Understanding Consciousness: Its Function and Brain Processes


Gerd Sommerhoff

  • Citations
  • Add to My List
  • Text Size

  • Chapters
  • Front Matter
  • Back Matter
  • Subject Index
  • Part I: Consciousness Explained in Simple, Functional Terms

    Part II: The Fabric of the Underlying Brain Processes

  • Copyright

    View Copyright Page


    Of the many who have offered me their opinions, I am especially indebted to the following for their stimulating discussions or their comments on drafted sections of this manuscript: Roger Carpenter, Rodney Cotterill, Thomas Forster, Geoff Kendall, Klaus Kieslinger, Ray Paton, Nils Schweckendiek, Ed Scofield, Gysbert Stoet and Chris Town. Special thanks are also due to Nigel Harris for his valuable advice in the development of my IT and computer facilities.

    For permission to reproduce copyright material I am indebted to the MIT Press (Figure 2.3), Blackwell Scientific Publications (Figure 2.4), John Wiley & Sons (Figure 4.1), and World Scientific Publishing (Figure 9.3). Also to the Cambridge University Press for the passage quoted from Blakemore (1977) in Chapter 6, to Vintage for that quoted from Rosenfield (1992) in the same chapter, and to Ulric Neisser for that quoted from Neisser (1976) in Chapter 8.

    Preface: Problems of Substance and of Presentation

    The problem of consciousness, of what it is, what it does, why it evolved, and how it arises in the brain, has been described as the least understood of all the fundamental problems still facing the life sciences. The philosopher Daniel Dennett has called it ‘just about the last remaining mystery and the one about which we are still in a terrible muddle’ (Dennett, 1991, p. 22). It is a serious issue, not only because the relation between mind and brain can never be fully understood until the nature of consciousness is understood, but also because of the large number of academic disciplines that are directly or indirectly affected by our perceptions of the nature of consciousness.

    In the many multidisciplinary conferences and new publications on consciousness that have occurred since Dennett's words were written, new technologies have produced a wealth of new empirical data, but at the theoretical level one still meets almost as many different views about consciousness as there are contributors to the discussion. There is not even the beginning in sight of a consensus about what kind of property we are actually here talking about, or where this property is to be found. According to some views, only humans have consciousness, while at the opposite extreme one even meets the belief that any system interacting with the environment has consciousness, e.g. a thermostat but not a thermometer. Again, while some authors regard consciousness as an essential product of neural activities, in the eyes of others it is no more than an inessential by-product of such activities and a mere spectator in the brain. A few regard the problem as insoluble and textbooks on cognitive science tend to play safe by not mentioning the topic at all. It is indeed a terrible muddle.

    There is no way out of this muddle except by way of definite decisions, foremost a decision about what shall be understood by consciousness in the context of a scientific investigation. And these decisions must offer rewards and conceptual clarifications that can persuade others to go along with them. In this book I propose and follow up three main steps and hope to convince the reader of their rewards. The first step concerns the meaning of the word and I shall come to that in a moment. My second step is to regard consciousness as a biological property that has evolved in consequence of the function it performs. And my third is to proceed from this basis with an imaginative search for the most powerful and yet simplest empirically supported hypotheses that can explain the nature of this property, why it evolved and how it is implemented in the brain. At the same time I have taken into account that consciousness can be viewed either objectively as a particular faculty of the brain, or subjectively as particular qualities of experience, often called the ‘qualia’. And I have held that a scientific model of consciousness needs to cover both.

    The model I have arrived at does indeed do so, yet stands out by its basic simplicity. For it is formulated in terms of just two key concepts, and just four propositions – all accurately defined. Two of these propositions are hypotheses, fully supported by the empirical evidence. One postulates the existence of neural processes in the brain that perform certain specified representational functions. The other subjects these to capacity limitations. The remaining two propositions explain the objective and subjective aspects of conscious experience in terms of these underlying brain processes. The two key concepts relate to two different senses in which the term ‘representation’ is to be understood in the context of the theory. In fact, until second thoughts prevailed, the title I adopted for this book was The Biological Simplicity of Consciousness.

    This simplicity is not achieved by trimming the meaning of consciousness, as the reader may at first have suspected. On the contrary, the notion of consciousness on which I have settled goes well beyond most theories by embracing all of the following facets of consciousness: awareness of the surrounding world, of the self as an entity, and of such things as thoughts and feelings. And it covers them both from the objective and the subjective perspective, explaining at the same time why we have subjective experience in the first place.

    However, with an eye on both the evolutionary context and common perceptions, I have taken consciousness to be a property that can in principle be possessed also by creatures lacking a language faculty, such as the prelinguistic infant, the deaf-mute and our animal cousins. Hence in human consciousness I deal only with the subverbal levels of awareness. I call this the primary consciousness and argue that the most fundamental questions about the nature of consciousness and the mind-brain relation can be answered if this primary consciousness is understood. Chapter 5, for example, begins with a number of basic questions that are answered by my model.

    I have to add two further warnings. First, most of my definitions are functional, and this may worry readers who happen to be acquainted with the long-drawn-out philosophical disputes about ‘functionalism’. The issues that occupied these disputes are irrelevant here. Since mine is a biological approach, brain processes are quite rightly defined in terms of the role they play in meeting the organism's needs. The biological science of physiology, for example, is exclusively concerned with functional explanations.

    Second, in view of the strong interest in consciousness found in many quarters in which a knowledge of the brain cannot be taken for granted, including among computer scientists, robotics engineers and students of artificial intelligence (AI), I have attempted to write in a language addressed to the general reader (without loss of precision where it mattered), and have added an extensive glossary. However, now and then I have also simplified where this seemed permissible. In my sketches of brain sections, for example, I have entered only those details that are relevant to the issues under discussion. I have had to make similar decisions as regards the bibliography. In view of the wide-ranging topics discussed in this book, a complete list of references to work done in the various fields would have been far beyond my capacity, and probably also beyond that of any single author. With an eye also on the general reader, I have confined myself in most cases to just a single key reference – leaving it to the bibliography of that publication to point readers to related work, should they want to follow up the topic in question.

    There may be occasions when this economy will tax the patience of the professionals. I can only hope that this will not deter them from what they may stand to gain overall from the conceptual clarifications and new perspectives the book has to offer, as well as its specific answers to (inter alia) the questions of what consciousness is, what it does, why it evolved and how it arises in the brain.

    Square brackets refer readers to other sections in the book, the use of bold type for a brain-related term directs them to the glossary. (This applies only at the term's first occurrence and as an occasional reminder.)

  • Appendix A: Real and Artificial Neurons

    The Neuron

    Neurons do all the fast information processing work in the brain. In the human brain there are some 100 billion of them and they come in all shapes and sizes. But, with few exceptions, they have certain central features in common. Among these are treelike branches, called the dendrites on which are situated most of the synapses, the points at which a neuron receives inputs from other neurons. These afferent contacts come in many different forms (Figure A1), and there may be up to 100,000 synapses on a single neuron. The treelike formations of the dendrites can be of great complexity. Many have protrusions, called dendritic spines, on which afferent fibres form synapses. Synapses can also occur between dendrites; neighbouring dendrites can influence each other and their activities summate – to mention just some of the complications. In contrast, each neuron has only a single output fibre, called the axon, to carry messages away from it. This is a long and slender process that issues from the cell body of the neuron and is nourished by it. It can extend over considerable distances and will generally branch out extensively into the so-called axon collaterals, thus making synaptic contacts with a large number of other neurons. An excited neuron discharges through its axon and these impulses are all-or-nothing events. They consist of brief changes in the electrical potential across the axonal membrane. These may be recorded as axon potentials, also called spikes. They always have the same amplitude and this does not diminish as the impulses travel along the axon, but they can vary greatly in frequency. Each discharge is followed by an absolute refractory period of a few milliseconds in which no new discharge can be created, followed by a relative refractory period in which spikes can be generated but only at a reduced sensitivity. In this manner the frequency of the discharges comes to reflect the intensity of the total afferent stimulation that the neuron receives at the synapses. This is summed not only spatially but also temporally over 100 milliseconds or so. Human nerve fibres can transmit up to 1,000 spikes per second.

    Figure A1 Composite representation of neuron to illustrate different types of neural elements. a, axon; cf, climbing fibre; d, dendrite; ds, dendritic spine; es, excitatory synapse; is, inhibitory synapse; pe, presynaptic element; pi, presynaptic inhibition; s, soma
    The Synapses

    The synapses are the junctions at which axon collaterals of one neuron impinge on the surface of another neuron or one of its dendrites and thus provide a site of information transfer. These terminals are of the nature of swellings or knobs at the afferent terminal, called boutons, which are separated from the body of the receiving (or ‘postsynaptic’) neuron by a minute cleft of only about a millionth of an inch. When a synapse is stimulated by spikes arriving in its afferent fibre, a neurotransmitter substance is released from the bouton. This diffuses across the synaptic cleft, where it acts on specific receptors on the membrane of the postsynaptic neuron, and opens gates of ion flow that in effect produce a local short-circuit and consequent electrical depolarization. This spreads electronically across the surface of the receiving neuron and sums with similar effects at other stimulated synapses. When this total depolarization, also known as the excitatory postsynaptic potential or EPSP reaches a certain critical point the neuron discharges through its axon. This is just a broad description of what is an extremely complex set of processes at the biochemical level. The responses of the receptors may also be influenced by what is happening at neighbouring synapses.

    Neurotransmitters differ widely over different regions of the brain, and the receptors have to match the local transmitter. About 50 different ones have been identified. Some appear to be mainly involved in the rapid transmission of information, e.g. glutamate, others in the production of temporary brain states, such as dopamine, which is active in brain structures influencing our emotional life, and is notably associated with pleasurable sensations and feelings of euphoria. The transmitter substances are produced and stored inside numerous small bodies called vesicles, which are situated in the boutons and discharge individually.

