The effects of a training package to teach note taking on the formation of equivalence classes.

Effective note taking may enhance learning outcomes for students and serve as a directly observable form of mediation within a test context. Frampton et al. (2023) used stimulus fading to teach note taking in the form of a graphic organizer (GO) during matching-to-sample baseline relations training (MTS-BRT). Moderately high yields were observed with young adults despite the use of linear series training, abstract stimuli, and five-member classes. The present study taught the same note taking strategy using an intervention package including video illustration, voice-over instructions, and feedback to eight college students. Participants were taught to construct the GO during MTS-BRT with three three-member classes of familiar stimuli. Then the effects of MTS-BRT alone with three five-member classes of abstract stimuli was evaluated. Participants efficiently completed training with familiar stimuli and passed the posttest on the first attempt. With the abstract stimuli, participants engaged in GO construction during MTS-BRT and the six participants that demonstrated high levels of fidelity to the trained note taking strategy passed the posttest on the first attempt. These results replicate findings from Frampton et al. while using a more efficient intervention package. Benefits of teaching overt mediation responses are discussed as well as future directions for translation to applied contexts.

Experiential grounding of abstract concepts: Processing of abstract mental state concepts engages brain regions involved in mentalizing, automatic speech, and lip movements.

concepts like mental state concepts lack a physical referent, which can be directly perceived. Classical theories therefore claim that abstract concepts require amodal representations detached from experiential brain systems. However, grounded cognition approaches suggest an involvement of modal experiential brain regions in the processing of abstract concepts. In the present functional magnetic resonance imaging study, we investigated the relation of the processing of abstract mental state concepts to modal experiential brain systems in a fine-grained fashion. Participants performed lexical decisions on abstract mental state as well as on verbal association concepts as control category. Experiential brain systems related to the processing of mental states, generating verbal associations, automatic speech as well as hand and lip movements were determined by corresponding localizer tasks. Processing of abstract mental state concepts neuroanatomically overlapped with activity patterns associated with processing of mental states, generating verbal associations, automatic speech and lip movements. Hence, mental state concepts activate the mentalizing brain network, complemented by perceptual-motor brain regions involved in simulation of visual or action features associated with social interactions, linguistic brain regions as well as face-motor brain regions recruited for articulation. The present results provide compelling evidence for the rich grounding of abstract mental state concepts in experiential brain systems related to mentalizing, verbal communication and mouth action.

Explicit and implicit category learning in categorical visual search.

Categorical search has been heavily investigated over the past decade, mostly using natural categories that leave the underlying category mental representation unknown. The categorization literature offers several theoretical accounts of category mental representations. One prominent account is that separate learning systems account for classification: an explicit learning system that relies on easily verbalized rules and an implicit learning system that relies on an associatively learned (nonverbalizable) information integration strategy. The current study assessed the contributions of these separate category learning systems in the context of categorical search using simple stimuli. Participants learned to classify sinusoidal grating stimuli according to explicit or implicit categorization strategies, followed by a categorical search task using these same stimulus categories. Computational modeling determined which participants used the appropriate classification strategy during training and search, and eye movements collected during categorical search were assessed. We found that the trained categorization strategies overwhelmingly transferred to the verification (classification response) phase of search. Implicit category learning led to faster search response and shorter target dwell times relative to explicit category learning, consistent with the notion that explicit rule classification relies on a more deliberative response strategy. Participants who transferred the correct category learning strategy to the search guidance phase produced stronger search guidance (defined as the proportion of trials on which the target was the first item fixated) with evidence of greater guidance in implicit-strategy learners. This demonstrates that both implicit and explicit categorization systems contribute to categorical search and produce dissociable patterns of data.

Infants' fast neural categorization of artificial objects: The impact of stimulus and task characteristics.

