- Email: [email protected]
Sensory systems
Sensory systems Editorial overview Wolf Singer* and Randall R Reed? Addresses ‘Max-Planck-Institute for Brain Research, Deutschordenstrasse 46, D-60528, Frankfurt, Germany; e-mail: singerampih-frankfurt.mpg.de tHoward Hughes Medical Institute, Department of Molecular Biology and Genetics, and Department of Neuroscience, The Johns Hopkins School of Medicine, 725 North Wolfe Street, Baltimore, Maryland 21205, USA; e-mail: [email protected] Current Opinion in Neurobiology 1997, 7:469-472 http://biomednet.com/elecref/0959438800700469 0 Current Biology Ltd ISSN 0959-4388
Introduction Sensory systems remain among the foremost paradigms for understanding the properties and organisation of the nervous system. The activities and special attributes of sensory systems at all levels, from the periphery to the most central regions of the brain, provide important pointers for how transduction of information and its subsequent processing can be combined to achieve sensitivity, specificity and plasticity. In this issue, a broad array of scientific approaches has been brought to bear on a diverse range of sensory modalities.
The extreme sensitivity
of sensory processing
The environmental selective pressure to evolve sensory systems with extraordinary sensitivity has given rise to a number of cases in which the physical parameters would seem to exceed those that could be achieved in biological systems. These systems appear to accomplish astonishing feats by central processing of signals derived from a large number of less discriminating and less sensitive primary sensory neurones. One particular example, the jamming avoidance response in weakly electric fish is considered by Kawasaki (pp 473-479). This behaviour provides an opportunity to explore the hyperacuity of a sensory system and the central mechanisms that underlie it. In contrast to the central mechanisms that contribute to hyperacuity, sensitivity in the auditory pathway arises from an active process in vertebrate hair cells which utilise a motor to mechanically amplify low intensity stimuli. The mechanisms for sensitivity in the outer hair cell are discussed by Hudspeth (pp 480-486). The auditory system is faced with having to transduce stimuli of energies that approach that of thermal noise. One attribute of sound stimuli that has been exploited by animals is its oscillatory, sinusoidal nature. The outer hair cell appears to undergo a variety of mechanical modulations, including the cylindrical shortening of the cell body in response to depolarisation. Although the existence of this active process is well accepted, only
recently have investigators begun to elucidate the cellular and molecular mechanisms that underlie this process and to understand the contribution of these amplification processes to auditory sensitivity. Acoustic location is achieved by exploiting interaural time differences. This function, mediated by brainstem neurones, requires that the time differences be retained along the auditory pathway. The review by Trussell (pp 487-492) highlights the recent advances in our understanding of the morphological, biophysical and biochemical adaptations that are required to maintain the critical timing in these pathways. In particular, the ability of the system to display plasticity suggests that timing differences are not intrinsic to the system but are subject to modulation by differential expression and activity of neurotransmitters and their associated receptors. The detection of painful stimuli differs in several respects from the other sensory modalities. The overriding consideration for the organism is to remove the affected part of the body from the painful stimulus. As a result, nociceptive neurones are polymodal and respond to heat, mechanical and chemical stimuli. In their’review, Cesare and McNaughton (pp 493-499) describe the considerable progress made recently at the physiological and molecular level in elucidating the transduction mechanisms and the modulation of neuronal sensitivity by bradykinin, prostaglandins and histamine. These agents play an important role in the sensitisation and desensitisation of the primary nociceptive response. The ability of the visual system to detect single photons is often quoted as an example of extreme sensitivity. Perhaps equally remarkable is the extraordinary range of light intensities that can be perceived by mammals. One process that contributes to this dynamic range, reviewed by Palczewski and Saari (pp SOO-504), is the inactivation of the transduction pathway by phosphorylation and protein-protein interactions. These processes are just some of the mechanisms that lead to reduced sensitivity. Additional processes as diverse as the modulation of retinal-specific guanylyl cyclases and the enzymes responsible for the metabolism of the retinal co-factor for rhodopsin also appear to contribute to the regulation of gain in the visual system.