    There are also synapses whose transmitter substances have an opposite, inhibitory effect. Instead of a depolarization, they produce a hyperpolarization. Most of these tend to be situated on the body of the postsynaptic neuron rather than a dendrite. Figure A1 is a simplified composite that gives some idea of the various forms in which these basic arrangements may be realized in practice. Inhibitory synapses are shown in black.

    The main significance of synapses in the context of this book lies in the fact that they can undergo lasting changes in their strength – or ‘weight’ as it is often called – as a transmitting medium, and that they can undergo these changes as the result of the activities in which they are involved. This is generally held to be the main site of learning changes and of lasting memory records. However, new dendrites can also grow and new synapses can be formed as the result of the ongoing activities. An early, and still sometimes suggested explanation of learning changes is the so-called ‘Hebbian synapse’. This type of synapse was first hypothesized in 1949 by Donald Hebb, who suggested that a synapse would increase in strength if it was active at the time that the postsynaptic neuron discharged. This would lead to a strengthening of active pathways which, in turn, could generate closely linked assemblies of neurons active at the same time (Hebb, 1949). However, as I mentioned in Chapter 8, this is not the only suggested mechanism of adaptive changes at the neural level. An interesting addition has been the recent discovery that in the presence of glutamate the receptors can also multiply, even to the point at which the effect of single afferent input can become strong enough to fire the postsynaptic neuron.

    Work done by a team at Duke University with a brain-derived neural growth factor (BDNF) and neurotrophin (NT–3) has demonstrated the positive effect of the former on the growth of dendrites, and especially in layer 4 of the cerebral cortex, whereas NT–3 here inhibited that growth. To their surprise, the opposite was found in layer 6 (as reported in Neuron, 18, p. 767). I mention this only to repeat the point that nothing is simple at this level of the brain's remarkable plasticity.

    Most of the space between the brain's neurons is taken up by the glial cells, which perform a variety of physiological supporting functions, and these, too, may be involved in memory storage. Studies of RNA and DNA concentrations have shown both to play a part in memory functions, the former only transiently. But how all of this fits together to explain the complete mechanisms of memory storage remains a mystery.

    Receptive Fields

    By the ‘receptive field’ of a neuron is meant the total field of stimuli that can activate it via the afferent fibres that impinge on it at the synapses. Peripheral neurons closest to the input from a sense organ tend to have a fixed and narrowly circumscribed field. Thus a spinal neuron in our sense of touch may respond to just a specific region of the skin. But higher up in the brain there will be neurons on which the outputs of lower-level neurons converge and the receptive fields thus coalesce. And when it comes to cortical regions in which neurons may receive inputs from up to 100,000 other neurons, the receptive fields may become both large and variable.

    Some of the variations found are in the nature of long-term adaptations. This applies in particular to the size of the population of neurons which are receptive to a particular category of stimuli. In the somatosensory cortex, for example, the size of the population of neurons receptive to a particular limb will depend on the variety of movement patterns which that limb can execute. Thus the fingers have a relatively much larger population of neurons receptive to them than, say, the upper arm. And if one or more limbs are lost – a couple of fingers, for example – adaptive changes tend to occur in which the now redundant population is taken over by the neighbouring limbs. This can be a comparatively quick change, as a team at the National Institute for Neurological Disorder and Stroke, near Washington, DC has found (New Scientist, 14 February 1998). When the afferent fibres of the lower arm were inactivated by a tight tourniquet at the elbow, the brain's internal representation of the upper arm was found to have begun extensions into the former lower-arm representation after only 20 minutes (see also Section 4.2). In cases of blindness in which the eyes fail to deliver an input to the primary visual cortex, so that it is now redundant, this region has frequently been found in due course to be co-opted by other senses, for example hearing.

    How is such transfer of function to be explained? Here, I think, we need to distinguish between the potential receptive field of a neuron and its dominant receptive field. By the potential receptive field of a neuron I mean the whole range of stimuli to which a neuron could in theory become receptive by virtue of the chain of connections that link this neuron to the stimulus sources concerned. But, although these connections exist, only the most powerful inputs they supply may in fact be effective. The sources of these powerful inputs I call the dominant receptive field. If for any reason these powerful inputs cease or are weakened, previously subdued inputs may now become effective. Hence we get the effect of shifting receptive fields, although it is only the dominance that shifts. Thus we must assume in the case of the strangled afferents of the lower arm that the lower-arm neurons already had upper-arm stimuli among their potential receptive fields, but the lower-arm stimuli formed the dominant group. When the ‘amputation’ of the lower arm caused these dominant inputs to vanish, the weaker voices of the upper-arm stimuli now began to have an effect and this was gradually strengthened by active engagement, either in the Hebbian way or by the growth of additional dendrites and synapses. The same applies in my earlier example of the cortical neurons that are responsive to inputs from the two fingers prior to their loss, and that now shift their receptive fields to the remaining fingers. It follows from the above that all fingers must have been wired to lie in the potential receptive field of the neurons in the cortical region concerned.

    It is plausible to assume that this is also what occurs in the rapid shifts that have been observed at other cortical levels. In fact, it is difficult to explain them in any other way. Thus in the extrastriate cortex there are neurons whose receptive fields shift when the subject's gaze is shifted (Gur & Snodderly, 1997). Again, neurons in the parietal cortex may be responsive to tactile stimuli to the arm and also have a visual receptive field. And here it has been shown that in some of these ‘bimodal’ neurons the latter field can move in accordance with the movements of the arm (Graziano et al., 1997). In the monkey similar bimodal cells have been found in a parallel region whose visual receptive fields covered the monkey's hand, but when the monkey was given a rake as a tool, these fields expanded to cover the full length of the rake (Iriki et al., 1996). Moveable receptive fields are also known in subcortical structures, for example in the superior colliculus, a structure deeply involved in the movement of the eyes. On our present understanding, all these shifts are shifts in dominance.

    When a given neuron is linked to a source of stimuli by a chain of intermediate neurons, it follows that its potential receptive field increases exponentially with the number of members in that chain. This shows the enormous plasticity possible in a system in which such chains exist and in which the dominant fraction of the inputs to a neuron can undergo adaptive changes.

    Artificial Neural Networks

    These networks can be created in either hardware or computer simulations and consist of individual units that mimic the basic features of real neurons by having a number of input channels but only a single output. The output is computed from the activity in the input channels according to weights attached to the separate input channels and can be distributed to any number of other units or ‘nodes’ in the system. The system is designed to undergo learning changes in the form of changes in the weights according to whatever formula the designer decides to adopt in order to achieve the desired results. The archetype of such systems is the three-layered system illustrated in Figure A2. It is an archetype in the sense that it was the first system to show remarkable capacities for trial-and-error learning and thus became the prototype for a great variety of modified and elaborated systems, distinguished by their trial-and-error learning capacities. Such advanced networks can be ‘trained’ by presenting them with examples of a complex problem, such as identifying a car in the digital image of a street, and causing the weights to be adjusted until the network produces the desired output – which, in advanced cases, may even include drawing an outline around the car.

    Figure A2 Neural network and sample algorithms

    As a simple example of the algorithms adopted, consider the so-called back-propagation formula when applied to the three-layered system in order to get it to recognize some particular input pattern. The system is given as initial state a random distribution of weights, thus producing random outputs in response to the presented variety of inputs. It is then programmed so that whenever it happens to give an output in the right direction, all the pathways that contributed to this output are retrospectively strengthened. Even though an extremely large number of trials may be required, this has proved a very effective formula. However, the neural mechanisms involved in the brain's reinforcement of successful actions are not sufficiently well understood for us to decide whether any parallels can be drawn here.

    Appendix B: Main Propositions and Definitions

    The Scope

    In this book consciousness is taken to have three main facets: an awareness of the surrounding world, of the self as an entity, and of one's thoughts and feelings. The explanations offered cover all three and also the fact that these components of awareness have both an objective aspect as particular faculties of the brain, and a subjective aspect as particular qualities of experience, often called the qualia. Both aspects are explained in terms of the functional architecture of the underlying brain processes. However, the theory concentrates exclusively on levels of consciousness that can also exist in creatures lacking a language faculty, such as the neonate, the deaf-mute and nonhuman animals. This subverbal level of consciousness is called the primary consciousness.

    The Four Main Propositions
    Proposition 1

    The first conjecture:

    The brain forms an extensive internal representation of the current state of the organism which includes representations of the total situation facing the organism both in the outer and the inner world. This is called the brain's Integrated Global Representation or IGR.

    Proposition 2

    The second conjecture:

    The IGR, however, is subject to capacity and/or access limitations.

    Proposition 3

    The first identity statement:

    The primary consciousness is the IGR.

    Proposition 4

    The second identity statement:

    The subjective or qualitative aspects of conscious experience, the qualia, consist of those components of the overall effect an event has on the organism which are included in the IGR and, according to Proposition 3, thus become part of our conscious experiences.

    Main Concepts
    Structural Representations


    The activity of a set N of neurons constitutes a structural representation of an entity X, if and only if it maps the structure of X – where ‘mapping’ is here to be understood as a one-to-one or many-to-one (but not all-to-one) correspondence.

    Functional Representations


    The activity of a set N of neurons constitutes a functional representation of an entity X, if and only if responses that need to be correctly related to X in some particular way are treated by the brain as responses that need to be correctly related to the activity of N in some particular way.

    States of Expectancy


    By a state of expectancy, conscious or unconscious, shall be meant a state of the brain that has two components:

    • a state of readiness for the occurrence of a particular event – that is to say, a state which facilitates or advances an appropriate reaction to that event, and
    • a state in which the occurrence of a significantly different event tends to elicit a characteristic reaction of surprise, technically known as an orienting reaction. Pavlov called it a ‘What is it?’ reflex.
    The Running World Model or RWM

    The Running World Model is conceived as the brain's internal representation of the current state of the external world, including the body and its place in that world. Most of the properties of the external world are represented here by the way in which they affect the outcome of our actions, i.e. by acquired act-outcome expectancies. But more general what-leads-to-what expectancies also play a part. Not all of the RWM enters the IGR, hence consciousness.

