Abstract“Sign stimuli” elicit specific patterns of behavior when an organism's motivation is appropriate. In the toad, visually released prey-catching involves orienting toward the prey, approaching, fixating, and snapping. For these action patterns to be selected and released, the prey must be recognized and localized in space. Toads discriminate prey from nonprey by certain spatiotemporal stimulus features. The stimulus-response relations are mediated by innate releasing mechanisms (RMs) with recognition properties partly modifiable by experience. Striato-pretecto-tectal connectivity determines the RM's recognition and localization (...) properties, whereas medialpallio-thalamo-tectal circuitry makes the system sensitive to changes in internal state and to prior history of exposure to stimuli. RMs encode the diverse stimulus conditions referring to the same prey object through different combinations of “specialized” tectal neurons, involving cells selectively tuned to prey features. The prey-selective neurons express the outcome of information processing in functional units consisting of interconnected cells. Excitatory and inhibitory interactions among feature-sensitive tectal and pretectal neurons specify the perceptual operations involved in distinguishing the prey from its background, selecting its features, and discriminating it from predators. Other connections indicate stimulus location. The results of these analyses are transmitted by specialized neurons projecting from the tectum to bulbar/spinal motor systems, providing a sensorimotor interface. Specific combinations of such projective neurons – mediating feature- and space-related messages – form “command releasing systems” that activate corresponding motor pattern generators for appropriate prey-catching action patterns. (shrink)

Neuroethology is a branch of biology that studies the neural basis of naturally occurring animal behavior. This science, particularly a recent program called computational neuroethology, has a similar structure to the interdisciplinary endeavor of cognitive science. I argue that it would be fruitful to conceive of cognitive science as the computational neuroethology of humans. However, there are important differences between the two sciences, including the fact that neuroethology is much more comparative in its perspective. Neuroethology (...) is a biological science and as such, evolution is a central notion. Its target organisms are studied in the context of their evolutionary history. The central goal of this paper is to argue that cognitive science can and ought to be more comparative in its approach to cognitive phenomena in humans. I show how the domain of cognitive phenomena can be divided up into four different classes, individuated by the relative phylogenetic uniqueness of the behavior. I then describe how comparative evidence can enrich our understanding in each of these different arenas. (shrink)

Computation and philosophy intersect three times in this essay. Computation is considered as an object, as a method, and as a model used in a certain line of philosophical inquiry concerning the relation of mind to matter. As object, the question considered is whether computation and related notions of mental representation constitute the best ways to conceive of how physical systems give rise to mental properties. As method and model, the computational techniques of artificial life and embodied evolutionary connectionism are (...) used to conduct prosthetically enhanced thought experiments concerning the evolvability of mental representations. Central to this essay is a discussion of the computer simulation and evolution of three-dimensional synthetic animals with neural network controllers. The minimally cognitive behavior of finding food by exhibit- ing positive chemotaxis is simulated with swimming and walking creatures. These simulations form the basis of a discussion of the evolutionary and neurocomputa- tional bases of the incremental emergence of more complex forms of cognition. Other related work has been used to attack computational and representational theories of cognition. In contrast, I argue that the proper understanding of the evolutionary emergence of minimally cognitive behaviors is computational and representational through and through. (shrink)

Computation and philosophy intersect three times in this essay. Computation is considered as an object, as a method, and as a model used in a certain line of philosophical inquiry concerning the relation of mind to matter. As object, the question considered is whether computation and related notions of mental representation constitute the best ways to conceive of how physical systems give rise to mental properties. As method and model, the computational techniques of artificial life and embodied evolutionary connectionism are (...) used to conduct prosthetically enhanced thought experiments concerning the evolvability of mental representations. Central to this essay is a discussion of the computer simulation and evolution of three‐dimensional synthetic animals with neural network controllers. The minimally cognitive behavior of finding food by exhibiting positive chemotaxis is simulated with swimming and walking creatures. These simulations form the basis of a discussion of the evolutionary and neurocomputational bases of the incremental emergence of more complex forms of cognition. Other related work has been used to attack computational and representational theories of cognition. In contrast, I argue that the proper understanding of the evolutionary emergence of minimally cognitive behaviors is computational and representational through and through. (shrink)

Recent accounts of multiscale modeling investigate ontic and epistemic constraints imposed by relations between component models at varying relative scales (macro, meso, micro). These accounts often focus especially on the role of the meso, or intermediate, relative scale in a multiscale model. We aid this effort by highlighting a novel role for mesoscale models: they can function as a focal point, and rationale, for disagreement between researchers who otherwise share theoretical commitments. We illustrate with a case study in multiscale modeling (...) of insect behavior, arguing that the cognitive map debate in neuroethology research is best understood as a mesoscale disagreement. (shrink)

