How can I find what I want? Can children, chimpanzees and capuchin monkeys form abstract representations to guide their behavior in a sampling task?

concepts are a powerful tool for making wide-ranging predictions in new situations based on little experience. Whereas looking-time studies suggest an early emergence of this ability in human infancy, other paradigms like the relational match to sample task often fail to detect abstract concepts until late preschool years. Similarly, non-human animals show difficulties and often succeed only after long training regimes. Given the considerable influence of slight task modifications, the conclusiveness of these findings for the development and phylogenetic distribution of abstract reasoning is debated. Here, we tested the abilities of 3 to 5-year-old children, chimpanzees, and capuchin monkeys in a unified and more ecologically valid task design based on the concept of "overhypotheses" (Goodman, 1955). Participants sampled high- and low-valued items from containers that either each offered items of uniform value or a mix of high- and low-valued items. In a test situation, participants should switch away earlier from a container offering low-valued items when they learned that, in general, items within a container are of the same type, but should stay longer if they formed the overhypothesis that containers bear a mix of types. We compared each species' performance to the predictions of a probabilistic hierarchical Bayesian model forming overhypotheses at a first and second level of abstraction, adapted to each species' reward preferences. Children and, to a more limited extent, chimpanzees demonstrated their sensitivity to abstract patterns in the evidence. In contrast, capuchin monkeys did not exhibit conclusive evidence for the ability of abstract knowledge formation.

High variability in learning materials benefits children's pattern practice

Concrete materials (e.g., pictures, objects) are believed to be helpful with learning, but not in all circumstances. Variability in these materials (i.e., using different materials vs. the same materials) could be an important factor. We compared how variability in concrete images influenced children's learning about repeating patterns (e.g., ABBABBABB). A total of 87 children aged 4 to 6 years from the United States (75% White; 44% female) completed an experiment via Zoom in which they received brief pattern training. Children were randomly assigned into Low, Medium, and High Variability training conditions, which differed in terms of whether the same materials were used over and over or they varied in their perceptual features. Children in the Low Variability condition performed better at the beginning of training, but this trend ultimately reversed. Children in the High Variability condition performed best by the end of training and on the posttest. Using variable materials may allow children to extract common structures across instances.

Sand dam contributions to year-round water security monitored through telemetered handpump data

Sand dams are a form of rainwater harvesting, prolific in arid and semi-arid lands. Water is provided partly via handpumps, which, as the only improved method of abstraction from sand dams, are important for drinking water security. Accelerometers and cellular transmitters were fitted to 30 handpumps by the Africa Sand Dam Foundation (ASDF) in 2019 to monitor the use and reliability of the handpumps by recording hourly water volume abstracted. Data from April 2019 to October 2021 for 26 of these sites, alongside qualitative data, were analysed and each handpump's contribution to year-round water security was explored, focusing on the long dry season when water supply from other sources is compromised. Abstraction was over 20 times higher in the long dry season than in any other season, and at sites with higher salinity, higher livestock use, and larger dam wall area. At 21 wells, abstraction was still being recorded at the end of at least one long dry season; however, high spatial and temporal heterogeneity between pumps and seasons means that not all sand dams deliver reliable water supply year-round. Quantifying the contribution that sand dams make to water security is crucial for understanding their resilience against a changing climate and can aid decision makers when choosing the most appropriate water management technique. Knowledge of temporal and site heterogeneity in abstraction can inform when other water sources need increasing and can help with sand dam design optimisation. Overall, our results indicate the positive contribution that sand dams make to year-round water security through the water that is abstracted through handpumps.

Specificity ratings for Italian data

Abstraction enables us to categorize experience, learn new information, and form judgments. Language arguably plays a crucial role in abstraction, providing us with words that vary in specificity (e.g., highly generic: tool vs. highly specific: muffler). Yet, human-generated ratings of word specificity are virtually absent. We hereby present a dataset of specificity ratings collected from Italian native speakers on a set of around 1K Italian words, using the Best-Worst Scaling method. Through a series of correlation studies, we show that human-generated specificity ratings have low correlation coefficients with specificity metrics extracted automatically from WordNet, suggesting that WordNet does not reflect the hierarchical relations of category inclusion present in the speakers' minds. Moreover, our ratings show low correlations with concreteness ratings, suggesting that the variables Specificity and Concreteness capture two separate aspects involved in abstraction and that specificity may need to be controlled for when investigating conceptual concreteness. Finally, through a series of regression studies we show that specificity explains a unique amount of variance in decision latencies (lexical decision task), suggesting that this variable has theoretical value. The results are discussed in relation to the concept and investigation of abstraction.

The Social Route to Abstraction: Interaction and Diversity Enhance Performance and Transfer in a Rule-Based Categorization Task

Capacities for abstract thinking and problem-solving are central to human cognition. Processes of abstraction allow the transfer of experiences and knowledge between contexts helping us make informed decisions in new or changing contexts. While we are often inclined to relate such reasoning capacities to individual minds and brains, they may in fact be contingent on human-specific modes of collaboration, dialogue, and shared attention. In an experimental study, we test the hypothesis that social interaction enhances cognitive processes of rule-induction, which in turn improves problem-solving performance. Through three sessions of increasing complexity, individuals and groups were presented with a problem-solving task requiring them to categorize a set of visual stimuli. To assess the character of participants' problem representations, after each training session, they were presented with a transfer task involving stimuli that differed in appearance, but shared relations among features with the training set. Besides, we compared participants' categorization behaviors to simulated agents relying on exemplar learning. We found that groups performed superior to individuals and agents in the training sessions and were more likely to correctly generalize their observations in the transfer phase, especially in the high complexity session, suggesting that groups more effectively induced underlying categorization rules from the stimuli than individuals and agents. Crucially, variation in performance among groups was predicted by semantic diversity in members' dialogical contributions, suggesting a link between social interaction, cognitive diversity, and abstraction.

