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The hypothesized role of Broca's area in sentence processing ranges from domain-general executive function to domain-specific computation that is specific to certain syntactic structures. We examined this issue by manipulating syntactic structure and conflict between syntactic and semantic cues in a sentence processing task. Functional neuroimaging revealed that activation within several Broca's area regions of interest reflected the parametric variation in syntactic-semantic conflict. These results suggest that Broca's area supports sentence processing by mediating between multiple incompatible constraints on sentence interpretation, consistent with this area's well-known role in conflict resolution in other linguistic and non-linguistic tasks. [ABSTRACT FROM AUTHOR]

Our environment contains temporal information unfolding simultaneously at multiple timescales. How do we learn and represent these dynamic and overlapping information streams? We investigated these processes in a statistical learning paradigm with simultaneous short and long timescale contingencies. Human participants (n = 96) played a game where they learned to quickly click on a target image when it appeared in one of nine locations, in eight different contexts. Across contexts, we manipulated the order of target locations: at a short timescale, the order of pairs of sequential locations in which the target appeared; at a longer timescale, the set of locations that appeared in the first versus the second half of the game. Participants periodically predicted the upcoming target location, and later performed similarity judgments comparing the games based on their order properties. Participants showed context-dependent sensitivity to order information at both short and long timescales, with evidence of stronger learning for short timescales. We modeled the learning paradigm using a gated recurrent network trained to make immediate predictions, which demonstrated multilevel learning timecourses and patterns of sensitivity to the similarity structure of the games that mirrored human participants. The model grouped games with matching rule structure and dissociated games based on low-level order information more so than high-level order information. The work shows how humans and models can rapidly and concurrently acquire order information at different timescales., (© 2024 Massachusetts Institute of Technology.)

Memory retrieval does not provide a perfect recapitulation of past events, but instead an imperfect reconstruction of event-specific details and general knowledge. However, it remains unclear whether this reconstruction relies on mixtures of signals from different memory systems, including one supporting general knowledge. Here, we investigate whether the anterior temporal lobe (ATL) distorts new memories because of prior category knowledge. In this preregistered experiment (n = 36), participants encoded and retrieved image-location associations. Most images' locations were clustered according to their category, but some were in random locations. With this protocol, we previously demonstrated that randomly located images were retrieved closer to their category cluster relative to their encoded locations, suggesting an influence of category knowledge. We combined this procedure with TMS delivered to the left ATL before retrieval. We separately examined event-specific details (error) and category knowledge (bias) to identify distinct signals attributable to different memory systems. We found that TMS to ATL attenuated bias in location memory, but this effect was limited to exploratory analyses of atypical category members of animal categories. The magnitude of error was not impacted, suggesting that a memory's fidelity can be decoupled from its distortion by category knowledge. This raises the intriguing possibility that retrieval is jointly supported by separable memory systems., (© 2023 Massachusetts Institute of Technology.)

Conceptual combination is the act of building complex concepts from simpler ones. Although research has examined how inferences about compound objects (e.g., fuzzy chair) are produced from their constituent concepts, little is known about the combinatorial processes that produce inferences about compound social categories (e.g., Irish musician). Using a computational approach, we investigated the relationship between ratings of 25 nationality-occupation combinations and ratings of their constituent concepts along the attribute dimensions of warmth and competence. We found that people incorporate uncertainty into their perceptions of compound social categories. Further, people are more likely to use a linear combination strategy when they are more certain about the attributes of the constituents and less familiar with the combination. Conversely, when social combinations are more familiar, their judged attributes deviate further from the predictions of a combinatorial model and are shared across participants, suggesting that stereotype-based knowledge plays a central role in the representation of complex social groups. Twenty-five non-human animal combinations (e.g., circus snake) serve as a comparison and were rated on size and ferocity. We found evidence that familiarity has different effects on the strategies used to combine person concepts and animal concepts, pointing to the possible existence of both common and distinct mechanisms for constructing social and non-social categories., Competing Interests: Declaration of Competing Interest None., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Tool-selective lateral occipitotemporal cortex (LOTC) responds preferentially to images of tools (hammers, brushes) relative to non-tool objects (clocks, shoes). What drives these responses? Unlike other objects, tools exert effects on their surroundings. We tested whether LOTC responses are influenced by event schemas that denote different temporal relations. Participants learned about novel objects embedded in different event sequences. Causer objects moved prior to the appearance of an environmental event (e.g. stars), while Reactor objects moved after an event. Visual features and motor association were controlled. During functional magnetic resonance imaging, participants viewed still images of the objects. We localized tool-selective LOTC and non-tool-selective parahippocampal cortex (PHC) by contrasting neural responses to images of familiar tools and non-tools. We found that LOTC responded more to Causers than Reactors, while PHC did not. We also measured responses to images of hands, which elicit overlapping responses with tools. Across inferior temporal cortex, voxels' tool and hand selectivity positively predicted a preferential response to Causers. We conclude that an event schema typical of tools is sufficient to drive LOTC and that category-preferential responses across the temporal lobe may reflect relational event structures typical of those domains., (© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

The brain is organized into networks at multiple resolutions, or scales, yet studies of functional network development typically focus on a single scale. Here, we derive personalized functional networks across 29 scales in a large sample of youths (n = 693, ages 8-23 years) to identify multi-scale patterns of network re-organization related to neurocognitive development. We found that developmental shifts in inter-network coupling reflect and strengthen a functional hierarchy of cortical organization. Furthermore, we observed that scale-dependent effects were present in lower-order, unimodal networks, but not higher-order, transmodal networks. Finally, we found that network maturation had clear behavioral relevance: the development of coupling in unimodal and transmodal networks are dissociably related to the emergence of executive function. These results suggest that the development of functional brain networks align with and refine a hierarchy linked to cognition., (© 2022. The Author(s).)