    Imaginative Representations


    To imagine an object of a certain type is for the brain to be in a state of readiness to perceive an object of that type without expecting the perception.

    Self-Reference and Self-Awareness

    In the present theory self-reference or implicit self-awareness denotes the fact that the contents of the IGR, hence of the primary consciousness, have the functional status of representations of the current state of the organism. Explicit self-awareness has three main levels:

    • The basic experiential or ‘apprehensive’ level. By this is meant how the above-mentioned self-reference manifests itself experientially and in the qualia of conscious experience.
    • The conceptual/autobiographical level. For example, when the self-reference is expressed in such statements as ‘I have a toothache’.
    • The conceptual/contemplative level. This occurs when introspectively one engages in thoughts about what kind of object or person one is.


    • Accommodation. Adjustments in the curvature of the eye's lens that brings fixated objects into sharper focus.
    • Afferent. Conducting information towards the brain or individual neurons.
    • Alexia. Inability to read, sometimes caused by lesions in the temporal lobe*.
    • Amygdala. A walnut-sized knot of neurons deep inside the brain below the level of the thalamus which forms part of the limbic system* and is held to be especially implicated in social sensitivities, judgements and attitudes. If damaged on both sides, the patient will show impoverished memory for emotionally charged events and, for example, fail to read expressions of fear and anxiety on the faces of other people.
    • Axon. The single fibre and its branches (called axon collaterals) through which an excited neuron discharges in an all or nothing fashion and at frequencies which depend on the degree of excitation.
    • Basal ganglia. A set of important nuclei surrounding the thalamus*, comprising the caudate nucleus*, the putamen*, the globus pallidus*, the substantia nigra*, and the subthalamic nucleus*. They form part of the extra-pyramidal motor system*, and, in conjunction with the cerebellum* figure as the highest subcortical level in the control of motor functions.
    • Binocular disparity. The disparity in retinal inputs resulting from the different locations from which the eyes see the world.
    • Blind spot. A small circular area, called the optic disk, where the retina* is interrupted by the bundle of nerve fibres leaving it.
    • Blindsight. The unconscious detection of external visual stimuli and their direction or movement, when lesions in the visual cortex* have caused total blindness at the conscious level.
    • Body schema. Also called body image. A coherent structural representation in the brain of the spatial relations involved in body posture, body movement and body surface.
    • Brainstem. The structures between the spinal cord and the midbrain*.
    • Brodmann numbers. The numbering of different cortical regions introduced at the turn of the century by the German anatomist Korbinian Brodmann on the basis of cytoarchitectonic differences. Although his criteria are still a matter of some dispute, as are the functional implications of his divisions, his system has worked well on the whole, and has remained one of the most widely used ways of charting the cortex.
    • Caudate nucleus. One of the basal ganglia*, implicated in the implementation of action plans generated in the premotor* and supplementary motor cortex*.
    • Central fissure. A deep cleft at the centre of the cortex, between the primary motor cortex* and the somatosensory cortex*.
    • Cerebellum. A large brainlike structure with a three-layered cortex which surrounds the back of the brain stem and contains about half the neurons of the central nervous systems. It is deeply implicated in the smooth control and timing of complex movement patterns, largely achieved through its acquired powers to predict the consequences of motor commands on the overall posture and movement of the body and its limbs. This speeds up the movement sequences, because if the brain had to rely entirely on sensory feedback to control the movement of the limbs, we would have to move very much more slowly.
    • Cerebral cortex. The convoluted grey rind of the two cerebral hemispheres. Generally composed of six layers of tightly packed neurons arranged in vertical columns communicating vertically with each other. Long-distance connections from other cortical regions arrive via the outermost layer while sensory afferents* from the thalamus arrive at intermediate layers and outputs flow from the bottom layers via fibres that jointly constitute the ‘white matter’. Often just called ‘the cortex’ where the context permits.
    • Cingulate gyrus. A part of the limbic system* implicated in emotion and especially aggression. It arches over the corpus callosum* and comprises Brodmann* areas 23, 24, 26, 29, 31 and 33.
    • Conditioning. A basic form of learning consisting of the formation of new stimulus-response or stimulus-stimulus associations. The concept was originally restricted to what is now called classical conditioning. The prototype of this was Pavlov's demonstration that if the presentation of food to a dog is regularly preceded by a bell, the dog will in due course start salivating simply at the sound of the bell.
    • Corpus callosum. The large bundle of about 800 million nerve fibres linking corresponding points in the two cortical hemispheres*.
    • Declarative memory. Memory of something that happened, as opposed to memory of how to do something.
    • Dendrites. The treelike outgrowths of neurons that receive afferents from other neurons.
    • Dorsal. On or towards the back of the body or (in upright species) the top of the brain.
    • EEG. Short for electroencephalographs, the readings of electrodes attached to the scalp which are sensitive to the bulk electrical activity of the underlying cortical cells.
    • Efferent. Conducting information away from the brain or individual neurons.
    • Entorhinal cortex. One of the polysensory associative regions in the medial cortex which both projects to the hippocampus* and receives inputs from it.
    • Episodic memory. The (not always faithful) part of the memory system that stores conscious personal experiences, including, for example, witnessed events.
    • Exteroceptive information. Information derived from the external senses, such as the eyes and ears.
    • Extra-pyramidal motor system. See Pyramidal tract.
    • fMRI. Functional Magnetic Resonance Imaging. A technique for mapping regional brain activity. It uses powerful magnetic fields to align the tiny magnetic dipoles of atomic nuclei in the brain. Carefully tuned radio pulses can then reveal changes in oxygen levels, which are indicative of blood flow, by measuring the frequencies at which the oxygen atoms resonate.
    • Fovea. An axially central region of the retina* in which the photoreceptors are extremely densely packed, permitting high resolution. It consists predominantly of wavelength-sensitive ‘cones’.
    • Frontal. Towards the front of the body or an organ.
    • Frontal eye fields. A region in the frontal cortex involved in the voluntary control of eye movements.
    • Ganglia. Groups of neurons at the periphery of the nervous system that perform some basic operations such as the enhancement of contrasts in the retina. But see basal ganglia*.
    • Globus pallidus. One of the basal ganglia*, which receives mainly inhibitory inputs from the putamen* and caudate nucleus*, and acts on both the thalamus* and subthalamic nucleus*.
    • Gyrus (pl. gyri). A bulge or raised fold in the surface of the cortex.
    • Haptic. To do with the sense of touch.
    • Hemi-. Means ‘half, as in hemisphere, hemifield.
    • Hemisphere. One of the two halves of the cerebral cortex* linked by the corpus callosum*.
    • Hippocampus. An older structure of the brain, shaped like a sea-horse (hence the name) which is folded into the temporal lobe below the hippocampal gyrus and inferior cingulate gyrus*. It draws upon a mass of inputs from other regions of the cerebral cortex*, and seems to be involved in a variety of supportive functions, including mediating the transfer of short-term to long-term memory, responding to novelty in the sensory inputs and containing cells that are sensitive to an organism's location.
    • Hypothalamus. Part of the limbic system* mainly concerned with the organism's physiological needs. It controls body temperature, eating, drinking, sexual drive, hormonal balance, and, to some extent, pain.
    • IGR or Integrated Global Representation. My name for a comprehensive internal representation* which I assume to be formed by the brain of the current state of the organism, which includes representations of the total situation facing the organism both in the outer and the inner world.
    • Insula. A cortical area hidden behind the temporal* and parietal lobes* and mainly implicated in the processing of visceral* information.
    • Internal representations. I distinguish a structural and functional sense of this phrase. Both are defined on pp. 17–21.
    • Interoceptive information. Information derived from the internal body sensors, such as those in muscles, tendons, joints and the vestibular system*.
    • Intersection and union (logic). The intersection of n classes of entities is the class of entities that are members of all, while the union of n classes of entities is the class of those that are a member of any one of them.
    • Lateral. Situated at or towards the side of a named structure.
    • LGN or lateral geniculate nucleus. One of the nuclei of the thalamus* which acts as relay station for the optical inputs.
    • Limbic system. A system of structures which governs the emotional and motivational forces in the determination of behaviour. It is not a very firm notion. Generally included are the hypothalamus*, amygdala*, septal nuclei, mammillary bodies*, parts of the thalamus*, and, at the cortical level, the cingulate gyrus*, the hippocampal gyrus*, including the entorhinal* region and the adjacent periamygdaloid and prepyriform regions.
    • Mammillary bodies. Distinct cell bodies involved in the processing of outputs from the limbic system*.
    • Medial cortical regions. Cortical regions on the inner side of the hemispheres (see Figure 2.1, p. 29). Some are important convergence zones which receive information of both the what and the where.
    • Microtubules. Fine longitudinal structures in the neuron that seem to be associated with the transport of substances.