Sensory processing in simple nervous systems The ability of insects to process sensory stimuli and evoke a wide repertoire of behavioural responses provides an opportunity to understand the mechanisms that me-
470
Sensory systems
diate these activities. Giurfa and Menzel (pp 505-513) summarise recent advances that have been achieved through the examination of complex behaviours in animals endowed with relatively simple neuronal circuitry. They provide evidence for distinct strategies that are used at different times in visually directed behavioural tasks. The application of these strategies is dependent on the nature of the visual cues.
Sensory codes, their generation modifiability
and
The extraction of features
Cognitive systems have to cope with combinatorial problems that result from the fact that perceptual objects are defined by unique constellations of features. Although the variety of basic features that nervous systems exploit to classify perceptual objects is limited, the diversity of such elementary features is virtually unlimited. In order to extract these basic features from sensory signals and to search for consistent relations among them, input signals have to be compared with one another. In the primary visual cortex of mammals, for example, particular spatial and temporal relations among the responses of retinal ganglion cells are evaluated by having the output of selected arrays of ganglion cells converge onto individual cortical neurones. This notion, already advocated in the pioneering studies of Hubel and Wiesel, has recently received further support from experiments suggesting that orientation-selective neurones receive converging input from linear arrays of retinal ganglion cells, the orientation of these linear arrays corresponding to the orientation preference of the respective cortical cells. However, the arguments and data presented in the review of Sompolinsky and Shapley (pp 514-522) suggest that the evaluation of relations among the responses of retinal ganglion cells may not be accomplished solely by such selective convergence in simple feedforward architectures but may, in addition, depend on highly dynamic interactions among groups of neurones that are coupled to each other through positive feedback loops. This is noteworthy for two reasons. First, it underlines the sophistication of cortical processing and demonstrates how difficult it is to arrive at a mechanistic understanding, even of processes as elementary as the generation of orientation-selective receptive fields. Second, it suggests that cortical operations may be much more dynamic than commonly assumed. The latter agrees with the growing evidence that the receptive fields of cortical neurones are not invariant but modified by the context in which their preferred feature is embedded. How well a cortical neurone responds to a particular trigger stimulus placed in its receptive field not only depends on the local configuration of the stimulus but also on the specific arrangement of contours outside the classical receptive field. Systematic investigations of these complex interactions are now becoming available in increasing number and their results indicate that cortical neurones
not only evaluate local relations between activity conveyed to them through subcortical input connections but also reflect by their modulated responses the spatial and the temporal context in which a particular trigger feature appears. The strategy to analyse and represent constellations of features by recombining input connections is iterated in prestriate visual cortical areas and leads to the generation of neurones that respond to constellations of features of ever increasing complexity. The extreme result of this representational strategy are neurones tuned to specific views of faces. Tanaka (pp 523-529) recapitulates the available data on response properties of neurones in those prestriate cortical areas that are involved in the processing and recognition of visual objects. In these higher areas, there are neurones that are selective for quite complex constellations of elementary features and, as in primary visual cortex, cells with similar preferences appear to be clustered in a columnar organisation. In general, these neurones are broadly tuned, suggesting that representations of individual objects consist of the joint activation of a cluster of neurones, each of which codes for a particular aspect of the object. Exceptions appear to be cells tuned to faces and objects with which the animal had been familiarised previously through extensive training. From evidence for experience-dependent modifications of receptive field properties, Tanaka concludes that the brain might use two strategies for the representation of objects: patterns of particular behavioural relevance, such as faces or highly familiar objects, appear to be represented by the specific responses of a few sharply tuned cells, whereas unfamiliar objects seem to be represented in a more distributed way. This implies that the receptive fields of neurones in higher cortical areas remain susceptible to extensive modifications in the adult. Experience-dependent
plasticity
