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How does the human brain encode semantic information about objects? This paper reconciles two seemingly contradictory views. The first proposes that local neural populations independently encode semantic features; the second, that semantic representations arise as a dynamic distributed code that changes radically with stimulus processing. Combining simulations with a well-known neural network model of semantic memory, multivariate pattern classification, and human electrocorticography, we find that both views are partially correct: information about the animacy of a depicted stimulus is distributed across ventral temporal cortex in a dynamic code possessing feature-like elements posteriorly but with elements that change rapidly and nonlinearly in anterior regions. This pattern is consistent with the view that anterior temporal lobes serve as a deep cross-modal 'hub' in an interactive semantic network, and more generally suggests that tertiary association cortices may adopt dynamic distributed codes difficult to detect with common brain imaging methods., Competing Interests: TR, CC, QL, AS, TK, TK, SM, RT, AI, RM, ML No competing interests declared, (© 2021, Rogers et al.)

The hippocampus replays experiences during quiet rest periods, and this replay benefits subsequent memory. A critical open question is how memories are prioritized for this replay. We used functional magnetic resonance imaging (fMRI) pattern analysis to track item-level replay in the hippocampus during an awake rest period after participants studied 15 objects and completed a memory test. Objects that were remembered less well were replayed more during the subsequent rest period, suggesting a prioritization process in which weaker memories-memories most vulnerable to forgetting-are selected for replay. In a second session 12 hours later, more replay of an object during a rest period predicted better subsequent memory for that object. Replay predicted memory improvement across sessions only for participants who slept during that interval. Our results provide evidence that replay in the human hippocampus prioritizes weakly learned information, predicts subsequent memory performance, and relates to memory improvement across a delay with sleep.

Semantic memory encompasses knowledge about both the properties that typify concepts (e.g. robins, like all birds, have wings) as well as the properties that individuate conceptually related items (e.g. robins, in particular, have red breasts). We investigate the impact of sleep on new semantic learning using a property inference task in which both kinds of information are initially acquired equally well. Participants learned about three categories of novel objects possessing some properties that were shared among category exemplars and others that were unique to an exemplar, with exposure frequency varying across categories. In Experiment 1, memory for shared properties improved and memory for unique properties was preserved across a night of sleep, while memory for both feature types declined over a day awake. In Experiment 2, memory for shared properties improved across a nap, but only for the lower-frequency category, suggesting a prioritization of weakly learned information early in a sleep period. The increase was significantly correlated with amount of REM, but was also observed in participants who did not enter REM, suggesting involvement of both REM and NREM sleep. The results provide the first evidence that sleep improves memory for the shared structure of object categories, while simultaneously preserving object-unique information.

Studies of semantic impairment arising from brain disease suggest that the anterior temporal lobes are critical for semantic abilities in humans; yet activation of these regions is rarely reported in functional imaging studies of healthy controls performing semantic tasks. Here, we combined neuropsychological and PET functional imaging data to show that when healthy subjects identify concepts at a specific level, the regions activated correspond to the site of maximal atrophy in patients with relatively pure semantic impairment. The stimuli were color photographs of common animals or vehicles, and the task was category verification at specific (e.g., robin), intermediate (e.g., bird), or general (e.g., animal) levels. Specific, relative to general, categorization activated the antero-lateral temporal cortices bilaterally, despite matching of these experimental conditions for difficulty. Critically, in patients with atrophy in precisely these areas, the most pronounced deficit was in the retrieval of specific semantic information.

Using semantic dementia (SD) as a reference point, the authors assessed semantic memory in four other neurodegenerative disorders: progressive nonfluent aphasia (PNFA), frontal variant frontotemporal dementia (fvFTD), Alzheimer's disease (AD), and posterior cortical atrophy (PCA). Individuals with SD were more impaired than other groups on semantic measures and showed a characteristic pattern across tasks: category fluency (CF) worse than letter fluency (LF), naming worse than comprehension, and visual and verbal comprehension equally affected, suggesting disruption to an amodal semantic system. Individuals with AD demonstrated a similar pattern to a milder degree. Although PNFA, fvFTD, and PCA groups had abnormal scores (relative to controls) on most semantic measures, their differing patterns across measures indicate that the apparent semantic impairment in these conditions is largely secondary to other factors., (Copyright (c) 2006 APA, all rights reserved.)