    • Midbrain. The region containing the colliculi, red nucleus, substantia nigra* and regional reticular formation*.
    • Motion parallax. The way in which the position of nearby objects shifts against the background of more distant ones when the head moves sideways to the line of vision.
    • Neglect. The effect of brain lesions which cause sections of the brain's world model to vanish from consciousness.
    • Neurotransmitter. The chemical substance secreted by excited synapses*, which diffuses across the narrow cleft that separates the synapse from the membrane of the neuron it contacts. Through receptors* straddling that membrane it effects voltage changes that spread across the remainder of the neuron's surface (see Appendix A). The chemical composition of neurotransmitters can differ widely over different regions of the brain and needs receptors to match.
    • Nucleus. A tight group of functionally associated neurons.
    • Occipital lobe. The lobe at the back tip of the brain which hosts the visual cortex*.
    • Occam's razor. The admonition given by Bishop William of Occam (c. 1285–c. 1349), a scholastic philosopher of some note, that ‘entities should not be multiplied without necessity’. In other words, the best explanations are those that make the fewest assumptions.
    • Optic chiasma. The crossover point in the optical tracts required because the right half of the visual field of both eyes is processed in the left hemisphere, and the left half in the right hemisphere.
    • Orienting reactions. A general class of original reactions to unexpected events, inhibited when familiarization comes to substitute more specific responses.
    • Parietal lobe. A cortical region and association area which lies between the visual* and somatosensory* cortex, heavily involved in the body schema* and in the visual control of movements.
    • PET or Positron Emission Tomography. A technique for mapping regional brain activity by measuring the local metabolic rate. It is based on administering radioactively labelled blood, blood sugars or important neurotransmitters*. A sphere of detector crystals placed around the skull measures the gamma rays emitted when positrons collide with electrons. It is a slow process since the scanner has to sift through 7 or 8 million signals every second to locate concentrations of the tracer.
    • Pons. Prominent part of the reticular formation*, including the parts that connect the cerebellum* to the midbrain*.
    • Prefrontal lobe. The part of the frontal lobe forward of the premotor* areas. Held to be the highest level at which the brain evaluates the current situation in the light of the organism's needs and desires, as conveyed by the limbic system*.
    • Premotor cortex. Motor association area in the frontal lobe anterior to the primary motor cortex*, and held to be implicated in the formation of patterns of movements and the learning of motor skills.
    • Primary motor cortex. A deep cortical strip in front of the central fissure*, which has direct connections to the motor nuclei (ganglia*) of the spinal cord and plays a dominant part in the fine adjustments of voluntary movements. Brodmann* area 4.
    • Proprioception. The senses in joints, tendons, muscles and the vestibular system* that inform about the position and position changes of the body and limbs relative to one another and to gravity.
    • Putamen. One of the basal ganglia*, situated at the level of the thalamus* and implicated in the processing of signals from the somatosensory* and motor areas of the cortex.
    • Pyramidal tract. A tract of efferent fibres originating in the motor cortex (mainly the primary*) and running straight down to the motor ganglia* in the spinal cord. It supplements the extra-pyramidal motor system which comprises the basal ganglia* and associated nuclei, as well as parts of the reticular formation*, and some of its work may be described as playing on the keyboard of built-in reflexes – activating some while inhibiting others.
    • Receptive fields. The field of stimuli that can activate a neuron via excitation in the totality of afferent* fibres that impinge on its synapses*. A distinction can be drawn between potential and dominant receptive fields, the latter being the effective portion of the former (see Appendix A). Neurons at the input end of a sensory receptor* tend to have a fixed and narrowly circumscribed field. Thus a primary neuron in our sense of touch will respond to just a specific region of the skin. But higher up in the brain there will be neurons on which the outputs of lower-level neurons converge and the receptive fields thus coalesce. At this level, too, the dominant fraction can undergo adaptive and sometimes rapid changes. In a chain of neurons the potential receptive field of the last one in the chain will depend exponentially on the number of neurons in that chain.
    • Receptors (on neural membranes). Protein molecules on the surface of a neural membrane which are responsive to the neurotransmitter* secreted by the contacting synapses*.
    • REM sleep. The Rapid Eye Movement phase of sleep, distinguished from the non-REM or slow-wave sleep. A periodic phase occurring about every 90 minutes and marked by jerky eye movements, dreams, and notable changes in the EEG* rhythms. PET* studies have shown that during dreaming the prefrontal* areas involved in action planning and self-reflection are turned off. On the other hand, structures involved in emotional reactions, such as the amygdala*, showed enhanced activity. Hence dreams are often fearful. Some occipital areas involved in vision and movement also showed high activity. This may account for the hallucinatory quality of dreams.
    • Representations. See Internal representations
    • Reticular formation. A complex network of ascending and descending neurons which runs the length of the brain stem and up to the thalamus*, through which it projects diffusely to the cerebral cortex*. Strongly implicated in sleep, arousal, visceral* functions like breathing and body posture. Also in consciousness: even partial damage can cause a coma.
    • Retina. A structured sheet covering two-thirds of the inner surface of the eyeball. It contains blood vessels, the eye's light-sensitive cells, and ganglia* whose output fibres leave it via the blind spot*. The light-sensitive cells, or photoreceptors, are of two types, the rods and cones. Only the cones are sensitive to specific wavelengths.
    • RWM or Running World Model. My name for the brain's internal representation of the current constitution and state of the external world and its properties, which the brain infers from its sensory inputs on the basis of past experience and other prior knowledge. It includes the body schema*.
    • Saccades. The eyes' rapid jumps from one point of fixation to another.
    • Somatosensory cortex. Region of the cortex receiving information from the mechanical sensors in muscles, tendons, joints and the skin. From Greek soma = body.
    • Spike. The brief all-or-nothing discharge of an excited neuron. Since the spikes are always of the same amplitude, the effective variable is their frequency, the number of spikes per second.
    • Substantia nigra. Part of the extra-pyramidal motor system*, situated at the upper end of the pons*. Degeneration here is held largely responsible for Parkinson's disease.
    • Subthalamic nucleus. A member of the basal ganglia*, which appears mainly to exercise a gain control over the globus pallidus*.
    • Sulcus. A groove in the convoluted surface of the cortex.
    • Superior colliculus. A nuclear structure deeply implicated in the control of eye movements. It contains both maps of the visual field and motor images of saccades*.
    • Supplementary motor area. A cortical motor association area lying on top of and medial to the premotor cortex*.
    • Synapse. The knob-like junction at which the outputs of one nerve cell via its axon* or axon-branch stimulate another nerve cell or a muscle fibre. The effect is mediated, generally by way of a chemical transmitter substance, across a narrow cleft that separates the knob from the receiving cell. However, electrical transmission is also known. The stimulus results in changes in the electrical potential of the cell which causes the cell to ‘discharge’ through its axon when the total effect of all active synapses reaches a certain critical level.
    • Temporal lobe. A forward-reaching lobe which occupies the lower middle part of the cortex between the visual and frontal* lobe and below the parietal*. Its inferior regions contain association areas heavily implicated in visual object recognition, but also auditory areas and some language areas.
    • Thalamus. A large integral body of nuclei* which lies as an intermediate station between the sensory inputs and the cortical areas where they are analysed. Each cortical region receives from an associated thalamic nucleus and feeds back to it. In part, but only in part, the thalamus acts here as an upward relay station of sensory and other afferents* to the respective reception areas of the cortex, for it has important functions of its own. Different sensory fibre tracks are regrouped within its massive domain, and there are many opportunities here for the interaction and integration of different modalities.
    • Topographical projections. Projections into a brain region of a system of sensory inputs, such as inputs from the retina, which maintain the spatial relations between the respective sensors.
    • Topography. The spatial relation of cells in a brain structure.
    • Union (logic). See Intersection* (logic).
    • Ventral. On or towards the front of the body or the base of the brain.
    • Vergence. Adjusting the angle between the eyes' line of vision to suit the distance of a fixated object (convergence if the angle is diminished, divergence if increased).
    • Vestibular system. The system in the inner ear and its semicircular canals that provides us with a sense of balance.
    • Viscera. The body's internal organs, in particular the abdomen.
    • Visual cortex. The convoluted cortical region in the occipital lobe* which receives the primary optical inputs and carries out the initial processing in a number of functionally distinct areas.
    • Working memory. Representations of recent events or experiences that maintain the continuity of the RWM*, including those that are kept alive ‘in the mind’ because of their relevance to current tasks, for example in serial tasks in which the subjects have to see the responses that still have to be made in the light of the responses already made.