Prevailing impacts of river management on microplastic transport in contrasting US streams: Rethinking global microplastic flux estimations

While microplastic inputs into rivers are assumed to be correlated with anthropogenic activities and to accumulate towards the sea, the impacts of water management on downstream microplastic transport are largely unexplored. A comparative study of microplastic abundance in Boulder Creek (BC), and its less urbanized tributary South Boulder Creek (SBC), (Colorado USA), characterized the downstream evolution of microplastics in surface water and sediments, evaluating the effects of urbanization and flow diversions on the up-to-downstream profiles of microplastic concentrations and loads. Water and sediment samples were collected from 21 locations along both rivers and microplastic properties determined by fluorescence microscopy and Raman spectroscopy. The degree of catchment urbanization affected microplastic patterns, as evidenced by greater water and sediment concentrations and loads in BC than the less densely populated SBC, which is consistent with the differences in the degree of urbanization between both catchments. Microplastic removal through flow diversions was quantified, showing that water diversions removed over 500 microplastic particles per second from the river, and caused stepwise reductions of downstream loads at diversion points. This redistribution of microplastics back into the catchment should be considered in large scale models quantifying plastic fate and transport to the oceans.

Pretend play as abstraction: Implications for early development and beyond

Humans are the only species that engages in sustained, complex pretend play. As pretend play is practically ubiquitous across cultures, it might support or afford a context for developmental advances during the juvenile period that have implications for functioning in adulthood. Early in development, learning to separate our thoughts from reality is practiced in pretend play and is associated with changes not just in cognition, but in emotional and social domains as well. Specifically, pretend play affords opportunities to engage in abstractions that could support abilities such as perspective-taking, emotion recognition and regulation, and cooperation and negotiation in childhood. In turn, the abstraction skills promoted by early pretend play might underlie creativity, innovation, and our capacity to feel empathy and moral obligation to others in later childhood and adulthood. In fact, because pretend play affords sharing our abstractions with others, it might be an early context for behaviors that ultimately promote the shared abstractions of human culture itself.

Show or tell? Exploring when (and why) teaching with language outperforms demonstration

People use a wide range of communicative acts across different modalities, from concrete demonstrations to abstract language. While these modalities are typically studied independently, we take a comparative approach and ask when and why one modality might outperform another. We present a series of real-time, multi-player experiments asking participants to teach concepts using either demonstrations or language. Our first experiment (N=416) asks when language might outperform demonstration. We manipulate the complexity of the concept being taught and find that language communicates complex concepts more effectively than demonstration. We then ask why language succeeds in this setting. We hypothesized that language allowed teachers to reference abstract object features (e.g., shapes and colors), while demonstration teachers could only provide concrete examples (specific positive or negative objects). To test this hypothesis, our second experiment (N=568) ablated object features from the teacher's interface. This manipulation severely impaired linguistic (but not demonstrative) teaching. Our findings suggest that language communicates complex concepts by directly transmitting abstract rules. In contrast, demonstrations transmit examples, requiring the learner to infer the rules.

A Halo abstraction for distributed n-dimensional structured grids within the C++ PGAS library DASH

The Partitioned Global Address Space (PGAS) library DASH provides C++ container classes for distributed N-dimensional structured grids. This article presents enhancements on top of the DASH library to support stencil operations and halo areas to conveniently and efficiently parallelize structured grids. The improvements include definitions of multiple stencil operators, automatic derivation of halo sizes, efficient halo data exchanges, as well as communication hiding optimizations. The main contributions of this article are two-fold. First, the halo abstraction concept and the halo wrapper software components are explained. Second, the code complexity and the runtime of an example code implemented in DASH and pure Message Passing Interface (MPI) are compared.

Evidence for abstract representations in children but not capuchin monkeys

The use of abstract higher-level knowledge (also called overhypotheses) allows humans to learn quickly from sparse data and make predictions in new situations. Previous research has suggested that humans may be the only species capable of abstract knowledge formation, but this remains controversial. There is also mixed evidence for when this ability emerges over human development. Kemp et al. (2007) proposed a computational model of how overhypotheses could be learned from sparse examples. We provide the first direct test of this model: an ecologically valid paradigm for testing two species, capuchin monkeys (Sapajus spp.) and 4- to 5-year-old human children. We presented participants with sampled evidence from different containers which suggested that all containers held items of uniform type (type condition) or of uniform size (size condition). Subsequently, we presented two new test containers and an example item from each: a small, high-valued item and a large but low-valued item. Participants could then choose from which test container they would like to receive the next sample - the optimal choice was the container that yielded a large item in the size condition or a high-valued item in the type condition. We compared performance to a priori predictions made by models with and without the capacity to learn overhypotheses. Children's choices were consistent with the model predictions and thus suggest an ability for abstract knowledge formation in the preschool years, whereas monkeys performed at chance level.

What is a related work? A typology of relationships in research literature

An important part of research is situating one's work in a body of existing literature, thereby connecting to existing ideas. Despite this, the various kinds of relationships that might exist among academic literature do not appear to have been formally studied. Here I present a graphical representation of academic work in terms of entities and relations, drawing on structure-mapping theory (used in the study of analogies). I then use this representation to present a typology of operations that could relate two pieces of academic work. I illustrate the various types of relationships with examples from medicine, physics, psychology, history and philosophy of science, machine learning, education, and neuroscience. The resulting typology not only gives insights into the relationships that might exist between static publications, but also the rich process whereby an ongoing research project evolves through interactions with the research literature.

Language level predicts perceptual categorization of complex reversible events in children

Language plays a well-documented role in perceptual object categorization, but little is known about its role in the categorization of complex events. We explored this here with a perspective from age or developmentally appropriate language capacities in neurotypical children between the ages of two and four years (N = 21), and from delayed language development in a clinical group of children (N = 20), whose verbal mental ages (VMA) often fell far below their chronological ages (CAs). All participants watched two demonstrations of a series of transitive events (e.g. tiger jumps over a girl). The toy agents were then moved out of sight, and participants had to act out the same event type, based on a different tiger and girl that were selected among two distractors. We aimed to determine how mastery of this task relates to CA in the neurotypical group, and whether task performance in the clinical group was predicted by VMA and a standardized measure of grammatical comprehension. Results from a series of logistic mixed-effect regression models showed that neurotypical children start to perform correctly on this task with a chance of around 50% during their third year of CA but reach ceiling performance only during their fourth. A similar pattern emerged for VMA in the clinical group, despite a wide range of CAs and diagnoses. In addition, grammatical comprehension predicted performance. These patterns suggest that language competence plays a role in the perceptual categorization and encoding of complex reversible events.

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Mental representations of complex event types were investigated.

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An event imitation task was used in children with and without language disorders.

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Chronological age and verbal mental age both predicted performance.

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Grammatical comprehension in the clinical group did as well.

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Cognizing complex events may be linguistically conditioned.

