Schizophrenia patients consistently show deficits on tasks of explicit learning and memory. In contrast, their performance on implicit processing tasks often appears to be relatively intact, though most studies have focused on implicit learning of motor skills. This study evaluated implicit learning in 59 medicated schizophrenia outpatients and 43 healthy controls using two different cognitive skill tasks. Participants completed a Probabilistic Classification task to assess procedural habit learning and an Artificial Grammar task to assess incidental learning of complex rule-based knowledge, as well as an explicit verbal learning and memory task. In addition to performing worse than controls on the explicit learning task, patients showed worse overall performance on the Probabilistic Classification task, which involves gradual learning through trial-by-trial performance feedback. However, patients and controls showed similar levels of learning on the Artificial Grammar task, suggesting a preserved ability to acquire complex rule-based knowledge in the absence of performance feedback. Discussion focuses on possible explanations for schizophrenia patients’ poor Probabilistic Classification task performance.
schizophrenia; implicit learning; neurocognition; habit learning
To avoid some conceptual and methodological pitfalls found in traditional artificial grammar learning tasks, we developed a new method of measuring implicit learning using immediate memory span. Subjects were presented with sequences generated by an artificial grammar and were asked to reproduce the patterns by pressing buttons on a response box. After exposure to these sequences, subjects showed selective improvement in immediate memory span for novel sequences governed by the same grammar. Individual differences in implicit learning covaried with measures of auditory digit span. Subjects with greater immediate memory processing capacity were better able to learn and subsequently exploit the information available in grammatical sequences. Our results are consistent with a detailed episodic coding framework in which implicit learning occurs as an incidental by-product of explicit task performance. Although subjects encode highly detailed information about specific instances, they use different aspects of this information to accomplish different task-specific demands.
In the current paper, we first evaluate the suitability of traditional serial
reaction time (SRT) and artificial grammar learning (AGL) experiments for
measuring implicit learning of social signals. We then report the results of a
novel sequence learning task which combines aspects of the SRT and AGL paradigms
to meet our suggested criteria for how implicit learning experiments can be
adapted to increase their relevance to situations of social intuition. The
sequences followed standard finite-state grammars. Sequence learning and
consciousness of acquired knowledge were compared between 2 groups of 24
participants viewing either sequences of individually presented letters or
sequences of body-posture pictures, which were described as series of yoga
movements. Participants in both conditions showed above-chance classification
accuracy, indicating that sequence learning had occurred in both stimulus
conditions. This shows that sequence learning can still be found when learning
procedures reflect the characteristics of social intuition. Rule awareness was
measured using trial-by-trial evaluation of decision strategy (Dienes & Scott, 2005; Scott & Dienes, 2008). For letters,
sequence classification was best on trials where participants reported
responding on the basis of explicit rules or memory, indicating some explicit
learning in this condition. For body-posture, classification was not above
chance on these types of trial, but instead showed a trend to be best on those
trials where participants reported that their responses were based on intuition,
familiarity, or random choice, suggesting that learning was more implicit.
Results therefore indicate that the use of traditional stimuli in research on
sequence learning might underestimate the extent to which learning is implicit
in domains such as social learning, contributing to ongoing debate about
levels of conscious awareness in implicit learning.