    Anderson, J.R. (1978). ‘Arguments concerning representations for mental imagery.’Psychological Review, 85, pp. 249–77. http://dx.doi.org/10.1037/0033-295X.85.4.249
    Anderson, R.A., Essik, G.K. & Siegel, R.M. (1985). ‘Encoding of spatial locations by posterior parietal neurons.’Science, 230, pp. 456–8. http://dx.doi.org/10.1126/science.4048942
    Andreason, N.C., O'Leary, D.S., Cisadlo, T., Arndt, S., Rezai, K., Watkins, G.I., Ponto, L. & Hochwa, R.D. (1995). ‘Remembering the past: two facets of episodic memory explored with positron emission tomography.’American Journal of Psychiatry, 152 (11), pp. 1576–85.
    Baars, B.J. (1988). A Cognitive Theory of Consciousness. Cambridge, UK: Cambridge University Press.
    Baars, B.J. & Banks, W.P. (1992). ‘On returning to consciousness.’Consciousness and Cognition, 1 (1), pp. 1–6. http://dx.doi.org/10.1016/1053-8100%2892%2990036-A
    Baddeley, A.D. (1986). Working Memory. Oxford: Oxford University Press.
    Baillargeon, R. (1993). ‘The object concept revisited. New directions in the investigation of infants’ physical knowledge.’ in C.E.Granrud (ed.) Visual Perception and Cognition in Infancy. Hillsdale, NJ: Lawrence Erlbaum.
    Barlow, H.B. (1987). ‘The biological role of consciousness.’ in C.Blakemore & S.Greenfield (eds) Mindwaves. Oxford: Basil Blackwell.
    Barlow, H.B. (1991). ‘Vision tells you more than “what is where”.’ in A.Gorea (ed.) Representations of Vision: trends and tacit assumptions of vision research. Cambridge, UK: Cambridge University Press.
    Behrmann, M., Winocur, G. & Moscovitch, M. (1992). ‘Association between mental imagery and object recognition in a brain-damaged patient.’Nature, 159 (6396), pp. 636–7. http://dx.doi.org/10.1038/359636a0
    Beninger, R.J., Kendall, S.B. & Vanderwolf, C.H. (1974). ‘The ability of rats to discriminate their own behaviours.’Canadian Journal of Psychology, 28, pp. 79–91. http://dx.doi.org/10.1037/h0081979
    Beritashvilli (Beritoff), I.S. (1963). ‘The characteristics and origin of voluntary movements in higher vertebrates.’Progress in Brain Research, 1, pp. 30–8.
    Berlyne, D.E. (1960). Conflict, Arousal and Curiosity. New York: McGraw-Hill. http://dx.doi.org/10.1037/11164-000
    Bisiach, E. & Geminiani, G. (1991). ‘Anosognosia related to hemiplegia and hemianopia.’ in G.Prigitano & D.L.Schacter (eds) Awareness of Deficit after Brain Injury. New York: Academic Press.
    Bisiach, E. & Luzzatti, C. (1978). ‘Unilateral neglect of representational space.’Cerebral Cortex, 14, pp. 129–33.
    Blackmore, S. (1992). ‘The nature of consciousness.’ Lecture given in February to the Cambridge University Science Society.
    Blakemore, C. (1977). Mechanics of Mind. Cambridge, UK: Cambridge University Press.
    Blakemore, C. (1990). ‘Understanding images in the brain.’ in H.Barlow, C. Blakemore & M.Weston-Smith (eds) Images and Understanding. Cambridge, UK: Cambridge University Press.
    Blakemore, C. & Greenfield, S. (eds) (1987). Midwives. Oxford: Basil Blackwell.
    Blakemore, S.J., Rees, G. & Frith, C.D. (1998). ‘How do we predict the consequences of our actions?’Neuropsychologia, 36 (6), pp. 521–9. http://dx.doi.org/10.1016/S0028-3932%2897%2900145-0
    Blumenthal, A.L. (1977). The Process of Cognition. Englewood Cliffs, NJ: Prentice-Hall.
    Boden, M. (1988). Computer Models of Mind. Cambridge, UK: Cambridge University Press.
    Borsook, D., Becerra, L., Fishmaan, S., Edwards, A., Jennings, C.I., Stojanovie, M., Papinicolas, L., Ramachandran, V.S., Gonsalez, R.G. & Breiter, H. (1998). ‘Acute plasticity in the human somatosensory cortex following amputation.’Neuroreports, 9 (6), pp. 1013–17. http://dx.doi.org/10.1097/00001756-199804200-00011
    Bower, T.G.R. (1971). ‘The object in the world of the infant.’Scientific American, 225, pp. 30–8. http://dx.doi.org/10.1038/scientificamerican1071-30
    Brewer, J.B., Zhao, Z., Desmond, J.E., Glover, G.H. & Gabriell, J.D. (1998). ‘Making memories: brain activity that predicts how well visual experience will be remembered.’Science, 281, pp. 1185–7. http://dx.doi.org/10.1126/science.281.5380.1185
    Broadbent, D.E. (1952). ‘Listening to two synchronous messages.’Journal of Experimental Psychology, 44, pp. 51–5. http://dx.doi.org/10.1037/h0056491
    Brotchie, P.R., Anderson, R.A., Snyder, L.M. & Goodman, S.J. (1995). ‘Head position signal used by parietal neurons to encode locations of visual stimuli.’Nature, 375, pp. 232–5. http://dx.doi.org/10.1038/375232a0
    Cabeza, R., Kapur, S., Craik, F.I.M., Mcintosh, A.H., Houle, S.A. & Tulving, E. (1997). ‘Functional neuroanatomy of recall and recognition: a PET study of episodic memory.’Journal of Cognitive Neuroscience, 9, pp. 254–5. http://dx.doi.org/10.1162/jocn.1997.9.2.254
    Carpenter, R.H.S. (1988). Movement of the Eyes. London: Pion.
    Carpenter, R.H.S. (1996). Neurophysiology. London: Arnold.
    Carpenter, R.H.S. (1999). ‘A neural mechanism that randomises behaviour.’Journal of Consciousness Studies, 6 (1), pp. 13–22.
    Chalmers, D.J. (1995). ‘Facing up to the problem of consciousness.’Journal of Consciousness Studies, 2 (3), pp. 200–19.
    Chalmers, D.J. (1996). The Conscious Mind. New York: Oxford University Press.
    Churchland, P.S. & Sejnowski, T.J. (1992). The Computational Brain. Cambridge, MA: MIT Press.
    Cohen, M.S., Kosslyn, S.M., Breiter, H.C., DiGirolamo, G.J., Thompson, W.L., Anderson, A.K., Brookheimer, S.Y., Rosen, B.R. & Belliveau, J.W. (1996). ‘Changes in cortical activity during mental rotation. A mapping study using functional MRI.’Brain, 119, pp. 89–100. http://dx.doi.org/10.1093/brain/119.1.89
    Colby, C.L., Duhamel, J.R. & Goldberg, M.E. (1995). ‘Oculocentric spatial representation in parietal cortex.’Cerebral Cortex, 5 (5), pp. 470–81. http://dx.doi.org/10.1093/cercor/5.5.470
    Cotterill, R.M.J. (1998). The Enchanted Loom. Cambridge, UK: Cambridge University Press.
    Craik, K. (1943). The Nature of Explanation. Cambridge, UK: Cambridge University Press.
    Crick, F. (1994). The Astonishing Hypothesis. New York: Simon & Shuster.
    Damasio, A.R. (1994). Descartes' Error. New York: G.P. Putnam & Sons.
    Damasio, A.R. (1998). ‘Investigating the biology of consciousness.’Philosophical Transactions of the Royal Society, Section B, 353, pp. 1879–82. http://dx.doi.org/10.1098/rstb.1998.0339
    Davis, K.D., Kiss, Z.H., Luo, L., Tasker, R.R., Lozano, A.M. & Dostrovsky, J.O. (1998). ‘Phantom sensations generated by thalamic microstimulation. ‘Nature, 391, pp. 385–7. http://dx.doi.org/10.1038/34905
    Decety, J. (1996). ‘The neurophysiological basis of motor imagery.’Behavioral Brain Research, 77 (1–2), pp. 45–52. http://dx.doi.org/10.1016/0166-4328%2895%2900225-1
    Deiber, M.P., Wise, S.P., Honda, M., Catalan, M.J., Grafman, J. & Hallett, M. (1997). ‘Frontal and parietal networks for conditional motor learning: a positron emission tomography study.’Journal of Neurophysiology, 78 (2), pp. 977–99.
    Dennett, D.C. (1991). Consciousness Explained. Boston: Little, Brown.
    Dennett, D.C. (1997). ‘The unimagined preposterousness of zombies.’Journal of Consciousness Studies, 2 (4), pp. 322–5.
    Deubel, H. & Schneider, W.X. (1996). ‘Saccade target selection and object recognition: evidence for a common attentional mechanism.’Vision Research, 36 (12), pp. 1827–37. http://dx.doi.org/10.1016/0042-6989%2895%2900294-4
    Ducom, J.C. (1999). ‘Lights, sounds, action! Report on the work of Ducom and his colleagues.’New Scientist, 2183 (24 April), p. 6.
    Duncan, J. (1998). ‘Converging levels of analysis in cognitive neuroscience of visual attention.’Philosophical Transactions of the Royal Society, Section B, 353, pp. 1307–17. http://dx.doi.org/10.1098/rstb.1998.0285
    Eccles, J.C. & Popper, K.R. (1977). The Self and its Brain. Berlin: Springer International. http://dx.doi.org/10.1007/978-3-642-61891-8
    Edelman, G.M. (1992). Bright Air, Brilliant Fire. London: Allen Lane.
    Faillenot, I., Sakata, H., Costes, N., Decety, J. & Jeannerod, M. (1997). ‘Visual working memory for shape and 3D-orientation: a PET study.’Neuroreport, 8 (4), pp. 859–62. http://dx.doi.org/10.1097/00001756-199703030-00010
    Farah, M.J. (1985). ‘Psychophysical basis for a shared representational medium for mental images and percepts.’Journal of Experimental Psychology: General, 114, pp. 91–103. http://dx.doi.org/10.1037/0096-3445.114.1.91
    Farah, M.J. (1997). ‘Consciousness of perception after brain damage.’Seminar Neurology, 17 (2), pp. 145–52. http://dx.doi.org/10.1055/s-2008-1040924
