The status of cognitive neuroscience Stephen M. Kosslyn Harvard Cognitive
University,
neuroscience
fields: experimental science.
The
approach
Cambridge, Massachusetts,
rests on findings,
psychology,
strong
greater integration
trend
and Lisa M. Shin
methods,
systems-level
over
the
past
few
across these fields. The influence
on current
research
on memory,
and theory
neuroscience, years
USA from
three
and computer
has
been
for
a
of this interdisciplinary
perception,
and language will
be illustrated.
Current
Opinion
in Neurobiology
Introduction Researchers in the field of cognitive neuroscience seek to understand how brain function gives rise to mental activ ities such as perception, memory, and language. These goals are shared by several other fields, but cognitive neuroscience has a uniquely interdisciplinary approach. It draws on methods and theoretical constructs from three older fields: experimental psychology, neuroscience, and computer science. (For a brief history of how cognitive neuroscience grew out of these fields, see [ 11.) Research in cognitive neuroscience still bears the stamp of each of these disciplines, and is often particularly beholden to one of them. Nevertheless, the integration that is taking place across the different facets of the field is particularly striking, as will be illustrated in this review.
Tips of the iceberg Our purpose is not to review the current status of all of cognitive neuroscience, or even just one area. Rather, it is to illustrate the way the field as a whole appears to be developing. Thus, the following examples have been chosen to highlight certain trends. Let us begin by considering ways in which experimental psychology has given rise to recent work in cognitive neuroscience. Experimental psychology is, at its roots, concerned with the study of behavior. By carefully examining behavior, psychologists hope to infer principles about how the mind/brain operates. Two areas of experimental psychology have recently had a large impact on cognitive neuroscience. First, the study of human memory has been galvanized by the distinction between ‘explicit’ and ‘implicit’ memory [2]. Explicit memories (such as one’s address or dog’s name) can be called upon in a variety of contexts, can be used by processes involving reasoning, and can enter consciousness. In contrast, implicit memones can be evoked only in a highly restricted range of circumstances, cannot be used by processes involved in
1992, 2: 14&149
reasoning, and cannot enter consciousness (they are etident only because they affect how one performs a task). One form of implicit memory is reflected in ‘repetition priming’. For example, subjects are initially shown words and asked to judge how much they like them. Later they are given the first three letters of a word (a word ‘stem,’ such as ‘cas-‘) and are asked to say the first word that comes to mind (e.g. ‘castle’). This is repeated with a series of words, some of which had been shown initially and some of which had not. If a word had been shown previously, subjects were more likely to complete the stem into that word, even if they had no explicit memory of having seen the word. It is well documented that this form of implicit memory is partly specific to a given sensory modality, and even specific to particular typographic fonts within the visual modality. Marsolek, Kosslyn and Squire [3] have related the above findings to the brain, showing that these as pects of implicit memory are restricted to the right cerebral hemisphere. This was predicted by reasoning about the function of neural networks used in reading. In order to read the meaning of a word, one must map very different inputs into a single output, ignoring variations in typographic font, size, and so on. In contrast, in order to recognize a font or someone’s signature, one must preserve these variations. Such incompatible goals suggest that two mechanisms are at work, and empirical results bear out this possibility. Another area of experimental psychology that has provided grist for cognitive neuroscience is the study of visual perception. Hummel and Biederman [4], studying the representation of shape, have exploited the fact that once people have named a picture, they can name it faster on subsequent occasions. The authors provide evidence that this sort of priming is based on the presence of specific types of parts (which they call ‘geons’). Naming an object primes subsequent naming only if the parts of the two versions have common shapes. Such findings are now being used to characterize processing in the temporal lobes (I Beiderman et al, unpublished data);
Abbreviations MRI-magnetic
146
resonance imaging; PET-positron @
emission tomograpghy.
Current Biology Ltd ISSN 0959-4388
The status of cognitive neuroscience Kosslyn contrary
to what
researchers have nition in patients resections. The lobe in monkeys
has been reported with monkeys, these not found deficits in visual object recogwho have had unilateral temporal lobe human analog to the inferior temporal apparently has yet to be identified.