There is growing interest in how neuromodulators shape brain networks. Recent neuroimaging studies provide evidence that brainstem arousal systems, such as the locus coeruleus-norepinephrine system (LC-NE), influence functional connectivity and brain network topology, suggesting they have a role in flexibly reconfiguring brain networks in order to adapt behavior and cognition to environmental demands. To date, however, the relationship between brainstem arousal systems and functional connectivity has not been assessed within the context of a task with an established relationship between arousal and behavior, with most prior studies relying on incidental variations in arousal or pharmacological manipulation and static brain networks constructed over long periods of time. These factors have likely contributed to a heterogeneity of effects across studies. To address these issues, we took advantage of the association between LC-NE-linked arousal and exploration to probe the relationships between exploratory choice, arousal-as measured indirectly via pupil diameter-and brain network dynamics. Exploration in a bandit task was associated with a shift toward fewer, more weakly connected modules that were more segregated in terms of connectivity and topology but more integrated with respect to the diversity of cognitive systems represented in each module. Functional connectivity strength decreased, and changes in connectivity were correlated with changes in pupil diameter, in line with the hypothesis that brainstem arousal systems influence the dynamic reorganization of brain networks. More broadly, we argue that carefully aligning dynamic network analyses with task designs can increase the temporal resolution at which behaviorally- and cognitively-relevant modulations can be identified, and offer these results as a proof of concept of this approach., Competing Interests: Declaration of Competing Interest The authors declare that they have no competing interests., (Copyright © 2021. Published by Elsevier Inc.)

Prior knowledge has long been known to shape new episodic memories. However, it is less clear how prior knowledge can scaffold the learning of a new class of information, and how this can bias memory for the episodes that contributed to its acquisition. We aimed to quantify distortions in episodic memories resulting from the use of prior category knowledge to facilitate learning new information. Across 4 experiments, participants encoded and retrieved image-location associations. Most members of a category (e.g., birds) were located near each other, such that participants could leverage their prior category knowledge to learn the spatial locations of categories as they encoded specific image locations. Critically, some typical and atypical category members were in random locations. We decomposed location memory into 2 measures: error, a measure of episodic specificity; and bias toward other category members, a measure of the influence of newly-learned information about category locations. First, we found that location memory was more accurate for images whose locations were spatially consistent with their category membership. Second, when images were spatially inconsistent (i.e., in random locations), retrieval of typical category members was more biased toward their category's location relative to atypical ones. These effects replicated across 3 experiments, disappeared when images were not arranged by category, and were stronger than effects observed with images arranged by visual similarity rather than category membership. Our observations provide compelling evidence that memory is a reconstruction of multiple sources of prior knowledge, new learning, and memory for specific events. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Our experiences in the world support memories not only of specific episodes but also of the generalities (the 'gist') across related experiences. It remains unclear how these two types of memories evolve and influence one another over time. In two experiments, 173 human participants encoded spatial locations from a distribution and reported both item memory (specific locations) and gist memory (center for the locations) across 1-2 months. Experiment 1 demonstrated that after 1 month, gist memory was preserved relative to item memory, despite a persistent positive correlation between them. Critically, item memories were biased toward the gist over time. Experiment 2 showed that a spatial outlier item changed this relationship and that the extraction of gist is sensitive to the regularities of items. Our results suggest that the gist starts to guide item memories over longer durations as their relative strengths change., Competing Interests: TZ, AT, ST No competing interests declared, AS Reviewing editor, eLife, (© 2021, Zeng et al.)

Theories of the processes involved in creative cognition posit that cognitive control has a negative effect on creative idea generation but a positive effect on creative idea evaluation. Brain stimulation research has started to examine empirically the effects of cognitive control, with several reports of decreased cognitive control facilitating creative ideation. Such studies have shown how decreased cognitive control mechanisms facilitate creative idea generation, potentially by allowing participants access to less inhibited weaker-related associations, thereby increasing novelty. In the current study, we advance this line of work by investigating how cognitive control affects creative thinking, potentially inhibiting or facilitating novel idea generation based on task demands. Participants read sentences with the final word missing and were instructed to complete the sentence with an uncommon (but appropriate) ending. Participants performed this task while undergoing either anodal (excitatory), cathodal (inhibitory), or sham (control) transcranial direct current stimulation over their left prefrontal cortex. These responses were then rated for their novelty and appropriateness by an independent sample of raters. We found that anodal stimulation increased the appropriateness and decreased the novelty of participants' responses. Contrary to previous studies, we did not find that cathodal stimulation increased the novelty of participants' responses, which may be due to the nature of our task. Overall, we demonstrate how cognitive control mechanisms may inhibit novel idea generation.

The cognitive and neural structure of conceptual knowledge affects how concepts combine in language and thought. Examining the principles by which individual concepts (e.g., diamond, baseball) combine into more complex phrases (e.g., "baseball diamond") can illuminate not only how the brain combines concepts but also the key ingredients of conceptual structure. Here we specifically tested the role of feature uncertainty in the modulation of conceptual brightness evoked by adjective-noun combinations (e.g., "dark diamond") in male and female human subjects. We collected explicit ratings of conceptual brightness for 45 noun concepts and their "dark" and "light" combinations, resulting in a measure reflecting the degree of conceptual brightness modulation in each noun concept. Feature uncertainty was captured in an entropy measure, as well as in a predictive Bayesian model of feature modulation. We found that feature uncertainty (i.e., entropy) and the Bayesian model were both strong predictors of these behavioral effects. Using fMRI, we observed the neural responses evoked by the concepts and combinations in a priori ROIs. Feature uncertainty predicted univariate responses in left inferior frontal gyrus, and multivariate responses in left anterior temporal lobe were predicted by degree of conceptual brightness modulation. These findings suggest that feature uncertainty is a key ingredient of conceptual structure, and inform cognitive neuroscience theories of conceptual combination by highlighting the role of left inferior frontal gyrus and left anterior temporal lobe in the process of flexible feature modulation during comprehension of complex language. SIGNIFICANCE STATEMENT The meaning of a word depends on the words surrounding it. The challenge of understanding how flexible meaning emerges in language can be simplified by studying adjective-noun phrases. We tested whether the uncertainty of a feature (i.e., brightness) in a given noun concept (e.g., diamond) influences how the adjective and noun concepts combine. We analyzed feature uncertainty using two probabilistic measures, and found that feature uncertainty predicted people's explicit interpretations of adjective-noun phrases (e.g., "dark diamond"). Using fMRI, we found that combined concepts evoked responses in left inferior frontal gyrus and left anterior temporal lobe that related to our measures of feature modulation and uncertainty. These findings reveal the cognitive and neural processes supporting conceptual combination and complex language use., (Copyright © 2020 the authors.)

