The interaction-dominant approach to perception and action, originally formulated in the mid-1990s, has matured and gained remarkable momentum as an entailment of the dynamical hypotheses proposed at that time. This framework seeks to explain the fluid and intricate interplay of causality spanning the entire organism by integrating high-dimensional details with low-dimensional constraints across various scales of behavior. Both Chemero (2024) and Wallot et al. (2024) have skillfully explored the theoretical implications and methodological challenges this perspective introduces. We echo Chemero's (2024) and Wallot et al.'s (2024) focus on multifractality, while also underscoring new efforts to model the synergetic relationships and cascading dynamics inherent in this interaction-dominant approach.

The 1998 article by van Gelder proposed a Dynamical Hypothesis (DH) in cognitive science consisting of Nature (cognitive agents are dynamical systems) and Knowledge (cognitive agents should be understood dynamically) hypotheses in contrast to the Computational Hypothesis (CH) that cognitive agents are computers. My commentary focuses on the contributions of Paxton and Necaise et al. in interpersonal motor coordination and radicalization across social media. I do not think that either contribution supports the Nature hypothesis but does conform with the Knowledge hypothesis. I conclude by describing cognitive agents as living systems (or nonliving systems that mimic aspects of living systems) that can be alternately viewed to support the DH or CH or both at the same time.

Engraved portable objects from Upper Palaeolithic and earlier sites are argued to be cognitive tools designed to store information for the purposes of calculation, record-keeping, or communication. This paper reviews the surprisingly long intellectual history of comparisons between these ancient objects and message sticks: marked graphic devices traditionally used for long-distance communication in Indigenous Australia. I argue that, while such comparisons have often been misguided, more cautious applications of ethnographic analogy may yield useful insights. A systematic analysis of historical observations together with more recent fieldwork, indicate that Australian message sticks are primarily tools of social cognition, as opposed to cognition tout court, and rely on orality and other context to become meaningful. Further, the practice of message stick communication may help clarify ongoing problems in the interpretation of Upper Palaeolithic objects including their possible role in aggregation activities, the distinction between decoration and notation, and the interplay between graphic sequences and speech.

An enigma for human languages is that children learn to understand words in their mother tongue extremely fast. The cognitive sciences have not been able to fully understand the mechanisms behind this highly efficient learning process. In order to provide at least a partial answer to this problem, I have developed a cognitive model of the semantics of natural language in terms of conceptual spaces. I present a background to conceptual spaces and provide a brief summary of their main features, in particular how it handles learning of concepts. I then apply the model to give a geometric account of the semantics of different word classes. In particular, I propose a "single-domain hypotheses" for the semantics of all word classes except nouns. These hypotheses provide a partial answer to the enigma of how words are learned. Next, a dynamic cognitive model of events is introduced that replaces and extends the function of thematic roles. I apply it to analyze the meanings of different kinds of verbs. I argue that the model also explains some aspects of syntactic structure. In particular, I propose that a sentence typically refers to an event. Some further applications of conceptual spaces are briefly presented.

Throughout the long history of Classic Maya hieroglyphs, a logosyllabic writing system used from the late first millennium BCE through the mid-second millennium CE in southern Mesoamerica, the most commonly recorded phonetic value was the syllable u (/ʔu/). With over a dozen different u hieroglyphs, Classic Maya scribes had more options for recording /ʔu/ than any other syllable or logograph. Cognitive approaches to writing systems typically attribute graphemic variation (i.e., alternation between signs with equivalent linguistic value) to semantic differences like animacy or to non-linguistic factors like identity. Distribution of Classic Maya u hieroglyphs, however, suggests that morphosyntactic context influenced which grapheme scribes wrote and when. This case suggests that scribal knowledge of Classic Maya hieroglyphs included ideas about writing's relationship to language. It also highlights the cognitive relevance of morphosyntax for a writing system's users as they differentiate among graphic signs with identical linguistic denotation.