This paper introduces a special issue of "Cognitive Science" initiated on the 25th anniversary of the publication of "Parallel Distributed Processing" (PDP), a two-volume work that introduced the use of neural network models as vehicles for understanding cognition. The collection surveys the core commitments of the PDP framework, the key issues the framework has addressed, and the debates the framework has spawned, and presents viewpoints on the current status of these issues. The articles focus on both historical roots and contemporary developments in learning, optimality theory, perception, memory, language, conceptual knowledge, cognitive control, and consciousness. Here we consider the approach more generally, reviewing the original motivations, the resulting framework, and the central tenets of the underlying theory. We then evaluate the impact of PDP both on the field at large and within specific subdomains of cognitive science and consider the current role of PDP models within the broader landscape of contemporary theoretical frameworks in cognitive science. Looking to the future, we consider the implications for cognitive science of the recent success of machine learning systems called "deep networks"--systems that build on key ideas presented in the PDP volumes.

Three experiments with 88 college-aged participants explored how unlabeled experiences--learning episodes in which people encounter objects without information about their category membership--influence beliefs about category structure. Participants performed a simple one-dimensional categorization task in a brief supervised learning phase, then made a large number of unsupervised categorization decisions about new items. In all three experiments, the unsupervised experience altered participants' implicit and explicit mental category boundaries, their explicit beliefs about the most representative members of each category, and even their memory for the items encountered during the supervised learning phase. These changes were influenced by both the range and frequency distribution of the unlabeled stimuli: mental category boundaries shifted toward the middle of the range and toward the trough of the bimodal distribution of unlabeled items, whereas beliefs about the most representative category members shifted toward the modes of the unlabeled distribution. One consequence of this shift in representations is a false-consensus effect (Experiment 3) where participants, despite receiving very disparate training experiences, show strong agreement in judgments about representativeness and boundary location following unsupervised category judgments. (Contains 5 figures.)

Patients with semantic dementia show a specific pattern of impairment on both verbal and non-verbal "pre-semantic" tasks, e.g., reading aloud, past tense generation, spelling to dictation, lexical decision, object decision, colour decision and delayed picture copying. All seven tasks are characterised by poorer performance for items that are atypical of the domain and "regularisation errors" (irregular/atypical items are produced as if they were domain-typical). The emergence of this pattern across diverse tasks in the same patients indicates that semantic memory plays a key role in all of these types of "pre-semantic" processing. However, this claim remains controversial because semantically impaired patients sometimes fail to show an influence of regularity. This study demonstrates that (a) the location of brain damage and (b) the underlying nature of the semantic deficit affect the likelihood of observing the expected relationship between poor comprehension and regularity effects. We compared the effect of multimodal semantic impairment in the context of semantic dementia and stroke aphasia on the seven "pre-semantic" tasks listed above. In all of these tasks, the semantic aphasia patients were less sensitive to typicality than the semantic dementia patients, even though the two groups obtained comparable scores on semantic tests. The semantic aphasia group also made fewer regularisation errors and many more unrelated and perseverative responses. We propose that these group differences reflect the different locus for the semantic impairment in the two conditions: patients with semantic dementia have degraded semantic representations, whereas semantic aphasia patients show deregulated semantic cognition with concomitant executive deficits. These findings suggest a reinterpretation of single-case studies of comprehension-impaired aphasic patients who fail to show the expected effect of regularity on "pre-semantic" tasks. Consequently, such cases do not demonstrate the independence of these tasks from semantic memory. (Contains 9 figures and 6 tables.)