Schacter et al. [5*] have also used priming to study the nature of visual representations. They first asked subjects to decide whether geometric figures faced left or right, and later asked them to decide whether such figures depicted possible objects or impossible objects (Escherlike drawings). If subjects had seen a possible object during the first phase, they were better at the subsequent judgment, but there was no such priming for impossible objects. This linding suggests that the mechanisms representing visual forms in memory are tailored to specify properties of possible shapes. Schacter et al. [6] provide convergent evidence for this conclusion by showing that patients with organic memory disorders nevertheless show normal amounts of priming in their picture evaluation task, even though they cannot explicitly recall having seen the primed figure before. The results suggest that the priming reflects the operation of perceptual systems, which are intact in these patients, and not high-level ‘semantic’ memories. Another strand of recent work in cognitive neuroscience has grown directly out of neuroscience proper. Neuroscience is concerned with how neurons work, how they are organized, and how they operate to produce behavior; neuroscientists focus on the structure (neuroanatomy) and function (neurophysiology) of the nervous system. Perhaps the majority of research in cognitive neuroscience is rooted in ‘systems level’ neuroscience, which is concerned with the structure and function of neural circuits, and often relies on animal models. Research probing brain-behavior relations in animals has a long history, and has made steady progress. Such studies are now having an increasingly large impact on research in humans. For example, it had long been thought, based p,nmarily on research with rats, that the hippocampus has a,special role in spatial memory per se. Cave and Squire [7] have shown, however, that patients with medial temporal lobe damage have equivalent deficits for spatial and non-spatial information. One of the most exciting new neuroscience-oriented developments in cognitive neuroscience is that brainscanning techniques now allow researchers to test hypotheses, in awake humans, about the roles of specific neural structures. Indeed, sophisticated brain-scanning techniques, particularly positron emission tomography (PET), are no longer treated as exotic methodologies, but are now a standard part of the toolbox. These techniques are allowing researchers to begin to characterize how particular aspects of high-level ‘cognitive’ tasks are carried out in specific regions of the brain. For example, Petersen et al. [w] have shown that words and pronounceable non-words activate a specific part of left medial extrastriate visual cortex, which is not activated by random strings of letters or strings of letter-like ‘false fonts.’ Moreover, there is now a healthy debate about the best way to design PET experiments and analyze data, with members of the Washington University group [8**]
and Shin
advocating a componential approach and members of the Hammersmith Hospital (London) group [9] advocating an approach based on continuous variables (‘statistical parameter mapping’). Among the more innovative advances in brain scanning is the use of magnetic resonance imaging (MRI) to track indicators of metabolic activity. Belliveau et al. [lo*] have shown that this technique can localize activity in primary visual cortex in humans. Indeed, these researchers have recently succeeded in eliminating the need for invasive contrast agents; instead, they have used MRI to track the water content of blood directly (JW Belliveau, personal communication). This approach offers enormous promise, potentially allowing researchers to study processing in the human brain at new levels ,of spatial and temporal resolution. Recently, PET findings have motivati *dies with braindamaged patients. The original work of the Washington University group (for a summa;ir: See [ 111) was of interest in part because of what it failed to show: many of the cortical areas thought to be involved in reading and language failed to be activated during these tasks. The original inferences were based on the patterns of behavioral deficits that appeared following brain damage. Recently, some researchers have attempted to reconcile such disparities by using finely honed behavioral tests when examining brain-damaged patients. For example, Janer and Pardo [12] noted that PET scanning studies identified a region of the anterior cingulate cortex as a component of an attentional system; this component is thought to be specifically involved in ‘the selection of processing procedures’ (i.e. paying attention to and selecting the operations that must be performed to carry out a task; see [13,14]). Despite this, deficits in attention had not been found in patients with damage in this area. Janer and Pardo [ 121 tested one such patient before and after surgery, using three response time tasks that required this kind of attentional process. The tasks were modifications of those that had been used in previous PET scanning studies. In one, the patient was shown a series of nouns and had to decide, as quickly as possible, whether each named a dangerous animal. In another, the patient was shown a series of nouns and required to say aloud a verb that was appropriate for each (e.g. if the noun had been ‘hammer’, the patient might have said ‘pound). In the final task, the patient named the presentation color of words (i.e. the color of the letters on the screen), and the words either named that color or a different color (this was a modified version of the Stroop task). In contrast with the performance on standardized neuropsychological tasks (which tap a complex mixture of cognitive processes), the patient showed a marked decrement in performance in all three tasks immediately after the operation. Thus, the researchers garnered convergent evidence for the role of the anterior cingulate in one sort of attention. It was also of interest that the subject spontaneously recovered several months after surgety; this suggests that other parts of the attention system are able to compensate for the damage. At the same time that advances are being made in understanding the broad sweep of how the brain accomplishes