This study explores how 7-month-old infants categorize graphical images varying in basic perceptual features by using a fast periodic visual stimulation (FPVS) task. Most participants were Caucasian and their parents had a higher education, but the family's socioeconomic background was mixed. Experiment 1 (N = 23) tested brain responses to configurational versus scrambled image sequences and found an oddball effect for both conditions, with configurational information leading to stronger neural responses. Experiment 2 explored the role of category learning for later FPVS performance: Group A (control; n = 22) participated in the FPVS categorization task only. Group B (fam; n = 21) was first familiarized with standard exemplars. Group C (fam + contrast; n = 29) was presented an additional exemplar of the contrasting category before the FPVS task. Electroencephalogram analyses revealed a decrease in Nc amplitude (measuring attention) throughout the familiarization phase. Long looking at the out-of-category exemplar in Group C indicated infants' visual interest. Brain responses in the subsequently presented FPVS were strong but did not differ between groups. This highlights the ability of the infant brain to organize perceptual input very rapidly without requiring familiarization but also points to the need for further studies exploring brain processes associated with infants' category learning and categorization at the brain level. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Resolving the associative learning paradox by category learning in pigeons.

A wealth of evidence indicates that humans can engage two types of mechanisms to solve category-learning tasks: declarative mechanisms, which involve forming and testing verbalizable decision rules, and associative mechanisms, which involve gradually linking stimuli to appropriate behavioral responses.1,2,3 In contrast to declarative mechanisms, associative mechanisms have received surprisingly little attention in the broader category-learning literature. Although various forms of associatively driven artificial intelligence (AI) have matched-and even surpassed-humans' performance on several challenging problems,3,4,5,6 associative learning is routinely dismissed as being too simple to power the impressive cognitive achievements of both humans and non-human species.6,7,8,9 Here, we attempt to resolve this paradox by demonstrating that pigeons-which appear to rely solely on associative learning mechanisms in several tasks that promote declarative rule use by humans3,10,11,12-succeed at learning a novel, highly demanding category structure that ought to hinder declarative rule use: the sectioned-rings task. Our findings highlight the power and flexibility that associative mechanisms afford in the realm of category learning.

Word-association norms for 1,100 French words with varying levels of concreteness.

The organisation of concepts in the mental lexicon is a widely studied research topic in experimental psychology. For instance, several studies have shown that whereas concrete concepts are organised according to semantic similarity, abstract concepts are organised according to verbal association. However, these results are not systematically replicated, mainly due to a lack of normative database especially in French. To that end, we introduce a French word-association database for 1,100 cues with varying levels of concreteness from abstract to concrete concepts. Analyses from the word-association task revealed stronger association strength for concrete concepts compared with abstract concepts. Additional results showed that cues tend to elicit responses of a similar level of concreteness. The database will be useful for investigators interested in French verbal associations for abstract and concrete concepts. The data (available on OSF https://osf.io/dhuqs/) introduce responses organised according to association strength and provides cue concreteness.

Multi-dimensional sensorimotor grounding of concrete and abstract categories.

Semantic categories, and the concepts belonging to them, have commonly been defined by their relative concreteness, that is, their reliance on perception. However, sensorimotor grounding must be regarded as going beyond the basic five senses and incorporate a multi-dimensional variety of perceptual and action experience. We present a series of exploratory analyses examining the sensorimotor grounding of participant-produced member concepts for 117 categories, spanning concrete (e.g. animal and furniture) and highly abstract (e.g. unit of time and science) categories. We found that both concrete and abstract categories are strongly grounded in multi-dimensional sensorimotor experience. Both domains were dominated by vision and, to a lesser extent, head movements, but concrete categories were more grounded in touch and hand-arm action, while abstract categories were more grounded in hearing and interoception. Importantly, this pattern of grounding was not uniform, and subdomains of concrete (e.g. ingestibles, animates, natural categories and artefacts) and abstract (e.g. internal, social and non-social) categories were grounded in different profiles of sensorimotor experience. Overall, these findings suggest that the distinction between abstract and concrete categories is not as clearcut as ontological assumptions might suggest, and that the strength and diversity of sensorimotor grounding in abstract categories must not be underestimated. This article is part of the theme issue 'Concepts in interaction: social engagement and inner experiences'.