implicit learning; social intuition; intuition; artificial grammar learning; human movement; consciousness; fringe consciousness
Within a few sentences, listeners learn to understand severely degraded speech such as noise-vocoded speech. However, individuals vary in the amount of such perceptual learning and it is unclear what underlies these differences. The present study investigates whether perceptual learning in speech relates to statistical learning, as sensitivity to probabilistic information may aid identification of relevant cues in novel speech input. If statistical learning and perceptual learning (partly) draw on the same general mechanisms, then statistical learning in a non-auditory modality using non-linguistic sequences should predict adaptation to degraded speech. In the present study, 73 older adults (aged over 60 years) and 60 younger adults (aged between 18 and 30 years) performed a visual artificial grammar learning task and were presented with 60 meaningful noise-vocoded sentences in an auditory recall task. Within age groups, sentence recognition performance over exposure was analyzed as a function of statistical learning performance, and other variables that may predict learning (i.e., hearing, vocabulary, attention switching control, working memory, and processing speed). Younger and older adults showed similar amounts of perceptual learning, but only younger adults showed significant statistical learning. In older adults, improvement in understanding noise-vocoded speech was constrained by age. In younger adults, amount of adaptation was associated with lexical knowledge and with statistical learning ability. Thus, individual differences in general cognitive abilities explain listeners' variability in adapting to noise-vocoded speech. Results suggest that perceptual and statistical learning share mechanisms of implicit regularity detection, but that the ability to detect statistical regularities is impaired in older adults if visual sequences are presented quickly.
perceptual learning; statistical learning; individual differences; aging; working memory; attention switching control; processing speed; vocabulary
Context-free grammars are fundamental for the description of linguistic syntax. However, most artificial grammar learning experiments have explored learning of simpler finite-state grammars, while studies exploring context-free grammars have not assessed awareness and implicitness. This paper explores the implicit learning of context-free grammars employing features of hierarchical organization, recursive embedding and long-distance dependencies. The grammars also featured the distinction between left- and right-branching structures, as well as between centre- and tail-embedding, both distinctions found in natural languages. People acquired unconscious knowledge of relations between grammatical classes even for dependencies over long distances, in ways that went beyond learning simpler relations (e.g. n-grams) between individual words. The structural distinctions drawn from linguistics also proved important as performance was greater for tail-embedding than centre-embedding structures. The results suggest the plausibility of implicit learning of complex context-free structures, which model some features of natural languages. They support the relevance of artificial grammar learning for probing mechanisms of language learning and challenge existing theories and computational models of implicit learning.
We used a prototype extraction task to assess implicit learning of a meaningful novel visual category. Cortical activation was monitored in young adults with functional magnetic resonance imaging. We observed occipital deactivation at test consistent with perceptually based implicit learning, and lateral temporal cortex deactivation reflecting implicit acquisition of the category's semantic nature. Medial temporal lobe (MTL) activation during exposure and test suggested involvement of explicit memory as well. Behavioral performance of Alzheimer's disease (AD) patients and healthy seniors was also assessed, and AD performance was correlated with gray matter volume using voxel-based morphometry. AD patients showed learning, consistent with preserved implicit memory, and confirming that AD patients' implicit memory is not limited to abstract patterns. However, patients were somewhat impaired relative to healthy seniors. Occipital and lateral temporal cortical volume correlated with successful AD patient performance, and thus overlapped with young adults' areas of deactivation. Patients' severe MTL atrophy precluded involvement of this region. AD patients thus appear to engage a cortically based implicit memory mechanism, whereas their relative deficit on this task may reflect their MTL disease. These findings suggest that implicit and explicit memory systems collaborate in neurologically intact individuals performing an ostensibly implicit memory task.
Alzheimer's; explicit memory; fMRI; implicit memory; medial temporal
Although learning a second language (L2) as an adult is notoriously difficult, research has shown that adults can indeed attain native language-like brain processing and high proficiency levels. However, it is important to then retain what has been attained, even in the absence of continued exposure to the L2—particularly since periods of minimal or no L2 exposure are common. This event-related potential (ERP) study of an artificial language tested performance and neural processing following a substantial period of no exposure. Adults learned to speak and comprehend the artificial language to high proficiency with either explicit, classroom-like, or implicit, immersion-like training, and then underwent several months of no exposure to the language. Surprisingly, proficiency did not decrease during this delay. Instead, it remained unchanged, and there was an increase in native-like neural processing of syntax, as evidenced by several ERP changes—including earlier, more reliable, and more left-lateralized anterior negativities, and more robust P600s, in response to word-order violations. Moreover, both the explicitly and implicitly trained groups showed increased native-like ERP patterns over the delay, indicating that such changes can hold independently of L2 training type. The results demonstrate that substantial periods with no L2 exposure are not necessarily detrimental. Rather, benefits may ensue from such periods of time even when there is no L2 exposure. Interestingly, both before and after the delay the implicitly trained group showed more native-like processing than the explicitly trained group, indicating that type of training also affects the attainment of native-like processing in the brain. Overall, the findings may be largely explained by a combination of forgetting and consolidation in declarative and procedural memory, on which L2 grammar learning appears to depend. The study has a range of implications, and suggests a research program with potentially important consequences for second language acquisition and related fields.