    Farah, M.J., Peronnet, F., Gonon, M.A. & Girard, M.H. (1988). ‘Electrophysiological evidence for a shared representational medium for visual images and visual percepts.’Journal of Experimental Psychology: General, 117, pp. 248–57. http://dx.doi.org/10.1037/0096-3445.117.3.248
    Felleman, D.J. & Van Essen, D.C. (1991). ‘Distributed hierarchical processing in primate cerebral cortex.’Cerebral Cortex, 1 (1) Gan.–Feb.), pp. 1–47. http://dx.doi.org/10.1093/cercor/1.1.1-a
    Ffytche, D.H., Howard, R.J., Brammer, M.J., David, A., Woodruff, P. & Williams, S. (1998). ‘The anatomy of conscious vision: an fMRI study of visual hallucinations.’Nature Neuroscience, 1 (8), pp. 738–2. http://dx.doi.org/10.1038/3738
    Fink, G.R., Markowitsch, H.J., Reinkemeier, M., Bruckbauer, T., Kessler, J. & Heiss, W.D. (1996). ‘Cerebral representation of one's own past: neural networks involved in autobiographical memory.’Journal of Neuroscience, 16 (13), pp. 4275–82.
    Finke, R.A. (1985). ‘Theories relating mental imagery to perception.’Psychological Bulletin, 98, pp. 236–59. http://dx.doi.org/10.1037/0033-2909.98.2.236
    Finke, R.A. & Kosslyn, S.M. (1980). ‘Mental imagery acuity in the peripheral visual field.’Journal of Experimental Psychology: Human Perception and Performance, 6, pp. 244–64. http://dx.doi.org/10.1037/0096-1523.6.1.126
    Fodor, J.A. (1975). The Language of Thought. Hassocks, UK: The Harvester Press.
    Földiak, P. (1992). ‘Models of sensory coding.’ Dissertation, Department of Physiology, University of Cambridge.
    Frith, C. & Dolan, R. (1996). ‘The role of the prefrontal cortex in higher cognitive functions.’Cognitive Brain Research, 5 (1–2), pp. 175–88. http://dx.doi.org/10.1016/S0926-6410%2896%2900054-7
    Fuster, J.M. (1997). The Prefrontal Cortex (
    3rd ed.
    ). New York: Lippincott-Raven.
    Gallese, V., Fadiga, L., Fogassi, L. & Rozzolatti, G. (1996). ‘Action recognition in premotor cortex.’Brain, 119, pp. 593–609. http://dx.doi.org/10.1093/brain/119.2.593
    Gallistel, C.R. (1989). ‘Animal cognition: the representation of space, time and number.’Annual Review of Psychology, 40, pp. 155–89. http://dx.doi.org/10.1146/annurev.ps.40.020189.001103
    Gardner, M. (1996). ‘Computers near the threshold?’Journal of Consciousness Studies, 3 (1), pp. 89–94.
    Gazzaniga, M. S. & LeDoux, J.E. (1978). The Integrated Mind. New York: Plenum.
    Georgopolous, A.P., Lurito, J.T., Petrides, M., Schwartz, A.B. & Massey, J.T. (1989). ‘Mental rotation of the neuronal population vector.’Science, 243, pp. 141–272.
    Gibson, J.J. (1979). The Ecological Approach to Visual Perception. Boston: Houghton-Mifflin.
    Gobnik, A., Meltzoff, A.N. & Kuhl, P. (2000). How Babies Think: the science of childhood. New York: Weidenfeld and Nicolson.
    Goldstein, K. (1948). Language and Language Disturbances. New York: Grune and Statton.
    Goodale, M.A., Jacobson, L.S. & Keiller, J.M. (1994). ‘Differences in visual control of pantomimed and natural grasping movements.’Neuropsychologia, 32, pp. 1159–78. http://dx.doi.org/10.1016/0028-3932%2894%2990100-7
    Goubet, N. & Clifton, R.K. (1998). ‘Object and event representation in 6-month-old infants.’Developmental Psychology, 34 (1), pp. 63–76. http://dx.doi.org/10.1037/0012-1649.34.1.63
    Grady, C.L., McIntosh, A.R., Rajah, M.N. & Craik, F.I. (1998). ‘Neural correlates of the episodic encoding of pictures and words.’Proceeding of the National Academy of Science, 95, pp. 2703–8. http://dx.doi.org/10.1073/pnas.95.5.2703
    Grafton, S.T., Arbib, M.A., Fadiga, I. & Rizolatti, G. (1996). ‘Localization of grasp representations in humans by positron emission tomography. 2. Observation compared with imagination.’Experimental Brain Research, 112 (1), pp. 103–11. http://dx.doi.org/10.1007/BF00227183
    Graziano, M.S.A., Hu, X.T.A. & Gross, C.G. (1997). ‘Visiospatial properties of ventral premotor cortex.’Journal of Neurophysiology, 77 (5), pp. 2268–92.
    Greenfield, S. (1998). ‘How might the brain generate consciousness?’ in S.Rose (ed.) From Brains to Consciousness?London: Allen Lane.
    Gregory, R.L. (1970). ‘On how little information controls so much behaviour.’ in A.T.Welfod & L.Housiadas (eds) Contemporary Problems in Perception. London: Taylor & Francis.
    Gregory, R.L. (1987). The Oxford Companion to the Mind. Oxford: Oxford University Press.
    Gregory, R.L. & Wallace, J.G. (1963). Recovery from Blindness: a Case Study. Cambridge, UK: Cambridge University Press.
    Grossberg, S. (1980). ‘How does the brain build a cognitive code?’Psychological Review, 87, pp. 1–2. http://dx.doi.org/10.1037/0033-295X.87.1.1
    Guariglia, C., Padovani, P. & Pizzamiglio, L. (1993). ‘Unilateral neglect restricted to visual imager.’Nature, 383, pp. 78–81.
    Gur, M. & Snodderly, D.M. (1997). ‘Visual receptive fields of neurons in the primary visual cortex (V1) move in space with the eye movements of fixation.’Vision Research, 37, pp. 257–65. http://dx.doi.org/10.1016/S0042-6989%2896%2900182-4
    Gyr, J., Willey, R. & Henry, A. (1979). ‘Motor-sensory feedback and geometry of visual space: an attempted replication.’Behavioral and Brain Sciences, 2, pp. 59–94. http://dx.doi.org/10.1017/S0140525X00060702
    Haith, M.M. (1993). ‘Future-oriented processes in infancy. The case for visual expectations.’ in C.E.Granrud (ed.) Visual Perception and Cognition in Infancy. Hillsdale, NJ: Lawrence Erlbaum.
    Halligan, P.W. & Marshall, J.C. (1993). ‘The history and clinical presentation of neglect.’ in L.H.Robertson & J.C.Marshall (eds) Unilateral Neglect: clinical and experimental studies. Hove, UK: Lawrence Erlbaum.
    Hameroff, S.R. (1994). ‘Quantum coherence in micro tubules: a neural basis for emergent consciousness?’Journal of Consciousness Studies, 1, pp. 98–118.
    Hayhoe, M., Lachter, J. & Feldman, J. (1991). ‘Integration of form across saccadic eye movements.’Perception, 20 (3), pp. 393–02. http://dx.doi.org/10.1068/p200393
    Head, H. (1920). Studies in Neurology, 2. London: Frowde, Hodder & Stoughton.
    Hebb, D.O. (1949). Organization of Behaviour. New York: John Wiley & Sons.
    Heijden, A.H.C. van der (1992). Selective Attention in Vision. London: Routledge & Kegan Paul.
    Held, R. & Hein, A (1963). ‘Movement-produced stimulation in the development of visually guided behaviour.’Journal of Comparative and Physiological Psychology, 56, pp. 872–6. http://dx.doi.org/10.1037/h0040546
    Helmholtz, H. von (1867). Handbuch der Physiologischen Optik, Vol. III. Leipzig: Leopold Voss.
    Hietanen, J.K. & Perrett, D.I. (1993). ‘Motion sensitive cells in macaque superior temporal polysensory area. Lack of response to the sight of the animal's own limb movement.’Experimental Brain Research, 93 (1), pp. 117–28. http://dx.doi.org/10.1007/BF00227786
    Hochberg, J. (1968). ‘In the mind's eye.’ in R.N.Huber (ed.) Contemporary Theory and Research in Perception. New York: Holt, Reinhart & Winston.
    Hofstadter, D. (1989). Godel, Escher, Bach: An Eternal Golden Braid. New York: Basic Books.
    Holst, E. von & Mittelstaedt, H. (1950). ‘Das Reafferenz Prinzip.’Naturwissenschaften, 37, pp. 465–76.
    Hubel, D.H. & Wiesel, T.N. (1962). ‘Receptive fields, binocular interaction and functional architecture in the cat's visual cortex.’Journal of Physiology (London), 166, pp. 106–54.
    Humphrey, N. (1992). A History of the Mind. London: Chatto & Windus.
    Ingvar, D.H. (1994). ‘The will of the brain: cerebral correlates of willful acts.’Journal of Theoretical Biology, 171 (1), pp. 7–12. http://dx.doi.org/10.1006/jtbi.1994.1206
    Iriki, A., Tanaka, M. & Iwamura, Y. (1996). Neuroreports, 7 (14), pp. 2325–30. http://dx.doi.org/10.1097/00001756-199610020-00010
    Jackendoff, R. (1987). Consciousness and the Computational Mind. Cambridge, MA: MIT Press.
    James, W. (1890). Principles of Psychology (2 vols). New York: Dover. http://dx.doi.org/10.1037/10538-000
    Jaynes, J. (1976). ‘The origins of consciousness.’ In The Breakdown of the Bicameral Mind. Boston: Houghton Mifflin.
    Jeannerod, M. (1994). ‘The representing brain: neural correlates of motor intention and imagery.’Behavioral and Brain Sciences, 17, pp. 187–245. http://dx.doi.org/10.1017/S0140525X00034026
    Jeannerod, M. (1997). The Cognitive Neuroscience of Action. Oxford: Blackwells.
    Jenkins, I.H., Brooks, D.J., Nixon, P.D., Frackowiak, R.S.J. & Passingham, R.E. (1994). ‘Motor sequence learning: a study with positron emission tomography.’Journal of Neuroscience, 14, pp. 1775–90.
    Johnson-Laird, P.N. (1983). Mental Models. Cambridge, UK: Cambridge University Press.
