Trends in Cognitive Sciences

More than incurious: the development of deliberate ignorance In an information-rich world the ability to choose not to know is an important cognitive tool. But what are the developmental origins of deliberate ignorance? We identify a selection of cognitive capacities and changes in children’s information ecology that make deliberate ignorance increasingly possible – and desirable – across development.

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Rapid decay of perceptual memory in dyslexia The basic mechanisms that underlie developmental dyslexia – a difficulty in acquiring reading expertise – are still debated. We propose that such difficulties should be understood within the broad framework of learning and skill acquisition. Behavioral and neural studies, as well as computational analyses, imply that acquiring expertise has atypical dynamics in dyslexia, largely due to reduced perceptual memory, which is manifested in faster decay of perceptual traces of both speech and non-speech stimuli. This faster behavioral decay is associated with faster decay of neural adaptation to stimulus regularities in perceptual cortices. We propose that these atypical dynamics lead to a slower accumulation of language statistics, manifested in reduced complexity of perceptual categories, slower acquisition of words, and – counterintuitively – larger relative difficulties as exposure to stimuli grows.

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Sensory reformatting for a working visual memory A core function of visual working memory (WM) is to sustain mental representations of recent visual inputs, thereby bridging moments of experience. This is thought to occur in part by recruiting early ‘sensory’ cortical regions, via flexible fronto-parietal mechanisms. The nature of visual cortex activity during WM has been elusive, but new evidence suggests that early WM representations can transform from a sensory-like code into a format that is shaped by task context and optimized for behavior. Here, we review evidence for transformations in visual cortical WM coding, the various forms they take, and their functional importance. Visual cortex may be an active workspace during WM, where flexible and ‘good enough’ WM representations serve to interface with perception and action.

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Online Now: Can only meat machines be conscious?

How do we see style? In a recent series of experiments, Boger and Firestone ask: How do we perceive style?’. Their findings suggest that style perception relies on basic perceptual processes involved in differentiating image content from its context. Their research highlights that we need to understand both content and style processing to fully understand perception.

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Dense longitudinal neuroimaging reveals individual brain change trajectories

Review by Sophia Vinci-Booher, Xueying Ren, Kendrick Kay, Chen Yu, Franco Pestilli, & James Booth

tinyurl.com/jhb5py5d

It's a privilege to be part of this new review in @cp-trendscognsci.bsky.social: Testing circuit-level theories of consciousness with modern neuroimaging and biophysical modeling 🧵

#eeg #consci #consciousness #neuroscience

www.cell.com/trends/cogni...

🚨Out now in @cp-trendscognsci.bsky.social 🚨

We explore the use of cognitive theories/models with real-world data for understanding mental health.

We review emerging studies and discuss challenges and opportunities of this approach.

With @yaelniv.bsky.social and @eriknook.bsky.social

Thread ⬇️

There is a lot of talk about LLMs revolutionizing education. But once you get into it, things are not that trivial.

Here, we summarize the questions that emerge when trying to implement AI Tutors nationwide.

Out now in @cp-trendscognsci.bsky.social

#edusky

authors.elsevier.com/a/1ltdo4sIRv...

Our recent review article "The Psychology of Virality" with @jayvanbavel.bsky.social
is on the front cover of this month's issue of
@cp-trendscognsci.bsky.social.

Can AI really help solve the loneliness epidemic? Advances in artificial intelligence offer an enticing solution to a global problem: perhaps interacting with large language models (LLMs) can help all…

Great piece in @cp-trendscognsci.bsky.social on why AI won't solve the loneliness epidemic:

"presenting AI as a scalable solution to the loneliness epidemic risks overlooking the structural and societal roots of the problem and may allow us to abdicate our responsibility as a society."

Online Now: A world of things and stuff

Dense longitudinal neuroimaging reveals individual brain change trajectories Longitudinal measurements of brain structure and function are critical for understanding how humans change over time. Traditional longitudinal approaches sample sparsely across large windows of time to estimate coarse, long-term brain changes. This review showcases insights from dense longitudinal neuroimaging (DLN), an emerging approach that samples densely across relatively short windows of time to precisely estimate individual trajectories of brain change. DLN measures multiple samples from individuals throughout critical periods of rapid change. It allows precise estimates of nonlinear trajectories to advance a mechanistic understanding of brain change. Novel findings from this approach are improving our understanding of human cognition, such as the role of the motor system in visual development and learning.

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Developing an AI-based General Personal Tutor for education The vision of a universal artificial intelligence (AI) tutor has remained elusive, despite decades of effort. Could large language models (LLMs) be the game-changer? We overview novel issues arising from developing a nationwide AI tutor. We highlight the practical questions that point to specific gaps in our scientific understanding of the learning process.

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Deliberating on the role of dopamine The role of dopamine in signalling reward prediction errors is well established, but its involvement in more complex decision-making processes is less clear. In recent work, Kocharian et al. demonstrate that dopamine also encodes imagined outcomes and decision confidence, revealing a richer, more nuanced role in learning and behaviour.

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Online Now: Pseudo-specificity, pseudo-modules, and pseudo-models in paranoia

Online Now: Primate neuroethology: a new synthesis

Cognitive modeling of real-world behavior for understanding mental health A core strength of computational psychiatry is its focus on theory-driven research, in which cognitive processes are precisely quantified using computational models that formalize specific theoretical mechanisms. However, the data used in these studies often come from traditional laboratory-based cognitive tasks, which have unclear ecological validity. In this review we propose that the same theoretical frameworks and computational models can be applied to real-world data such as experience sampling, passive data, and digital-behavior data (e.g., online activity such as on social media). In turn, modeling real-world data can benefit from a theory-driven computational approach to move from purely predictive to explanatory power. We illustrate these points using emerging studies and discuss the challenges and opportunities of using real-world data in computational psychiatry.