In this event-related fMRI study we investigated the effect of 5 days of implicit acquisition on preference classification by means of an artificial grammar learning (AGL) paradigm based on the structural mere-exposure effect and preference classification using a simple right-linear unification grammar. This allowed us to investigate implicit AGL in a proper learning design by including baseline measurements prior to grammar exposure. After 5 days of implicit acquisition, the fMRI results showed activations in a network of brain regions including the inferior frontal (centered on BA 44/45) and the medial prefrontal regions (centered on BA 8/32). Importantly, and central to this study, the inclusion of a naive preference fMRI baseline measurement allowed us to conclude that these fMRI findings were the intrinsic outcomes of the learning process itself and not a reflection of a preexisting functionality recruited during classification, independent of acquisition. Support for the implicit nature of the knowledge utilized during preference classification on day 5 come from the fact that the basal ganglia, associated with implicit procedural learning, were activated during classification, while the medial temporal lobe system, associated with explicit declarative memory, was consistently deactivated. Thus, preference classification in combination with structural mere-exposure can be used to investigate structural sequence processing (syntax) in unsupervised AGL paradigms with proper learning designs.
fMRI; artificial syntax; implicit learning; artificial grammar learning; inferior frontal gyrus; structural mere-exposure; preference classification
It is widely believed that adults cannot learn a foreign language in the same way that children learn a first language. However, recent evidence suggests that adult learners of a foreign language can come to rely on native-like language brain mechanisms. Here, we show that the type of language training crucially impacts this outcome. We used an artificial language paradigm to examine longitudinally whether explicit training (that approximates traditional grammar-focused classroom settings) and implicit training (that approximates immersion settings) differentially affect neural (electrophysiological) and behavioral (performance) measures of syntactic processing. Results showed that performance of explicitly and implicitly trained groups did not differ at either low or high proficiency. In contrast, electrophysiological (ERP) measures revealed striking differences between the groups’ neural activity at both proficiency levels in response to syntactic violations. Implicit training yielded an N400 at low proficiency, whereas at high proficiency, it elicited a pattern typical of native speakers: an anterior negativity followed by a P600 accompanied by a late anterior negativity. Explicit training, by contrast, yielded no significant effects at low proficiency and only an anterior positivity followed by a P600 at high proficiency. Although the P600 is reminiscent of native-like processing, this response pattern as a whole is not. Thus, only implicit training led to an electrophysiological signature typical of native speakers. Overall, the results suggest that adult foreign language learners can come to rely on native-like language brain mechanisms, but that the conditions under which the language is learned may be crucial in attaining this goal.
Even without explicit instruction, learners are able to extract information about the form of a language simply by attending to input that reflects the underlying grammar. Here we explore the role of variability in this learning by asking whether varying the number of unique exemplars heard by the learner affects learning of an artificial syntactic form.
Learners with normal language (n=16) and language-based learning disability (LLD) (n=16) were exposed to strings of nonwords that represented an underlying grammar. Half heard 3 exemplars sixteen times each (low variability group) and half heard 24 exemplars twice each (high variability group). Learners were then tested for recognition of items heard and generalization of the grammar with new nonword strings.
Only those learners with LLD who were in the high variability group were able to demonstrate generalization of the underlying grammar. For learners with normal language, both those in the high and the low variability groups showed generalization of the grammar, but relative effect sizes suggested a larger learning effect in the high variability group.
