Understanding Consciousness: Its Function and Brain Processes
`This is surely the ultimate expression of the top-down approach to consciousness, written with Sommerhoff's characteristic clarity and precision. It says far more than other books four times the size of this admirably concise volume. This book is destined to become a pillar of the subject' -Rodney Cotterill, Technical University of Denmark The problem of consciousness has been described as a mystery about which we are still in a terrible muddle and in Understanding Consciousness: Its Function and Brain Processes, the author unravels this mystery through a clarification of the main concepts related to consciousness, followed by a comprehensive biological explanation. Consequently, this book will be idea
- Front Matter
- Back Matter
- Subject Index
Part I: Consciousness Explained in Simple, Functional Terms
- Chapter 1: A Methodical Biological Approach and its Conclusions
- The Three Facets of Consciousness That Need to Be Covered
- The Two Perspectives That Need to Be Covered
- Four Propositions That Jointly Cover Both Requirements
- The Structural and Functional Senses of ‘Representation’
- The Validity of the Basic Model
- Chapter 2: Awareness of the Surrounding World
- The Running World Model (RWM)
- The Visual Contribution
- The Brain as an Anticipation Machine
- Imaginative Representations
- More about Entry into Consciousness
- The Question of the Underlying Neural Connections
- Chapter 3: Awareness of the Self as an Entity and of One's Thoughts and Feelings
- Introducing Self-Reference and Self-Awareness
- Problems Avoided by This Account of Self-Reference
- Self-Awareness and Attention
- Awareness of One's Thoughts and Feelings
- Chapter 4: A Closer Look at the Four Main Propositions
- The Primary Consciousness
- The IGR
- Protecting the Cortex from Overload
- Self-Reference Holds the Key
- The Qualia: Are They Really the ‘Hard’ Problem?
- An Interpretation of the Main Divisions of Mental Events
- The Freedom of the Will (1)
- The Nature of Functional Descriptions
- Do Functional Explanations Here Pose a Special Problem?
- The Directiveness of Organic Activities
- Computer Simulations and Computational Approaches
- Chapter 5: Questions and Answers
- Some Fundamental Questions That Now Have an Answer
- The Freedom of the Will (2)
- Molyneux's Question: When Sight is Restored to the Blind
- The Split Brain and the Unity of Consciousness
- The Thought Experiment of a Spectrum Inversion
- Do Human Foetuses Have Consciousness?
- Do Animals Have Consciousness?
- Could Computers or Robots Have Consciousness?
- Looking Across to the Philosophies of Mind
Part II: The Fabric of the Underlying Brain Processes
- Chapter 6: The RWM
- Evidence in Support of the Concept
- Selection for Attention and for Consciousness
- The Missing Limbs: The Phenomenon of Neglect
- The Extensive Range of Associations in the RWM
- Some Features of the RWM in Animals
- Chapter 7: Acquired Expectancies
- A Functional Definition of States of Expectancy
- Internal Representation of Spatial Relationships
- Chapter 8: Imaginative Representations
- Mental Images
- Concepts and Their Representations
- More Empirical Pointers
- Episodic Memory Recall
- Working Memory
- Chapter 9: Where Does Consciousness Reside in the Brain?
- No ‘Cartesian Theatre’
- Overview of the Main Structures Involved in Visuomotor Responses
- Evidence from Brain Lesions
- Evidence from Unit Responses
- Evidence from Physical Stimulation
- Evidence from Brain Imaging
- The Prefrontal Cortex
- The Seat of Consciousness: What Our Model Suggests
© Gerd Sommerhoff 2000
First published 2000
All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, transmitted or utilized in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, without permission in writing from the Publishers.
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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.[Page x]
Preface: Problems of Substance and of Presentation[Page xi]
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 [Page xii]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.
[Page xiii]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.)[Page xiv]
Appendix A: Real and Artificial Neurons[Page 155]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[Page 156]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 [Page 157]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 [Page 158]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 [Page 159]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 [Page 160]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 [Page 161]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[Page 162]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 PropositionsProposition 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.[Page 163]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 ConceptsStructural 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:
The Running World Model or RWM
- 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 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 [Page 164]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*. [Page 166]
- 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. [Page 167]
- 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, [Page 168]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*. [Page 169]
- 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*. [Page 170]
- 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. [Page 171]
- 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. [Page 172]
- 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.
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