The psychophysical evidence for perceptual learning, reviewed by Karni and Bertini (pp 530-535), also points towards substantial, experience-dependent malleability of visual functions in the adult. Here, the central issue is that practice with particular visual discrimination tasks leads to very long-lasting, if not permanent, improvement of the specific functions required for the performance of the trained tasks. Quite unexpectedly, these improvements include low-level visual functions, suggesting that modifications occur at processing levels as peripheral as the primary visual cortex. This contrasts the commonly held notion that response properties of neurones at peripheral levels of visual processing are no longer modifiable in the adult-but it agrees with the more recent evidence suggesting that response properties are not only determined by the architecture of rigid anatomical connections but also depends on dynamic interactions (see above). Two aspects of these perceptual learning phenomena are particularly fascinating. First, the specificity with which these functional changes occur
Editorial overview Singer and Reed
suggests that learning takes place selectively in those structures that are directly involved in the accomplishment of the task -and there appears to be a general rule that changes occur at the lowest possible level of processing. Second, the time course of the learning process and its dependence on central states show numerous similarities with developmental learning. So far, few attempts have been made to find electrophysiological correlates of these perceptual learning processes-but because the behavioural phenomena are so robust and clearly defined, it should be possible to exploit this paradigm when searching for correlates of learning. Signature of distributed codes
The search for neuronal codes and their experience-dependent modification has concentrated mainly on the response properties of individual neurones. This approach has been extremely fruitful, and most of our knowledge on the processing of sensory information is based on such data. However, it is conceivable that information is contained not only in the explicit responses of individual neurones but also in the temporal relations among the firing patterns of populations of simultaneously active neurones. Often, these relations are established by dynamic interactions among the neurones and, therefore, are not locked precisely to the temporal structure of the applied stimuli. Hence, these relations cannot be detected by comparing responses that have been obtained by recording sequentially from different neurones - but only if the activity of different neurones is recorded simultaneously with multiple electrodes. The most conspicuous examples of internally generated, temporal relations among the firing patterns of distributed neurones are synchronous oscillations. They are observed in a large variety of brain structures and occur at many different frequencies and spatial scales. Ritz and Sejnowski (pp 536-546) review recent data on the putative mechanisms that support the temporal patterning of neuronal responses and their synchronisation. This comprehensive review of a rapidly expanding field of research suggests that several different mechanisms cooperate: pacemaker currents in both excitatory and inhibitory neurones that are tuned to different oscillation frequencies, variable resonance properties that are determined by the geometry of dendritic arborizations, balanced interactions between excitatory and inhibitory neurones that lead to network oscillations and, finally, conduction delays that are tuned to sustain synchronous oscillations in a particular frequency range. Moreover, there is evidence that modulatory systems play a critical role in determining the frequency range of oscillations. Because the physiological effects and the relative contributions of these different mechanisms are often difficult to disentangle in neurophysiological experiments, simulation studies have become an increasingly important tool for the analysis of these dynamic processes. Ritz and Sejnowski have included these computational studies in their review
471
and, most importantly, give concise interpretations of their results -an effort that will be gratefully appreciated by neurobiologists who are not familiar with reading mathematical papers. A still unresolved and fruitfully controversial issue is whether these internally generated temporal relations among neuronal firing patterns have a function in neuronal processing, and, if so, which one. Ritz and Sejnowski review some of the current concepts and let the reader judge. The review by Laurent (pp 547-553) also focuses on the temporal patterning of neuronal responses, but concentrates on recent results on olfactory coding indicating that information is indeed contained in the precise temporal relations between the firing patterns of distributed neurones. Data from the olfactory system of insects suggest that the neuronal code of specific odours can only be deciphered by evaluating the precise temporal relations among the spike activity of a set of neurones and not by comparing the response amplitudes of individual neurones. Multielectrode recordings from the mammalian brain point in the same direction. There is increasing evidence for an internally generated, temporal patterning of responses and, in some cases, these patterns correlate as well or even better with sensory-motor processes than with modulations of the response amplitude of individual neurones. It may be worthwhile also to include analyses of such internally generated interactions and their modifications in the search for neuronal correlates of learning processes. Modifications of the receptive field properties of individual neurones tend to be slow, suggesting the possibility that rapid learning may result from modifications in those circuits that support the dynamic interactions among groups of neurones and determine the specific temporal patterning of the activity of such groups. Distributed processing