Wernicke (1900, as cited in G. H. Eggert, 1977) suggested that semantic knowledge arises from the interaction of perceptual representations of objects and words. The authors present a parallel distributed processing implementation of this theory, in which semantic representations emerge from mechanisms that acquire the mappings between visual representations of objects and their verbal descriptions. To test the theory, they trained the model to associate names, verbal descriptions, and visual representations of objects. When its inputs and outputs are constructed to capture aspects of structure apparent in attribute-norming experiments, the model provides an intuitive account of semantic task performance. The authors then used the model to understand the structure of impaired performance in patients with selective and progressive impairments of conceptual knowledge. Data from 4 well-known semantic tasks revealed consistent patterns that find a ready explanation in the model. The relationship between the model and related theories of semantic representation is discussed.

Contemporary clinical and basic neuroscience studies have increasingly implicated the anterior temporal lobe regions, bilaterally, in the formation of coherent concepts. Mounting convergent evidence for the importance of the anterior temporal lobe in semantic memory is found in patients with bilateral anterior temporal lobe damage (e.g. semantic dementia), functional neuroimaging and repetitive transcranial magnetic stimulation studies. If this proposal is correct, then one might expect patients with anterior temporal lobe resection for long-standing temporal lobe epilepsy to be semantically impaired. Such patients, however, do not present clinically with striking comprehension deficits but with amnesia and variable anomia, leading some to conclude that semantic memory is intact in resection for temporal lobe epilepsy and thus casting doubt over the conclusions drawn from semantic dementia and linked basic neuroscience studies. Whilst there is a considerable neuropsychological literature on temporal lobe epilepsy, few studies have probed semantic memory directly, with mixed results, and none have undertaken the same type of systematic investigation of semantic processing that has been conducted with other patient groups. In this study, therefore, we investigated the semantic performance of 20 patients with resection for chronic temporal lobe epilepsy with a full battery of semantic assessments, including more sensitive measures of semantic processing. The results provide a bridge between the current clinical observations about resection for temporal lobe epilepsy and the expectations from semantic dementia and other neuroscience findings. Specifically, we found that on simple semantic tasks, the patients’ accuracy fell in the normal range, with the exception that some patients with left resection for temporal lobe epilepsy had measurable anomia. Once the semantic assessments were made more challenging, by probing specific-level concepts, lower frequency/more abstract items or measuring reaction times on semantic tasks versus those on difficulty-matched non-semantic assessments, evidence of a semantic impairment was found in all individuals. We conclude by describing a unified, computationally inspired framework for capturing the variable degrees of semantic impairment found across different patient groups (semantic dementia, temporal lobe epilepsy, glioma and stroke) as well as semantic processing in neurologically intact participants. [ABSTRACT FROM PUBLISHER]

In this précis of our recent book, Semantic Cognition: A Parallel Distributed Processing Approach (Rogers & McClelland 2004), we present a parallel distributed processing theory of the acquisition, representation, and use of human semantic knowledge. The theory proposes that semantic abilities arise from the flow of activation among simple, neuron-like processing units, as governed by the strengths of interconnecting weights; and that acquisition of new semantic information involves the gradual adjustment of weights in the system in response to experience. These simple ideas explain a wide range of empirical phenomena from studies of categorization, lexical acquisition, and disordered semantic cognition. In this précis we focus on phenomena central to the reaction against similarity-based theories that arose in the 1980s and that subsequently motivated the 'theory-theory" approach to semantic knowledge. Specifically, we consider (1) how concepts differentiate in early development, (2) why some groupings of items seem to form "good" or coherent categories while others do not, (3) why different properties seem central or important to different concepts, (4) why children and adults sometimes attest to beliefs that seem to contradict their direct experience, (5) how concepts reorganize between the ages of 4 and 10, and (6) the relationship between causal knowledge and semantic knowledge. The explanations our theory offers for these phenomena are illustrated with reference to a simple feed- forward connectionist model. The relationships between this simple model, the broader theory, and more general issues in cognitive science are discussed. [ABSTRACT FROM AUTHOR]