Is Phonology Embodied? Evidence from Mechanical Stimulation

Across languages, certain syllables are systematically preferred to others (e.g., plaf > ptaf). Here, we examine whether these preferences arise from motor simulation. In the simulation account, ill-formed syllables (e.g., ptaf) are disliked because their motor plans are harder to simulate. Four experiments compared sensitivity to the syllable structure of labial- vs. corona-initial speech stimuli (e.g., plaf > pnaf > ptaf vs. traf > tmaf > tpaf); meanwhile, participants (English vs. Russian speakers) lightly bit on their lips or tongues. Results suggested that the perception of these stimuli was selectively modulated by motor stimulation (e.g., stimulating the tongue differentially affected sensitivity to labial vs. coronal stimuli). Remarkably, stimulation did not affect sensitivity to syllable structure. This dissociation suggests that some (e.g., phonetic) aspects of speech perception are reliant on motor simulation, hence, embodied; others (e.g., phonology), however, are possibly abstract. These conclusions speak to the role of embodiment in the language system, and the separation between phonology and phonetics, specifically.

Analysis of a Real-World Progression Variable and Related Endpoints for Patients with Five Different Cancer Types

Introduction

We previously demonstrated that real-world progression (rwP) can be ascertained from unstructured electronic health record (EHR)-derived documents using a novel abstraction approach for patients with advanced non-small cell lung cancer (base case). The objective of this methodological study was to assess the reliability, clinical relevance, and the need for disease-specific adjustments of this abstraction approach in five additional solid tumor types.

Methods

Patients with metastatic breast cancer (mBC), advanced melanoma (aMel), small cell lung cancer (SCLC), metastatic renal cell carcinoma (mRCC), and advanced gastric/esophageal cancer (aGEC) were selected from a real-world database. Disease-specific additions to the base case were implemented as needed. The resulting abstraction approach was applied to each disease cohort to capture rwP events and dates. To provide comprehensive clinical context, real-world progression-free survival (rwPFS) and time to progression (rwTTP) were compared to real-world overall survival (rwOS), time to next treatment (rwTTNT), and time to treatment discontinuation (rwTTD). Endpoint estimates were assessed using the Kaplan–Meier method. Correlations between real-world endpoints and rwOS were calculated using Spearman’s ρ.

Results

Additions to the base-case rwP abstraction approach were required for mBC, aMel, and SCLC. Inter-abstractor agreement for rwP occurrence, irrespective of date, ranged from 88% to 97%. Occurrence of clinically relevant downstream events (new antineoplastic systemic therapy start, antineoplastic systemic therapy end, or death relative to the rwP event) ranged from 59% (aMel) to 72% (mBC). Median rwPFS ranged from 3.7 (aMel) to 7.7 (mBC) months, and median rwTTP ranged from 4.6 (aMel) to 8.3 (mRCC) months. Correlations between rwOS and rwPFS ranged from 0.52 (aMel) to 0.82 (SCLC). The correlation between rwOS and rwTTD was often lower relative to other comparisons (range 0.40–0.62).

Conclusion

Derivation of a rwP variable from EHR documentation is feasible and reliable across the five solid tumors. Endpoint analyses show that rwP produces clinically meaningful information.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12325-022-02091-8.

A neurocomputational model of creative processes

Creativity is associated with finding novel, surprising, and useful solutions. We argue that creative cognitive processes, divergent thinking, abstraction, and improvisation are constructed on different novelty-based processes. The prefrontal cortex plays a role in creative ideation by providing a control mechanism. Moreover, thinking about novel solutions activates the distant or loosely connected neurons of a semantic network that involves the hippocampus. Novelty can also be interpreted as different combinations of earlier learned processes, such as the motor sequencing mechanism of the basal ganglia. In addition, the cerebellum is responsible for the precise control of movements, which is particularly important in improvisation. Our neurocomputational perspective is based on three creative processes centered on novelty seeking, subserved by the prefrontal cortex, hippocampus, cerebellum, basal ganglia, and dopamine. The algorithmic implementation of our model would enable us to describe commonalities and differences between these creative processes based on the proposed neural circuitry. Given that most previous studies have mainly provided theoretical and conceptual models of creativity, this article presents the first brain-inspired neural network model of creative cognition.

The sources of the concept of extension in the work of W. R. Bion

Bion frequently resorts to mathematical thought in his use of abstractions that account for "elements of psychoanalysis"; among these, the concept of extension plays a central role. The author's hypothesis is that Bion borrowed the concept of extension from Alfred North Whitehead, whose book An Introduction to Mathematics, published in 1911, Bion read. The examples that both Bion and Whitehead use to illustrate the process of extension are almost the same. It is on the basis of this concept of extension that Bion accounts for the psychic growth of each individual, and for the analytic process in terms of transference interpretations in three registers - the senses, the personal myth of the patient, and passion. Bion's description of extension in the psychoanalytical field helps to make explicit some aspects of the psychoanalytic process, with an emphasis on the intuition of the analyst. The author's argument is illustrated with clinical material from the analysis of an autistic child.

The epistemic benefits of generalisation in modelling II: expressive power and abstraction

This paper contributes to the philosophical accounts of generalisation in formal modelling by introducing a conceptual framework that allows for recognising generalisations that are epistemically beneficial in the sense of contributing to the truth of a model result or component. The framework is useful for modellers themselves because it is shown how to recognise different kinds of generalisation on the basis of changes in model descriptions. Since epistemically beneficial generalisations usually de-idealise the model, the paper proposes a reformulation of the well-known distinction between abstraction and idealisation. A reformulated notion of abstraction is needed because the extant accounts yield wrong judgments when model-modifications introduce implicit assumptions.

