Trends in Cognitive Sciences

Leveraging cognitive neuroscience for making and breaking real-world habits Habits are the behavioral output of two brain systems. A stimulus–response (S–R) system that encourages us to efficiently repeat well-practiced actions in familiar settings, and a goal-directed system...

The good news? If there’s more than one mechanism driving compulsive behaviour, there’s likely more than one way to intervene! We talk about this in our @cp-trendscognsci.bsky.social review @eikekofi.bsky.social @parnianrafei.bsky.social

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

Brain–computer interfaces as a causal probe for scientific inquiry Establishing causal relationships between neural activity and brain function requires experimental perturbations of neural activity. Many existing perturbation methods modify activity by directly applying external signals to the brain. We review an alternative approach where brain–computer interfaces (BCIs) leverage volitional control of neural activity to manipulate and causally perturb it. We highlight the potential of BCIs to manipulate neural activity in ways that are flexible, accurate, and adhere to intrinsic biophysical and network-level constraints to investigate the consequences of configuring neural population activity in specified ways. We discuss the advantages and disadvantages of using BCIs as a perturbation tool compared with other perturbation methods and how BCIs can expand the scope of questions that can be addressed about brain function.

Online Now: Brain–computer interfaces as a causal probe for scientific inquiry

Towards large language models with human-like episodic memory Cognitive neuroscience research has made tremendous progress over the past decade in addressing how episodic memory (EM; memory for unique past experiences) supports our ability to understand real-world events. Despite this progress, we still lack a computational modeling framework that is able to generate precise predictions regarding how EM will be used when processing high-dimensional naturalistic stimuli. Recent work in machine learning that augments large language models (LLMs) with external memory could potentially accomplish this, but current popular approaches are misaligned with human memory in various ways. This review surveys these differences, suggests criteria for benchmark tasks to promote alignment with human EM, and ends with potential methods to evaluate predictions from memory-augmented models using neuroimaging techniques.

Online Now: Towards large language models with human-like episodic memory

Reward is enough for social learning Adaptive behaviour relies on selective social learning, yet the mechanisms underlying this capacity remain debated. A new account demonstrates that key strategies can emerge through reward-based learning of social features, explaining the widely observed flexibility of social learning and illuminating the cognitive basis of cultural evolution.

Online Now: Reward is enough for social learning

Relying on PRIME young adults limits cognitive science

Science & Society by Patricia Lockwood (@thepsychologist) & Wouter van den Bos

Open Access: tinyurl.com/4c353uvt

What will society think about AI consciousness? Lessons from the animal case

Science & Society by Lucius Caviola, Jeff Sebo, & Jonathan Birch, tinyurl.com/5desw2rp

Similar types of information (e.g., negative, high-arousal, or moral information) tend to spread both online via social media and offline via gossip.

Check out our new paper on the “Psychology of Virality” in TiCS via @steverathje.bsky.social

📣 New paper in @cp-trendscognsci.bsky.social by CSL-Lab's @mh-christiansen.bsky.social and @yngwienielsen.bsky.social reappraising what structural priming tells us about the representation of language: it's about context — not grammar.

Free download until Aug 8: authors.elsevier.com/a/1lIFK4sIRv...

The psychology of virality Why do some ideas spread widely, while others fail to catch on? Here, we review the psychology of information spread, or the psychology of ‘virality’. Similar types of information tend to spread in many contexts, both online and offline. This is likely because similar psychological processes drive information spread across contexts. We explain how these psychological processes interact with structural features of information environments, including norms, networks, and incentive structures. Surprisingly, widely shared content is often not widely liked, a phenomenon called ‘the paradox of virality’. We discuss the strengths and limitations of the information-as-virus metaphor. We also discuss future directions for the field, such as leveraging recent advances in artificial intelligence (AI) to better understand how information spreads across cultures and contexts.

Online Now: The psychology of virality

Pharmacological enhancement of fear extinction Pharmacological agents theorized to modulate fear extinction could enhance treatments for anxiety and trauma-related disorders, but fear conditioning and treatment studies testing these agents often yield null or conflicting results. We review principles of extinction learning relevant to the design of studies that test pharmacological enhancements of extinction. We then critically review the methodologies of existing studies for three pharmacological agents [d-cycloserine (DCS), glucocorticoids (GCs), and L-DOPA] with respect to key learning principles. While each agent has promising support in rodent models, many human studies are not designed to adequately detect an agent’s effects on extinction learning. We provide specific recommendations, informed by these learning principles, for future study designs that may clarify whether, how, and under what conditions agents impact extinction.