147
148
Cognitive neuroscience
‘higher mental functions’, other researchers are making increasingly closer contact with neurobiology and molecular biology. For example, Kandel and colleagues [15] are discovering the genetic basis of specific properties of neurons. These techniques promise to allow researchers to trace the development and subsequent organization of populations of neurons, which will provide unique insights into their structure and function. There has also been an enormous upsurge of interest in computationally-oriented cognitive neuroscience, focusing on ‘neural network computer models. Such work has provided precise new ways to characterize brain function. Perhaps the most interesting development here has been the attempt to formulate detailed models of actual neural circuits. For example, Hasselmo, Anderson and Bower [I61 have modeled the specific connections that allow olfactory cortex to learn new associations to scents. This work is of interest because it suggests the existence of several mechanisms (which depend on the action of acetylcholine) that may be involved more generally in irttiating the process of memory storage. In addition, there are now many models of the ways in which subjects per form specific tasks, and some of these provide accounts for the effects of brain damage on behavior. For exam ple, Hinton and Shallice [I7**] have described a model that accounts for specific deficits in reading that occur following brain damage. The effort to specify the details of biological information processing has moved cognitive neuroscience closer to computational neuroscience proper. Researchers in cognitive neuroscience typically attempt to identify components of a system and specify how they operate together to produce a behavior; in contrast, researchers in compu tational neuroscience focus on how individual neurons compute specific functions (which may be involved in carrying out specific behaviors). These two enterprises are merging into one another. For example, Mumford [ 18.1, who comes from a cognitive neuroscience orientation, has formulated a computational model that specifies what the thalamus does when it integrates information in different sensory modalities; in contrast, Zhang [ 191,who comes from a computational neuroscience orientation, has developed principles that may underlie the dynamics and formation of self-organized cortical maps, which play specific roles in information processing. One consequence of the increasingly close relation to computational neuroscience is the development of better modeling tools. For example, Mazzoni, Andersen and Jordan [ 201 report a new, ‘biologically plausible’ learning procedure for neural network models. This procedure adjusts the weights on connections in a network using local information about the strengths of synapses and a global ‘reinforcement signal’. Mazzoni et al. have used this procedure to train a network to specify the locations of points in space. They then examined the network’s ‘hidden units’ (internal to the network, not directly connected to input or output), and found that they had response properties very much like those of neurons found in area 7a of the monkey brain, which is known to be involved in encoding location.
Concluding
remarks
This review has focused on developments that have emerged from (and rely primarily upon) three different foundations: experimental psychology, neuroscience, and computer science, and in so doing has illustrated how the different facets of the field of cognitive neuroscience are becoming increasingly integrated. Indeed, methods and concepts from all three foundations are melding together. Moreover, the common goal is to understand brain function as computations that give rise to behavior (for a further elaboration, see [I] >. Until recently, psychology, and all of its attendant questions, had not been integrated into the natural sciences. Cognitive neuroscience promises to root psychology in the fertile soil of biology, chemistry and physics. It is our hope that these developments will not only enrich psychology, but will play a role in the development of these other sciences as well.
Acknowledgement The authors were supported by funding from the National Science Foundation, Grant BNS 90 09619, and the National Institute of Health, Grant NINCDS 2 POl-17778-09.
References
and recommended
Papers of particular interest, published view, have been highlighted as: . of special interest .. of outstanding interest
reading
within the annual period of rem
SM, ANDERSEN RA (EDs): Frontiers of Cognitive Neuroscience. Cambridge, Massachusetts: MIT Press; 1992.
1.
KOSSLYN
2.
GRAM: P, SCHACTER DL: Implicit and Explicit Memory for New Associations in Normal and Amnesic Subjects. J Exp Psycbol
3.
MARSOLEK
4.
HCJMMELJE, UIEDERMAN I: Dynamic Binding in a Neural Network for Shape Recognition. Psychol RetI 1992, in press.
5. .
SCHACTER DL, CWPER
6.
SCHACTER DL, COOPER LA, THARAN M, RUBENS AE3: Preserved Priming of Novel Objects in Patients with Memory Disorders. J Cog Neurosci 1991, 3~117-130.
7.