A word is worth a thousand pictures: A 20-year comparative analysis of aberrant abstraction in schizophrenia, affective psychosis, and non-psychotic depression

thinking is a cognitive process that involves the assimilation of concepts reduced from diffuse sensory input, organized, and interpreted in a manner beyond the obvious. There are multiple facets by which abstraction is measured that include semantic, visual-spatial and social comprehension. This study examined the prevalence and course of abstract and concrete responses to semantic proverbs and aberrant abstraction (composite score of semantic, visual-spatial, and social comprehension) over 20 years in 352 participants diagnosed with schizophrenia, affective psychosis, and unipolar non-psychotic depression. We utilized linear models, two-way ANOVA and contrasts to compare groups and change over time. Linear models with Generalized Estimation Equation (GEE) to determine association. Our findings show that regardless of diagnosis, semantic proverb interpretation improves over time. Participants with schizophrenia give more concrete responses to proverbs when compared to affective psychosis and unipolar depressed without psychosis. We also show that the underlying structure of concretism encompasses increased conceptual overinclusion at index hospitalization and idiosyncratic associations at follow-up; whereas, abstract thinking overtime encompasses increased visual-spatial abstraction at index and rich associations with increased social comprehension scores at follow-up. Regardless of diagnosis, premorbid functioning, descriptive characteristics, and IQ were not associated with aberrant abstraction. Delusions are highly and positively related to aberrant abstraction scores, while hallucinations are mildly and positively related to this score. Lastly, our data point to the importance of examining the underlying interconnected structures of 'established' constructs vis-à-vis mixed methods to provide a description of the rich interior world that may not always map onto current quantitative measures.

Metacognitive resources for adaptive learning⋆

Biological organisms display remarkably flexible behaviours. This is an area of active investigation, in particular in the fields of artificial intelligence, computational and cognitive neuroscience. While inductive biases and broader cognitive functions are undoubtedly important, the ability to monitor and evaluate one's performance or oneself -- metacognition -- strikes as a powerful resource for efficient learning. Often measured as decision confidence in neuroscience and psychology experiments, metacognition appears to reflect a broad range of abstraction levels and downstream behavioural effects. Within this context, the formal investigation of how metacognition interacts with learning processes is a recent endeavour. Of special interest are the neural and computational underpinnings of confidence and reinforcement learning modules. This review discusses a general hierarchy of confidence functions and their neuro-computational relevance for adaptive behaviours. It then introduces novel ways to study the formation and use of meta-representations and nonconscious mental representations related to learning and confidence, and concludes with a discussion on outstanding questions and wider perspectives.

Space modulates cross-domain transfer of abstract rules in infants

Developmental studies have shown that infants exploit ordinal information to extract and generalize repetition-based rules from a sequence of items. Within the visual modality, this ability is constrained by the spatial layout within which items are delivered given that a left-to-right orientation boosts infants' rule learning, whereas a right-to-left orientation hinders this ability. Infants' rule learning operates across different domains and can also be transferred across modalities when learning is triggered by speech. However, no studies have investigated whether the transfer of rule learning occurs across different domains when language is not involved. Using a visual habituation procedure, we tested 7-month-old infants' ability to extract rule-like patterns from numerical sequences and generalize them to non-numerical sequences of visual shapes and whether this ability is affected by the spatial orientation. Infants were first habituated to left-to-right or right-to-left oriented numerical sequences instantiating an ABB rule and were then tested with the familiar rule instantiated across sequences of single geometrical shapes and a novel (ABA) rule. Results showed a transfer of learning from number to visual shapes for left-to-right oriented sequences but not for right-to-left oriented ones (Experiment 1) even when the direction of the numerical change (increasing vs. decreasing) within the habituation sequences violated a small-left/large-right number-space association (Experiment 2). These results provide the first demonstration that visual rule learning mechanisms in infancy operate at a high level of abstraction and confirm earlier findings that left-to-right oriented directional cues facilitate infants' representation of order.

Clinical Data Abstraction: A Research Study

This is the second part in a two-part research study on clinical data abstraction.1 Clinical data abstraction is the process of capturing key administrative and clinical data elements from a medical record. Very little is known about how the abstraction function is organized and managed today. A research study to gather data on how the clinical data abstraction function is managed in healthcare organizations across the country was performed. Results show that the majority of the healthcare organizations surveyed have a decentralized system, still perform the abstraction in-house as part of the coding workflow, and use manual abstraction followed by natural language processing (NLP) and simple query. The qualifications and training of abstractors varied across abstraction functions, however coders followed by nurses and health information management (HIM) professionals were the three top performers in abstraction. While, in general, abstraction is decentralized in most enterprises, two enterprise-wide abstraction models emerged from our study. In Model 1, the HIM department is responsible for coding, as well as all of the abstraction functions except the cancer registry and trauma registry abstraction. In Model 2, the quality department is responsible for all of the abstraction functions except the cancer registry, trauma registry, and coding function.

Assessing abstract thought and its relation to language with a new nonverbal paradigm: Evidence from aphasia

In recent years, language has been shown to play a number of important cognitive roles over and above the communication of thoughts. One hypothesis gaining support is that language facilitates thought about abstract categories, such as democracy or prediction. To test this proposal, a novel set of semantic memory task trials, designed for assessing abstract thought non-linguistically, were normed for levels of abstractness. The trials were rated as more or less abstract to the degree that answering them required the participant to abstract away from both perceptual features and common setting associations corresponding to the target image. The normed materials were then used with a population of people with aphasia to assess the relationship of abstract thought to language. While the language-impaired group with aphasia showed lower overall accuracy and longer response times than controls in general, of special note is that their response times were significantly longer as a function of a trial's degree of abstractness. Further, the aphasia group's response times in reporting their degree of confidence (a separate, metacognitive measure) were negatively correlated with their language production abilities, with lower language scores predicting longer metacognitive response times. These results provide some support for the hypothesis that language is an important aid to abstract thought and to metacognition about abstract thought.

Primate memory, from simple associations to abstract concepts

The hippocampus is a neural structure central to the formation of memories and wayfinding. To understand the neural mechanisms at work during memory formation over multiple episodes, Electrophysiological recordings show that neurons in the macaque hippocampus encode complex conjunctions of traits relevant to the navigational task during virtual navigation. While a majority encode environment-specific cues, about one third exhibit correlated firing across different environments sharing the same spatial structure. The similarity of firing appeared to encode the logic of the task in a way akin to a schema. The existence of the schema cells offers a foundation for abstraction in the monkey and suggests that memory storage in the primate could proceed in a similar way from simple cue associations up to conceptual thinking.

Modeling the Influence of Language Input Statistics on Children's Speech Production

We trained a computational model (the Chunk-Based Learner; CBL) on a longitudinal corpus of child-caregiver interactions in English to test whether one proposed statistical learning mechanism-backward transitional probability-is able to predict children's speech productions with stable accuracy throughout the first few years of development. We predicted that the model less accurately reconstructs children's speech productions as they grow older because children gradually begin to generate speech using abstracted forms rather than specific "chunks" from their speech environment. To test this idea, we trained the model on both recently encountered and cumulative speech input from a longitudinal child language corpus. We then assessed whether the model could accurately reconstruct children's speech. Controlling for utterance length and the presence of duplicate chunks, we found no evidence that the CBL becomes less accurate in its ability to reconstruct children's speech with age.