Evidence for distributed processing, albeit at a much higher level of complexity, is reviewed in the contributions by Courtney and Ungerleider (pp 554-561) and by Rizzolatti, Fogassi and Gallese (pp 562-567). Courtney and Ungerleider concentrate on recent fMRI data that permit identification of cortical regions involved in higher cognitive functions. The results indicate that many different cortical areas are active during any particular cognitive act -but they also show a puzzling degree of functional specialisation, in particular of higher cortical areas. The high sensitivity and spatial resolution of the fMR1 method makes it possible to track in a trial-by-trial analysis the-differential activation of various cortical areas in response to specific tasks. This approach has revealed close correlations between the primate and the human brain with respect to the functional specialisation and topological arrangement of cortical areas. Moreover, it is about to provide a wealth of fascinating data on the organisation of processes that are difficult or impossible to analyse in animals. This includes functions associated with
47 2
Sensory systems
language competence but also imagery and voluntary shifts of attention that are difficult to control if one cannot rely on verbal instructions and reports. This area of research is among the most rapidly expanding in the neurosciences and capable of bridging the gaps between data obtained from animal experimentation and behavioural studies in humans. With respect to the distributed nature of cortical processing, the data reviewed by Rizzolatti et al. paint a similar picture as the contribution of Courtney and Ungerleider. While the latter concentrate on the occipital and temporal regions of neocortex involved in object recognition, Rizzolatti et a/. review recent electrophysiological and imaging data on cortical regions subserving the location of objects in space and the preparation of appropriate reaching and grasping movements. These cortical areas form a highly interconnected network that includes parts of the occipital, the parietal and the frontal lobes. Electrophysiological recordings from neurones in the parietal cortex suggest fascinating relations between processes hitherto thought to be quite independent, such as the preparation of targeting movements on the one hand and voluntary shifts of attention in space on the other. Moreover, these results are likely to change classic concepts of the functional role of the parietal cortex. Patients with lesions in the parietal cortex suffer from contralateral sensory neglect and a distortion of their perception of contralateral hemispace. It has been inferred from this that the parietal cortex serves to generate a unified representation of space. Recent data indicate that each of the numerous areas in the parietal lobe is specialised to accomplish a particular sensory motor transformation that permits the programming of appropriate targeting movements of the hand, the arm, the eye, and the head, and each of these areas is closely interconnected with the respective regions in premotor cortex of the frontal lobe. It is thus difficult to disentangle sensory from motor functions, and it seems that the joint activity of all these areas together would serve as a dynamic representation of space. Summary
Together, the various contributions dealing with the organisation of sensory codes and representations emphasise the
distributed nature of neuronal processes. At all levels of processing, the responses of individual neurones appear to represent only components of the representational space that is dealt with by the various processing streams: components of perceptual objects in areas serving the identification and recognition of patterns, and components of sensory-motor acts in the processing stream devoted to the preparation and execution of targeting movements in space. The unitary concept of a particular object, located at a particular point in space, appears to be an emergent property of the joint activity of these various analytical processes. The responses of individual neurones at the top of the processing hierarchy devoted to object identification tell little about the location of objects in space because their receptive fields often extend over the whole visual field. Likewise, neurones in the processing stream devoted to the preparation of grasping movements code information about the shape of objects only in as much as is required to adjust the grip of the hands to the shape of the targetbut so far there is little evidence that the neurones signal anything more specific about the particular attributes of the objects, such as their fine texture, colour, or identity. This raises the challenging question of how the distributed computational results obtained at various processing levels of different processing streams are bound together, both within and across modalities.