Influence of language on perception and concept formation in a brain-constrained deep neural network model.

A neurobiologically constrained model of semantic learning in the human brain was used to simulate the acquisition of concrete and abstract concepts, either with or without verbal labels. Concept acquisition and semantic learning were simulated using Hebbian learning mechanisms. We measured the network's category learning performance, defined as the extent to which it successfully (i) grouped partly overlapping perceptual instances into a single (abstract or concrete) conceptual representation, while (ii) still distinguishing representations for distinct concepts. Co-presence of linguistic labels with perceptual instances of a given concept generally improved the network's learning of categories, with a significantly larger beneficial effect for abstract than concrete concepts. These results offer a neurobiological explanation for causal effects of language structure on concept formation and on perceptuo-motor processing of instances of these concepts: supplying a verbal label during concept acquisition improves the cortical mechanisms by which experiences with objects and actions along with the learning of words lead to the formation of neuronal ensembles for specific concepts and meanings. Furthermore, the present results make a novel prediction, namely, that such 'Whorfian' effects should be modulated by the concreteness/abstractness of the semantic categories being acquired, with language labels supporting the learning of abstract concepts more than that of concrete ones. This article is part of the theme issue 'Concepts in interaction: social engagement and inner experiences'.

Abstract and concrete concepts in conversation.

Concepts allow us to make sense of the world. Most evidence on their acquisition and representation comes from studies of single decontextualized words and focuses on the opposition between concrete and abstract concepts (e.g., "bottle" vs. "truth"). A significant step forward in research on concepts consists in investigating them in online interaction during their use. Our study examines linguistic exchanges analyzing the differences between sub-kinds of concepts. Participants were submitted to an online task in which they had to simulate a conversational exchange by responding to sentences involving sub-kinds of concrete (tools, animals, food) and abstract concepts (PS, philosophical-spiritual; EMSS, emotional-social, PSTQ, physical-spatio-temporal-quantitative). We found differences in content: foods evoked interoception; tools and animals elicited materials, spatial, auditive features, confirming their sensorimotor grounding. PS and EMSS yielded inner experiences (e.g., emotions, cognitive states, introspections) and opposed PSTQ, tied to visual properties and concrete agency. More crucially, the various concepts elicited different interactional dynamics: more abstract concepts generated higher uncertainty and more interactive exchanges than concrete ones. Investigating concepts in situated interactions opens new possibilities for studying conceptual knowledge and its pragmatic and social aspects.

Similarities and differences in the neural representations of abstract concepts across English and Mandarin.

Recent research suggests there is a neural organization for representing abstract concepts that is common across English speakers. To investigate the possible role of language on the representation of abstract concepts, multivariate pattern analytic (MVPA) techniques were applied to fMRI data to compare the neural representations of 28 individual abstract concepts between native English and Mandarin speakers. Factor analyses of the activation patterns of the 28 abstract concepts from both languages characterized this commonality in terms of a set of four underlying neurosemantic dimensions, indicating the degree to which a concept is verbally represented, internal to the person, contains social content, and is rule-based. These common semantic dimensions (factors) underlying the 28 concepts provided a sufficient basis for reliably identifying the individual abstract concepts from their neural signature in the other language with a mean rank accuracy of 0.65 (p < .001). Although the neural dimensions used for representing abstract concepts are common across languages, differences in the meaning of some individual concepts can be accommodated in terms of differential salience of particular dimensions. These semantic dimensions constitute a set of neurocognitive resources for abstract concept representations within a larger set of regions responsible for general semantic processing.

Modelling brain representations of abstract concepts.

conceptual representations are critical for human cognition. Despite their importance, key properties of these representations remain poorly understood. Here, we used computational models of distributional semantics to predict multivariate fMRI activity patterns during the activation and contextualization of abstract concepts. We devised a task in which participants had to embed abstract nouns into a story that they developed around a given background context. We found that representations in inferior parietal cortex were predicted by concept similarities emerging in models of distributional semantics. By constructing different model families, we reveal the models' learning trajectories and delineate how abstract and concrete training materials contribute to the formation of brain-like representations. These results inform theories about the format and emergence of abstract conceptual representations in the human brain.