Color associations in abstract semantic domains

The embodied cognition paradigm has stimulated ongoing debate about whether sensory data - including color - contributes to the semantic structure of abstract concepts. Recent uses of linguistic data in the study of embodied cognition have been focused on textual corpora, which largely precludes the direct analysis of sensory information. Here, we develop an automated approach to multimodal content analysis that detects associations between words based on the color distributions of their Google Image search results. Crucially, we measure color using a transformation of colorspace that closely resembles human color perception. We find that words in the abstract domains of academic disciplines, emotions, and music genres, cluster in a statistically significant fashion according to their color distributions. Furthermore, we use the lexical ontology WordNet and crowdsourced human judgments to show that this clustering reflects non-arbitrary semantic structure, consistent with metaphor-based accounts of embodied cognition. In particular, we find that images corresponding to more abstract words exhibit higher variability in colorspace, and semantically similar words have more similar color distributions. Strikingly, we show that color associations often reflect shared affective dimensions between abstract domains, thus revealing patterns of aesthetic coherence in everyday language. We argue that these findings provide a novel way to synthesize metaphor-based and affect-based accounts of embodied semantics.

Abstraction and interpretation during the qualitative content analysis process

Qualitative content analysis and other 'standardised' methods are sometimes considered to be technical tools used for basic, superficial, and simple sorting of text, and their results lack depth, scientific rigour, and evidence. To strengthen the trustworthiness of qualitative content analyses, we focus on abstraction and interpretation during the analytic process. To our knowledge, descriptions of these concepts are sparse; this paper therefore aims to elaborate on and exemplify the distinction and relation between abstraction and interpretation during the different phases of the process of qualitative content analysis. We address the relations between abstraction and interpretation when selecting, condensing, and coding meaning units and creating categories and themes on various levels. The examples used are based on our experiences of teaching and supervising students at various levels. We also highlight the phases of de-contextualisation and re-contextualisation in describing the analytic process. We argue that qualitative content analysis can be both descriptive and interpretative. When the data allow interpretations of the latent content, qualitative content analysis reveals both depth and meaning in participants' utterances.

Abstractive summarization of long texts by representing multiple compositionalities with temporal hierarchical pointer generator network

In order to tackle the problem of abstractive summarization of long multi-sentence texts, it is critical to construct an efficient model, which can learn and represent multiple compositionalities better. In this paper, we introduce a temporal hierarchical pointer generator network that can represent multiple compositionalities in order to handle longer sequences of texts with a deep structure. We demonstrate how a multilayer gated recurrent neural network organizes itself with the help of an adaptive timescale in order to represent the compositions. The temporal hierarchical network is implemented with a multiple timescale architecture where the timescale of each layer is also learned during the training process through error backpropagation through time. We evaluate our proposed model using an Introduction-Abstract summarization dataset from scientific articles and the CNN/Daily Mail summarization benchmark dataset. The results illustrate that, we successfully implement a summary generation system for long texts by using the multiple timescale with adaptation concept. We also show that we have improved the summary generation system with our proposed model on the benchmark dataset.

On abstraction: decoupling conceptual concreteness and categorical specificity

Conceptual concreteness and categorical specificity are two continuous variables that allow distinguishing, for example, justice (low concreteness) from banana (high concreteness) and furniture (low specificity) from rocking chair (high specificity). The relation between these two variables is unclear, with some scholars suggesting that they might be highly correlated. In this study, we operationalize both variables and conduct a series of analyses on a sample of > 13,000 nouns, to investigate the relationship between them. Concreteness is operationalized by means of concreteness ratings, and specificity is operationalized as the relative position of the words in the WordNet taxonomy, which proxies this variable in the hypernym semantic relation. Findings from our studies show only a moderate correlation between concreteness and specificity. Moreover, the intersection of the two variables generates four groups of words that seem to denote qualitatively different types of concepts, which are, respectively, highly specific and highly concrete (typical concrete concepts denoting individual nouns), highly specific and highly abstract (among them many words denoting human-born creation and concepts within the social reality domains), highly generic and highly concrete (among which many mass nouns, or uncountable nouns), and highly generic and highly abstract (typical abstract concepts which are likely to be loaded with affective information, as suggested by previous literature). These results suggest that future studies should consider concreteness and specificity as two distinct dimensions of the general phenomenon called abstraction.

A dataset for evaluating one-shot categorization of novel object classes

With the advent of deep convolutional neural networks, machines now rival humans in terms of object categorization. The neural networks solve categorization with a hierarchical organization that shares a striking resemblance to their biological counterpart, leading to their status as a standard model of object recognition in biological vision. Despite training on thousands of images of object categories, however, machine-learning networks are poorer generalizers, often fooled by adversarial images with very simple image manipulations that humans easily distinguish as a false image. Humans, on the other hand, can generalize object classes from very few samples. Here we provide a dataset of novel object classifications in humans. We gathered thousands of crowd-sourced human responses to novel objects embedded either with 1 or 16 context sample(s). Human decisions and stimuli together have the potential to be re-used (1) as a tool to better understand the nature of the gap in category learning from few samples between human and machine, and (2) as a benchmark of generalization across machine learning networks.

[Subjectivity and objectivity, illness and disease]

When we are ill, what helps us recover? What constitutes disease, what legitimates it and what role do subjective complaints play? A medicine that focuses on measuring and correcting facts but ignores individual illness experience and context wastes diagnostic and therapeutic potential.

What Does a Horgous Look Like? Nonsense Words Elicit Meaningful Drawings

To what extent do people attribute meanings to "nonsense" words? How general is such attribution of meaning? We used a set of words lacking conventional meanings to elicit drawings of made-up creatures. Separate groups of participants rated the nonsense words and the drawings on several semantic dimensions and selected what name best corresponded to each creature. Despite lacking conventional meanings, "nonsense" words elicited a high level of consistency in the produced drawings. Meaning attributions made to nonsense words corresponded with meaning attributions made by separate people to drawings that were inspired by the name. Naïve participants were able to recover the name that inspired the drawing with greater-than-chance accuracy. These results suggest that people make liberal and consistent use of non-arbitrary relationships between forms and meanings. OPEN RESEARCH BADGES: This article has been awarded Open Materials and Open Data badges. All materials and data are publicly accessible via the Open Science Framework at https://osf.io/8juyc/. Learn more about the Open Practices badges from the Center for Open Science: https://osf.io/tvyxz/wiki.