CAVE CR, SQLJIRE LR: Equivalent Impairment of Spatial and
1985, 11:501-518.
CJ, KOSSLMVSM, SQUIRE LR: Form-Specilic Visual Priming in the Right Cerebral Hemisphere. J Exp Psychof 1992, in press.
LA, DELANEY SM, PETERSEN MA, THARAN Implicit Memory for Possible and Impossible Objects: Constraints on the Construction of Structural Descriptions. J Exp P~ycbol 1991, 17:3-19. Priming only occurred for drawings that could depict actual objects, which probably reflects the basic properties of the mechanisms that store visual information, M:
Nonspatial Memory Following Damage to the Human Hippocampus. Hippocampw 1991, 1:32%340. PETERSEN SE, Fox PT, SNYDER AZ, RAKHLEME: Activation of Extrastriate and Frontal Cortical Areas by Visual Words and Word-Like Stimuli. Science 1990, 249:1041-1044. PET is used to distinguish between words and pronounceable nonwords, on the one hand, and non-pronounceable strings of letters and
8.
..
The status of coanitive
‘false fonts’ (novel letter-like symbols), on the other. The results may implicate one mechanism that is used in reading per se and another that is used more generally in information retrieval or comprehension. 9.
FR~STON KJ, FRXH CD, LIDDLE PF, FRACKOWLAKRSJ: Investigating a Network Model of Word Generation with Positron Emission Tomography. Proc R Sot Lond [B] 1991, 244:101~106.
10. .
BELUVEA~J JW, KENNEDY DN, MCKINSTRY RC, BUCHBINDERBR, WEISSKOFFRM, COHEN MS, VEVEA JM, BRADY TJ, ROSEN BR:
Functional Mapping of the Human Visual Cortex by Magnetic Resonance Imaging. Science 1991, 254:716-719. A potentially revolutionary methodology is described, using MRl to track brain function. 11.
POSNER MI, PETERSENSE, Fox PT, RAICHLEME: Localization of Cognitive Operations in the Human Brain. Science 1988, 240:1627-1631.
12.
JANER KW, PARDOJV: Deficits in Selective Attention Following Bilateral Anterior Cingulotomy. J Cog Neurosci 1991, 3:231-241.
13.
PARDOJV, PARW PJ, JANERKW, RAICHLEIME: The Anterior Cingulate Cortex Mediates Processing Selection in the Stroop Attentional Con&t Paradigm. Proc Nat1 Acud Sci USA 1990, 87256259.
14.
POSNERMI, PETERSENSE: The Attention System of the Human Brain. Annu Rev Neurasci 1990, 132542.
15.
BRUNETJ, SHAPIROE, FOSTERSA, HANDELER, 11~0 y: IdentIfication of a Peptide Specific for Aplysia Sensory Neurons by PCR-Based Differential Screening. Science 1991, 252:856859.
16.
neuroscience
Kosslyn
and Shin
HASSELMOME, ANDERSON BP, BOWERJM: Cholinergic Modulation of Cortical Associative Memory Function. J Neuro plysiol 1992, in press.
HINTON GE, SHAILICE T: Lesioning an Attractor Network: Investigations of Acquired Dyslexia. Psychl Rev 1991, 98:74-95. A ‘neural network’ model is constructed, trained fo ‘interpret’ word-like inputs, and then damaged. The patterns of errors following damage in some respects mirror those found in certain kinds of brain-damaged patients. Hence, the model offers potential accounts for the Endings with patients, and provides new hypotheses that can be tested directly.
17. ..
MUMFORD D: On the Computational Architecture of the Neocortex: I. The Role of the Thalamo-Cortical Loop. Biol Cybern 1991, 65:135-145. A useful review of the literature, and a good example of interdisciplinaty thinking. The hypotheses about the role of the thalamus are likely to stimulate additional laboratory work. 18. .
19.
ZHANGJ: Dynamics and Formation of Self-Organizing Maps. Neural Comp 1991, 3:5-.
20.
MAZONI P, ANDER~ENRA, JORDAN%: !i’ $ofe Biologically Plausible Learning Rule than Back P&p@ation Applied to a Network Model of Cortical &ea 7a. Cerebr Cortex 1991, 1:293_307.
SM Kosslyn’ and LM Shin, Department of Psychology, 1236 William James Hall, 33 Kirkland Street, Harvard University, Cambridge, Massachusetts 02138, USA * To whom all correspondence
should
be addressed
149
University,
neuroscience
fields: experimental science.