Commentary: genomic imprinting
in the brain
Recent advances in the molecular genetics of mice and men have allowed the detailed analysis of genetically inherited diseases leading to brain dysfunction. A subset of these diseases, including Prader-Willi syndrome, Angelman syndrome, Turner’s syndrome, bipolar depression and schizophrenia, display unusual patterns of inheritance in which the phenotype differs depending on which parent contributes the defective gene. This phenomenon, genetic imprinting, is beginning to be understood at the molecular level and suggests differential roles for the maternal and paternal genomes in regulating cellular growth and the development of the nervous system. The Commentary by Keverne (pp 463468) summarises our current understanding of genomic imprinting in the nervous system.
Introduction Sensory systems remain among the foremost paradigms for understanding the properties and organisation of the nervous system. The activities and special attributes of sensory systems at all levels, from the periphery to the most central regions of the brain, provide important pointers for how transduction of information and its subsequent processing can be combined to achieve sensitivity, specificity and plasticity. In this issue, a broad array of scientific approaches has been brought to bear on a diverse range of sensory modalities.
The extreme sensitivity
of sensory processing
The environmental selective pressure to evolve sensory systems with extraordinary sensitivity has given rise to a number of cases in which the physical parameters would seem to exceed those that could be achieved in biological systems. These systems appear to accomplish astonishing feats by central processing of signals derived from a large number of less discriminating and less sensitive primary sensory neurones. One particular example, the jamming avoidance response in weakly electric fish is considered by Kawasaki (pp 473-479). This behaviour provides an opportunity to explore the hyperacuity of a sensory system and the central mechanisms that underlie it. In contrast to the central mechanisms that contribute to hyperacuity, sensitivity in the auditory pathway arises from an active process in vertebrate hair cells which utilise a motor to mechanically amplify low intensity stimuli. The mechanisms for sensitivity in the outer hair cell are discussed by Hudspeth (pp 480-486). The auditory system is faced with having to transduce stimuli of energies that approach that of thermal noise. One attribute of sound stimuli that has been exploited by animals is its oscillatory, sinusoidal nature. The outer hair cell appears to undergo a variety of mechanical modulations, including the cylindrical shortening of the cell body in response to depolarisation. Although the existence of this active process is well accepted, only
recently have investigators begun to elucidate the cellular and molecular mechanisms that underlie this process and to understand the contribution of these amplification processes to auditory sensitivity. Acoustic location is achieved by exploiting interaural time differences. This function, mediated by brainstem neurones, requires that the time differences be retained along the auditory pathway. The review by Trussell (pp 487-492) highlights the recent advances in our understanding of the morphological, biophysical and biochemical adaptations that are required to maintain the critical timing in these pathways. In particular, the ability of the system to display plasticity suggests that timing differences are not intrinsic to the system but are subject to modulation by differential expression and activity of neurotransmitters and their associated receptors. The detection of painful stimuli differs in several respects from the other sensory modalities. The overriding consideration for the organism is to remove the affected part of the body from the painful stimulus. As a result, nociceptive neurones are polymodal and respond to heat, mechanical and chemical stimuli. In their’review, Cesare and McNaughton (pp 493-499) describe the considerable progress made recently at the physiological and molecular level in elucidating the transduction mechanisms and the modulation of neuronal sensitivity by bradykinin, prostaglandins and histamine. These agents play an important role in the sensitisation and desensitisation of the primary nociceptive response. The ability of the visual system to detect single photons is often quoted as an example of extreme sensitivity. Perhaps equally remarkable is the extraordinary range of light intensities that can be perceived by mammals. One process that contributes to this dynamic range, reviewed by Palczewski and Saari (pp SOO-504), is the inactivation of the transduction pathway by phosphorylation and protein-protein interactions. These processes are just some of the mechanisms that lead to reduced sensitivity. Additional processes as diverse as the modulation of retinal-specific guanylyl cyclases and the enzymes responsible for the metabolism of the retinal co-factor for rhodopsin also appear to contribute to the regulation of gain in the visual system.
Sensory processing in simple nervous systems The ability of insects to process sensory stimuli and evoke a wide repertoire of behavioural responses provides an opportunity to understand the mechanisms that me-
470
Sensory systems
diate these activities. Giurfa and Menzel (pp 505-513) summarise recent advances that have been achieved through the examination of complex behaviours in animals endowed with relatively simple neuronal circuitry. They provide evidence for distinct strategies that are used at different times in visually directed behavioural tasks. The application of these strategies is dependent on the nature of the visual cues.