Knowledge of predictive relations is a core aspect of learning. Beyond individual relations, we also represent intuitive theories of the world, which include interrelated sets of relations. We asked whether individual predictive relations learned incidentally in the same context become associatively bound and whether they spontaneously influence later learning. Participants performed a cover task while watching three sequences of events. Each sequence contained the same set of events, but differed in how the events related to each other. The first two sequences each had two strong predictive relations (R1 & R2, and R3 & R4). The third contained either a consistent pairing of relations (R1 & R2) or an inconsistent pairing (R1 & R3). We found that participants' learning of the individual relations in the third sequence was affected by pairing consistency, suggesting the mind associates relations to each other as part of the intrinsic way it learns about the world. This was despite participants' minimal ability to verbally describe most of the relations they had learned. Thus, participants spontaneously developed the expectation that pairs of relations should cohere, and this affected their ability to learn new evidence. Such associative binding of relational information may help us build intuitive theories., (Copyright © 2020 Elsevier B.V. All rights reserved.)

When learning about events through visual experience, one must not only identify which events are visually similar but also retrieve those events' associates-which may be visually dissimilar-and recognize when different events have similar predictive relations. How are these demands balanced? To address this question, we taught participants the predictive structures among four events, which appeared in four different sequences, each cued by a distinct object. In each, one event ("cause") was predictably followed by another ("effect"). Sequences in the same relational category had similar predictive structure, while across categories, the effect and cause events were reversed. Using functional magnetic resonance imaging data, we measured "associative coding," indicated by correlated responses between effect and cause events; "perceptual coding," indicated by correlated responses to visually similar events; and "relational category coding," indicated by correlated responses to sequences in the same relational category. All three models characterized responses within the right middle temporal gyrus (MTG), but in different ways: Perceptual and associative coding diverged along the posterior to anterior axis, while relational categories emerged anteriorly in tandem with associative coding. Thus, along the posterior-anterior axis of MTG, the representation of the visual attributes of events is transformed to a representation of both specific and generalizable relational attributes., (© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

The same concept can mean different things or be instantiated in different forms, depending on context, suggesting a degree of flexibility within the conceptual system. We propose that a feature-based network model can be used to capture and predict this flexibility. We modeled individual concepts (e.g., BANANA, BOTTLE) as graph-theoretical networks, in which properties (e.g., YELLOW, SWEET) were represented as nodes and their associations as edges. In this framework, networks capture within-concept statistics that reflect how properties relate to one another across instances of a concept. We extracted formal measures of these networks that capture different aspects of network structure, and explored whether a concept's network structure relates to its flexibility of use. To do so, we compared network measures to a text-based measure of semantic diversity, as well as to empirical data from a figurative-language task and an alternative-uses task. We found that network-based measures were predictive of the text-based and empirical measures of flexible concept use, highlighting the ability of this approach to formally capture relevant characteristics of conceptual structure. Conceptual flexibility is a fundamental attribute of the cognitive and semantic systems, and in this proof of concept we reveal that variations in concept representation and use can be formally understood in terms of the informational content and topology of concept networks.

A fundamental cognitive process is to map value and identity onto the objects we learn about. However, what space best embeds this mapping is not completely understood. Here we develop tools to quantify the space and organization of such a mapping in neural responses as reflected in functional MRI, to show that quick learners have a higher dimensional representation than slow learners, and hence more easily distinguishable whole-brain responses to objects of different value. Furthermore, we find that quick learners display more compact embedding of their neural responses, and hence have higher ratios of their stimuli dimension to their embedding dimension, which is consistent with greater efficiency of cognitive coding. Lastly, we investigate the neurophysiological drivers at smaller scales and study the complementary distinguishability of whole-brain responses. Our results demonstrate a spatial organization of neural responses characteristic of learning and offer geometric measures applicable to identifying efficient coding in higher-order cognitive processes.

Brain imaging research shows that viewing tools activates regions of the cortex implicated in performing actions with that tool. Grounded (or embodied) theories of cognition propose that this activity reflects the activation of motor representations that are constitutive of the object concept. Behaviorally, participants respond faster with the hand that is aligned with the handle of an object. This stimulus-response compatibility (SRC) effect is often taken as evidence supporting the hypothesis that motor representations are activated in response to the visual presentation of tools during conceptual processing. To test this hypothesis, we trained participants to use a set of novel tools (manipulation group) or to report spatial information about the tools (spatial group) in preparation for a Martian archeological dig. We investigated compatibility effects in a conceptual judgment task and a visual discrimination task. Compatibility effects were observed for both groups regardless of experience. These effects were predicted by the salient parts of objects specified by task demands and not by motor experience with the objects. This result provides evidence that compatibility effects with tools reflect a general stimulus-response compatibly effect due to visual attention. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

The pervasive presence of relational information in concepts, and its indirect presence in sensory input, raises the question of how it is extracted from experience. We operationalized experience as a stream of events in which reliable predictive relationships exist among random ones, and in which learners are naïve as to what they will learn (i.e., a statistical learning paradigm). First, we asked whether predictive event pairs would spontaneously be seen as causing each other, given no instructions to evaluate causality. We found that predictive information indeed informed later causal judgments but did not lead to a spontaneous sense of causality. Thus, event contingencies are relevant to causal inference, but such interpretations may not occur fully bottom-up. A second question was how such experience might be used to learn about novel objects. Because events occurred either around or involving a continually present object, we were able to distinguish objects from events. We found that objects can be attributed causal properties by virtue of a higher-order structure, in which the object's identity is linked not to the increased likelihood of its effect, but rather, to the predictive structure among events, given its presence. This is an important demonstration that objects' causal properties can be highly abstract: They need not refer to an occurrence of a sensory event per se, or its link to an object, but rather to whether or not a predictive relationship holds among events in its presence. These learning mechanisms may be important for acquiring abstract knowledge from experience. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Theories of embodied cognition propose that we recognize tools in part by reactivating sensorimotor representations of tool use in a process of simulation. If motor simulations play a causal role in tool recognition then performing a concurrent motor task should differentially modulate recognition of experienced vs. non-experienced tools. We sought to test the hypothesis that an incompatible concurrent motor task modulates conceptual processing of learned vs. non-learned objects by directly manipulating the embodied experience of participants. We trained one group to use a set of novel, 3-D printed tools under the pretense that they were preparing for an archeological expedition to Mars (manipulation group); we trained a second group to report declarative information about how the tools are stored (storage group). With this design, familiarity and visual attention to different object parts was similar for both groups, though their qualitative interactions differed. After learning, participants made familiarity judgments of auditorily presented tool names while performing a concurrent motor task or simply sitting at rest. We showed that familiarity judgments were facilitated by motor state-dependence; specifically, in the manipulation group, familiarity was facilitated by a concurrent motor task, whereas in the spatial group familiarity was facilitated while sitting at rest. These results are the first to directly show that manipulation experience differentially modulates conceptual processing of familiar vs. unfamiliar objects, suggesting that embodied representations contribute to recognizing tools.

