Neural Dynamics During the Generation and Evaluation of Creative and Non-Creative Ideas.

What are the neural dynamics that drive creative thinking? Recent studies have provided much insight into the neural mechanisms of creative thought. Specifically, the interaction between the executive control, default mode, and salience brain networks has been shown to be an important marker of individual differences in creative ability. However, how these different brain systems might be recruited dynamically during the two key components of the creative process-generation and evaluation of ideas-remains far from understood. In the current study we applied state-of-the-art network neuroscience methodologies to examine the neural dynamics related to the generation and evaluation of creative and non-creative ideas using a novel within-subjects design. Participants completed two functional magnetic resonance imaging sessions, taking place a week apart. In the first imaging session, participants generated either creative (alternative uses) or non-creative (common characteristics) responses to common objects. In the second imaging session, participants evaluated their own creative and non-creative responses to the same objects. Network neuroscience methods were applied to examine and directly compare reconfiguration, integration, and recruitment of brain networks during these four conditions. We found that generating creative ideas led to significantly higher network reconfiguration than generating non-creative ideas, whereas evaluating creative and non-creative ideas led to similar levels of network integration. Furthermore, we found that these differences were attributable to different dynamic patterns of neural activity across the executive control, default mode, and salience networks. This study is the first to show within-subject differences in neural dynamics related to generating and evaluating creative and non-creative ideas.

Rapid learning of temporal dependencies at multiple timescales.

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 9 locations, in 8 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 vs. second half of the game. Participants periodically predicted the upcoming target location, and later performed similarity judgements 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.

Disruption of Anterior Temporal Lobe Reduces Distortions in Memory From Category Knowledge.

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.

Constructing complex social categories under uncertainty.

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.

Novel objects with causal event schemas elicit selective responses in tool- and hand-selective lateral occipitotemporal cortex.

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.

Dissociable multi-scale patterns of development in personalized brain networks.

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.

Tracking the relation between gist and item memory over the course of long-term memory consolidation.

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.

The modulation of brain network integration and arousal during exploration.

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.

Noninvasive brain stimulation to lateral prefrontal cortex alters the novelty of creative idea generation.

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.

Semantic influences on episodic memory distortions.

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).

Feature Uncertainty Predicts Behavioral and Neural Responses to Combined Concepts.

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.

Incidental binding between predictive relations.

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.

Transformation of Event Representations along Middle Temporal Gyrus.

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.

Effective learning is accompanied by high-dimensional and efficient representations of neural activity.

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.

From the structure of experience to concepts of structure: How the concept "cause" is attributed to objects and events.

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).

Implementing a concept network model.

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.

Investigating grounded conceptualization: Stimulus-response compatibility for tool handles is due to spatial attention.

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).

Investigating grounded conceptualization: motor system state-dependence facilitates familiarity judgments of novel tools.

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.

Neural activity in human visual cortex is transformed by learning real world size.

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.

Individual differences in response precision correlate with adaptation bias.

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.