Online research in philosophy

Almost all computational models of the mind and brain ignore details about neurotransmitters, hormones, and other molecules. The neglect of neurochemistry in cognitive science would be appropriate if the computational properties of brains relevant to explaining mental functioning were in fact electrical rather than chemical. But there is considerable evidence that chemical complexity really does matter to brain computation, including the role of proteins in intracellular computation, the operations of synapses and neurotransmitters, and the effects of neuromodulators such as hormones. Neurochemical computation has implications for understanding emotions, cognition, and artificial intelligence.

Neuroanatomy and neurophysiology are insufficient to specify function. Modeling is essential to elucidate function, but psychophysics is also required. An example is the cognitive and sensorimotor branches of the visual system: anatomy shows direct cross talk between the branches. Psychophysics in normal humans shows links from cognitive to sensorimotor, but the reverse link is excluded by visual illusions affecting the cognitive system but not the sensorimotor system.

What is computational cognitive modeling? What exactly can it contribute to cognitive science? What has it contributed thus far? Where is it going? Answering such questions may sound overly defensive to the insiders of computational cognitive modeling, and may even seem so to some other cognitive scientists, but they are very much needed in a volume like this—because they lie at the very foundation of this field. Many insiders and outsiders alike would like to take a balanced and rational look at these questions, without indulging in excessive cheer-leading, which, as one would expect, happens sometimes amongst computational modeling enthusiasts.

A neurophilosopher?s take on the self, free will, human understanding, and the experience of God, from the perspective of the brain.

Evolutionary thinking has expanded in the last decades, spreading from its traditional stronghold - the explanation of speciation and adaptation in Biology - to new domains including the human sciences. The essays in this collection attest to the illuminating power of evolutionary thinking when applied to the understanding of the human mind. The contributors to Cognition, Evolution and Rationality use an evolutionary standpoint to approach the nature of the human mind, including both cognitive and behavioral functions. Cognitive science is by its nature an interdisciplinary subject and the essays use a variety of disciplines including the Philosophy of Science, the Philosophy of Mind, Game Theory, Robotics and Computational Neuroanatomy to investigate the workings of the mind. The topics covered by the essays range from general methodological issues to long-standing philosophical problems such as how rational human beings actually are. This book will be of interest across a number of fields, including philosophy, evolutionary theory and cognitive science.

After reading this paper, Richard Rorty sent the following comment: Doubtless in some sense I am doing "epistemology" and for all I know the name will survive as that of something which has little to do with Kant. But I am not convinced that philosophers are making themselves as useful to cognitive science as they claim, or that cognitive science is more than an awkward place-holder for neurology. My hunch is that when neurology comes into its own, notions like "cognition" will dry up and blow away. (See Michael Williams UNNATURAL DOUBTS for a good argument that 'knowledge' or 'cogntion' is not profitably thought of as a natural kind.).

The past three decades have witnessed a remarkable growth of research interest in the mind. This trend has been acclaimed as the ‘cognitive revolution’ in psychology. At the heart of this revolution lies the claim that the mind is a computational system. The purpose of this paper is both to elucidate this claim and to evaluate its implications for cognitive psychology. The nature and scope of cognitive psychology and cognitive science are outlined, the principal assumptions underlying the information processing approach to cognition are summarised and the nature of artificial intelligence and its relationship to cognitive science are explored. The ‘computational metaphor’ of mind is examined and both the theoretical and methodological issues which it raises for cognitive psychology are considered. Finally, the nature and significance of ‘connectionism’—the latest paradigm in cognitive science—are briefly reviewed.

Arbib et al. describe mathematical and computational models in neuroscience as well as neuroanatomy and neurophysiology of several important brain structures. This is a useful guide to mathematical and computational modelling of the structure and function of nervous system. The book highlights the need to develop a theory of brain functioning, and it offers some useful approaches and concepts.