Mr M, a patient with semantic dementia--a neurodegenerative disease that is characterized by the gradual deterioration of semantic memory--was being driven through the countryside to visit a friend and was able to remind his wife where to turn along the not-recently-travelled route. Then, pointing at the sheep in the field, he asked her "What are those things?" Prior to the onset of symptoms in his late 40s, this man had normal semantic memory. What has gone wrong in his brain to produce this dramatic and selective erosion of conceptual knowledge? [ABSTRACT FROM AUTHOR]

Investigations of memory in rats and nonhuman primates have demonstrated functional specialization within the medial temporal lobe (MTL), a set of heavily interconnected structures including the hippocampal formation and underlying entorhinal, perirhinal, and parahippocampal cortices. Most studies in humans, however, especially in patients with brain damage, suggest that the human MTL is a unitary memory system supporting all types of declarative memory, our conscious memory for facts and events. To resolve this discrepancy, amnesic patients with either selective hippocampal damage or more extensive MTL damage were tested on variations of an object discrimination task adapted from the nonhuman primate literature. Although both groups were equally impaired on standard recall-based memory tasks, they exhibited different profiles of performance on the object discrimination test, arguing against a unitary view of MTL function. Cases with selective hippocampal damage performed normally, whereas individuals with broader MTL lesions were impaired. Furthermore, deficits in this latter group were related not to the number of discriminations to be learned and remembered, but to the degree of "feature ambiguity," a property of visual discriminations that can emerge when features are part of both rewarded and unrewarded stimuli. These findings resolve contradictions between published studies in humans and animals and introduce a new way of characterizing the impairments that arise after damage to the MTL. [ABSTRACT FROM AUTHOR]

Although patients with semantic deficits can sometimes show good performance on tests of object decision, we present evidence that this pattern applies when nonsense-objects do not respect the regularities of the domain. In a newly designed test of object-decision, 20 patients with semantic dementia viewed line drawings of a real and chimeric animal side-by-side, and were asked to decide which was real. The real animal was either more typical (real > nonreal) or less typical (nonreal > real) than the chimera. Performance was significantly better in the real > nonreal condition, and success in both conditions was modulated by patients' degree of semantic impairment. A similar effect of item typicality was revealed in a subset of items selected from a standard test battery. Object-decision scores were highly correlated with other pictorial and verbal assessments of conceptual knowledge, suggesting that impaired performance on all tasks resulted from the degradation of a unitary underlying system. [ABSTRACT FROM AUTHOR]

State-of-the-art brain imaging studies have recently produced a variety of sometimes contradictory conclusions about the neural systems that support human semantic memory. Multivariate techniques deployed in this work adopt implicit or explicit assumptions that limit the types of signal they can detect, and thus the types of hypotheses they can test. We lay out the space of possible cognitive and neural representations and then critically review contemporary methods to determine which analyses can test which hypotheses. The results account for the heterogeneity of recent findings and identify an important empirical and methodological gap that makes it difficult to connect the imaging literature to neurocomputational models of semantic processing. A key goal for cognitive neuroscience is to understand the neurocognitive systems that support semantic memory. Recent multivariate analyses of neuroimaging data have contributed greatly to this effort, but the rapid development of these novel approaches has made it difficult to track the diversity of findings and to understand how and why they sometimes lead to contradictory conclusions. We address this challenge by reviewing cognitive theories of semantic representation and their neural instantiation. We then consider contemporary approaches to neural decoding and assess which types of representation each can possibly detect. The analysis suggests why the results are heterogeneous and identifies crucial links between cognitive theory, data collection, and analysis that can help to better connect neuroimaging to mechanistic theories of semantic cognition. [ABSTRACT FROM AUTHOR]