The
approach
Cambridge, Massachusetts,
rests on findings,
psychology,
strong
greater integration
trend
and Lisa M. Shin
methods,
systems-level
over
the
past
few
across these fields. The influence
on current
research
on memory,
and theory
neuroscience, years
USA from
three
and computer
has
been
for
a
of this interdisciplinary
perception,
and language will
be illustrated.
Current
Opinion
in Neurobiology
Introduction Researchers in the field of cognitive neuroscience seek to understand how brain function gives rise to mental activ ities such as perception, memory, and language. These goals are shared by several other fields, but cognitive neuroscience has a uniquely interdisciplinary approach. It draws on methods and theoretical constructs from three older fields: experimental psychology, neuroscience, and computer science. (For a brief history of how cognitive neuroscience grew out of these fields, see [ 11.) Research in cognitive neuroscience still bears the stamp of each of these disciplines, and is often particularly beholden to one of them. Nevertheless, the integration that is taking place across the different facets of the field is particularly striking, as will be illustrated in this review.
Tips of the iceberg Our purpose is not to review the current status of all of cognitive neuroscience, or even just one area. Rather, it is to illustrate the way the field as a whole appears to be developing. Thus, the following examples have been chosen to highlight certain trends. Let us begin by considering ways in which experimental psychology has given rise to recent work in cognitive neuroscience. Experimental psychology is, at its roots, concerned with the study of behavior. By carefully examining behavior, psychologists hope to infer principles about how the mind/brain operates. Two areas of experimental psychology have recently had a large impact on cognitive neuroscience. First, the study of human memory has been galvanized by the distinction between ‘explicit’ and ‘implicit’ memory [2]. Explicit memories (such as one’s address or dog’s name) can be called upon in a variety of contexts, can be used by processes involving reasoning, and can enter consciousness. In contrast, implicit memones can be evoked only in a highly restricted range of circumstances, cannot be used by processes involved in
1992, 2: 14&149
reasoning, and cannot enter consciousness (they are etident only because they affect how one performs a task). One form of implicit memory is reflected in ‘repetition priming’. For example, subjects are initially shown words and asked to judge how much they like them. Later they are given the first three letters of a word (a word ‘stem,’ such as ‘cas-‘) and are asked to say the first word that comes to mind (e.g. ‘castle’). This is repeated with a series of words, some of which had been shown initially and some of which had not. If a word had been shown previously, subjects were more likely to complete the stem into that word, even if they had no explicit memory of having seen the word. It is well documented that this form of implicit memory is partly specific to a given sensory modality, and even specific to particular typographic fonts within the visual modality. Marsolek, Kosslyn and Squire [3] have related the above findings to the brain, showing that these as pects of implicit memory are restricted to the right cerebral hemisphere. This was predicted by reasoning about the function of neural networks used in reading. In order to read the meaning of a word, one must map very different inputs into a single output, ignoring variations in typographic font, size, and so on. In contrast, in order to recognize a font or someone’s signature, one must preserve these variations. Such incompatible goals suggest that two mechanisms are at work, and empirical results bear out this possibility. Another area of experimental psychology that has provided grist for cognitive neuroscience is the study of visual perception. Hummel and Biederman [4], studying the representation of shape, have exploited the fact that once people have named a picture, they can name it faster on subsequent occasions. The authors provide evidence that this sort of priming is based on the presence of specific types of parts (which they call ‘geons’). Naming an object primes subsequent naming only if the parts of the two versions have common shapes. Such findings are now being used to characterize processing in the temporal lobes (I Beiderman et al, unpublished data);
Abbreviations MRI-magnetic
146
resonance imaging; PET-positron @
emission tomograpghy.
Current Biology Ltd ISSN 0959-4388
The status of cognitive neuroscience Kosslyn contrary
to what
researchers have nition in patients resections. The lobe in monkeys
has been reported with monkeys, these not found deficits in visual object recogwho have had unilateral temporal lobe human analog to the inferior temporal apparently has yet to be identified.