The way that our brain processes visual information is directly affected by our experience. Repeated exposure to a visual stimulus triggers experience-dependent plasticity in the visual cortex of many species. Humans also have the unique ability to acquire visual knowledge through instruction. We introduced human participants to the real-world size of previously unfamiliar species, and to the functional motion of novel tools, during a functional magnetic resonance imaging scan. Using machine learning, we compared activity patterns evoked by images of the new items, before and after participants learned the animals' real-world size or tools' motion. We found that, after acquiring size information, participants' visual activity patterns for the new animals became more confusable with activity patterns evoked by similar-sized known animals in early visual cortex, but not in ventral temporal cortex, reflecting an influence of new size knowledge on posterior, but not anterior, components of the ventral stream. In contrast, learning the functional motion of new tools did not lead to an equivalent change in recorded activity. Finally, the time-points marked by evidence of new size information in early visual cortex were more likely to show size information and greater activation in the right angular gyrus, a key hub of semantic knowledge and spatial cognition. Overall, these findings suggest that learning an item's real-world size by instruction influences subsequent activity in visual cortex and in a region that is central to semantic and spatial brain systems., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Instructions have a powerful effect on learning and decision-making, biasing choice even in the face of disconfirming feedback. Detrimental biasing effects have been reported in a number of studies in which instruction was given prior to trial-and-error learning. Previous work has attributed individual differences in instructional bias to variations in prefrontal and striatal dopaminergic genes, suggesting a role for prefrontally-mediated cognitive control processes in biasing learning. The current study replicates and extends these findings. Human subjects performed a probabilistic reinforcement learning task after receiving inaccurate instructions about the quality of one of the options. In order to establish a causal relationship between prefrontal cortical mechanisms and instructional bias, we applied transcranial direct current stimulation over dorsolateral prefrontal cortex (anodal, cathodal, or sham) while subjects performed the task. We additionally genotyped subjects for the COMT Val158Met genetic polymorphism, which influences the breakdown of prefrontal dopamine, and for the DAT1/SLC6A3 variable number tandem repeat, which affects expression of striatal dopamine transporter. We replicated the finding that the COMT Met allele is associated with increased instructional bias and further demonstrated that variation in DAT1 has similar effects to variation in COMT, with 9-repeat carriers demonstrating increased bias relative to 10-repeat homozygotes. Consistent with increased top-down regulation of reinforcement learning, anodal subjects demonstrated greater bias relative to sham, though this effect was present only early in training. In contrast, there was no effect of cathodal stimulation. Finally, we fit computational models to subjects' data to better characterize the mechanisms underlying instruction bias. A novel choice bias model, in which instructions influence decision-making rather than learning, was found to best account for subjects' behavior. Overall, these data provide further evidence for the role of frontostriatal interactions in biasing instructed reinforcement learning, which adds to the growing literature documenting both costs and benefits of cognitive control.

The internal representation of stimuli is imperfect and subject to bias. Noise introduced at initial encoding and during maintenance degrades the precision of representation. Stimulus estimation is also biased away from recently encountered stimuli, a phenomenon known as adaptation. Within a Bayesian framework, greater biases are predicted to result from poor precision. We tested for this effect on individual difference measures. Through an online experiment, 202 subjects contributed data. During separate face and color blocks, they performed three different tasks: an immediate stimulus match, a delayed match-to-sample, and a delayed match following 5 s of adaptation. The stimulus spaces were circular, and subjects entered their responses on a color/face wheel. Bias and precision of responses were extracted while accounting for the probability of random guesses. We found that the adaptation manipulation induced the expected bias in responses, and the magnitude of this bias varied reliably and substantially between subjects. Across subjects, there was a negative correlation between mean precision and bias. This relationship was replicated in a new experiment with 192 subjects. This result is consistent with a Bayesian observer model, in which the precision of perceptual representation influences the magnitude of perceptual bias.

High-level cognitive constructs, such as creativity and intelligence, entail complex and multiple processes, including cognitive control processes. Recent neurocognitive research on these constructs highlight the importance of dynamic interaction across neural network systems and the role of cognitive control processes in guiding such a dynamic interaction. How can we quantitatively examine the extent and ways in which cognitive control contributes to creativity and intelligence? To address this question, we apply a computational network control theory (NCT) approach to structural brain imaging data acquired via diffusion tensor imaging in a large sample of participants, to examine how NCT relates to individual differences in distinct measures of creative ability and intelligence. Recent application of this theory at the neural level is built on a model of brain dynamics, which mathematically models patterns of inter-region activity propagated along the structure of an underlying network. The strength of this approach is its ability to characterize the potential role of each brain region in regulating whole-brain network function based on its anatomical fingerprint and a simplified model of node dynamics. We find that intelligence is related to the ability to "drive" the brain system into easy to reach neural states by the right inferior parietal lobe and lower integration abilities in the left retrosplenial cortex. We also find that creativity is related to the ability to "drive" the brain system into difficult to reach states by the right dorsolateral prefrontal cortex (inferior frontal junction) and higher integration abilities in sensorimotor areas. Furthermore, we found that different facets of creativity-fluency, flexibility, and originality-relate to generally similar but not identical network controllability processes. We relate our findings to general theories on intelligence and creativity., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

[This corrects the article DOI: 10.1371/journal.pcbi.1006234.].

Brain anatomy and physiology support the human ability to navigate a complex space of perceptions and actions. To maneuver across an ever-changing landscape of mental states, the brain invokes cognitive control-a set of dynamic processes that engage and disengage different groups of brain regions to modulate attention, switch between tasks, and inhibit prepotent responses. Current theory posits that correlated and anticorrelated brain activity may signify cooperative and competitive interactions between brain areas that subserve adaptive behavior. In this study, we use a quantitative approach to identify distinct topological motifs of functional interactions and examine how their expression relates to cognitive control processes and behavior. In particular, we acquire fMRI BOLD signal in twenty-eight healthy subjects as they perform two cognitive control tasks-a Stroop interference task and a local-global perception switching task using Navon figures-each with low and high cognitive control demand conditions. Based on these data, we construct dynamic functional brain networks and use a parts-based, network decomposition technique called non-negative matrix factorization to identify putative cognitive control subgraphs whose temporal expression captures distributed network structures involved in different phases of cooperative and competitive control processes. Our results demonstrate that temporal expression of the subgraphs fluctuate alongside changes in cognitive demand and are associated with individual differences in task performance. These findings offer insight into how coordinated changes in the cooperative and competitive roles of cognitive systems map trajectories between cognitively demanding brain states., Competing Interests: The authors have declared that no competing interests exist.