Online Now: Pharmacological enhancement of fear extinction

Attentional sampling resolves competition along the visual hierarchy Navigating the environment involves engaging with multiple objects, each activating specific neuronal populations. When objects appear together, these populations compete. Classical attention theories suggest that selection involves biasing one population over another. Recent research shows that perception fluctuates over time at ~8 Hz for single-object attention and 4 Hz for two-object attention, possibly because of the division of the 8-Hz rhythm between competing objects. This opinion surveys these fluctuations, coined ‘attentional sampling,’ across the visual hierarchy. We propose that sampling is a selection mechanism that negotiates neuronal competition. It manifests as early as eye channels and extends to complex features higher in the visual hierarchy. We discuss the cognitive significance of this mechanism and its potential neuronal implementation.

Online Now: Attentional sampling resolves competition along the visual hierarchy

Looking deeper into the algorithms underlying human planning Humans possess a remarkable ability to form sophisticated multi-step plans even in complex environments. In this review article, we consider efforts that attempt to characterize the mechanisms underlying human planning using a computational framework, primarily focusing on methods that search a tree of possible solutions. These studies range from experimental probes for heuristics that people employ while thinking ahead to normative models for reducing the computational costs of planning. Additionally, we examine the recent successes of artificial intelligence in the domain of planning and how these innovations can be applied to better understand human sequential decision-making. As examples, we highlight this approach in two tasks that require planning many steps into the future, namely 4-in-a-row and chess.

Online Now: Looking deeper into the algorithms underlying human planning

The unfathomable richness of seeing Many hold that visual experience is sparse and its richness illusory, relying on high-level summaries rather than detailed content. However, we argue here that seeing is more than this – it is unfathomably rich. We distinguish three levels of visual phenomenology: high level object and scene categorizations; mid-level feature groupings; and a fundamental spatial field composed of spots and their spatial relations. Crucially, we argue that seeing objects requires seeing the groupings that compose them, and that seeing groupings requires seeing the spatial field that grounds them. Even the most basic feeling of spatial extendedness implies rich phenomenal structure. It follows that much of what we see cannot be used, reported, or remembered. And yet we see it.

Online Now: The unfathomable richness of seeing

And yet, the hippocampus codes conjunctively Quian Quiroga’s recent letter in TiCS [1] raises a healthy debate about how the human hippocampus encodes episodic experience. We welcome the discussion and, while we respectfully disagree on several issues, we hope that it will stimulate experiments clarifying how the hippocampus encodes episodic memory. Here, we address four issues about hippocampal coding and argue that: (i) single-trial reinstatement is a statistically robust, widely used measure; (ii) episode-specific neurons (ESNs) cannot be explained as reactivated concept cells; (iii) repeated-story paradigms are ill-suited to test one-shot conjunctive coding; and (iv) concept cells alone cannot disambiguate similar events.

Online Now: And yet, the hippocampus codes conjunctively

Structure uncovered: understanding temporal variability in perceptual decision-making Studies of perceptual decision-making typically present the same stimulus repeatedly over the course of an experimental session but ignore the order of these observations, assuming unrealistic stability of decision strategies over trials. However, even ‘stable,’ ‘steady-state,’ or ‘expert’ decision-making behavior features significant trial-to-trial variability that is richly structured in time. Structured trial-to-trial variability of various forms can be uncovered using latent variable models such as hidden Markov models and autoregressive models, revealing how unobservable internal states change over time. Capturing such temporal structure can avoid confounds in cognitive models, provide insights into inter- and intra-individual variability, and bridge the gap between neural and cognitive mechanisms of variability in perceptual decision-making.

Online Now: Structure uncovered: understanding temporal variability in perceptual decision-making

Relying on PRIME young adults limits cognitive science Cognitive science has made remarkable strides in understanding cognition and behaviour. However, a critical issue persists. Most studies focus on PRIME populations – young adults who are productive, researchable, independent, mobile, and educated. While convenient, the overreliance on them has profound implications for generalising research findings and addressing global challenges.

Online Now: Relying on PRIME young adults limits cognitive science

A neurocomputational account of motivated seeing Do goals, beliefs, and desires affect visual experience? This question has long been controversial in cognitive science. There exists extensive literature documenting motivational effects on perceptual reports, but these findings could reflect biases in what people report seeing rather than what they see. Here, we propose that examining the underlying neurocomputational processes can provide new perspectives on this longstanding debate. We review evidence suggesting that motivation biases both perception and action, but does so via distinct neural systems: amygdala and locus coeruleus (LC)-norepinephrine (NE) activity enhances sensory representations for desirable stimuli, while striatal dopamine biases action selection toward goal-congruent actions. The neurocomputational approach provides a framework to advance a mechanistic understanding of motivated seeing and how these biases are shaped by context.