The results demonstrate that the structure of the learning context can determine the ability to generalize from specific training items to novel cases.
Typically developing children aged 5 to 8 years were exposed to artificial grammar learning. Following an implicit exposure phase, half of the participants received neutral instructions at test while the other half received instructions making a direct, explicit reference to the training phase. We first aimed to assess whether implicit learning operated in the two test conditions. We then evaluated the differential impact of age on learning performances as a function of test instructions. The results showed that performance did not vary as a function of age in the implicit instructions condition, while age effects emerged when explicit instructions were employed at test. However, performance was affected differently by age and the instructions given at test, depending on whether the implicit learning of short or long units was assessed. These results suggest that the claim that the implicit learning process is independent of age needs to be revised.
This study tested the procedural deficit hypothesis of specific language impairment (SLI) by comparing children’s performance in two motor procedural learning tasks and an implicit verbal sequence learning task. Participants were 7- to 11-year-old children with SLI (n= 48), typically-developing age-matched children (N = 20) and younger typically-developing children matched for receptive grammar (N = 28). In a serial reaction time task, the children with SLI performed at the same level as the grammar-matched children, but poorer than age-match controls in learning motor sequences. When tested with a motor procedural learning task that did not involve learning sequential relationships between discrete elements (i.e., pursuit rotor), the children with SLI performed comparably with age-matched children and better than younger grammar-matched controls. In addition, poor implicit learning of word sequences in a verbal memory task (Hebb effect) was found in the children with SLI. Together, these findings suggest that SLI might be characterized by deficits in learning sequence-specific information, rather than generally weak procedural learning.
procedural learning; sequence learning; SLI
This study tested the procedural deficit hypothesis of specific language impairment (SLI) by comparing children’s performance in two motor procedural learning tasks and an implicit verbal sequence learning task. Participants were 7- to 11-year-old children with SLI (n = 48), typically developing age-matched children (n = 20) and younger typically developing children matched for receptive grammar (n = 28). In a serial reaction time task, the children with SLI performed at the same level as the grammar-matched children, but poorer than age-matched controls in learning motor sequences. When tested with a motor procedural learning task that did not involve learning sequential relationships between discrete elements (i.e. pursuit rotor), the children with SLI performed comparably with age-matched children and better than younger grammar-matched controls. In addition, poor implicit learning of word sequences in a verbal memory task (the Hebb effect) was found in the children with SLI. Together, these findings suggest that SLI might be characterized by deficits in learning sequence-specific information, rather than generally weak procedural learning.
The domain of syntax is seen as the core of the language faculty and as the most critical difference between animal vocalizations and language. We review evidence from spontaneously produced vocalizations as well as from perceptual experiments using artificial grammars to analyse animal syntactic abilities, i.e. abilities to produce and perceive patterns following abstract rules. Animal vocalizations consist of vocal units (elements) that are combined in a species-specific way to create higher order strings that in turn can be produced in different patterns. While these patterns differ between species, they have in common that they are no more complex than a probabilistic finite-state grammar. Experiments on the perception of artificial grammars confirm that animals can generalize and categorize vocal strings based on phonetic features. They also demonstrate that animals can learn about the co-occurrence of elements or learn simple ‘rules’ like attending to reduplications of units. However, these experiments do not provide strong evidence for an ability to detect abstract rules or rules beyond finite-state grammars. Nevertheless, considering the rather limited number of experiments and the difficulty to design experiments that unequivocally demonstrate more complex rule learning, the question of what animals are able to do remains open.