Decoding the information structure underlying the neural representation of concepts.

The nature of the representational code underlying conceptual knowledge remains a major unsolved problem in cognitive neuroscience. We assessed the extent to which different representational systems contribute to the instantiation of lexical concepts in high-level, heteromodal cortical areas previously associated with semantic cognition. We found that lexical semantic information can be reliably decoded from a wide range of heteromodal cortical areas in the frontal, parietal, and temporal cortex. In most of these areas, we found a striking advantage for experience-based representational structures (i.e., encoding information about sensory-motor, affective, and other features of phenomenal experience), with little evidence for independent taxonomic or distributional organization. These results were found independently for object and event concepts. Our findings indicate that concept representations in the heteromodal cortex are based, at least in part, on experiential information. They also reveal that, in most heteromodal areas, event concepts have more heterogeneous representations (i.e., they are more easily decodable) than object concepts and that other areas beyond the traditional "semantic hubs" contribute to semantic cognition, particularly the posterior cingulate gyrus and the precuneus.

Differential temporo-spatial pattern of electrical brain activity during the processing of abstract concepts related to mental states and verbal associations.

Refined grounded cognition accounts propose that abstract concepts might be grounded in brain circuits involved in mentalizing. In the present event-related potential (ERP) study, we compared the time course of neural processing in response to semantically predefined abstract mental states and verbal association concepts during a lexical decision task. In addition to scalp ERPs, source estimates of underlying volume brain activity were determined to reveal spatio-temporal clusters of greater electrical brain activity to abstract mental state vs. verbal association concepts, and vice versa. Source estimates suggested early (onset 194 ms), but short-lived enhanced activity (offset 210 ms) to verbal association concepts in left occipital regions. Increased occipital activity might reflect retrieval of visual word form or access to visual conceptual features of associated words. Increased estimated source activity to mental state concepts was obtained in visuo-motor (superior parietal, pre- and postcentral areas) and mentalizing networks (lateral and medial prefrontal areas, insula, precuneus, temporo-parietal junction) with an onset of 212 ms, which extended to later time windows. The time course data indicated two processing phases: An initial conceptual access phase, in which linguistic and modal brain circuits rapidly process features depending on their relevance, and a later conceptual elaboration phase, in which elaborative processing within feature-specific networks further refines the concept. This study confirms the proposal that abstract concepts are based on representations in distinct neural circuits depending on their semantic feature content. The present research also highlights the importance of investigating sets of abstract concepts with a defined semantic content.

Scheduling math practice: Students' underappreciation of spacing and interleaving.

Many randomized controlled experiments in the classroom have found that mathematics learning is improved dramatically when practice problems of one kind are distributed across multiple assignments (spaced) and mixed with other kinds of problems (interleaved). In two studies, we investigated students' knowledge of spacing and interleaving. In Study 1, 193 undergraduates designed learning schedules for a hypothetical math class. In Study 2, 175 undergraduates selected from among five hypothetical schedules in response to a variety of questions, provided reasons for their selections, and rated the utility of spacing and interleaving. In both studies, most participants incorrectly judged schedules with minimal degrees of spacing and interleaving to be most effective. Also, schedules with more spacing and interleaving were perceived as more difficult, less enjoyable, and less common. Participants' ratings of utility revealed mixed perspectives on spacing and an underappreciation of interleaving. Altogether, these findings demonstrate that most students fail to recognize the benefits of spaced and interleaved practice. Further, by identifying specific ways in which their beliefs about spacing and interleaving fall short, we reveal opportunities to reshape students' beliefs to foster these effective learning techniques. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Attention enhances category representations across the brain with strengthened residual correlations to ventral temporal cortex.

