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)

A model of the neuropsychology of anxiety is proposed. The model is based in the first instance upon an analysis of the behavioural effects of the antianxiety drugs in animals. From such psychopharmacologi-cal experiments the concept of a “behavioural inhibition system” has been developed. This system responds to novel stimuli or to those associated with punishment or nonreward by inhibiting ongoing behaviour and increasing arousal and attention to the environment. It is activity in the BIS that constitutes anxiety and that (...) is reduced by antianxiety drugs. The effects of the antianxiety drugs in the brain also suggest hypotheses concerning the neural substrate of anxiety. Although the benzodiazepines and barbiturates facilitate the effects of γ-aminobutyrate, this is insufficient to explain their highly specific behavioural effects. Because of similarities between the behavioural effects of certain lesions and those of the antianxiety drugs, it is proposed that these drugs reduce anxiety by impairing the functioning of a widespread neural system including the septo-hippocampal system, the Papez circuit, the prefrontal cortex, and ascending monoaminergic and cholinergic pathways which innervate these forebrain structures. Analysis of the functions of this system suggests that it acts as a comparator: it compares predicted to actual sensory events and activates the outputs of the BIS when there is a mismatch or when the predicted event is aversive. Suggestions are made as to the functions of particular pathways within this overall brain system. The resulting theory is applied to the symptoms and treatment of anxiety in man, its relations to depression, and the personality of individuals who are susceptible to anxiety or depression. (shrink)

The appropriate methodology for psychological research depends on whether one is studying mental algorithms or their implementation. Mental algorithms are abstract specifications of the steps taken by procedures that run in the mind. Implementational issues concern the speed and reliability of these procedures. The algorithmic level can be explored only by studying across-task variation. This contrasts with psychology's dominant methodology of looking for within-task generalities, which is appropriate only for studying implementational issues.The implementation-algorithm distinction is related to a number of (...) other “levels” considered in cognitive science. Its realization in Anderson's ACT theory of cognition is discussed. Research at the algorithmic level is more promising because it is hard to make further fundamental scientific progress at the implementational level with the methodologies available. Protocol data, which are appropriate only for algorithm-level theories, provide a richer source than data at the implementational level. Research at the algorithmic level will also yield more insight into fundamental properties of human knowledge because it is the level at which significant learning transitions are defined.The best way to study the algorithmic level is to look for differential learning outcomes in pedagogical experiments that manipulate instructional experience. This provides control and prediction in realistically complex learning situations. The intelligent tutoring paradigm provides a particularly fruitful way to implement such experiments.The implications of this analysis for the issue of modularity of mind, the status of language, research on human/computer interaction, and connectionist models are also examined. (shrink)

It is traditionally believed that cerebral activation (the presence of low voltage fast electrical activity in the neocortex and rhythmical slow activity in the hippocampus) is correlated with arousal, while deactivation (the presence of large amplitude irregular slow waves or spindles in both the neocortex and the hippocampus) is correlated with sleep or coma. However, since there are many exceptions, these generalizations have only limited validity. Activated patterns occur in normal sleep (active or paradoxical sleep) and during states of anesthesia (...) and coma. Deactivated patterns occur, at times, during normal waking, or during behavior in awake animals treated with atropinic drugs. Also, the fact that patterns characteristic of sleep, arousal, and waking behavior continue in decorticate animals indicates that reticulo-cortical mechanisms are not essential for these aspects of behavior. (shrink)