birdsong; artificial grammar learning; syntax; language; vocalization; rule learning
White matter plays an important role in various domains of cognitive function. While disruptions in white matter are known to affect many domains of behavior and cognition, the ability to acquire grammatical regularities has been mostly linked to the left hemisphere, perhaps due to its dependence on linguistic stimuli. The role of white matter in the right hemisphere in grammar acquisition is yet unknown. Here we show for the first time that in the domain of pitch, intact white matter connectivity in right-hemisphere analogs of language areas is important for grammar learning. A pitch-based artificial grammar learning task was conducted on subjects who also underwent diffusion tensor imaging. Probabilistic tractography using seed regions of interest in the right inferior frontal gyrus and right middle temporal gyrus showed positive correlations between tract volume and learning performance. Furthermore, significant correlations were observed between learning performance and FA in white matter underlying the supramarginal gyrus, corresponding to the right temporal-parietal junction of the arcuate fasciculus. The control task of recognition did not correlate with tract volume or FA, and control tracts in the left hemisphere did not correlate with behavioral performance. Results show that the right ventral arcuate fasciculus is important in pitch-based artificial grammar learning, and that brain structures subserving learning may be tied to the hemisphere that processes the stimulus more generally.
diffusion tensor imaging; white matter; plasticity; learning; memory; pitch; grammar; music
Patients with amnesia have deficits in declarative memory but intact memory for motor and perceptual skills, which suggests that explicit memory and implicit memory are distinct. However, the evidence that implicit motor learning is intact in amnesic patients is contradictory. This study investigated implicit sequence learning in amnesic patients with Korsakoff’s syndrome (N = 20) and matched controls (N = 14), using the classical Serial Reaction Time Task and a newly developed Pattern Learning Task in which the planning and execution of the responses are more spatially demanding. Results showed that implicit motor learning occurred in both groups of participants; however, on the Pattern Learning Task, the percentage of errors did not increase in the Korsakoff group in the random test phase, which is indicative of less implicit learning. Thus, our findings show that the performance of patients with Korsakoff’s syndrome is compromised on an implicit learning task with a strong spatial response component.
Korsakoff’s syndrome; Amnesia; Implicit learning; Motor learning; Sequence learning; Memory
Grammar acquisition is a high level cognitive function that requires the extraction of complex rules. While it has been proposed that offline time might benefit this type of rule extraction, this remains to be tested. Here, we addressed this question using an artificial grammar learning paradigm. During a short-term memory cover task, eighty-one human participants were exposed to letter sequences generated according to an unknown artificial grammar. Following a time delay of 15 min, 12 h (wake or sleep) or 24 h, participants classified novel test sequences as Grammatical or Non-Grammatical. Previous behavioral and functional neuroimaging work has shown that classification can be guided by two distinct underlying processes: (1) the holistic abstraction of the underlying grammar rules and (2) the detection of sequence chunks that appear at varying frequencies during exposure. Here, we show that classification performance improved after sleep. Moreover, this improvement was due to an enhancement of rule abstraction, while the effect of chunk frequency was unaltered by sleep. These findings suggest that sleep plays a critical role in extracting complex structure from separate but related items during integrative memory processing. Our findings stress the importance of alternating periods of learning with sleep in settings in which complex information must be acquired.
Are explicit versus implicit learning mechanisms reflected in the brain as distinct neural structures, as previous research indicates, or are they distinguished by brain networks that involve overlapping systems with differential connectivity? In this functional MRI study we examined the neural correlates of explicit and implicit learning of artificial grammar sequences. Using effective connectivity analyses we found that brain networks of different connectivity underlie the two types of learning: while both processes involve activation in a set of cortical and subcortical structures, explicit learners engage a network that uses the insula as a key mediator whereas implicit learners evoke a direct frontal-striatal network. Individual differences in working memory also differentially impact the two types of sequence learning.