How does attention enhance neural representations of goal-relevant stimuli while suppressing representations of ignored stimuli across regions of the brain? While prior studies have shown that attention enhances visual responses, we lack a cohesive understanding of how selective attention modulates visual representations across the brain. Here, we used functional magnetic resonance imaging (fMRI) while participants performed a selective attention task on superimposed stimuli from multiple categories and used a data-driven approach to test how attention affects both decodability of category information and residual correlations (after regressing out stimulus-driven variance) with category-selective regions of ventral temporal cortex (VTC). Our data reveal three main findings. First, when two objects are simultaneously viewed, the category of the attended object can be decoded more readily than the category of the ignored object, with the greatest attentional enhancements observed in occipital and temporal lobes. Second, after accounting for the response to the stimulus, the correlation in the residual brain activity between a cortical region and a category-selective region of VTC was elevated when that region's preferred category was attended vs. ignored, and more so in the right occipital, parietal, and frontal cortices. Third, we found that the stronger the residual correlations between a given region of cortex and VTC, the better visual category information could be decoded from that region. These findings suggest that heightened residual correlations by selective attention may reflect the sharing of information between sensory regions and higher-order cortical regions to provide attentional enhancement of goal-relevant information.

Modelling concrete and abstract concepts using brain-constrained deep neural networks.

A neurobiologically constrained deep neural network mimicking cortical area function relevant for sensorimotor, linguistic and conceptual processing was used to investigate the putative biological mechanisms underlying conceptual category formation and semantic feature extraction. Networks were trained to learn neural patterns representing specific objects and actions relevant to semantically 'ground' concrete and abstract concepts. Grounding sets consisted of three grounding patterns with neurons representing specific perceptual or action-related features; neurons were either unique to one pattern or shared between patterns of the same set. Concrete categories were modelled as pattern triplets overlapping in their 'shared neurons', thus implementing semantic feature sharing of all instances of a category. In contrast, abstract concepts had partially shared feature neurons common to only pairs of category instances, thus, exhibiting family resemblance, but lacking full feature overlap. Stimulation with concrete and abstract conceptual patterns and biologically realistic unsupervised learning caused formation of strongly connected cell assemblies (CAs) specific to individual grounding patterns, whose neurons were spread out across all areas of the deep network. After learning, the shared neurons of the instances of concrete concepts were more prominent in central areas when compared with peripheral sensorimotor ones, whereas for abstract concepts the converse pattern of results was observed, with central areas exhibiting relatively fewer neurons shared between pairs of category members. We interpret these results in light of the current knowledge about the relative difficulty children show when learning abstract words. Implications for future neurocomputational modelling experiments as well as neurobiological theories of semantic representation are discussed.

Time course of brain activity during the processing of motor- and vision-related abstract concepts: flexibility and task dependency.

Grounded cognition theories assume that conceptual processing depends on modality-specific brain systems in a context-dependent fashion. Although the relation of abstract concepts to modality-specific systems is less obvious than for concrete concepts, recent behavioral and neuroimaging studies indicated a foundation of abstract concepts in vision and action. However, due to their poor temporal resolution, neuroimaging studies cannot determine whether sensorimotor activity reflects rapid access to conceptual information or later conceptual processes. The present study therefore assessed the time course of abstract concept processing using event-related potentials (ERPs) and compared ERP responses to abstract concepts with a strong relation to vision or action. We tested whether possible ERP effects to abstract word categories would emerge in early or in later time windows and whether these effects would depend on the depth of the conceptual task. In Experiment 1, a shallow lexical decision task, early feature-specific effects starting at 178 ms were revealed, but later effects beyond 300 ms were also observed. In Experiment 2, a deep conceptual decision task, feature-specific effects with an onset of 22 ms were obtained, but effects again extended beyond 300 ms. In congruency with earlier neuroimaging work, the present feature-specific ERP effects suggest a grounding of abstract concepts in modal brain systems. The presence of early and late feature-specific effects indicates that sensorimotor activity observed in neuroimaging experiments may reflect both rapid conceptual and later post-conceptual processing. Results furthermore suggest that a deep conceptual task accelerates access to conceptual sensorimotor features, thereby demonstrating conceptual flexibility.