Retrieval practice-the process of actively calling information to mind rather than passively studying materials-has been proven to be a highly effective learning strategy. However, only recently, researchers have started to examine differences between learners in terms of the optimal conditions of retrieval practice in applied educational settings. In this study (N = 118), we focus on learners with dyslexia. We compare their performance to the performance of typical learners in an adaptive retrieval practice task using both typing-based and speech-based response conditions. We find that typical learners outperform learners with dyslexia when they are asked to respond by typing, but that this difference disappears when learners respond by speech. Using a mathematical model to decompose response times, we demonstrate that this typing-specific disadvantage in learners with dyslexia is mainly a consequence of processing delays, rather than poorer memory performance. These findings contribute to a better understanding of the mechanisms underlying declarative learning in dyslexia, and they can be used to tailor educational technology toward the needs of neurodiverse learners.

This paper explores the role of measurement as a cognitive technology across human history, emphasizing the coexistence of formal and informal measurement systems. While standardized systems dominate contemporary culture and are well documented across large-scale societies of the past, this manuscript highlights the less explored domain of informal measurement practices that have been integral to daily life from the past to the present. Through the examination of body-based measurement systems and proportional heuristics, we demonstrate how these informal strategies were not merely precursors to formal standards but essential adaptive tools for solving everyday problems. Often, these informal solutions come with practical advantages. This manuscript calls for a broader recognition of their significance in cultural and technological evolution.

Studies of homesigns have shed light on the human capacity for language and on the challenging problem of language acquisition. The study of homesign has evolved from a perspective grounded in gesture studies and child development to include sign language linguistics and the role of homesigns in language emergence at the community level. One overarching finding is that homesigns more closely resemble sign languages used by linguistic communities than they resemble the gestures produced by hearing people along with spoken language. Homesigns may not exhibit all of the linguistic properties of community languages, but the properties they do exhibit are language properties, and for the people who use them, homesigns are their language. Further, the linguistic structures in homesigns are innovated by the deaf people who use them and are imperfectly learned by their hearing communication partners. I close with a call to action: We cannot celebrate discoveries about the mind made possible by studies of homesigns and emerging languages while ignoring the pervasiveness of language deprivation among deaf people, and the relative lack of deaf participation in science, even in studies of sign languages. While the scientific community learns much from studying homesigns and sign languages, we also have a responsibility to work toward ensuring that every deaf person has access to language, communication, and education.

Standard models of lexical production assume that speakers access representations of meaning, grammar, and different aspects of sound in a roughly sequential manner (whether or not they admit cascading or interactivity). In contrast, we review evidence for a parallel activation model in which these representations are accessed in parallel. According to this account, word learning involves the binding of the meaning, grammar, and sound of a word into a single representation. This representation is then activated as a whole during production, and so all linguistic components are available simultaneously. We then note that language comprehension involves extensive use of prediction and argue that comprehenders use production mechanisms to determine (roughly) what they would say next if they were speaking. So far, theories of prediction-by-production have assumed sequential lexical production. We therefore reinterpret such evidence in terms of parallel lexical production.

How do teachers' gestures influence students' learning? This article reviews research investigating the role of gestures in communication, focusing on teachers' communication with their students, primarily in mathematics and science instruction. We first briefly consider gesture's role in communication more generally as a backdrop for considering teaching as a special context for communication. We then describe teachers' spontaneous gesturing in teaching contexts, and we consider how teachers' spontaneous gestures might influence students' learning. We then consider experimental studies that provide causal support for the effects of teachers' gestures on students' learning. We conclude by discussing future directions and implications for educational practice.

Cognitive models that represent individuals provide many benefits for understanding the full range of human behavior. One way in which individual differences emerge is through differences in knowledge. In dynamic situations, where decisions are made from experience, models built upon a theory of experiential choice (instance-based learning theory; IBLT) can provide accurate predictions of individual human learning and adaptivity to changing environments. Here, we demonstrate how an instance-based learning (IBL) cognitive model, implemented in a cognitive architecture (Adaptive Control of Thought-Rational), can be used to model an individual's decisions in a cybersecurity defense task, accounting for both population average and individual variances. The same IBL model structure with identical architectural parameters generates the full range of human behavior through stochastic memory retrieval processes operating over and contributing to unique experiences. Recurrence quantification analyses allow us to look beyond average behavior between and within individuals to sequential patterns of trial-to-trial behavior. We show how model-tracing and knowledge-tracing techniques can be used to align the model to an individual in real time to drive adaptive and personalized signaling algorithms for a cybersecurity defense system. We also present a method for introspecting into the cognitive model to gain further insight into the cognitive salience of features factored into individual decisions. The combination of techniques provides a blueprint for personalized modeling of individuals. We discuss the results and implications of this adaptive and personalized method for cybersecurity defense and more generally for intelligent artifacts tailored to individual differences in domains such as human-machine teaming.