In the present experiment, we used event-related potentials (ERP) to investigate the role of immediate and delayed feedback in an artificial grammar learning (AGL) task. Two groups of participants were engaged in classifying non-word strings according to an underlying rule system, not known to the participants. Visual feedback was provided after each classification either immediately or with a short delay of 1 s. Both groups were able to learn the artificial grammar system as indicated by an increase in classification performance. However, the gain in performance was significantly larger for the group receiving immediate feedback as compared to the group receiving delayed feedback. Learning was accompanied by an increase in P300 activity in the ERP for delayed as compared to immediate feedback. Irrespective of feedback delay, both groups exhibited learning related decreases in the feedback-related positivity (FRP) elicited by positive feedback only. The feedback-related negativity (FRN), however, remained constant over the course of learning. These results suggest, first, that delayed feedback is less effective for AGL as task requirements are very demanding, and second, that the FRP elicited by positive prediction errors decreases with learning while the FRN to negative prediction errors is elicited in an all-or-none fashion by negative feedback throughout the entire experiment.
artificial grammar learning; ERN; feedback positivity; delayed feedback
The present study investigated whether a temporal hierarchical structure favors implicit learning. An artificial pitch grammar implemented with a set of tones was presented in two different temporal contexts, notably with either a strongly metrical structure or an isochronous structure. According to the Dynamic Attending Theory, external temporal regularities can entrain internal oscillators that guide attention over time, allowing for temporal expectations that influence perception of future events. Based on this framework, it was hypothesized that the metrical structure provides a benefit for artificial grammar learning in comparison to an isochronous presentation. Our study combined behavioral and event-related potential measurements. Behavioral results demonstrated similar learning in both participant groups. By contrast, analyses of event-related potentials showed a larger P300 component and an earlier N2 component for the strongly metrical group during the exposure phase and the test phase, respectively. These findings suggests that the temporal expectations in the strongly metrical condition helped listeners to better process the pitch dimension, leading to improved learning of the artificial grammar.
Considerable evidence suggests that people acquire artificial grammars incidentally and implicitly, an indispensable capacity for the acquisition of music or language. However, less research has been devoted to exploring constraints affecting incidental learning. Within the domain of music, the extent to which Narmour's (1990) melodic principles affect implicit learning of melodic structure was experimentally explored. Extending previous research (Rohrmeier, Rebuschat & Cross, 2011), the identical finite-state grammar is employed having terminals (the alphabet) manipulated so that melodies generated systematically violated Narmour's principles. Results indicate that Narmour-inconsistent melodic materials impede implicit learning. This further constitutes a case in which artificial grammar learning is affected by prior knowledge or processing constraints.
Implicit learning is often assumed to be an effortless process. However, some
artificial grammar learning and sequence learning studies using dual tasks seem
to suggest that attention is essential for implicit learning to occur. This
discrepancy probably results from the specific type of secondary task that is
used. Different secondary tasks may engage attentional resources differently and
therefore may bias performance on the primary task in different ways. Here, we
used a random number generation (RNG) task, which may allow for a closer
monitoring of a participant’s engagement in a secondary task than the popular
secondary task in sequence learning studies: tone counting (TC). In the first
two experiments, we investigated the interference associated with performing RNG
concurrently with a serial reaction time (SRT) task. In a third experiment, we
compared the effects of RNG and TC. In all three experiments, we directly
evaluated participants’ knowledge of the sequence with a subsequent sequence
generation task. Sequence learning was consistently observed in all experiments,
but was impaired under dual-task conditions. Most importantly, our data suggest
that RNG is more demanding and impairs learning to a greater extent than TC.
Nevertheless, we failed to observe effects of the secondary task in subsequent
sequence generation. Our studies indicate that RNG is a promising task to
explore the involvement of attention in the SRT task.
implicit learning; attention; serial reaction time task; random number generation task; tone counting task
Impaired verbal memory in schizophrenia is a key rate-limiting factor for functional outcome, does not respond to currently available medications, and shows only modest improvement after conventional behavioral remediation. The authors investigated an innovative approach to the remediation of verbal memory in schizophrenia, based on principles derived from the basic neuroscience of learning-induced neuroplasticity. The authors report interim findings in this ongoing study.
Fifty-five clinically stable schizophrenia subjects were randomly assigned to either 50 hours of computerized auditory training or a control condition using computer games. Those receiving auditory training engaged in daily computerized exercises that placed implicit, increasing demands on auditory perception through progressively more difficult auditory-verbal working memory and verbal learning tasks.