    Jueptner, M., Stephan, K.M., Frith, C.D., Brooks, D.J., Frackowiak, R.S.J. & Passingham, R.E. (1996). ‘The anatomy of motor learning. The frontal cortex and attention to action.’Journal of Neurophysiology, 77, pp. 1313–24.
    Kammer, T., Bellemann, M.E., Guckel, F., Brix, G., Gass, A., Shlemmer, H. & Spitser, M. (1997). ‘Functional MR imaging of the prefrontal cortex: specific activation in a working memory task.’Magnetic Resonance Imaging, 15 (8), pp. 879–89. http://dx.doi.org/10.1016/S0730-725X%2897%2900021-0
    Kellman, P.J. (1993). ‘Kinematic foundations of infant visual perception.’ in C.E.Granrud (ed.) Visual Perception and Cognition in Infancy. Hillsdale, NJ: Lawrence Erlbaum.
    Kellman, P.J., Geltiman, H. & Spelke, E.R. (1987). ‘Object observer motion in the perception of objects by infants.’Journal of Experimental Psychology: Human Perception and Performance, 13, pp. 586–93. http://dx.doi.org/10.1037/0096-1523.13.4.586
    Kellman, P.J. & Spelke, E.R. (1983). ‘Perception of partly occluded objects in infancy.’Cognitive Psychologt, 15, pp. 483–524. http://dx.doi.org/10.1016/0010-0285%2883%2990017-8
    Kinomura, S., Larsson, J., Gulyas, B. & Roland, P.E. (1996). ‘Activation by attention of the human reticular formation and thalamic intralaminar nuclei.’Science, 274, pp. 512–15. http://dx.doi.org/10.1126/science.271.5248.512
    Kinsboume, M. (1988). ‘Integrated field theory of consciousness.’ in A.J.Marcel & E.Bisiach (eds) Consciousness in Contemporary Science. Oxford: Clarendon Press.
    Kinsboume, M. (1995). ‘The intralaminar thalamic nuclei.’Consciousness and Cognition, 4, pp. 167–71. http://dx.doi.org/10.1006/ccog.1995.1023
    Kohler, I. (1964). ‘The formation and transformation of the perceptual world.’ (Fiss, H., Trans.). Psychological Issues, 3, pp. 1–173.
    Köhler, W. (1925). The Mentality of Apes. New York: Harcourt Brace.
    Kohonen, T. (1984). Self-organization and Associative Memory. New York: Springer.
    Komhuber, H. & Deecke, L. (1965). ‘Hirnpotentialänderungen bei Wilkürbe-wegungen und passiven Bewegungen des Menschen: Bereitschaftspotentiale und Reafferente Potentiale.’ In Pflüger's Archiv der Gesamten Physiologie. Menschen – Tiere, 284, pp. 1–17.
    Kosslyn, S.M. (1978). ‘Imagery and internal representations.’ in E.Rosch & B.B.Lloyd (eds) Cognition and Categorization. Hillsdale, NJ: Lawrence Erlbaum.
    Kosslyn, S.M. (1983). Ghosts in the Mind's Machine: creating and using images in the brain. New York: W.W. Norton.
    Kosslyn, S.M., Thompson, W.L., Kim, I.J. & Alpert, N.M. (1995). ‘Topographical representations of mental images in primary visual cortex.’Nature, 378 (6556), pp. 496–8. http://dx.doi.org/10.1038/378496a0
    Krause, W., Gibbons, H. & Shack, B. (1998). ‘Concept activation and coordination of activation procedure require two different networks.’Neuroreport, 9 (7), pp. 1849–53. http://dx.doi.org/10.1097/00001756-199805110-00071
    Krechevski, I. (1932). ‘“Hypotheses” in rats.’Psychological Review, 39, pp. 516–32. http://dx.doi.org/10.1037/h0073500
    Krushinski, L.V. (1965). ‘Solutions of elementary problems by animals on the basis of extrapolation.’ In N.Wiener & J.P.Schade (eds) Cybernetics and the Nervous System. Amsterdam: Elsevier.
    Lacquantini, F. & Maioli, C. (1965). ‘The role of preparation and tuning anticipatory to reflex responses during catching.’ In N.Wiener & J.P.Scade (eds) Cybernetics and the Nervous System. Amsterdam: Elsevier.
    Legerstee, M. (1998). ‘Mental and bodily awareness in infancy: consciousness of self-existence.’Journal of Consciousness Studies, S (5–6), pp. 627–44.
    Libet, B. (1993). ‘The neural time factor in conscious and unconscious events.’ In Experimental and Theoretical Studies of Consciousness. CIBA Foundation Symposium 174. New York: John Wiley & Sns.
    Libet, B. (1994). ‘A testable field theory of mind-brain interaction.’Journal of Consciousness Studies, 1 (1), pp. 119–26.
    Libet, B., Wright, E.W. & Gleason, C. (1982). ‘Readiness potentials preceding unrestricted “spontaneous” vs. pre-planned voluntary acts.’Electroencephalography and Clinical Neurophysiology, 54, pp. 322–35. http://dx.doi.org/10.1016/0013-4694%2882%2990181-X
    Luria, A.R. (1959). ‘Disorders of “simultaneous perception” in case of bilateral occipitoparietal brain injury.’Brain, 83, pp. 437–49. http://dx.doi.org/10.1093/brain/82.3.437
    McGinn, C. (1991). The Problem of Consciousness. Oxford: Basil Blackwell.
    McGuire, P.K., Paulesu, E., Frackowiak, R.S. & Frith, C.D. (1996). ‘Brain activity during stimulus independent thought.’Neuroreport, 7 (13), pp. 2095–9.
    Maguire, E.A., Frackowiak, R.S.J. & Frith, C.D. (1997). ‘Recalling routes around London: activation of the right hippocampus in taxi drivers.’Journal of Neuroscience, 17 (18), pp. 7103–10.
    Maquet, P., Degueldre, C., Delfiore, G., Aerts, J., Peters, J.-M, Luxen, A. & Franck, G. (1997). ‘Functional neuroanatomy of human slow wave sleep.’Journal of Neuroscience, 17 (8), pp. 2807–12.
    Marr, D. (1982). Vision. San Francisco: Freeman.
    Marshall, J.C., Halligan, P.W. & Robertson, I.H. (1993). ‘Contemporary theories of unilateral neglect: a critical review.’ In L.H.Robertson & J.C.Marshall (eds) Unilateral Neglect: Clinical and Experimental Studies. Hove, UK: Lawrence Erlbaum.
    Melzack, R. (1990). ‘Phantom limb pain.’Trends in Neuroscience, 13 (3), pp. 88–92. http://dx.doi.org/10.1016/0166-2236%2890%2990179-E
    Melzack, R. & Wall, P.D. (1996). The Challenge of Pain. London: Penguin.
    Meredith, S. (1991). As reported in New Scientist, 5 September, p. 52.
    Milner, A.D. & Goodale, M.A. (1995). The Visual Brain in Action. Oxford: Oxford University Press.
    Minsky, M. (1986). The Society of Mind. New York: Simon & Schuster.
    Mountcastle, V.B., Lynch, J.C., Georgopolous, A., Sakata, H. & Acuna, C. (1975). ‘Posterior parietal association cortex of the monkey: command functions for operation within extrapersonal space’. Journal of Neurophysiology, 38, pp. 871–908.
    Nagel, T. (1974). ‘What is it like to be a bat?’Philosophical Review, 38, pp. 435–50. http://dx.doi.org/10.2307/2183914
    Neisser, U. (1976). Cognition and Reality. San Francisco: Freeman.
    Newman, J. & Baars, B.J. (1993). ‘A neural attentional model for access to consciousness. A Global Workspace perspective.’Concepts in Neuroscience, 4 (2), pp. 255–90.
    Nobre, A.C., Sebestyen, G.N., Gitelman, D.R., Mesulam, M.M., Frackowiak, R.S. & Frith, C.D. (1997). ‘Functional localization of the system for visuospatial attention using positron emission tomography.’Brain, 120 (3), pp. 515–33. http://dx.doi.org/10.1093/brain/120.3.515
    Noton, D. & Stark, L. (1971). ‘Scanpaths in saccadic eye movements while viewing and recognising patterns.’Vision Research, 11, pp. 929–41. http://dx.doi.org/10.1016/0042-6989%2871%2990213-6
    Nyberg, L. (1998). ‘Mapping episodic memory.’Behavioural Brain Research, 90 (2), pp. 107–14. http://dx.doi.org/10.1016/S0166-4328%2897%2900094-6
    O'Keefe, J. (1976). ‘Place units in the hippocampus of the freely moving rat.’Experimental Neurology, 51, pp. 78–109. http://dx.doi.org/10.1016/0014-4886%2876%2990055-8
    Olsen, C.R. & Gettner, S.N. (1995). ‘Object-centered direction selectivity in the macaque supplementary eye fields.’Science, 269, pp. 985–8. http://dx.doi.org/10.1126/science.7638625
    Olson, E.T. (1998). ‘There is no problem of the self.’Journal of Consciousness Studies, 5 (5–6), pp. 645–57.
    Olton, D.S. (1979). ‘Mazes, maps and memory.’American Psychologist, 34, pp. 588–96. http://dx.doi.org/10.1037/0003-066X.34.7.583
    Owen, A.M., Milner, B., Petrides, M. & Evans, AC (1996). ‘Memory for object features versus memory for object location: a positron-emission tomography study of encoding and retrieval processes.’Proceedings of the National Academy of Science, USA, 93 (17), pp. 9212–17. http://dx.doi.org/10.1073/pnas.93.17.9212
    Pani, J.R. (1982). ‘A functional approach to mental imagery.’ Paper presented at the twenty-third annual meeting of the Psychonomic Society, Baltimore, MD.
    Penfield, W.G. & Jasper, H. (1954). Epilepsy and the Functional Anatomy of the Human Brain. Boston: Little, Brown.
    Penrose, R. (1989). The Emperor's New Mind. Oxford: Oxford University Press.
    Penrose, R. (1994). Shadows of the Mind. Oxford: Oxford University Press.
    Perner, J. (1991). Understanding the Representational Mind. Cambridge, MA: MIT Press.
    Perner, J. & Ruffman, T. (1995). ‘Episodic memory and autonoetic consciousness: developmental evidence and a theory of childhood amnesia.’Journal of Experimental Child Psychology, 59, pp. 516–48. http://dx.doi.org/10.1006/jecp.1995.1024
