Describes the various senses as sensory systems that are attuned to the environment. Develops the notion of rich sensory information that specifies the distal environment. Includes a discussion of affordances.

Gathering information from both published and unpublished material and interviews with Gibson's family, colleagues, and friends, Reed (philosophy, Drexel U.) chronicles Gibson's life and intellectual development and his attempts to synthesize several contrasting intellectual traditions into what he ultimately called an "ecological approach" to psychology. Annotation(c) 2003 Book News, Inc., Portland, OR (booknews.com).

_Behavioral and Brain Sciences_ , 15, 183-247, 1992. Reprinted in _The Philosopher's Annual_ , Grim, Mar and Williams, eds., vol. XV-1992, 1994, pp. 23-68; Noel Sheehy and Tony Chapman, eds., _Cognitive Science_ , Vol. I, Elgar, 1995, pp.210-274.

This paper presents a general computational treatment of how mammals are able to deal with visual objects and environments. The model tries to cover the entire range from behavior and phenomenological experience to detailed neural encodings in crude but computationally plausible reductive steps. The problems addressed include perceptual constancies, eye movements and the stable visual world, object descriptions, perceptual generalizations, and the representation of extrapersonal space.The entire development is based on an action-oriented notion of perception. The observer is assumed to (...) be continuously sampling the ambient light for information of current value. The central problem of vision is taken to be categorizing and locating objects in the environment. The critical step in this process is the linking of visual information to symbolic object descriptions; this is calledindexing, from the analogy of identifying a book from index terms. The system must also identifysituationsand use this knowledge to guide movement and other actions in the environment. The treatment focuses on the different representations of information used in the visual system.The four representational frames capture information in the following forms: retinotopic, head-based, symbolic, and allocentric. The functional roles of the four frames, the communication among them, and their suggested neurophysiological realization constitute the core of the paper. The model is perforce crude, but appears to be consistent with all relevant findings. (shrink)

The posterior parietal cortex (PPC) is the most likely site where egocentric spatial relationships are represented in the brain. PPC cells receive visual, auditory, somaesthetic, and vestibular sensory inputs; oculomotor, head, limb, and body motor signals; and strong motivational projections from the limbic system. Their discharge increases not only when an animal moves towards a sensory target, but also when it directs its attention to it. PPC lesions have the opposite effect: sensory inattention and neglect. The PPC does not seem (...) to contain a “map” of the location of objects in space but a distributed neural network for transforming one set of sensory vectors into other sensory reference frames or into various motor coordinate systems. Which set of transformation rules is used probably depends on attention, which selectively enhances the synapses needed for making a particular sensory comparison or aiming a particular movement. (shrink)

Purely parallel neural networks can model object recognition in brief displays – the same conditions under which illusory conjunctions have been demonstrated empirically. Correcting errors of illusory conjunction is the “tag-assignment” problem for a purely parallel processor: the problem of assigning a spatial tag to nonspatial features, feature combinations, and objects. This problem must be solved to model human object recognition over a longer time scale. Our model simulates both the parallel processes that may underlie illusory conjunctions and the serial (...) processes that may solve the tag-assignment problem in normal perception. One component of the model extracts pooled features and another provides attentional tags that correct illusory conjunctions. Our approach addresses two questions: How can objects be identified from simultaneously attended features in a parallel, distributed representation? How can the spatial selectional requirements of such an attentional process be met by a separation of pathways for spatial and nonspatial processing? Our analysis of these questions yields a neurally plausible simulation of tag assignment based on synchronizing feature processing activity in a spatial focus of attention. (shrink)

Damasio remarks, it "informs virtually all research on mind and brain, explicitly or implicitly." Indeed, serial information processing models generally run this risk (Kinsbourne, 1985). The commentaries provide a wealth of confirming instances of the seductive power of this idea. Our sternest critics Block, Farah, Libet, and Treisman) adopt fairly standard Cartesian positions; more interesting are those commentators who take themselves to be mainly in agreement with us, but who express reservations or offer support with arguments that betray a continuing (...) allegiance to one or another tenet of the view we sought to discredit. (shrink)

This monograph explains in terms of specified neuronal brain mechanisms and systems, how the human brain does its cognitive work. It elucidates functions such as declarative and episodic learning, imagery, spatial representation, object recognition, semantic processing, narrative comprehension, planning, and motivation. Neurophysiological, psychological, and clinical findings are presented in support of the theoretical model, and a variety of computer simulation tests demonstrate its competence. -/- .

"Theorizing about brain functions is often considered slightly disreputable and anyhow a waste of time -perhaps even 'philoso- ical'" 1 P. S. CHURCHLAND At present there are no unanimously accepted general con cepts of brain operation and function. This is especially the case with regard to so-called "higher" functions such as per ception, memory or the coupling between sensory input and motor output. There are a number of different reasons for this. Some may be related to experimental limitations allowing the (...) simultaneous recording of the activities of only a restricted number of neurones. But there are also conceptual difficulties hindering the transition from "single-neurone" schemes, in which neurones are assigned relatively specific tasks (such as feature detection), to more complex schemes of nerve cell as semblies (for a discussion of some of the difficulties see Abeles 1982; von der Malsburg 1981; Kriiger 1983). Whilst much is known about the basic properties and functions of single neu rones, whose operations we hope to understand in the foresee able future, this does not hold true in the same way for the working of large assemblies of neurones. (shrink)