This paper attempts to reconcile the claims that the mind is both flat (Chater, 2018) and highly rational (Oaksford & Chater, 2020). According to the flat mind hypothesis, the mind is a mass of inconsistent and contradictory fragments of experience. However, standard accounts of rationality from formal epistemology argue that to be rational, our beliefs must be consistent, and we must believe all the logical consequences of our beliefs. A social account of rationality is developed based on Brandom's (1994) logical expressivism, in which respecting the norms of logic and probability theory is still central but where these standards apply to our public commitments in social dialogical contexts rather than to our individual belief systems (Skovgaard-Olsen, 2017). According to this account, even if someone's individual beliefs are inconsistent, they cannot be condemned as irrational if they acknowledge the inconsistency and seek to resolve it. It is shown how this approach interacts with people's fragmented and shallow world knowledge, and its social distribution yields some counterintuitive consequences, such as it sometimes being rational individually not seeking to resolve contradictions. Other consequences of this social expressivist approach are considered, including for dual process theories of reasoning, our view of beliefs, the status of logic, and Fodor's (1983) view of central systems. It is concluded that people can have flat minds and yet be highly rational.

Ancient Roman "technical memory" is not (as much of the modern specialist literature would have it) a generative technology of association. Rather it is (as a literal reading of the texts would suggest) a specialized tool for precise serial recall. Modern experimental evidence both confirms the fitness for the purpose of the technique and shows why that purpose is not trivial, as some have suggested. While the mechanism(s) by which the technique operates are not fully understood, a review of the current literature suggests that it would have had the advantage over other mnemonic techniques by virtue of recruiting a variety of cognitive capacities. These likely include spatial/navigational mechanisms and possibly visual/imagery-based ones as well. Finally, small differences between the method as recorded in the ancient texts and similar methods that have been the subject of laboratory experiments are used to suggest possible directions for further experimentation.

Past research suggests that Working Memory plays a role in determining relative clause attachment bias. Disambiguation preferences may further depend on Processing Speed and explicit memory demands in linguistic tasks. Given that Working Memory and Processing Speed decline with age, older adults offer a way of investigating the factors underlying disambiguation preferences. Additionally, older adults might be subject to more severe similarity-based memory interference given their larger vocabularies and slower lexical access. Nevertheless, memory interference and sentence disambiguation have not been combined in studies on older adults before. We used a self-paced reading paradigm under memory load interference conditions. Older (n = 30) and Younger (n = 35) readers took part in the study online; reading times were recorded and measures of comprehension accuracy and load recall were collected. This setup allowed for the implicit measurement of attachment biases and memory interference effects interactively. Results show that similarity-based interference affected both age groups equally, but was more pronounced in NP2-biased structures, which took participants generally longer to read. Attachment preferences did not differ by group and were unaffected by Working Memory span. However, accuracy on recall prompts was predicted by Working Memory span in both groups. Findings of greater interference in syntactically dispreferred structures support unified processing models where parsing constraints naturally interact. The lack of age differences on our measures further aligns with research finding age-invariant implicit language processing.

Debates surrounding the origin of recovered memories of child abuse have traditionally focused on two conflicting arguments, namely that these memories are either false memories or instances of repressed memories (i.e., reflecting the idea that people can unconsciously block traumatic autobiographical experiences and eventually regain access). While scientific evidence for the first is clearly established, the second is the subject of a controversy in the academic, clinical, and legal fields. This controversy rages on today. In this introductory article to our topic "Beyond Repressed Memory: Current Alternative Solutions to the Controversy," we present alternative and more parsimonious explanations for repressed memories that we sorted into three categories: cognitive, motivational, and biological factors. Our aim is to provide a timely overview to help clinical and legal professionals, academics, and the general public to move beyond the idea that traumatic memories can be unconsciously repressed.