From action to abstraction: The sensorimotor grounding of metaphor in Parkinson's disease

Embodied cognition theories propose that the semantic representations engaged in during language comprehension are partly supported by perceptual and motor systems, via simulation. Activation in modality-specific regions of cortex is associated with the comprehension of literal language that describes the analogous modalities, but studies addressing the grounding of non-literal or figurative language, such as metaphors, have yielded mixed results. Differences in the psycholinguistic characteristics of sentence stimuli across studies have likely contributed to this lack of consensus. Furthermore, previous studies have been largely correlational, whilst patient studies are a critical way of determining if intact sensorimotor function is necessary to understand language drawing on sensorimotor information. We designed a battery of metaphorical and literal sentence stimuli using action and sound words, with an unprecedented level of control over critical psycholinguistic variables, to test hypotheses about the grounding of metaphorical language. In this Registered Report, we assessed the comprehension of these sentences in 41 patients with Parkinson's disease, who were predicted to be disproportionately affected by the action sentences relative to the sound sentences, and compared their performance to that of 39 healthy age-matched controls who were predicted to show no difference in performance due to sensory modality. Using preregistered Bayesian model comparison methods, we found that PD patients' comprehension of literal action sentences was not impaired, while there was some evidence for a slowing of responses to action metaphors. Follow up exploratory analyses suggest that this response time modality effect was driven by one type of metaphor (predicate) and was absent in another (nominal), despite the fact that the action semantics were similar in both syntactic forms. These results suggest that the conditions under which PD patients demonstrate hypothesized embodiment effects are limited. We offer a critical assessment of the PD action language literature and discuss implications for the embodiment debate. In addition, we suggest how future studies could leverage Bayesian statistical methods to provide more convincing evidence for or against embodied cognition effects.

The career of measurement

Units as they exist today are highly abstract. Meters, miles, and other modern measures have no obvious basis in tangible phenomena and can be applied broadly across domains. Historical examples suggest, however, that units have not always been so abstract. Here, we examine this issue systematically. We begin by analyzing linear measures in the Oxford English Dictionary (OED) and in an ethnographic database that spans 114 cultures (HRAF). Our survey of both datasets shows, first, that early length units have mostly come from concrete sources-body parts, artifacts, events, and other tangible phenomena-and, second, that they have often been tied to particular contexts. Measurement units have thus undergone a shift from highly concrete to highly abstract. How did this shift happen? Drawing on historical surveys and case studies-as well as data from the OED and HRAF-we next propose a reconstruction of how abstract units might have evolved gradually through a series of overlapping stages. We also consider the cognitive processes that underpin this evolution-in particular, comparison. Finally, we discuss the cognitive origins of units. Units are not only slow to emerge historically, they are also slow to be acquired developmentally, and mastering them appears to have cognitive consequences. Taken together, these observations suggest that units are not inevitable intuitions, but are best thought of as culturally evolved cognitive tools. By analyzing the career of measurement in detail, we illustrate how such tools-abstract as they are today-can arise from concrete, often bodily origins.

Does practice in category learning increase rule use or exemplar use-or both?

Categorization research has demonstrated the use of both rules and remembered exemplars in classification, although there is disagreement over whether learners shift from one to the other or use both strategies simultaneously. Theoretical arguments can motivate predictions for both rule use and exemplar use increasing with more practice. We describe a single large experiment (n = 190) that manipulated the number of training items (category size), the number of presentations of each training item, and the similarity between the training and the transfer stimuli in order to discover when rules and exemplars are most likely to be used. Results showed that rules and exemplars both influenced classification and that exemplars were used more often with smaller categories, with more training on items, and when test items were similar to training items. There was no consistent evidence of a shift from rule-based to exemplar-based categorization with more learning. Importantly, we found a number of conditions in which rules and exemplars were both used, even within individual participants. We discuss our results in terms of hybrid models of classification.

Mechanism diagrams and abstraction-by-aggregation

Mechanism diagrams exhibit visually the organized parts and operations of a biological mechanism. A mechanism diagram can facilitate mechanistic research by providing a mechanistic explanation of the phenomenon of interest. Much research has been focusing on the mechanistic explanation and the explanatory mechanistic models. As a specific type of scientific diagram, a simple mechanism diagram can be explanatory by drawing on the rich explanatory resources of non-depicted background knowledge. The relationship between the visually depicted and the background knowledge is underexplored. It is unclear how the non-depicted background knowledge of a mechanism diagram contributes to providing a better-informed explanation of the phenomenon of interest in biological sciences. With the aim to explore this relationship, I articulate that a mechanism diagram provides a mechanistic explanation by a process called abstraction-by-aggregation. Through visual cues, the unified relevant background knowledge provides an epistemic access to a better-informed explanation.

Synthetic biology toolkits and applications in Saccharomyces cerevisiae

Synthetic biologists construct biological components and systems to look into biological phenomena and drive a myriad of practical applications that aim to tackle current global challenges in energy, healthcare and the environment. While most tools have been established in bacteria, particularly Escherichia coli, recent years have seen parallel developments in the model yeast strain Saccharomyces cerevisiae, one of the most well-understood eukaryotic biological system. Here, we outline the latest advances in yeast synthetic biology tools based on a framework of abstraction hierarchies of parts, circuits and genomes. In brief, the creation and characterization of biological parts are explored at the transcriptional, translational and post-translational levels. Using characterized parts as building block units, the designing of functional circuits is elaborated with examples. In addition, the status and potential applications of synthetic genomes as a genome level platform for biological system construction are also discussed. In addition to the development of a toolkit, we describe how those tools have been applied in the areas of drug production and screening, study of disease mechanisms, pollutant sensing and bioremediation. Finally, we provide a future outlook of yeast as a workhorse of eukaryotic genetics and a chosen chassis in this field.