Value guides behavior. With knowledge of stimulus values and action consequences, behaviors that maximize expected reward can be selected. Prior work has identified several brain structures critical for representing both stimuli and their values. Yet, it remains unclear how these structures interact with one another and with other regions of the brain to support the dynamic acquisition of value-related knowledge. Here, we use a network neuroscience approach to examine how BOLD functional networks change as 20 healthy human subjects learn the values of novel visual stimuli over the course of four consecutive days. We show that connections between regions of the visual, frontal, and cingulate cortices become stronger as learning progresses, with some of these changes being specific to the type of feedback received during learning. These results demonstrate that functional networks dynamically track behavioral improvement in value judgments, and that interactions between network communities form predictive biomarkers of learning., Competing Interests: Competing Interests: The authors have declared that no competing interests exist.

Cognitive flexibility describes the human ability to switch between modes of mental function to achieve goals. Mental switching is accompanied by transient changes in brain activity, which must occur atop an anatomical architecture that bridges disparate cortical and subcortical regions by underlying white matter tracts. However, an integrated perspective regarding how white matter networks might constrain brain dynamics during cognitive processes requiring flexibility has remained elusive. To address this challenge, we applied emerging tools from graph signal processing to examine whether BOLD signals measured at each point in time correspond to complex underlying anatomical networks in 28 individuals performing a perceptual task that probed cognitive flexibility. We found that the alignment between functional signals and the architecture of the underlying white matter network was associated with greater cognitive flexibility across subjects. By computing a concise measure using multi-modal neuroimaging data, we uncovered an integrated structure-function correlate of human behavior.

Object concepts refer to unique clusters of properties that can be selectively activated or inhibited depending on what information is currently relevant. This conceptual "stretching" enables limitless new meanings to be generated, and figurative language provides a useful framework in which to study this conceptual flexibility. Here we probe the cognitive and neural mechanisms underlying the comprehension of novel metaphors as a means of understanding the conceptual flexibility inherent to language processing more generally. We show that novel metaphor comprehension involves the activation or inhibition of conceptual properties that are either relevant or irrelevant to the metaphor, and that left inferior frontal gyrus is recruited in this process, supporting a role for this region in the fine-tuning of conceptual meaning. Our results are consistent with a flexible, compositional account of conceptual structure in which semantic control mechanisms operate over conceptual properties during figurative language comprehension in order to create context-dependent meaning., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Our use of tools is situated in different contexts. Prior evidence suggests that diverse regions within the ventral and dorsal streams represent information supporting common tool use. However, given the flexibility of object concepts, these regions may be tuned to different types of information when generating novel or uncommon uses of tools. To investigate this, we collected fMRI data from participants who reported common or uncommon tool uses in response to visually presented familiar objects. We performed a pattern dissimilarity analysis in which we correlated cortical patterns with behavioral measures of visual, action, and category information. The results showed that evoked cortical patterns within the dorsal tool use network reflected action and visual information to a greater extent in the uncommon use group, whereas evoked neural patterns within the ventral tool use network reflected categorical information more strongly in the common use group. These results reveal the flexibility of cortical representations of tool use and the situated nature of cortical representations more generally.

Network science has emerged as a powerful tool through which we can study the higher-order architectural properties of the world around us. How human learners exploit this information remains an essential question. Here, we focus on the temporal constraints that govern such a process. Participants viewed a continuous sequence of images generated by three distinct walks on a modular network. Walks varied along two critical dimensions: their predictability and the density with which they sampled from communities of images. Learners exposed to walks that richly sampled from each community exhibited a sharp increase in processing time upon entry into a new community. This effect was eliminated in a highly regular walk that sampled exhaustively from images in short, successive cycles (i.e., that increasingly minimized uncertainty about the nature of upcoming stimuli). These results demonstrate that temporal organization plays an essential role in learners' sensitivity to the network architecture underlying sensory input.

The angular gyrus (AG) and anterior temporal lobe (ATL) have been found to respond to a number of tasks involving combinatorial processing. In this study, we investigate the conceptual combination of nominal compounds, and ask whether ATL/AG activity is modulated by the type of combinatorial operation applied to a nominal compound. We compare relational and attributive interpretations of nominal compounds and find that ATL and AG both discriminate these two types, but in distinct ways. While right AG demonstrated greater positive task-responsive activity for relational compounds, there was a greater negative deflection in the BOLD response in left AG for relational compounds. In left ATL, we found an earlier peak in subjects' BOLD response curves for attributive interpretations. In other words, we observed dissociations in both AG and ATL between relational and attributive nominal compounds, with regard to magnitude in the former and to timing in the latter. These findings expand on prior studies that posit roles for both AG and ATL in conceptual processing generally, and in conceptual combination specifically, by indicating possible functional specializations of these two regions within a larger conceptual knowledge network., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Using novel virtual cities, we investigated the influence of verbal and visual strategies on the encoding of navigation-relevant information in a large-scale virtual environment. In 2 experiments, participants watched videos of routes through 4 virtual cities and were subsequently tested on their memory for observed landmarks and their ability to make judgments regarding the relative directions of the different landmarks along the route. In the first experiment, self-report questionnaires measuring visual and verbal cognitive styles were administered to examine correlations between cognitive styles, landmark recognition, and judgments of relative direction. Results demonstrate a tradeoff in which the verbal cognitive style is more beneficial for recognizing individual landmarks than for judging relative directions between them, whereas the visual cognitive style is more beneficial for judging relative directions than for landmark recognition. In a second experiment, we manipulated the use of verbal and visual strategies by varying task instructions given to separate groups of participants. Results confirm that a verbal strategy benefits landmark memory, whereas a visual strategy benefits judgments of relative direction. The manipulation of strategy by altering task instructions appears to trump individual differences in cognitive style. Taken together, we find that processing different details during route encoding, whether due to individual proclivities (Experiment 1) or task instructions (Experiment 2), results in benefits for different components of navigation-relevant information. These findings also highlight the value of considering multiple sources of individual differences as part of spatial cognition investigations. (PsycINFO Database Record, ((c) 2017 APA, all rights reserved).)