Sensory codes, their generation modifiability
and
The extraction of features
Cognitive systems have to cope with combinatorial problems that result from the fact that perceptual objects are defined by unique constellations of features. Although the variety of basic features that nervous systems exploit to classify perceptual objects is limited, the diversity of such elementary features is virtually unlimited. In order to extract these basic features from sensory signals and to search for consistent relations among them, input signals have to be compared with one another. In the primary visual cortex of mammals, for example, particular spatial and temporal relations among the responses of retinal ganglion cells are evaluated by having the output of selected arrays of ganglion cells converge onto individual cortical neurones. This notion, already advocated in the pioneering studies of Hubel and Wiesel, has recently received further support from experiments suggesting that orientation-selective neurones receive converging input from linear arrays of retinal ganglion cells, the orientation of these linear arrays corresponding to the orientation preference of the respective cortical cells. However, the arguments and data presented in the review of Sompolinsky and Shapley (pp 514-522) suggest that the evaluation of relations among the responses of retinal ganglion cells may not be accomplished solely by such selective convergence in simple feedforward architectures but may, in addition, depend on highly dynamic interactions among groups of neurones that are coupled to each other through positive feedback loops. This is noteworthy for two reasons. First, it underlines the sophistication of cortical processing and demonstrates how difficult it is to arrive at a mechanistic understanding, even of processes as elementary as the generation of orientation-selective receptive fields. Second, it suggests that cortical operations may be much more dynamic than commonly assumed. The latter agrees with the growing evidence that the receptive fields of cortical neurones are not invariant but modified by the context in which their preferred feature is embedded. How well a cortical neurone responds to a particular trigger stimulus placed in its receptive field not only depends on the local configuration of the stimulus but also on the specific arrangement of contours outside the classical receptive field. Systematic investigations of these complex interactions are now becoming available in increasing number and their results indicate that cortical neurones
not only evaluate local relations between activity conveyed to them through subcortical input connections but also reflect by their modulated responses the spatial and the temporal context in which a particular trigger feature appears. The strategy to analyse and represent constellations of features by recombining input connections is iterated in prestriate visual cortical areas and leads to the generation of neurones that respond to constellations of features of ever increasing complexity. The extreme result of this representational strategy are neurones tuned to specific views of faces. Tanaka (pp 523-529) recapitulates the available data on response properties of neurones in those prestriate cortical areas that are involved in the processing and recognition of visual objects. In these higher areas, there are neurones that are selective for quite complex constellations of elementary features and, as in primary visual cortex, cells with similar preferences appear to be clustered in a columnar organisation. In general, these neurones are broadly tuned, suggesting that representations of individual objects consist of the joint activation of a cluster of neurones, each of which codes for a particular aspect of the object. Exceptions appear to be cells tuned to faces and objects with which the animal had been familiarised previously through extensive training. From evidence for experience-dependent modifications of receptive field properties, Tanaka concludes that the brain might use two strategies for the representation of objects: patterns of particular behavioural relevance, such as faces or highly familiar objects, appear to be represented by the specific responses of a few sharply tuned cells, whereas unfamiliar objects seem to be represented in a more distributed way. This implies that the receptive fields of neurones in higher cortical areas remain susceptible to extensive modifications in the adult. Experience-dependent
plasticity
The psychophysical evidence for perceptual learning, reviewed by Karni and Bertini (pp 530-535), also points towards substantial, experience-dependent malleability of visual functions in the adult. Here, the central issue is that practice with particular visual discrimination tasks leads to very long-lasting, if not permanent, improvement of the specific functions required for the performance of the trained tasks. Quite unexpectedly, these improvements include low-level visual functions, suggesting that modifications occur at processing levels as peripheral as the primary visual cortex. This contrasts the commonly held notion that response properties of neurones at peripheral levels of visual processing are no longer modifiable in the adult-but it agrees with the more recent evidence suggesting that response properties are not only determined by the architecture of rigid anatomical connections but also depends on dynamic interactions (see above). Two aspects of these perceptual learning phenomena are particularly fascinating. First, the specificity with which these functional changes occur
