsalou's discussion might suggest. Language does not directly carry meaning, but rather serves, along (...) with countless other situational elements, as a powerful instrument for prompting its construction. (shrink)

Barsalou's interesting model might benefit from defining simulation and clarifying the implications of prior critiques for simulations (and not just for perceptual symbols). Contrary to claims, simulators (or frames) appear, in the limit, to be amodal. In addition, the account of abstract terms seems extremely limited.

The teleological language in the target article is ill-advised, as it obscures the question of whether ecological and cultural inheritances are directed or random. Laland et al. present a very broad palette of explanatory possibilities; evolutionary simulation models could help narrow down the processes important in a particular case. Examples of such models are offered in the areas of language change and the Baldwin effect.

A slight modification of Webb's diagrammatic representation of the dimensions for describing models is proposed which extends it to cover a range of theoretical models as well as material models. It is also argued that beyond a certain level robotic simulations could offer a number of real advantages over computer simulations of organisms interacting with their environment.

Computational neuroscientists not only employ computer models and simulations in studying brain functions. They also view the modeled nervous system itself as computing. What does it mean to say that the brain computes? And what is the utility of the ‘brain-as-computer’ assumption in studying brain functions? In previous work, I have argued that a structural conception of computation is not adequate to address these questions. Here I outline an alternative conception of computation, which I call the (...) analog-model. The term ‘analog-model’ does not mean continuous, non-discrete or non-digital. It means that the functional performance of the system simulates mathematical relations in some other system, between what is being represented. The brain-as-computer view is invoked to demonstrate that the internal cellular activity is appropriate for the pertinent information-processing task.Keywords: Computation; Computational neuroscience; Analog computers; Representation; Simulation. (shrink)

The authors explain our attraction to strange, literary places as resulting from our attraction to strange places in real life. I believe this is correct and important. The aim of the following commentary is to show that their main conclusion is closely related to – even (retrospectively) predictable from – the operation of simulation and the consequences of that operation for storytelling.