Traditional approaches to understanding the brain's resilience to neuropathology have identified neurophysiological variables, often described as brain or cognitive "reserve," associated with better outcomes. However, mechanisms of function and resilience in large-scale brain networks remain poorly understood. Dynamic network theory may provide a basis for substantive advances in understanding functional resilience in the human brain. In this perspective, we describe recent theoretical approaches from network control theory as a framework for investigating network level mechanisms underlying cognitive function and the dynamics of neuroplasticity in the human brain. We describe the theoretical opportunities offered by the application of network control theory at the level of the human connectome to understand cognitive resilience and inform translational intervention., (Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.)

An object's perceived readiness-for-action (e.g., its size, the degree of rotation from its canonical position, the user's viewpoint) can influence semantic knowledge retrieval. Yet, the organization of object knowledge may also be affected by body-specific sensorimotor experiences. Here, we investigated whether people's history of performing motor actions with their hands influences the knowledge they store and retrieve about graspable objects. We compared object representations between healthy right- and left-handers (Experiment 1), and between unilateral stroke patients, whose motor experience was changed by impairment of either their right or left hand (Experiment 2). Participants saw pictures of graspable everyday items with the handles oriented toward either the left or right hand, and they generated the type of grasp they would employ (i.e., clench or pinch) when using each object, responding orally. In both experiments, hand dominance and object orientation interacted to predict response times. In Experiment 1, judgments were fastest when objects were oriented toward the right hand in right-handers, but not in left-handers. In Experiment 2, judgments were fastest when objects were oriented toward the left hand in patients who had lost the use of their right hand, even though these patients were right-handed prior to brain injury. Results suggest that at least some aspects of object knowledge are determined by motor experience, and can be changed by new patterns of motor experience. People with different bodily characteristics, who interact with objects in systematically different ways, form correspondingly different neurocognitive representations of the same common objects. (PsycINFO Database Record, ((c) 2017 APA, all rights reserved).)

To successfully comprehend a sentence that contains a homonym, readers must select the ambiguous word's context-appropriate meaning. The outcome of this process is influenced both by top-down contextual support and bottom-up, word-specific characteristics. We examined how these factors jointly affect the neural signatures of lexical ambiguity resolution. We measured the similarity between multi-voxel patterns evoked by the same homonym in two distinct linguistic contexts: once after subjects read sentences that biased interpretation toward each homonym's most frequent, dominant meaning, and again after interpretation was biased toward a weaker, subordinate meaning. We predicted that, following a subordinate-biasing context, the dominant yet inappropriate meaning would nevertheless compete for activation, manifesting in increased similarity between the neural patterns evoked by the two word meanings. In left anterior temporal lobe (ATL), degree of within-word pattern similarity was positively predicted by the association strength of each homonym's dominant meaning. Further, within-word pattern similarity in left ATL was negatively predicted by item-specific responses in a region of left ventrolateral prefrontal cortex (VLPFC) sensitive to semantic conflict. These findings have implications for psycholinguistic models of lexical ambiguity resolution, and for the role of left VLPFC function during this process. Moreover, these findings demonstrate the utility of item-level, similarity-based analyses of fMRI data for our understanding of competition between co-activated word meanings during language comprehension., (Copyright © 2016 Elsevier Inc. All rights reserved.)

In the cognitive domain, enormous variation in methodological approach prompts questions about the generalizability of behavioral findings obtained from studies of transcranial direct current stimulation (tDCS). To determine the impact of common variations in approach, we systematically manipulated two key stimulation parameters-current polarity and intensity-and assessed their impact on a task of inhibitory control (the Eriksen Flanker). Ninety participants were randomly assigned to one of nine experimental groups: three stimulation conditions (anode, sham, cathode) crossed with three intensity levels (1.0, 1.5, 2.0 mA). As participants performed the Flanker task, stimulation was applied over left dorsolateral prefrontal cortex (DLPFC; electrode montage: F3-RSO). The behavioral impact of these manipulations was examined using mixed effects linear regression. Results indicate a significant effect of stimulation condition (current polarity) on the magnitude of the interference effect during the Flanker; however, this effect was specific to the comparison between anodal and sham stimulation. Inhibitory control was therefore improved by anodal stimulation over the DLPFC. In the present experimental context, no reliable effect of stimulation intensity was observed, and we found no evidence that inhibitory control was impeded by cathodal stimulation. Continued exploration of the stimulation parameter space, particularly with more robustly powered sample sizes, is essential to facilitating cross-study comparison and ultimately working toward a reliable model of tDCS effects.

During sentence comprehension, real-time identification of a referent is driven both by local, context-independent lexical information and by more global sentential information related to the meaning of the utterance as a whole. This paper investigates the cognitive factors that limit the consideration of referents that are supported by local lexical information but not supported by more global sentential information. In an eye-tracking paradigm, participants heard sentences like "She will eat the red pear" while viewing four black-and-white (colorless) line-drawings. In the experimental condition, the display contained a "local attractor" (e.g., a heart), which was locally compatible with the adjective but incompatible with the context ("eat"). In the control condition, the local attractor was replaced by a picture which was incompatible with the adjective (e.g., "igloo"). A second factor manipulated contextual constraint, by using either a constraining verb (e.g., "eat"), or a non-constraining one (e.g., "see"). Results showed consideration of the local attractor, the magnitude of which was modulated by verb constraint, but also by each subject's cognitive control abilities, as measured in a separate Flanker task run on the same subjects. The findings are compatible with a processing model in which the interplay between local attraction, context, and domain-general control mechanisms determines the consideration of possible referents.

Pictorial examples during creative thinking tasks can lead participants to fixate on these examples and reproduce their elements even when yielding suboptimal creative products. Semantic memory research may illuminate the cognitive processes underlying this effect. Here, we examined whether pictures and words differentially influence access to semantic knowledge for object concepts depending on whether the task is close- or open-ended. Participants viewed either names or pictures of everyday objects, or a combination of the two, and generated common, secondary, or ad hoc uses for them. Stimulus modality effects were assessed quantitatively through reaction times and qualitatively through a novel coding system, which classifies creative output on a continuum from top-down-driven to bottom-up-driven responses. Both analyses revealed differences across tasks. Importantly, for ad hoc uses, participants exposed to pictures generated more top-down-driven responses than those exposed to object names. These findings have implications for accounts of functional fixedness in creative thinking, as well as theories of semantic memory for object concepts.