In neuroethology, the nervous system and behavior are analyzed in the context of the animal's natural habitat and evolutionary history. For the last 30 years the influence of genetics on neuroethology has steadily grown, particularly in Drosophila. Genetic variants reveal new properties of neurons; they help to dissect neuronal circuits and complex behavioral systems; genetics provides new methods to visualize certain brain structures and to assign behavioral functions to them; and, finally, genetic variants can be used to test (...) ecological models. While single‐gene mutations can have highly specific behavioral effects, molecular analysis of the corresponding genes reveals that the latter normally have a much broader functional scope. The ‘graininess’ of a functional model of the brain, therefore, is defined by the independent regulatory units of the genes rather than by the genes themselves. (shrink)

Berichte zur Wissenschaftsgeschichte, EarlyView.

Are attributions of content and function determinate, or is there no fact of the matter to be fixed? Daniel Dennett has argued in favor of indeterminacy and concludes that, in practice, content and function cannot be fixed. The discovery of an electrical modality in vertebrates offers one concrete instance where attributions of function and content are supported by a strong scientific consensus. A century ago, electroreception was unimagined, whereas today it is widely believed that many species of bony fish, amphibians, (...) sharks, skates, and rays possess this non-human sensory modality. A look at the history of science related to this discovery reveals a highly interdisciplinary endeavor, encompassing ethology, behavioral analysis, neuroscience, and evolutionary biology. While each area provides important evidence, none is sufficient on its own to fix content and function. Instead, I argue that an interdisciplinary, neuroethological approach is required to carry out such determinations. Further, a detailed consideration of biological research suggests that while content and function claims are empirically underdetermined and uncertain, there is insufficient reason to believe in an additional problem of indeterminism. In particular, Dennett's indeterminism arises from a research methodology -- logical adaptationism -- that generates evidence from only one of the areas of neuroethology. However, logical adaptationism does not reflect adaptationism as it is practiced in contemporary biology. I conclude that Dennett is faced with a dilemma: On the one hand, he can hold to logical adaptationism and the indeterminism that results from it, while giving up the relevance of his arguments to biological practice. On the other, he can embrace a more accurate version of adaptationism -- one which plays a role in a larger neuroethological framework -- but from which no strong indeterminacy claims follow. (shrink)

Neuroethological investigations of mammalian and avian auditory systems have documented species-specific specializations for processing complex acoustic signals that could, if viewed in abstract terms, have an intriguing and striking relevance for human speech sound categorization and representation. Each species forms biologically relevant categories based on combinatorial analysis of information-bearing parameters within the complex input signal. This target article uses known neural models from the mustached bat and barn owl to develop, by analogy, a conceptualization of human processing of consonant plus (...) vowel sequences that offers a partial solution to the noninvariance dilemma the locus equations orderly output constraint”) is hypothesized based on the notion of an evolutionarily conserved auditory-processing strategy. High correlation and linearity between critical parameters in the speech signal that help to cue place of articulation categories might have evolved to satisfy a preadaptation by mammalian auditory systems for representing tightly correlated, linearly related components of acoustic signals. (shrink)

How should biological behaviour be modelled? A relatively new approach is to investigate problems in neuroethology by building physical robot models of biological sensorimotor systems. The explication and justification of this approach are here placed within a framework for describing and comparing models in the behavioural and biological sciences. First, simulation models – the representation of a hypothesis about a target system – are distinguished from several other relationships also termed “modelling” in discussions of scientific explanation. Seven dimensions on (...) which simulation models can differ are defined and distinctions between them discussed: 1. Relevance: whether the model tests and generates hypotheses applicable to biology. 2. Level: the elemental units of the model in the hierarchy from atoms to societies. 3. Generality: the range of biological systems the model can represent. 4. Abstraction: the complexity, relative to the target, or amount of detail included in the model. 5. Structural accuracy: how well the model represents the actual mechanisms underlying the behaviour. 6. Performance match: to what extent the model behaviour matches the target behaviour. 7. Medium: the physical basis by which the model is implemented. No specific position in the space of models thus defined is the only correct one, but a good modelling methodology should be explicit about its position and the justification for that position. It is argued that in building robot models biological relevance is more effective than loose biological inspiration; multiple levels can be integrated; that generality cannot be assumed but might emerge from studying specific instances; abstraction is better done by simplification than idealisation; accuracy can be approached through iterations of complete systems; that the model should be able to match and predict target behaviour; and that a physical medium can have significant advantages. These arguments reflect the view that biological behaviour needs to be studied and modelled in context, that is, in terms of the real problems faced by real animals in real environments. Key Words: animal behaviour; levels; models; neuroethology; realism; robotics; simulation. (shrink)