Editorial overview Singer and Reed
suggests that learning takes place selectively in those structures that are directly involved in the accomplishment of the task -and there appears to be a general rule that changes occur at the lowest possible level of processing. Second, the time course of the learning process and its dependence on central states show numerous similarities with developmental learning. So far, few attempts have been made to find electrophysiological correlates of these perceptual learning processes-but because the behavioural phenomena are so robust and clearly defined, it should be possible to exploit this paradigm when searching for correlates of learning. Signature of distributed codes
The search for neuronal codes and their experience-dependent modification has concentrated mainly on the response properties of individual neurones. This approach has been extremely fruitful, and most of our knowledge on the processing of sensory information is based on such data. However, it is conceivable that information is contained not only in the explicit responses of individual neurones but also in the temporal relations among the firing patterns of populations of simultaneously active neurones. Often, these relations are established by dynamic interactions among the neurones and, therefore, are not locked precisely to the temporal structure of the applied stimuli. Hence, these relations cannot be detected by comparing responses that have been obtained by recording sequentially from different neurones - but only if the activity of different neurones is recorded simultaneously with multiple electrodes. The most conspicuous examples of internally generated, temporal relations among the firing patterns of distributed neurones are synchronous oscillations. They are observed in a large variety of brain structures and occur at many different frequencies and spatial scales. Ritz and Sejnowski (pp 536-546) review recent data on the putative mechanisms that support the temporal patterning of neuronal responses and their synchronisation. This comprehensive review of a rapidly expanding field of research suggests that several different mechanisms cooperate: pacemaker currents in both excitatory and inhibitory neurones that are tuned to different oscillation frequencies, variable resonance properties that are determined by the geometry of dendritic arborizations, balanced interactions between excitatory and inhibitory neurones that lead to network oscillations and, finally, conduction delays that are tuned to sustain synchronous oscillations in a particular frequency range. Moreover, there is evidence that modulatory systems play a critical role in determining the frequency range of oscillations. Because the physiological effects and the relative contributions of these different mechanisms are often difficult to disentangle in neurophysiological experiments, simulation studies have become an increasingly important tool for the analysis of these dynamic processes. Ritz and Sejnowski have included these computational studies in their review
471
and, most importantly, give concise interpretations of their results -an effort that will be gratefully appreciated by neurobiologists who are not familiar with reading mathematical papers. A still unresolved and fruitfully controversial issue is whether these internally generated temporal relations among neuronal firing patterns have a function in neuronal processing, and, if so, which one. Ritz and Sejnowski review some of the current concepts and let the reader judge. The review by Laurent (pp 547-553) also focuses on the temporal patterning of neuronal responses, but concentrates on recent results on olfactory coding indicating that information is indeed contained in the precise temporal relations between the firing patterns of distributed neurones. Data from the olfactory system of insects suggest that the neuronal code of specific odours can only be deciphered by evaluating the precise temporal relations among the spike activity of a set of neurones and not by comparing the response amplitudes of individual neurones. Multielectrode recordings from the mammalian brain point in the same direction. There is increasing evidence for an internally generated, temporal patterning of responses and, in some cases, these patterns correlate as well or even better with sensory-motor processes than with modulations of the response amplitude of individual neurones. It may be worthwhile also to include analyses of such internally generated interactions and their modifications in the search for neuronal correlates of learning processes. Modifications of the receptive field properties of individual neurones tend to be slow, suggesting the possibility that rapid learning may result from modifications in those circuits that support the dynamic interactions among groups of neurones and determine the specific temporal patterning of the activity of such groups. Distributed processing