At first glance, conceptual representations (e.g., our internal notion of the object "lemon") seem static; we have the impression that there is something that the concept lemon "means" (a sour, yellow, football-shaped citrus fruit) and that this meaning does not vary. Research in semantic memory has traditionally taken this "static" perspective. Consequently, only effects demonstrated across a variety of contexts have typically been considered informative regarding the architecture of the semantic system. In this review, we take the opposite approach: We review instances of context-dependent conceptual activation at many different timescales-from long-term experience, to recent experience, to the current task goals, to the unfolding process of conceptual activation itself-and suggest that the pervasive effects of context across all of these timescales indicate that rather than being static, conceptual representations are constantly changing and are inextricably linked to their contexts.

A core question in cognitive science concerns how humans acquire and represent knowledge about their environments. To this end, quantitative theories of learning processes have been formalized in an attempt to explain and predict changes in brain and behavior. We connect here statistical learning approaches in cognitive science, which are rooted in the sensitivity of learners to local distributional regularities, and network science approaches to characterizing global patterns and their emergent properties. We focus on innovative work that describes how learning is influenced by the topological properties underlying sensory input. The confluence of these theoretical approaches and this recent empirical evidence motivate the importance of scaling-up quantitative approaches to learning at both the behavioral and neural levels., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Human visual perception is both stable and adaptive. Perception of complex objects, such as faces, is shaped by the long-term average of experience as well as immediate, comparative context. Measurements of brain activity have demonstrated corresponding neural mechanisms, including norm-based responses reflective of stored prototype representations, and adaptation induced by the immediately preceding stimulus. Here, we consider the possibility that these apparently separate phenomena can arise from a single mechanism of sensory integration operating over varying timescales. We used fMRI to measure neural responses from the fusiform gyrus while subjects observed a rapid stream of face stimuli. Neural activity at this cortical site was best explained by the integration of sensory experience over multiple sequential stimuli, following a decaying-exponential weighting function. Although this neural activity could be mistaken for immediate neural adaptation or long-term, norm-based responses, it in fact reflected a timescale of integration intermediate to both. We then examined the timescale of sensory integration across the cortex. We found a gradient that ranged from rapid sensory integration in early visual areas, to long-term, stable representations in higher-level, ventral-temporal cortex. These findings were replicated with a new set of face stimuli and subjects. Our results suggest that a cascade of visual areas integrate sensory experience, transforming highly adaptable responses at early stages to stable representations at higher levels., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Left ventrolateral prefrontal cortex (VLPFC) has been implicated in both integration and conflict resolution in sentence comprehension. Most evidence in favor of the integration account comes from processing ambiguous or anomalous sentences, which also poses a demand for conflict resolution. In two eye-tracking experiments we studied the role of VLPFC in integration when demands for conflict resolution were minimal. Two closely-matched groups of individuals with chronic post-stroke aphasia were tested: the Anterior group had damage to left VLPFC, whereas the Posterior group had left temporo-parietal damage. In Experiment 1 a semantic cue (e.g., "She will eat the apple") uniquely marked the target (apple) among three distractors that were incompatible with the verb. In Experiment 2 phonological cues (e.g., "She will see an eagle."/"She will see a bear.") uniquely marked the target among three distractors whose onsets were incompatible with the cue (e.g., all consonants when the target started with a vowel). In both experiments, control conditions had a similar format, but contained no semantic or phonological contextual information useful for target integration (e.g., the verb "see", and the determiner "the"). All individuals in the Anterior group were slower in using both types of contextual information to locate the target than were individuals in the Posterior group. These results suggest a role for VLPFC in integration beyond conflict resolution. We discuss a framework that accommodates both integration and conflict resolution., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Information in the human visual system is encoded in the activity of distributed populations of neurons, which in turn is reflected in functional magnetic resonance imaging (fMRI) data. Over the last fifteen years, activity patterns underlying a variety of perceptual features and objects have been decoded from the brains of participants in fMRI scans. Through a novel multi-study meta-analysis, we have analyzed and modeled relations between decoding strength in the visual ventral stream, and stimulus and methodological variables that differ across studies. We report findings that suggest: (i) several organizational principles of the ventral stream, including a gradient of pattern granulation and an increasing abstraction of neural representations as one proceeds anteriorly; (ii) how methodological choices affect decoding strength. The data also show that studies with stronger decoding performance tend to be reported in higher-impact journals, by authors with a higher h-index. As well as revealing principles of regional processing, our results and approach can help investigators select from the thousands of design and analysis options in an empirical manner, to optimize future studies of fMRI decoding., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

One of the most remarkable features of the human brain is its ability to adapt rapidly and efficiently to external task demands. Novel and non-routine tasks, for example, are implemented faster than structural connections can be formed. The neural underpinnings of these dynamics are far from understood. Here we develop and apply novel methods in network science to quantify how patterns of functional connectivity between brain regions reconfigure as human subjects perform 64 different tasks. By applying dynamic community detection algorithms, we identify groups of brain regions that form putative functional communities, and we uncover changes in these groups across the 64-task battery. We summarize these reconfiguration patterns by quantifying the probability that two brain regions engage in the same network community (or putative functional module) across tasks. These tools enable us to demonstrate that classically defined cognitive systems-including visual, sensorimotor, auditory, default mode, fronto-parietal, cingulo-opercular and salience systems-engage dynamically in cohesive network communities across tasks. We define the network role that a cognitive system plays in these dynamics along the following two dimensions: (i) stability vs. flexibility and (ii) connected vs. isolated. The role of each system is therefore summarized by how stably that system is recruited over the 64 tasks, and how consistently that system interacts with other systems. Using this cartography, classically defined cognitive systems can be categorized as ephemeral integrators, stable loners, and anything in between. Our results provide a new conceptual framework for understanding the dynamic integration and recruitment of cognitive systems in enabling behavioral adaptability across both task and rest conditions. This work has important implications for understanding cognitive network reconfiguration during different task sets and its relationship to cognitive effort, individual variation in cognitive performance, and fatigue.

