The Perception Of Causality

Originally published in 1963, this is a classic work on the psychology of perception. By means of suitable patterns on a partly concealed rotating disc Michotte was able to give the impression of objects in movement; and where certain conditions of speed, position, and time-interval were satisfied, his subjects received the impression of a causal interaction between two objects – for example, the impression that one object has ‘bumped into’ another (the ‘Launching Effect’) or is carrying it along (the ‘Entraining Effect’). In a further group of experiments Michotte studies the conditions in which moving objects look as though they are alive. A large number of experiments are described, and on the basis of them Michotte formulates a theory as to the conditions in which causal impressions occur. He also compares his own views on causality with those of Hume, Maine de Biran, and Piaget.

In this investigation of the psychological relationship between shape and time, Leyton argues compellingly that shape is used by the mind to recover the past and as such it forms a basis for memory. Michael Leyton's arguments about the nature of perception and cognition are fascinating, exciting, and sure to be controversial. In this investigation of the psychological relationship between shape and time, Leyton argues compellingly that shape is used by the mind to recover the past and as such it forms a basis for memory. He elaborates a system of rules by which the conversion to memory takes place and presents a number of detailed case studies--in perception, linguistics, art, and even political subjugation--that support these rules. Leyton observes that the mind assigns to any shape a causal history explaining how the shape was formed. We cannot help but perceive a deformed can as a dented can. Moreover, by reducing the study of shape to the study of symmetry, he shows that symmetry is crucial to our everyday cognitive processing. Symmetry is the means by which shape is converted into memory. Perception is usually regarded as the recovery of the spatial layout of the environment. Leyton, however, shows that perception is fundamentally the extraction of time from shape. In doing so, he is able to reduce the several areas of computational vision purely to symmetry principles. Examining grammar in linguistics, he argues that a sentence is psychologically represented as a piece of causal history, an archeological relic disinterred by the listener so that the sentence reveals the past. Again through a detailed analysis of art he shows that what the viewer takes to be the experience of a painting is in fact the extraction of time from the shapes of the painting. Finally he highlights crucial aspects of the mind's attempt to recover time in examples of political subjugation.

Which causal patterns are involved in mental processes?On what mechanisms does the self-organisation of cognitive structure rest? Can a naturalistic view account for the basic resources of intentionality, while avoiding the objections to reductive materialism? By considering the developmental, phenomenological and biological aspects linking mind and causality, this volume offers a state-of-the art theoretical proposal emphasising the fine-tuning of cognition with the complexity of bodily dynamics.In contrast to the de-coupling of mind from the physical environment in classical information-processing models, growth of brain’s architecture and stabilisation of perception­–action cycles are considered decisive, with no need for an eliminative approach to representations pursued by neural network models. The tools provided by physics and biology for the description of massive causal interactions, on top of which ‘qualitative’ changes occur, are exploited to suggest a model of the mind as a many-layered, co-evolving system. (Series A)

Causal reasoning is one of our most central cognitive competencies, enabling us to adapt to our world. Causal knowledge allows us to predict future events, or diagnose the causes of observed facts. We plan actions and solve problems using knowledge about cause-effect relations. Without our ability to discover and empirically test causal theories, we would not have made progress in various empirical sciences. The handbook brings together the leading researchers in the field of causal reasoning and offers state-of-the-art presentations of theories and research. It provides introductions of competing theories of causal reasoning, and discusses its role in various cognitive functions and domains. The final section presents research from neighboring fields.

Leading philosophers and psychologists offer a rigorous assessment of the commonsense view that perceptual experience is an immediate awareness of mind-independent objects. They examine the nature of perception, its role in the acquisition of knowledge, the role of causation in perception, and how perceptual understanding develops in humans.

"This book brings together a collection of studies from international researchers who demonstrate the brain's remarkable capacity to adapt its representation of the visual world in response to changes in its environment."--BOOK JACKET.

This book is concerned with sensory cue integration both within and between sensory modalities, and focuses on the emerging way of thinking about cue combination in terms of uncertainty. These probabilistic approaches derive from the realization that our sensors are noisy and moreover are often affected by ambiguity. For example, mechanoreceptor outputs are variable and they cannot distinguish if a perceived force is caused by the weight of an object or by force we are producing ourselves. The probabilistic approaches elaborated in this book aim at formalizing the uncertainty of cues. They describe cue combination as the nervous system's attempt to minimize uncertainty in its estimates and to choose successful actions. Some computational approaches described in the chapters of this book are concerned with the application of such statistical ideas to real-world cue-combination problems. Others ask how uncertainty may be represented in the nervous system and used for cue combination. Importantly, across behavioral, electrophysiological and theoretical approaches, Bayesian statistics is emerging as a common language in which cue-combination problems can be expressed.