Encoding and inhibition of arbitrary episodic context with abstract concepts.

Context is critical for conceptual processing, but the mechanism underpinning its encoding and reinstantiation during abstract concept processing is unclear. Context may be especially important for abstract concepts-we investigated whether episodic context is recruited differently when processing abstract compared with concrete concepts. Experiments 1 and 2 presented abstract and concrete words in arbitrary contexts at encoding (Experiment 1: red/green colored frames; Experiment 2: male/female voices). Recognition memory for these contexts was worse for abstract concepts. Again using frame color and voice as arbitrary contexts, respectively, Experiments 3 and 4 presented words from encoding in the same or different context at test to determine whether there was a greater recognition memory benefit for abstract versus concrete concepts when the context was unchanged between encoding and test. Instead, abstract concepts were less likely to be remembered when context was retained. This suggests that at least some types of episodic context-when arbitrary-are attended less, and may even be inhibited, when processing abstract concepts. In Experiment 5, we utilized a context-spatial location-which (as we show) tends to be relevant during real-world processing of abstract concepts. We presented words in different locations, preserving or changing location at test. Location retention conferred a recognition memory advantage for abstract concepts. Thus, episodic context may be encoded with abstract concepts when context is relevant to real-world processing. The systematic contexts necessary for understanding abstract concepts may lead to arbitrary context inhibition, but greater attention to contexts that tend to be more relevant during real-world processing.

A cognitive category-learning model of rule abstraction, attention learning, and contextual modulation.

We introduce the Category Abstraction Learning (CAL) model, a cognitive framework formally describing category learning built on similarity-based generalization, dissimilarity-based abstraction, two attention learning mechanisms, error-driven knowledge structuring, and stimulus memorization. Our hypotheses draw on an array of empirical and theoretical insights connecting reinforcement and category learning. The key novelty of the model is its explanation of how rules are learned from scratch based on three central assumptions. (a) Category rules emerge from two processes of stimulus generalization (similarity) and its direct inverse (category contrast) on independent dimensions. (b) Two attention mechanisms guide learning by focusing on rules, or on the contexts in which they produce errors. (c) Knowing about these contexts inhibits executing the rule, without correcting it, and consequently leads to applying partial rules in different situations. The model is designed to capture both systematic and individual differences in a broad range of learning paradigms. We illustrate the model's explanatory scope by simulating several benchmarks, including the classic Six Problems, the 5-4 problem, and linear separability. Beyond the common approach of predicting average response probabilities, we also propose explanations for more recently studied phenomena that challenge existing learning accounts, regarding task instructions, individual differences in rule extrapolation in three different tasks, individual attention shifts to stimulus features during learning, and other phenomena. We discuss CAL's relation to different models, and its potential to measure the cognitive processes regarding attention, abstraction, error detection, and memorization from multiple psychological perspectives. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Concept neurons in the human medial temporal lobe flexibly represent abstract relations between concepts.

Concept neurons in the medial temporal lobe respond to semantic features of presented stimuli. Analyzing 61 concept neurons recorded from twelve patients who underwent surgery to treat epilepsy, we show that firing patterns of concept neurons encode relations between concepts during a picture comparison task. Thirty-three of these responded to non-preferred stimuli with a delayed but well-defined onset whenever the task required a comparison to a response-eliciting concept, but not otherwise. Supporting recent theories of working memory, concept neurons increased firing whenever attention was directed towards this concept and could be reactivated after complete activity silence. Population cross-correlations of pairs of concept neurons exhibited order-dependent asymmetric peaks specifically when their response-eliciting concepts were to be compared. Our data are consistent with synaptic mechanisms that support reinstatement of concepts and their relations after activity silence, flexibly induced through task-specific sequential activation. This way arbitrary contents of experience could become interconnected in both working and long-term memory.