Successful language comprehension requires one to correctly match symbols in an utterance to referents in the world, but the rampant ambiguity present in that mapping poses a challenge. Sometimes the ambiguity lies in which of two (or more) types of things in the world are under discussion (i.e., lexical ambiguity); however, even a word with a single sense can have an ambiguous referent. This ambiguity occurs when an object can exist in multiple states. Here, we consider two cases in which the presence of multiple object states may render a single-sense word ambiguous. In the first case, one must disambiguate between two states of a single object token in a short discourse. In the second case, the discourse establishes two different tokens of the object category. Both cases involve multiple object states: These states are mutually exclusive in the first case, whereas in the second case, these states can logically exist at the same time. We use fMRI to contrast same-token and different-token discourses, using responses in left posterior ventrolateral prefrontal cortex (pVLPFC) as an indicator of conflict. Because the left pVLPFC is sensitive to competition between multiple, incompatible representations, we predicted that state ambiguity should engender conflict only when those states are mutually exclusive. Indeed, we find evidence of conflict in same-token, but not different-token, discourses. Our data support a theory of left pVLPFC function in which general conflict resolution mechanisms are engaged to select between multiple incompatible representations that arise in many kinds of ambiguity present in language.

The cognitive and neural systems that enable conceptual processing must support the ability to combine (and recombine) concepts to form an infinite number of ideas. Two candidate neural systems for conceptual combination-the left anterior temporal lobe (ATL) and the left angular gyrus (AG)-have been characterized as "semantic hubs" due to both functional and anatomical properties; however, these two regions likely support different aspects of composition. Here we consider two hypotheses for the role of AG in conceptual combination, both of which differ from a putative role for the ATL in "feature-based" combinatorics (i.e., meaning derived by combining concepts' features). Firstly, we examine whether AG is more sensitive to function-argument relations of the sort that arise when a predicate is combined with its arguments. Secondly, we examine the non-mutually exclusive possibility that AG represents information carried on a verb in particular, whether this be information about event composition or about thematic relations denoted uniquely by verbs. We identified voxels that respond differentially to two-word versus one-word stimuli, and we measured the similarity of the patterns in these voxels evoked by (1) pairs of two-word phrases that shared a noun that was an argument, thus sharing function-argument composition (e.g. eats meat and with meat), in comparison with two-word phrases that shared only a noun, not an argument (e.g., eats meat and tasty meat); and (2) stimulus pairs that shared only an event (operationalized here as sharing a verb; e.g. eats meat and eats quickly), in comparison to both of the above. We found that activity patterns in left AG tracked information relating to the presence of an event-denoting verb in a pair of two-word phrases. We also found that the neural similarity in AG voxel patterns between two phrases sharing a verb correlated with subjects' ratings of how similar the meanings of those two verb phrases were. These findings indicate that AG represents information specific to verbs, perhaps event structure or thematic relations mediated by verbs, as opposed to argument structure in general., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Highlights Does phonological similarity affect gesture production in the absence of speech?Participants produced gestures from pictures with no words presented or spoken.Same pictures and gestures but different training labels were used.Phonologically similar labels led to more errors in subsequent gestures.Thus, phonological similarity affects gesture production in the absence of speech. Are manual gestures affected by inner speech? This study tested the hypothesis that phonological form influences gesture by investigating whether phonological similarity between words that describe motion gestures creates interference for production of those gestures in the absence of overt speech. Participants learned to respond to a picture of a bottle by gesturing to open the bottle's cap, and to a picture of long hair by gesturing to twirl the hair. In one condition, the gestures were introduced with phonologically-similar labels "twist" and "twirl" (similar condition), while in the other condition, they were introduced with phonologically-dissimilar labels "unscrew" and "twirl" (dissimilar condition). During the actual experiment, labels were not produced and participants only gestured by looking at pictures. In both conditions, participants also gestured to a control pair that was used as a baseline. Participants made significantly more errors on gestures in the similar than dissimilar condition after correction for baseline differences. This finding shows the influence of phonology on gesture production in the absence of overt speech and poses new constraints on the locus of the interaction between language and gesture systems.

To make sense of the world around us, our brain must remember the overlapping features of millions of objects. Crucially, it must also represent each object's unique feature-convergence. Some theories propose that an integration area (or "convergence zone") binds together separate features. We report an investigation of our knowledge of objects' features and identity, and the link between them. We used functional magnetic resonance imaging to record neural activity, as humans attempted to detect a cued fruit or vegetable in visual noise. Crucially, we analyzed brain activity before a fruit or vegetable was present, allowing us to interrogate top-down activity. We found that pattern-classification algorithms could be used to decode the detection target's identity in the left anterior temporal lobe (ATL), its shape in lateral occipital cortex, and its color in right V4. A novel decoding-dependency analysis revealed that identity information in left ATL was specifically predicted by the temporal convergence of shape and color codes in early visual regions. People with stronger feature-and-identity dependencies had more similar top-down and bottom-up activity patterns. These results fulfill three key requirements for a neural convergence zone: a convergence result (object identity), ingredients (color and shape), and the link between them., (© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

The prevailing approach to the neuroscientific study of concepts is to characterize the neural pattern evoked by a given concept, averaging over any variation that might occur upon multiple retrieval attempts (e.g., across time, tasks, or people). This approach-which diverges substantially from approaches to studying conceptual processing with other methods-treats all variation as noise. Here, our goal is to determine whether variation in neural patterns evoked by semantic retrieval of a given concept is more than just measurement error, and instead reflects variation arising from contextual variability. We measured each concept's diversity of semantic contexts ("SV") by analyzing its word frequency and co-occurrence statistics in large text corpora. To measure neural variability, we conducted an fMRI study and sampled neural activity associated with each concept when it appeared in three separate, randomized contexts. We predicted that concepts with low SV would exhibit uniform activation patterns across stimulus presentations, whereas concepts with high SV would exhibit more dynamic representations over time. We observed that a concept's SV score predicted its corresponding neural variability. This finding supports a flexible, distributed organization of semantic memory, where a concept's meaning and its neural activity patterns both continuously vary across contexts., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

Rapid word learning, where words are 'fast mapped' onto new concepts, may help build vocabulary during childhood. Recent evidence has suggested that fast mapping might help to rapidly integrate information into memory networks of the adult neocortex. The neural basis for this learning by fast mapping determines key properties of the learned information., (Copyright © 2015 Elsevier Ltd. All rights reserved.)