Evidence for distributed processing, albeit at a much higher level of complexity, is reviewed in the contributions by Courtney and Ungerleider (pp 554-561) and by Rizzolatti, Fogassi and Gallese (pp 562-567). Courtney and Ungerleider concentrate on recent fMRI data that permit identification of cortical regions involved in higher cognitive functions. The results indicate that many different cortical areas are active during any particular cognitive act -but they also show a puzzling degree of functional specialisation, in particular of higher cortical areas. The high sensitivity and spatial resolution of the fMR1 method makes it possible to track in a trial-by-trial analysis the-differential activation of various cortical areas in response to specific tasks. This approach has revealed close correlations between the primate and the human brain with respect to the functional specialisation and topological arrangement of cortical areas. Moreover, it is about to provide a wealth of fascinating data on the organisation of processes that are difficult or impossible to analyse in animals. This includes functions associated with
47 2
Sensory systems
language competence but also imagery and voluntary shifts of attention that are difficult to control if one cannot rely on verbal instructions and reports. This area of research is among the most rapidly expanding in the neurosciences and capable of bridging the gaps between data obtained from animal experimentation and behavioural studies in humans. With respect to the distributed nature of cortical processing, the data reviewed by Rizzolatti et al. paint a similar picture as the contribution of Courtney and Ungerleider. While the latter concentrate on the occipital and temporal regions of neocortex involved in object recognition, Rizzolatti et a/. review recent electrophysiological and imaging data on cortical regions subserving the location of objects in space and the preparation of appropriate reaching and grasping movements. These cortical areas form a highly interconnected network that includes parts of the occipital, the parietal and the frontal lobes. Electrophysiological recordings from neurones in the parietal cortex suggest fascinating relations between processes hitherto thought to be quite independent, such as the preparation of targeting movements on the one hand and voluntary shifts of attention in space on the other. Moreover, these results are likely to change classic concepts of the functional role of the parietal cortex. Patients with lesions in the parietal cortex suffer from contralateral sensory neglect and a distortion of their perception of contralateral hemispace. It has been inferred from this that the parietal cortex serves to generate a unified representation of space. Recent data indicate that each of the numerous areas in the parietal lobe is specialised to accomplish a particular sensory motor transformation that permits the programming of appropriate targeting movements of the hand, the arm, the eye, and the head, and each of these areas is closely interconnected with the respective regions in premotor cortex of the frontal lobe. It is thus difficult to disentangle sensory from motor functions, and it seems that the joint activity of all these areas together would serve as a dynamic representation of space. Summary
Together, the various contributions dealing with the organisation of sensory codes and representations emphasise the
distributed nature of neuronal processes. At all levels of processing, the responses of individual neurones appear to represent only components of the representational space that is dealt with by the various processing streams: components of perceptual objects in areas serving the identification and recognition of patterns, and components of sensory-motor acts in the processing stream devoted to the preparation and execution of targeting movements in space. The unitary concept of a particular object, located at a particular point in space, appears to be an emergent property of the joint activity of these various analytical processes. The responses of individual neurones at the top of the processing hierarchy devoted to object identification tell little about the location of objects in space because their receptive fields often extend over the whole visual field. Likewise, neurones in the processing stream devoted to the preparation of grasping movements code information about the shape of objects only in as much as is required to adjust the grip of the hands to the shape of the targetbut so far there is little evidence that the neurones signal anything more specific about the particular attributes of the objects, such as their fine texture, colour, or identity. This raises the challenging question of how the distributed computational results obtained at various processing levels of different processing streams are bound together, both within and across modalities.
Commentary: genomic imprinting
in the brain
Recent advances in the molecular genetics of mice and men have allowed the detailed analysis of genetically inherited diseases leading to brain dysfunction. A subset of these diseases, including Prader-Willi syndrome, Angelman syndrome, Turner’s syndrome, bipolar depression and schizophrenia, display unusual patterns of inheritance in which the phenotype differs depending on which parent contributes the defective gene. This phenomenon, genetic imprinting, is beginning to be understood at the molecular level and suggests differential roles for the maternal and paternal genomes in regulating cellular growth and the development of the nervous system. The Commentary by Keverne (pp 463468) summarises our current understanding of genomic imprinting in the nervous system.