Abstraction, Multiple Exemplar Training and the Search for Derived Stimulus Relations in Animals

Symmetry and other derived stimulus relations are readily demonstrated in humans in a variety of experimental preparations. Comparable emergent relations are more difficult to obtain in other animal species and seem to require certain specialized conditions of training and testing. This article examines some of these conditions with an emphasis on what animal research may be able to tell us about the nature and origins of derived stimulus relations. We focus on two areas that seem most promising: 1) research generated by Urcuioli's (2008) theory of the conditions necessary to produce symmetry in pigeons, and 2) research that explores the effects of multiple exemplar training on emergent relations. Urcuioli's theory has successfully predicted emergent relations in pigeons by taking into account their apparent difficulty in abstracting the nominal training stimulus from other stimulus properties such as location and temporal position. Further, whereas multiple exemplar training in non-humans has not consistently yielded arbitrarily-applicable relational responding, there is a growing body of literature showing that it does result in abstracted same-different responding. Our review suggests that although emergent stimulus relations demonstrated in non-humans at present have not yet shown the flexibility or generativity apparent in humans, the research strategies reviewed here provide techniques that may permit the analysis of the origins of derived relational responding.

Above and Beyond Objects: The Development of Infants' Spatial Concepts

Early in development infants form categorical representations of small-scale spatial relations, such as left vs right and above vs below. This spatial skill allows infants to experience coherence in the layout of the objects in their environment and to note the equivalence of a spatial relation across changes in objects. Comparisons across studies of infant spatial categorization offer insight into the processes that contribute to the development of this skill. Rather than viewing contrasting results across studies as contradictory, identifying how infant spatial categorization tasks recruit distinct processes can not only reconcile findings but also yield insight into the starting points, development, and emerging nature of infants' representations of spatial relations. Also, situating infants' spatial categorization in the context of advances in nonspatial domains may reveal synergistic relations among these domains, particularly in relation to advances in infants' manipulative play with objects and their acquisition of spatial language. A central argument is that broadening the study of infants' spatial categorization may yield further insights into the nature of early spatial concepts and the processes that promote their development.

Metaphor: Bridging embodiment to abstraction

Embodied cognition accounts posit that concepts are grounded in our sensory and motor systems. An important challenge for these accounts is explaining how abstract concepts, which do not directly call upon sensory or motor information, can be informed by experience. We propose that metaphor is one important vehicle guiding the development and use of abstract concepts. Metaphors allow us to draw on concrete, familiar domains to acquire and reason about abstract concepts. Additionally, repeated metaphoric use drawing on particular aspects of concrete experience can result in the development of new abstract representations. These abstractions, which are derived from embodied experience but lack much of the sensorimotor information associated with it, can then be flexibly applied to understand new situations.

Vital brains: On the entanglement of media, minds, and models

The advent of functional imaging, hailed as a breakthrough for marrying morphological and functional approaches in brain research, invites a reflection upon the interplay between models, instruments, and theories. Brain research and theorizing about the brain are generally mediated by the research technologies employed. Going back into the history of brain research, the chapter explores the epistemic effects of research technologies by focusing on the localization debate in relation to different visualization strategies. In this way, one can differentiate between abstracting and concretizing approaches to brain modeling. These approaches form the basis for introducing the concept of vital abstraction by revisiting Grey Walter's The Living Brain. Walter's adventures in visualizing brain activity and constructing lively toys are described as a form of brain theorizing that is anchored in empirical research but focuses on the brain's vital activity instead of identifying morphological and structural details. The concept of vital abstraction is further explored by applying the concept of epistemic virtues to evaluate current brain models and for coming to terms with the dynamics of brain research.

The Paradox of Abstraction: Precision Versus Concreteness

We introduce a novel measure of abstractness based on the amount of information of a concept computed from its position in a semantic taxonomy. We refer to this measure as precision. We propose two alternative ways to measure precision, one based on the path length from a concept to the root of the taxonomic tree, and another one based on the number of direct and indirect descendants. Since more information implies greater processing load, we hypothesize that nouns higher in precision will have a processing disadvantage in a lexical decision task. We contrast precision to concreteness, a common measure of abstractness based on the proportion of sensory-based information associated with a concept. Since concreteness facilitates cognitive processing, we predict that while both concreteness and precision are measures of abstractness, they will have opposite effects on performance. In two studies we found empirical support for our hypothesis. Precision and concreteness had opposite effects on latency and accuracy in a lexical decision task, and these opposite effects were observable while controlling for word length, word frequency, affective content and semantic diversity. Our results support the view that concepts organization includes amodal semantic structures which are independent of sensory information. They also suggest that we should distinguish between sensory-based and amount-of-information-based abstractness.

Sleep-based memory processing facilitates grammatical generalization: Evidence from targeted memory reactivation

Generalization-the ability to abstract regularities from specific examples and apply them to novel instances-is an essential component of language acquisition. Generalization not only depends on exposure to input during wake, but may also improve offline during sleep. Here we examined whether targeted memory reactivation during sleep can influence grammatical generalization. Participants gradually acquired the grammatical rules of an artificial language through an interactive learning procedure. Then, phrases from the language (experimental group) or stimuli from an unrelated task (control group) were covertly presented during an afternoon nap. Compared to control participants, participants re-exposed to the language during sleep showed larger gains in grammatical generalization. Sleep cues produced a bias, not necessarily a pure gain, suggesting that the capacity for memory replay during sleep is limited. We conclude that grammatical generalization was biased by auditory cueing during sleep, and by extension, that sleep likely influences grammatical generalization in general.

Explaining the moral of the story

Although storybooks are often used as pedagogical tools for conveying moral lessons to children, the ability to spontaneously extract "the moral" of a story develops relatively late. Instead, children tend to represent stories at a concrete level - one that highlights surface features and understates more abstract themes. Here we examine the role of explanation in 5- and 6-year-old children's developing ability to learn the moral of a story. Two experiments demonstrate that, relative to a control condition, prompts to explain aspects of a story facilitate children's ability to override salient surface features, abstract the underlying moral, and generalize that moral to novel contexts. In some cases, generating an explanation is more effective than being explicitly told the moral of the story, as in a more traditional pedagogical exchange. These findings have implications for moral comprehension, the role of explanation in learning, and the development of abstract reasoning in early childhood.