I propose a cautionary assessment of the recent debate concerning the impact of the dynamical approach on philosophical accounts of scientific explanation in the cognitive sciences and, particularly, the cognitive neurosciences. I criticize the dominant mechanistic philosophy of explanation, pointing out a number of its negative consequences: In particular, that it doesn’t do justice to the field’s diversity and stage of development, and that it fosters misguided interpretations of dynamical models’ contribution. In order to support these arguments, I analyze a (...) case study in computational neuroethology and show why it should not be understood through a mechanistic lens; I specially focus on Zednik’s mechanistic interpretation of the case study. In addition, I argue for a greater appreciation of the relation between explanation and other epistemic goals in the field, as well as an increased sensitivity towards the associated contextual factors. (shrink)

Prey-catching behavior (PCB) in frogs and toads has been the focus of intense neuroethological research from the mid-twentieth century to the present and epitomizes some major themes in science and philosophy during this period. It reflects the movement from simple reflexology to more complex views of instinctive behavior, but it also displays a neural reductionism that denies subjectivity and individual agency The present article engages contemporary PCB research but provides a philosophically more promising picture of it based on Whitehead's nonreductionist (...) "philosophy of organism," which proposes that the flow of events from stimulus to response in organisms of all kinds is mediated by "the intervening touch of mentality " This approach resolves some basic mind-body and mind-nature issues that have long bedeviled modern philosophy and presents an image of a postmodern frog for a constructively postmodern science. (shrink)

How questions and why questions interact in complex ways within biological practice. One of the most fruitful accounts to think about this relation is the widely known systemic approach, which has its origin mainly in the works of Robert Cummins (1975, 1983). As we will show, this approach effectively manages to capture much of what biologists do, especially in areas such as molecular biology, neuroscience and neuroethology. Our aim with this work is to discuss the metatheoretical status of the (...) presuppositions behind systemic analysis. We will hold that these assumptions are of an empirical nature, and that they can be reconstructed as parts of a theory. (shrink)

Keeley has recently argued that the philosophical issue of how to analyse the concept of a sense can usefully be addressed by considering how scientists, and more specifically neuroethologists, classify the senses. After briefly outlining his proposal, which is based on the application of an ordered set of individually necessary and jointly sufficient conditions for modality differentiation, I argue, by way of two complementary counterexamples, that it fails to account fully for the way the senses are in fact individuated in (...) neuroethology and other relevant sciences. (shrink)

Few areas of scientific investigation have spawned more alternative approaches than animal behavior: comparative psychology, ethology, behavioral ecology, sociobiology, behavioral endocrinology, behavioral neuroscience, neuroethology, behavioral genetics, cognitive ethology, developmental psychobiology---the list goes on. Add in the behavioral sciences focused on the human animal, and you can continue the list with ethnography, biological anthropology, political science, sociology, psychology (cognitive, social, developmental, evolutionary, etc.), and even that dismal science, economics. Clearly, no reasonable-length chapter can do justice to such a varied collection. (...) We have opted therefore to focus on three of these subdisciplines and to provide a somewhat historical tour of them, mentioning along the way the philosophical points that are of particular interest to us, but allowing the development of these points to be limited only by the imaginations of our readers. For readers seeking a more-traditional historical survey, see Dewsbury (1984a, b) and Burghardt (1985a). Our chosen brief is to write about comparative psychology, ethology, and cognitive ethology, although other approaches, especially neuroscience, will be mentioned where appropriate. These sciences are philosophically significant because they are enmeshed in ancient philosophical questions about the nature of mind and purposeful action and about the differences between humans and other animals. These sciences are also clustered because of their attention to mechanistic explanations of individual animal behavior as opposed to attempting to capture regularities at a population level, such as the game-theoretic strategic models popular among behavioral ecologists. (shrink)

Intermediate constructs are required as bridges between complex behaviors and realistic models of neural circuitry. For cognitive scientists in general, schemas are the appropriate functional units; brain theorists can work with neural layers as units intermediate between structures subserving schemas and small neural circuits.After an account of different levels of analysis, we describe visuomotor coordination in terms of perceptual schemas and motor schemas. The interest of schemas to cognitive science in general is illustrated with the example of perceptual schemas in (...) high-level vision and motor schemas in the control of dextrous hands.Rana computatrix, the computational frog, is introduced to show how one constructs an evolving set of model families to mediate flexible cooperation between theory and experiment. Rana computatrix may be able to do for the study of the organizational principles of neural circuitry what Aplysia has done for the study of subcellular mechanisms of learning. Approach, avoidance, and detour behavior in frogs and toads are analyzed in terms of interacting schemas. Facilitation and prey recognition are implemented as tectal-pretectal interactions, with the tectum modeled by an array of tectal columns. We show how layered neural computation enters into models of stereopsis and how depth schemas may involve the interaction of accommodation and binocular cues in anurans. (shrink)