Our hands are always with us and are used for communication all over the world. When children do not have an established language model to learn from, they use their hands to gesture, and these gestures take on the forms of language. In this role, the hands reveal the fundamental properties of the mind that give shape to language. When children do learn an established language, they again use their hands to gesture. These gestures do not look like language but form an integrated system with language. In this role, the hands can convey ideas not found in the language they accompany. In both contexts, gesture provides a clear view of the mind hidden in our hands.

About 30 years ago, the Dynamical Hypothesis instigated a variety of insights and transformations in cognitive science. One of them was the simple observation that, quite unlike trial-based tasks in a laboratory, natural ecologically valid behaviors almost never have context-free starting points. Instead, they produce lengthy time series data that can be recorded with dense-sampling measures, such as heartrate, eye movements, EEG, etc. That emphasis on studying the temporal dynamics of extended behaviors may have been the trigger that led to a rethinking of what a "representation" is, and then of what a "cognitive agent" is. This most recent and perhaps most revolutionary transformation is the idea that a cognitive agent need not be a singular physiological organism. Perhaps a group of organisms, such as several people working on a joint task, can temporarily function as one cognitive agent - at least while they're working adaptively and successfully.

This is a commentary for a special issue on predictive processing and rational constructivist models of development. Mainly I use the opportunity to ask a bunch of questions about what these theoretical frameworks show us (and what they do not) and mostly where the open questions still are. To get meta for a moment, I thought these questions were the best way to maximize the value of my commentary: They have the highest probability of leading to the most uncertainty reduction for our field in the long term. Please read in that spirit.

Languages are neither designed in classrooms nor drawn from dictionaries-they are products of human minds and human interactions. However, it is challenging to understand how structure grows in these circumstances because generations of use and transmission shape and reshape the structure of the languages themselves. Laboratory studies on language emergence investigate the origins of language structure by requiring participants, prevented from using their own natural language(s), to create a novel communication system and then transmit it to others. Because the participants in these lab studies are already speakers of a language, it is easy to question the relevance of lab-based findings to the creation of natural language systems. Here, we take the findings from a lab-based language emergence paradigm and test whether the same pattern is also found in a new natural language: Nicaraguan Sign Language. We find evidence that signers of Nicaraguan Sign Language may show the same biases seen in lab-based language emergence studies: (1) they appear to condition word order based on the semantic dimension of intensionality and extensionality, and (2) they adjust this conditioning to satisfy language-internal order constraints. Our study adds to the small, but growing literature testing the relevance of lab-based studies to natural language birth, and provides convincing evidence that the biases seen in the lab play a role in shaping a brand new language.

It is widely believed that play and curiosity are key ingredients as children develop models of the world. There is also an emerging consensus that children are Bayesian learners who combine their structured prior beliefs with estimations of the likelihood of new evidence to infer the most probable model of the world. An influential school of thought within developmental psychology, rational constructivism, combines these two ideas to propose that children learn intuitive theories of how the world works in part by engaging in play activities that allow them to gather new information for testing their theories. There are still, however, at least two pieces missing from rational constructivist theories of development. First, rational constructivism has so far devoted little attention to explaining why children's preferred form of learning, play, feels so fun, enjoyable, and rewarding. Rational constructivism may suggest that children are curious and like to play because reducing uncertainty and learning better theories of the causal workings of the world is enjoyable. What remains unclear, however, is why reducing uncertainty in play is interesting, fun, and joyful, while doing so in other forms of learning can be frustrating or boring. Second, rational constructivism may have overlooked how children, during play, will take control of and manipulate their environment, sometimes in an effort to create ideal niches for surprise-extraction, sometimes for developing strategies for making the world fit with their predictions. These missing elements from rational constructivism can be provided by understanding the contribution of play to development in terms of predictive processing, an influential framework in cognitive neuroscience that models many of the brain's cognitive functions as processes of model-based, probabilistic prediction.