On Staying Grounded and Avoiding Quixotic Dead Ends

The 15 articles in this special issue on The Representation of Concepts illustrate the rich variety of theoretical positions and supporting research that characterize the area. Although much agreement exists among contributors, much disagreement exists as well, especially about the roles of grounding and abstraction in conceptual processing. I first review theoretical approaches raised in these articles that I believe are Quixotic dead ends, namely, approaches that are principled and inspired but likely to fail. In the process, I review various theories of amodal symbols, their distortions of grounded theories, and fallacies in the evidence used to support them. Incorporating further contributions across articles, I then sketch a theoretical approach that I believe is likely to be successful, which includes grounding, abstraction, flexibility, explaining classic conceptual phenomena, and making contact with real-world situations. This account further proposes that (1) a key element of grounding is neural reuse, (2) abstraction takes the forms of multimodal compression, distilled abstraction, and distributed linguistic representation (but not amodal symbols), and (3) flexible context-dependent representations are a hallmark of conceptual processing.

Psychicones: Visual Traces of the Soul in Late Nineteenth-Century Fluidic Photography

The article discusses attempts to visualise the soul on photographic plates at the end of the nineteenth century, as conducted by the French physician Hippolyte Baraduc in Paris. Although Baraduc refers to earlier experiments on fluidic photography in his book on The Human Soul (1896) and is usually mentioned as a precursor to parapsychological thought photography of the twentieth century, his work is presented as a genuine attempt at photographic soul-catching. Rather than producing mimetic representations of thoughts and imaginations, Baraduc claims to present the vital radiation of the psyche itself and therefore calls the images he produces psychicones. The article first discusses the difference between this method of soul photography and other kinds of occult media technologies of the time, emphasising the significance of its non-mimetic, abstract character: since the soul itself was considered an abstract entity, abstract traces seemed all the more convincing to the contemporary audience. Secondly, the article shows how the technological agency of photography allowed Baraduc's psychicones to be tied into related discourses in medicine and psychology. Insofar as the photographic plates displayed actual visual traces, Baraduc and his followers no longer considered hallucinations illusionary and pathological but emphasised the physical reality and normality of imagination. Yet, the greatest influence of soul photography was not on science but on art. As the third part of the paper argues, the abstract shapes on Baraduc's plates provided inspiration for contemporary avant-garde aesthetics, for example, Kandinsky's abstract paintings and the random streams of consciousness in surrealistic literature.

Hierarchical Bayesian models of cognitive development

This article provides an introductory overview of the state of research on Hierarchical Bayesian Modeling in cognitive development. First, a brief historical summary and a definition of hierarchies in Bayesian modeling are given. Subsequently, some model structures are described based on four examples in the literature. These are models for the development of the shape bias, for learning ontological kinds and causal schemata as well as for the categorization of objects. The Bayesian modeling approach is then compared with the connectionist and nativist modeling paradigms and considered in view of Marr's (1982) three description levels of information-processing mechanisms. In this context, psychologically plausible algorithms and ideas of their neural implementation are presented. In addition to criticism and limitations of the approach, research needs are identified.

Normal development and experimental embryology: Edmund Beecher Wilson and Amphioxus

This paper concerns the concept of normal development, and how it is enacted in experimental procedures. To that end, I use an historical case study to assess the three ways in which normal development is and has been produced, used, and interpreted in the practice of experimental biology. I argue that each of these approaches involves different processes of abstraction, which manage biological variation differently. I then document the way in which Edmund Beecher Wilson, a key contributor to late-nineteenth century experimental embryology, approached the study of normal development and show that his work does not fit any of the three established categories in the taxonomy. On the basis of this new case study, I present a new interpretation of normal development as a methodological norm which operates as a technical condition in various experimental systems. I close by suggesting the questions, and ways of investigating developmental biology, that are opened up by this perspective.

On the blessing of abstraction

The "blessing of abstraction" refers to the observation that acquiring abstract knowledge sometimes proceeds more quickly than acquiring more specific knowledge. This observation can be formalized and reproduced by hierarchical Bayesian models. The key notion is that more abstract layers of the hierarchy have a larger "effective" sample size, because they combine information across multiple specific instances lower in the hierarchy. This notion relies on specific variables being relatively concentrated around the abstract "overhypothesis". If the variables are highly dispersed, then the effective sample size for the abstract layers will not be appreciably larger than for the specific layers. Moreover, the blessing of abstraction is counterbalanced by the fact that data are more informative about lower levels of the hierarchy, because there is necessarily less stochasticity intervening between specific variables and the data. Thus, in certain cases abstract knowledge will be acquired more slowly than specific knowledge. This paper reports an experiment that shows how manipulating dispersion can produce both fast and slow acquisition of abstract knowledge in the same paradigm.

Cross-modal transfer of statistical information benefits from sleep

Extracting regularities from a sequence of events is essential for understanding our environment. However, there is no consensus regarding the extent to which such regularities can be generalised beyond the modality of learning. One reason for this could be the variation in consolidation intervals used in different paradigms, also including an opportunity to sleep. Using a novel statistical learning paradigm in which structured information is acquired in the auditory domain and tested in the visual domain over either 30 min or 24 h consolidation intervals, we show that cross-modal transfer can occur, but this transfer is only seen in the 24 h group. Importantly, the extent of cross-modal transfer is predicted by the amount of slow wave sleep (SWS) obtained. Additionally, cross-modal transfer is associated with the same pattern of decreasing medial temporal lobe and increasing striatal involvement which has previously been observed to occur across 24 h in unimodal statistical learning. We also observed enhanced functional connectivity after 24 h in a network of areas which have been implicated in cross-modal integration including the precuneus and the middle occipital gyrus. Finally, functional connectivity between the striatum and the precuneus was also enhanced, and this strengthening was predicted by SWS. These results demonstrate that statistical learning can generalise to some extent beyond the modality of acquisition, and together with our previously published unimodal results, support the notion that statistical learning is both domain-general and domain-specific.

The Representational Basis of Working Memory

Working memory refers to a system involved in the online maintenance and manipulation of information in the absence of external input. Due to the importance of working memory in higher-level cognition, a wealth of neuroscience studies has investigated its neural basis. These studies have often led to conflicting viewpoints regarding the importance of the prefrontal cortex (PFC) and posterior sensory cortices. Here, we review evidence for each position. We suggest that the relative contributions of the PFC and sensory cortices to working memory can be understood with respect to processing demands. We argue that procedures that minimize processing demands lead to increased importance of sensory representations, while procedures that permit transformational processing lead to representational abstraction that relies on the PFC. We suggest that abstract PFC representations support top-down control over posterior representations while also providing bottom-up inputs into higher-level cognitive processing. Although a number of contemporary studies have studied working memory while using procedures that minimize the role of the PFC, we argue that consideration of the PFC is critical for our understanding of working memory and higher-level cognition more generally.