    Perrett, D., Harries, H., Mistlin, A.J. & Citty, A.J. (1990). ‘Three stages in the classification of body movements by visual neurons.’ In H.Barlow, C.Blakemore & M.Weston-Smith (eds) Images and Understanding. Cambridge, UK: Cambridge University Press.
    Piaget, J. (1954). The Child's Conception of the World. London: Routledge & Kegan Paul.
    Piaget, J. & Inhelder, B. (1956). The Child's Conception of Space. New York: Humanities Press.
    Pinker, S. (1997). How the Mind Works. New York: W.W. Norton.
    Pribram, K.H. (1999). ‘Brain and the composition of conscious experience.’Journal of Consciousness Studies, 6 (5), pp. 19–42.
    Pylyshyn, Z.W. (1973). ‘What the mind's eye tells the mind's brain.’Psychological Bulletin, 80, pp. 1–24. http://dx.doi.org/10.1037/h0034650
    Quine, W.V. (1960). Word and Object. Cambridge, MA: MIT Press.
    Ramachandran, V.S. & Hirstein, W. (1998). ‘The perception of phantom limbs.’ The D.O. Hebb lecture. Brain, 121 (9), pp. 1603–30. http://dx.doi.org/10.1093/brain/121.9.1603
    Rader, N & Stern, J.D. (1982). ‘Visually elicited reaching in neonates.’Child Development, 53, pp. 1004–7. http://dx.doi.org/10.2307/1129140
    Rieser, J.J., Guth, D.A. & Hill, E.W. (1986). ‘Sensitivity to perceptive structure while walking without vision.’Perception, 15, pp. 173–88. http://dx.doi.org/10.1068/p150173
    Rizzolatti, G., Fadiga, L., Fogassi, L. & Gallese, V. (1997). ‘The space around us.’Science, 277, pp. 190–1. http://dx.doi.org/10.1126/science.277.5323.190
    Roberts, A.C., Robbins, T.W. & Weiskrantz, L. (eds) (1998). The Prefrontal Cortex. Oxford: Oxford University Press. http://dx.doi.org/10.1093/acprof:oso/9780198524410.001.0001
    Rochat, P. & Hespos, S.J. (1996). ‘Tracking and anticipating invisible transformations by 4- to 8-months old infants.’Cognitive Development, 11, pp. 3–17. http://dx.doi.org/10.1016/S0885-2014%2896%2990025-8
    Roelfsema, P.R. (1998). ‘Solutions for the binding problem.’Zeitung für Naturforschung, 53 (7–8), pp. 691–715.
    Roland, P.E. & Gulyas, B. (1994). ‘Visual imagery and visual representation.’Trends in Neuroscience, 7, pp. 2373–89.
    Rose, S. (1973) The Conscious Brain. London: Weidenfeld & Nicholson.
    Rosenfield, I. (1992). The Strange, Familiar and Forgotten: An anatomy of consciousness. London: Vintage.
    Rosenthal, D. (1993). ‘Thinking that one thinks.’ In M.Davies & G.W.Humphreys (eds) Consciousness: psychology and philosophical essays. Oxford: Blackwells.
    Rosier, F., Heil, M. & Hennighausen, E. (1995). ‘Exploring memory functions by means of brain electrical topography: a review.’Brain Topography, 7 (4), pp. 301–13. http://dx.doi.org/10.1007/BF01195256
    Ryle, G. (1949). The Concept of Mind. London: Hutchinson.
    Shacter, D.L., Uecker, A., Reiman, E., Yun, L.S., Bandy, D., Chen, K., Cooper, L.A. & Curran, T. (1997). ‘Effects of size and orientation change on hippocampal activation during episodic recognition: a PET study.’Neuroreports, 8 (18), pp. 3993–8. http://dx.doi.org/10.1097/00001756-199712220-00028
    Schilder, P. (1935). ‘The image and appearance of the human body.’Psychological Monographs, 4. London: Kegan, Trench & Trubner.
    Schupp, H.T., Lutzenberger, W., Birbaumer, N., Miltner, W. & Braun, C. (1994). ‘Neurophysiological differences between perception and imagery:Brain Research, 2, pp. 77–86.
    Seager, W. (1995). ‘Consciousness, information and panpsychism:Journal of Consciousness Studies, 2 (3), pp. 272–88.
    Searle, J.R. (1990). ‘Consciousness, explanatory inversion, and cognitive science.’Behavioral and Brain Sciences, 13, pp. 585–642. http://dx.doi.org/10.1017/S0140525X00080304
    Searle, J.R. (1992). The Rediscovery of the Mind. Cambridge, MA: MIT Press.
    Searle, J.R. (1997). The Mystery of Consciousness. London: Granta Books.
    Segal, S.J. & Fusella, V. (1970). ‘Influence of imagined pictures and sounds on detection of visual and auditory Signals.’Journal of Experimental Psychology, 83, pp. 458–64. http://dx.doi.org/10.1037/h0028840
    Servos, P. & Goodale, M.A. (1995). ‘Preserved visual imagery in visual form agnosia:Neuropsychologia, 33 (11), pp. 1383–94. http://dx.doi.org/10.1016/0028-3932%2895%2900071-A
    Shallice, T. (1982). ‘Specific impairment in planning.’Proceedings of the Royal Society, 298, pp. 199–209.
    Shallice, T., Fletcher, P., Frith, C.D., Grasby, P., Frackowiak, R.S.J. & Dolan, R.J. (1994). ‘Brain regions associated with the acquisition and retrieval of verbal episodic memory:Nature, 386, pp. 633–5http://dx.doi.org/10.1038/368633a0
    Shepard, R.N. (1984). ‘Kinematics of perceiving, imagining, thinking and dreaming:Psychological Review, 91, pp. 417–47. http://dx.doi.org/10.1037/0033-295X.91.4.417
    Shepard, R.N. & Metzler, J. (1971). ‘Mental rotation of three-dimensional objects.’Science, 171, pp. 701–3. http://dx.doi.org/10.1126/science.171.3972.701
    Smmerhoff, G. (1974). Logic of the Living Brain. London: John Wiley & Sns.
    Smmerhoff, G. (1990). Life, Brain and Consciousness. Amsterdam: Elsevier.
    Spelke, E.S. & Van de Walle, G.A. (1993). ‘Perceiving and reasoning about objects: insights from infants.’ In N.Eilan, R.McCarthy & W.Brewer (eds) Spatial Representation. Oxford: Basil Blackwell.
    Sperry, R.W. (1987). ‘Split brain and the mind: In R.Gregory & O.L.Zangwill (eds) The Oxford Companion to the Mind. Oxford: Oxford University Press.
    Standing, L. (1973). ‘Learning 10,000 pictures:Quarterly Journal of Experimental Psychology, 25, pp. 207–22. http://dx.doi.org/10.1080/14640747308400340
    Stoet, G. (1998). ‘The role of feature integration in action planning.’ Unpublished dissertation. University of Munich.
    Strange, B.A., Fletcher, P.C., Henson, R.N., Friston, K.J. & Dolan, R.J. (1999). ‘Segregating the functions of the human hippocampus:Proceedings of the National Academy of Science, 96 (7), pp. 4034–9http://dx.doi.org/10.1073/pnas.96.7.4034
    Strawson, G. (1997). ‘The self.’Journal of Consciousness Studies, 4 (5–6), pp. 405–28.
    Sutherland, S. (1989). The Macmillan Dictionary of Psychology. London: Macmillan Press.
    Taube, J.S., Muller, R.U. & Ranck, J.B. (1990). ‘Head-direction cells recorded from the postsubiculum in freely moving rats.’Journal of Neuroscience, 10, pp. 420–35.
    Tolman, E.C. (1932). Purposive Behavior in Animals and Men. New York: Appleton Century.
    Tolman, E.C. (1948). ‘Cognitive maps in rats and men.’Psychological Review, 55, pp. 189–208. http://dx.doi.org/10.1037/h0061626
    Tulving, E., Markowitsch, H.J., Kapur, S., Habib, R. & Houle, S. (1994). ‘Novelty encoding in the human brain: positron emission tomography data.’Neuroreport, 5 (18), pp. 2525–8. http://dx.doi.org/10.1097/00001756-199412000-00030
    Umeno, M.M. & Goldberg, M.F. (1997). ‘Spatial processing in monkey frontal eye field. (1) Predictive visual responses.’Journal of Neurophysiology, 78 (3), pp. 1373–83.
    Van der Meer, A.L.H., van der Weel, F.R. & Lee, D.N. (1950). ‘The functional significance of arm movements in neonates.’Science, 267, pp. 893–4.
    Walter, W. Grey (1964). ‘Slow potential waves in the human brain associated with expectancy, attention and decision.’Zeitschrift für die gesamte Neurologie, 206, pp. 309–22.
    Watanabe, M. (1996). ‘Reward expectancies in primate prefrontal cortex.’Nature, 382, pp. 629–32. http://dx.doi.org/10.1038/382629a0
    Weiskrantz, L. (1997). Consciousness Lost and Found. Oxford: Oxford University Press.
    Wessel, K., Zeffiro, T., Toro, C. & Hallett, M. (1997). ‘Self-paced versus metronome-paced finger movements. A positron emission tomography study.’Journal of Neuroimaging, 7 (3), pp. 145–51.
    Wilkins, K.L., McGrath, P.J., Finley, G.A. & Katz, J. (1998). ‘Phantom sensations and phantom limb pain in child and adolescent amputees.’Pain, 78 (1), pp. 7–12. http://dx.doi.org/10.1016/S0304-3959%2898%2900109-2
    Wurtz, R.H., Goldberg, M.E. & Robinson, D.L. (1982). ‘Brain mechanisms of visual attention.’Scientific American, 246 (6), pp. 100–5. http://dx.doi.org/10.1038/scientificamerican0682-124
    Wynn, K. (1992). ‘Addition and subtraction by human infants.’Nature, 358 (6389), pp. 749–54. http://dx.doi.org/10.1038/358749a0
    Zaporozhets, A.V. (1965). ‘The development of perception in the pre-school child.’European Research in Cognitive Development, 30 (2). Chicago: University of Chicago Press.
    Zeki, S. (1993). A Vision of the Brain. Oxford: Basil Blackwell.

    • Loading...
Back to Top