Schacter et al. [5*] have also used priming to study the nature of visual representations. They first asked subjects to decide whether geometric figures faced left or right, and later asked them to decide whether such figures depicted possible objects or impossible objects (Escherlike drawings). If subjects had seen a possible object during the first phase, they were better at the subsequent judgment, but there was no such priming for impossible objects. This linding suggests that the mechanisms representing visual forms in memory are tailored to specify properties of possible shapes. Schacter et al. [6] provide convergent evidence for this conclusion by showing that patients with organic memory disorders nevertheless show normal amounts of priming in their picture evaluation task, even though they cannot explicitly recall having seen the primed figure before. The results suggest that the priming reflects the operation of perceptual systems, which are intact in these patients, and not high-level ‘semantic’ memories. Another strand of recent work in cognitive neuroscience has grown directly out of neuroscience proper. Neuroscience is concerned with how neurons work, how they are organized, and how they operate to produce behavior; neuroscientists focus on the structure (neuroanatomy) and function (neurophysiology) of the nervous system. Perhaps the majority of research in cognitive neuroscience is rooted in ‘systems level’ neuroscience, which is concerned with the structure and function of neural circuits, and often relies on animal models. Research probing brain-behavior relations in animals has a long history, and has made steady progress. Such studies are now having an increasingly large impact on research in humans. For example, it had long been thought, based p,nmarily on research with rats, that the hippocampus has a,special role in spatial memory per se. Cave and Squire [7] have shown, however, that patients with medial temporal lobe damage have equivalent deficits for spatial and non-spatial information. One of the most exciting new neuroscience-oriented developments in cognitive neuroscience is that brainscanning techniques now allow researchers to test hypotheses, in awake humans, about the roles of specific neural structures. Indeed, sophisticated brain-scanning techniques, particularly positron emission tomography (PET), are no longer treated as exotic methodologies, but are now a standard part of the toolbox. These techniques are allowing researchers to begin to characterize how particular aspects of high-level ‘cognitive’ tasks are carried out in specific regions of the brain. For example, Petersen et al. [w] have shown that words and pronounceable non-words activate a specific part of left medial extrastriate visual cortex, which is not activated by random strings of letters or strings of letter-like ‘false fonts.’ Moreover, there is now a healthy debate about the best way to design PET experiments and analyze data, with members of the Washington University group [8**]
and Shin
advocating a componential approach and members of the Hammersmith Hospital (London) group [9] advocating an approach based on continuous variables (‘statistical parameter mapping’). Among the more innovative advances in brain scanning is the use of magnetic resonance imaging (MRI) to track indicators of metabolic activity. Belliveau et al. [lo*] have shown that this technique can localize activity in primary visual cortex in humans. Indeed, these researchers have recently succeeded in eliminating the need for invasive contrast agents; instead, they have used MRI to track the water content of blood directly (JW Belliveau, personal communication). This approach offers enormous promise, potentially allowing researchers to study processing in the human brain at new levels ,of spatial and temporal resolution. Recently, PET findings have motivati *dies with braindamaged patients. The original work of the Washington University group (for a summa;ir: See [ 111) was of interest in part because of what it failed to show: many of the cortical areas thought to be involved in reading and language failed to be activated during these tasks. The original inferences were based on the patterns of behavioral deficits that appeared following brain damage. Recently, some researchers have attempted to reconcile such disparities by using finely honed behavioral tests when examining brain-damaged patients. For example, Janer and Pardo [12] noted that PET scanning studies identified a region of the anterior cingulate cortex as a component of an attentional system; this component is thought to be specifically involved in ‘the selection of processing procedures’ (i.e. paying attention to and selecting the operations that must be performed to carry out a task; see [13,14]). Despite this, deficits in attention had not been found in patients with damage in this area. Janer and Pardo [ 121 tested one such patient before and after surgery, using three response time tasks that required this kind of attentional process. The tasks were modifications of those that had been used in previous PET scanning studies. In one, the patient was shown a series of nouns and had to decide, as quickly as possible, whether each named a dangerous animal. In another, the patient was shown a series of nouns and required to say aloud a verb that was appropriate for each (e.g. if the noun had been ‘hammer’, the patient might have said ‘pound). In the final task, the patient named the presentation color of words (i.e. the color of the letters on the screen), and the words either named that color or a different color (this was a modified version of the Stroop task). In contrast with the performance on standardized neuropsychological tasks (which tap a complex mixture of cognitive processes), the patient showed a marked decrement in performance in all three tasks immediately after the operation. Thus, the researchers garnered convergent evidence for the role of the anterior cingulate in one sort of attention. It was also of interest that the subject spontaneously recovered several months after surgety; this suggests that other parts of the attention system are able to compensate for the damage. At the same time that advances are being made in understanding the broad sweep of how the brain accomplishes