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Why were the textbooks wrong about brain plasticity? Schone and colleagues reveal surprising stability in the brain’s body map, challenging textbook notions of dramatic remapping. But why were the textbooks wrong? Because what was interpreted as plasticity was only half of the story. In fact, missing limb representations do persist, awaiting the right probe.

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Testing circuit-level theories of consciousness in humans Our understanding of the neural basis of consciousness is mostly restricted to large-scale brain activity patterns as measured by methods such as functional magnetic resonance imaging (fMRI) and magneto/electro-encephalography (M/EEG). In contrast, we lack even basic understanding of circuit-level mechanisms supporting consciousness – particularly in humans – despite the fundamental role that such mechanisms likely play in instantiating larger-scale brain activity patterns supporting conscious states and contents. Here, we review what progress has been made on circuit-level theories of consciousness (e.g., apical amplification theory, dendritic integration theory) and argue that such theories can be tested in humans using recently developed, state-of-the-art methods. Doing so will further facilitate translation of consciousness science into clinical settings and strengthen the bridge between circuit- and network-level theories of consciousness.

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Sleep and memory consolidation in insects Several cognitive functions of sleep, including a role in supporting memory consolidation, are conserved across the evolution of animal species. As outlined here, studies of insect behavior and neural circuits have identified key synaptic and circuit mechanisms through which sleep can influence long-term memories.

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Culture and in-group favoritism in social decision-making Although cultural differences in cognition and behavior are well-documented, collecting data from multiple cultural samples to explore relevant cognitive processes remains challenging. Rahal and Schulze Spüntrup address this by applying webcam-based eye-tracking to adults from 20 countries, revealing cultural variations in the cognitive processes underlying in-group favoritism during social decision-making.

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Confronting the connectivity crisis in human M/EEG research The cognitive neuroscience community using M/EEG has not converged on measures of task-related inter-regional brain connectivity that generalize across tasks and laboratories. We call for community-driven efforts to systematically test and validate connectivity metrics using shared datasets and protocols, aiming to establish robust, replicable frameworks for cognitive and clinical applications.

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Can AI really help solve the loneliness epidemic? Advances in artificial intelligence offer an enticing solution to a global problem: perhaps interacting with large language models (LLMs) can help alleviate loneliness. Although promising, evidence from cognitive neuroscience suggests that LLM interactions cannot satisfy psychological and physical needs for proximity. Addressing loneliness requires societal action, not simulating human relationships with artificial surrogates.

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How the insect brain keeps track of space Insects navigate by integrating a geocentric velocity vector, allowing them to track their position relative to a distant nest. Recent advances reveal in detail the key neural mechanisms supporting this behavior, offering new insight into how complex spatial cognition is implemented in brain circuits.

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Individual face recognition in wasps Paper wasp societies use behaviors like individual face recognition, configural face processing, social eavesdropping, and transitive inference to manage social relationships. Despite their evolutionary distance, wasps and vertebrates share similarities in their social recognition behavior, indicating that these behaviors can be implemented in miniature brains without a neocortex.

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Motor working memory Working memory (WM) is crucial for planning, reasoning, and learning, and is one of the most extensively studied topics in cognitive psychology and neuroscience. However, the concept of a WM subsystem for motor content – or 'motor working memory' (MWM) – is generally neglected, even though MWM likely plays an important role in everyday action. Here, we synthesize evidence that the brain both prospectively and retrospectively maintains motor content in WM and propose that MWM carries out multiple key computational functions in motor control and skill learning. A focused research program on MWM is overdue and will deepen our understanding of the links between cognition and action.

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Live questions about the mind’s eye We live much of our lives in our heads, detached from the here and now – as when we recollect the past, anticipate future possibilities, lose ourselves in a daydream, a novel, or our favourite corner of science [1]: ‘what sets us apart is…a life in the mind, the ability to imagine’ [2]. For most of us, sensory imagery, which allows us to experience the sensory properties of objects in their absence, is a central element of our imaginings [3]. The realisation that ~4% of people lack visual imagery, facilitated by a term with which to describe this, aphantasia [4], while an even higher proportion, with hyperphantasia, enjoy imagery rivalling the vividness of perception, has triggered a recent surge of research.

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The cognitive side of communication in social insects Social insects rely on multiple communication channels. These channels have traditionally been considered innate, eliciting stereotyped responses. However, recent research has shown that cognitive modulation occurs in communication contexts long assumed to be entirely genetically encoded, thus revealing a previously unrecognized cognitive plasticity in social insect communication.

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Pseudo-approaches lead to pseudo-explanations: reply to Corlett et al. Corlett et al. criticise a ‘social turn’ in delusions research according to which paranoia is a result of a dysfunction in social cognition [1]. Instead, they propose that, despite appearances, paranoia is solely the result of alterations to domain-general responses to uncertainty. We appreciate the effort to find a parsimonious explanation, and we agree that domain-general processes play an important role in understanding delusions. However, we reject the characterisation of previous work by us and others and question whether the dichotomies set up by Corlett et al.

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