Relative to the control group, subjects who received active training showed significant gains in global cognition, verbal working memory, and verbal learning and memory. They also showed reliable and significant improvement in auditory psychophysical performance; this improvement was significantly correlated with gains in verbal working memory and global cognition.
Intensive training in early auditory processes and auditory-verbal learning results in substantial gains in verbal cognitive processes relevant to psychosocial functioning in schizophrenia. These gains may be due to a training method that addresses the early perceptual impairments in the illness, that exploits intact mechanisms of repetitive practice in schizophrenia, and that uses an intensive, adaptive training approach.
Associative learning is a central building block of human cognition and in large part depends on mechanisms of synaptic plasticity, memory capacity and fronto–hippocampal interactions. A disorder like schizophrenia is thought to be characterized by altered plasticity, and impaired frontal and hippocampal function. Understanding the expression of this dysfunction through appropriate experimental studies, and understanding the processes that may give rise to impaired behavior through biologically plausible computational models will help clarify the nature of these deficits. We present a preliminary computational model designed to capture learning dynamics in healthy control and schizophrenia subjects. Experimental data was collected on a spatial-object paired-associate learning task. The task evinces classic patterns of negatively accelerated learning in both healthy control subjects and patients, with patients demonstrating lower rates of learning than controls. Our rudimentary computational model of the task was based on biologically plausible assumptions, including the separation of dorsal/spatial and ventral/object visual streams, implementation of rules of learning, the explicit parameterization of learning rates (a plausible surrogate for synaptic plasticity), and learning capacity (a plausible surrogate for memory capacity). Reductions in learning dynamics in schizophrenia were well-modeled by reductions in learning rate and learning capacity. The synergy between experimental research and a detailed computational model of performance provides a framework within which to infer plausible biological bases of impaired learning dynamics in schizophrenia.
Learning dynamics; Schizophrenia; Computational models
OBJECTIVES—To assess explicit memory and two
components of implicit memory—that is, perceptual-verbal skill
learning and lexical-semantic priming effects—as well as resting
cerebral blood flow (CBF) and oxygen metabolism (CMRO2)
during the acute phase of transient global amnesia.
METHODS—In a 59 year old woman, whose amnestic
episode fulfilled all current criteria for transient global amnesia, a
neuropsychological protocol was administered, including word learning,
story recall, categorical fluency, mirror reading, and word stem
completion tasks. PET was performed using the 15O steady
state inhalation method, while the patient still exhibited severe
anterograde amnesia and was interleaved with the cognitive tests.
RESULTS—There was a clear cut dissociation
between impaired long term episodic memory and preserved implicit
memory for its two components. Categorical fluency was significantly
altered, suggesting word retrieval strategy—rather than semantic
memory—impairment. The PET study disclosed a reduced CMRO2
with relatively or fully preserved CBF in the left prefrontotemporal
cortex and lentiform nucleus, and the reverse pattern over the left
CONCLUSIONS—The PET alterations with patchy
CBF-CMRO2 uncoupling would be compatible with a
migraine-like phenomenon and indicate that the isolated assessment of
perfusion in transient global amnesia may be misleading. The pattern of
metabolic depression, with sparing of the hippocampal area, is one
among the distinct patterns of brain dysfunction that underlie the
(apparently) uniform clinical presentation of transient global amnesia.
The finding of a left prefrontal hypometabolism in the face of impaired
episodic memory and altered verbal fluency would fit present day
concepts from PET activation studies about the role of this area in
episodic and semantic memory encoding/retrieval. Likewise, the changes affecting the lenticular nucleus but sparing the caudate would be
consistent with the normal performance in perceptual-verbal skill
learning. Finally, unaltered lexical-semantic priming effects, despite
left temporal cortex hypometabolism, suggest that these processes are
subserved by a more distributed neocortical network.