147
148
Cognitive neuroscience
‘higher mental functions’, other researchers are making increasingly closer contact with neurobiology and molecular biology. For example, Kandel and colleagues [15] are discovering the genetic basis of specific properties of neurons. These techniques promise to allow researchers to trace the development and subsequent organization of populations of neurons, which will provide unique insights into their structure and function. There has also been an enormous upsurge of interest in computationally-oriented cognitive neuroscience, focusing on ‘neural network computer models. Such work has provided precise new ways to characterize brain function. Perhaps the most interesting development here has been the attempt to formulate detailed models of actual neural circuits. For example, Hasselmo, Anderson and Bower [I61 have modeled the specific connections that allow olfactory cortex to learn new associations to scents. This work is of interest because it suggests the existence of several mechanisms (which depend on the action of acetylcholine) that may be involved more generally in irttiating the process of memory storage. In addition, there are now many models of the ways in which subjects per form specific tasks, and some of these provide accounts for the effects of brain damage on behavior. For exam ple, Hinton and Shallice [I7**] have described a model that accounts for specific deficits in reading that occur following brain damage. The effort to specify the details of biological information processing has moved cognitive neuroscience closer to computational neuroscience proper. Researchers in cognitive neuroscience typically attempt to identify components of a system and specify how they operate together to produce a behavior; in contrast, researchers in compu tational neuroscience focus on how individual neurons compute specific functions (which may be involved in carrying out specific behaviors). These two enterprises are merging into one another. For example, Mumford [ 18.1, who comes from a cognitive neuroscience orientation, has formulated a computational model that specifies what the thalamus does when it integrates information in different sensory modalities; in contrast, Zhang [ 191,who comes from a computational neuroscience orientation, has developed principles that may underlie the dynamics and formation of self-organized cortical maps, which play specific roles in information processing. One consequence of the increasingly close relation to computational neuroscience is the development of better modeling tools. For example, Mazzoni, Andersen and Jordan [ 201 report a new, ‘biologically plausible’ learning procedure for neural network models. This procedure adjusts the weights on connections in a network using local information about the strengths of synapses and a global ‘reinforcement signal’. Mazzoni et al. have used this procedure to train a network to specify the locations of points in space. They then examined the network’s ‘hidden units’ (internal to the network, not directly connected to input or output), and found that they had response properties very much like those of neurons found in area 7a of the monkey brain, which is known to be involved in encoding location.
Concluding
remarks
This review has focused on developments that have emerged from (and rely primarily upon) three different foundations: experimental psychology, neuroscience, and computer science, and in so doing has illustrated how the different facets of the field of cognitive neuroscience are becoming increasingly integrated. Indeed, methods and concepts from all three foundations are melding together. Moreover, the common goal is to understand brain function as computations that give rise to behavior (for a further elaboration, see [I] >. Until recently, psychology, and all of its attendant questions, had not been integrated into the natural sciences. Cognitive neuroscience promises to root psychology in the fertile soil of biology, chemistry and physics. It is our hope that these developments will not only enrich psychology, but will play a role in the development of these other sciences as well.
Acknowledgement The authors were supported by funding from the National Science Foundation, Grant BNS 90 09619, and the National Institute of Health, Grant NINCDS 2 POl-17778-09.
References
and recommended
Papers of particular interest, published view, have been highlighted as: . of special interest .. of outstanding interest
reading
within the annual period of rem
SM, ANDERSEN RA (EDs): Frontiers of Cognitive Neuroscience. Cambridge, Massachusetts: MIT Press; 1992.
1.
KOSSLYN
2.
GRAM: P, SCHACTER DL: Implicit and Explicit Memory for New Associations in Normal and Amnesic Subjects. J Exp Psycbol
3.
MARSOLEK
4.
HCJMMELJE, UIEDERMAN I: Dynamic Binding in a Neural Network for Shape Recognition. Psychol RetI 1992, in press.
5. .
SCHACTER DL, CWPER
6.
SCHACTER DL, COOPER LA, THARAN M, RUBENS AE3: Preserved Priming of Novel Objects in Patients with Memory Disorders. J Cog Neurosci 1991, 3~117-130.
7.
CAVE CR, SQLJIRE LR: Equivalent Impairment of Spatial and
1985, 11:501-518.
CJ, KOSSLMVSM, SQUIRE LR: Form-Specilic Visual Priming in the Right Cerebral Hemisphere. J Exp Psychof 1992, in press.
LA, DELANEY SM, PETERSEN MA, THARAN Implicit Memory for Possible and Impossible Objects: Constraints on the Construction of Structural Descriptions. J Exp P~ycbol 1991, 17:3-19. Priming only occurred for drawings that could depict actual objects, which probably reflects the basic properties of the mechanisms that store visual information, M:
Nonspatial Memory Following Damage to the Human Hippocampus. Hippocampw 1991, 1:32%340. PETERSEN SE, Fox PT, SNYDER AZ, RAKHLEME: Activation of Extrastriate and Frontal Cortical Areas by Visual Words and Word-Like Stimuli. Science 1990, 249:1041-1044. PET is used to distinguish between words and pronounceable nonwords, on the one hand, and non-pronounceable strings of letters and
8.
..
The status of coanitive
‘false fonts’ (novel letter-like symbols), on the other. The results may implicate one mechanism that is used in reading per se and another that is used more generally in information retrieval or comprehension. 9.
FR~STON KJ, FRXH CD, LIDDLE PF, FRACKOWLAKRSJ: Investigating a Network Model of Word Generation with Positron Emission Tomography. Proc R Sot Lond [B] 1991, 244:101~106.
10. .
BELUVEA~J JW, KENNEDY DN, MCKINSTRY RC, BUCHBINDERBR, WEISSKOFFRM, COHEN MS, VEVEA JM, BRADY TJ, ROSEN BR:
Functional Mapping of the Human Visual Cortex by Magnetic Resonance Imaging. Science 1991, 254:716-719. A potentially revolutionary methodology is described, using MRl to track brain function. 11.
POSNER MI, PETERSENSE, Fox PT, RAICHLEME: Localization of Cognitive Operations in the Human Brain. Science 1988, 240:1627-1631.
12.
JANER KW, PARDOJV: Deficits in Selective Attention Following Bilateral Anterior Cingulotomy. J Cog Neurosci 1991, 3:231-241.
13.
PARDOJV, PARW PJ, JANERKW, RAICHLEIME: The Anterior Cingulate Cortex Mediates Processing Selection in the Stroop Attentional Con&t Paradigm. Proc Nat1 Acud Sci USA 1990, 87256259.
14.
POSNERMI, PETERSENSE: The Attention System of the Human Brain. Annu Rev Neurasci 1990, 132542.
15.
BRUNETJ, SHAPIROE, FOSTERSA, HANDELER, 11~0 y: IdentIfication of a Peptide Specific for Aplysia Sensory Neurons by PCR-Based Differential Screening. Science 1991, 252:856859.
16.
neuroscience
Kosslyn
and Shin
HASSELMOME, ANDERSON BP, BOWERJM: Cholinergic Modulation of Cortical Associative Memory Function. J Neuro plysiol 1992, in press.
HINTON GE, SHAILICE T: Lesioning an Attractor Network: Investigations of Acquired Dyslexia. Psychl Rev 1991, 98:74-95. A ‘neural network’ model is constructed, trained fo ‘interpret’ word-like inputs, and then damaged. The patterns of errors following damage in some respects mirror those found in certain kinds of brain-damaged patients. Hence, the model offers potential accounts for the Endings with patients, and provides new hypotheses that can be tested directly.
17. ..
MUMFORD D: On the Computational Architecture of the Neocortex: I. The Role of the Thalamo-Cortical Loop. Biol Cybern 1991, 65:135-145. A useful review of the literature, and a good example of interdisciplinaty thinking. The hypotheses about the role of the thalamus are likely to stimulate additional laboratory work. 18. .
19.
ZHANGJ: Dynamics and Formation of Self-Organizing Maps. Neural Comp 1991, 3:5-.
20.
MAZONI P, ANDER~ENRA, JORDAN%: !i’ $ofe Biologically Plausible Learning Rule than Back P&p@ation Applied to a Network Model of Cortical &ea 7a. Cerebr Cortex 1991, 1:293_307.
SM Kosslyn’ and LM Shin, Department of Psychology, 1236 William James Hall, 33 Kirkland Street, Harvard University, Cambridge, Massachusetts 02138, USA * To whom all correspondence
should
be addressed
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