Online Now: A neurocomputational account of motivated seeing

Repairing cognitive distortions in political divides Political animosity is on the rise, undermining both well-being and collective responses to global challenges. Interventions to decrease animosity and division often fail to yield lasting, generalized benefits. Drawing on cognitive behavioral therapy (CBT) and new empirical evidence, we argue that entrenched political conflicts are laden with cognitive distortions similar to those observed in clinical contexts. We propose that, by adapting CBT insights to political settings, interventionists can complement and enhance current depolarizing efforts. We provide suggestions for how future efforts should equip individuals to recognize and correct biased thinking outside of the laboratory, offering a pathway toward durably mitigating division and hostility.

Online Now: Repairing cognitive distortions in political divides

Spared spatial imagery solves the puzzle of aphantasia The puzzle of aphantasia concerns how individuals reporting no visual imagery perform more-or-less normally on tasks presumed to depend on it [1]. In his splendid recent review in TiCS, Zeman [2] canvasses four ‘cognitive explanations’: (i) differences in description; (ii) ‘faulty introspection’; (iii) “unconscious or ‘sub-personal’ imagery”; and (iv) total lack of imagery. Difficulties beset all four. To make progress, we must recognize that imagery is a complex and multidimensional capacity and that aphantasia commonly reflects partial imagery loss with selective sparing.

Online Now: Spared spatial imagery solves the puzzle of aphantasia

Model-based animal cognition slips through the sequence bottleneck In a recent article in TiCS, Lind and Jon-And [1] argued that the sequence memory of animals constitutes a cognitive bottleneck, the ‘sequence bottleneck’, and that mental simulations require faithful representation of sequential information. They therefore concluded that animals cannot perform mental simulations, and that behavioral and neurobiological studies suggesting otherwise are best interpreted as results of associative learning. Through examples of predictive maps, cognitive control, and active sleep, we illustrate the overwhelming evidence that mammals and birds make model-based simulations, which suggests the sequence bottleneck to be more limited in scope than proposed by Lind and Jon-And [1].

Online Now: Model-based animal cognition slips through the sequence bottleneck

Decoupling speech processing from time Accurate processing of speech requires that listeners map temporally unfolding input to words. A long-held set of principles describes this process: lexical items are activated immediately and incrementally as speech arrives, perceptual and lexical representations rapidly decay to make room for new information; and lexical entries are temporally structured. In this framework; speech processing is tightly coupled to the temporally unfolding input. However, recent work challenges this: low-level auditory and higher-level lexical representations do not decay and are instead retained over long durations, speech perception may require encapsulated memory buffers, lexical representations are not strictly temporally structured, and listeners can substantially delay lexical access in some circumstances. These findings suggest that current theories and models of word recognition need to be reconceptualized.

Online Now: Decoupling speech processing from time

Varieties of aphantasia Close your eyes and visualize an apple. For most of us, this yields an experience of a faint image of an apple. However, for some people, there is no such experience. This is aphantasia [1]. I have introduced aphantasia with the help of introspective criteria: close your eyes, try to visualize, and tell me about your experience. Indeed, this is the way in which aphantasics are identified: if you fill out a questionnaire (typically, but not exclusively, the Vividness of Visual Imagery Questionnaire), and you score below a certain value, you are an aphantasic.

Online Now: Varieties of aphantasia

What will society think about AI consciousness? Lessons from the animal case How will society respond to the idea that artificial intelligence (AI) could be conscious? Drawing on lessons from perceptions of animal consciousness, we highlight psychological, social, and economic factors that shape perceptions of AI consciousness. These insights can inform emerging debates about AI moral status, ethical treatment, and future policy.

Online Now: What will society think about AI consciousness? Lessons from the animal case

Advancing a temporal science of behavior All events unfold over time, and the temporal parameters of events matter for cognition. Yet it is common for scholars across disciplines to summarize events using atemporal statistics. Here, we underscore the urgency of illuminating the temporal structure of behavior streams and testing implications for learning. We review evidence on the importance of timing for cognition, drawing on our expertise in developmental science. We provide a framework for the quantification of single behavior streams, coordination between multiple streams, and the organization of streams across extended and multiple timescales. We highlight opportunities for methodological, analytic, and theoretical innovation to advance a temporal science of behavior. Parameterizing the temporal structure of events will accelerate scientific progress on human, animal, and artificial learning systems.

Online Now: Advancing a temporal science of behavior

Constructing language: a framework for explaining acquisition Explaining how children build a language system is a central goal of research in language acquisition, with broad implications for language evolution, adult language processing, and artificial intelligence (AI). Here, we propose a constructivist framework for future theory-building in language acquisition. We describe four components of constructivism, drawing on wide-ranging evidence to argue that theories based on these components will be well suited to explaining developmental change. We show how adopting a constructivist framework both provides plausible answers to old questions (e.g., how children build linguistic representations from their input) and generates new questions (e.g., how children adapt to the affordances provided by different cultures and languages).

Online Now: Constructing language: a framework for explaining acquisition

Context, not grammar, is key to structural priming Structural priming – a change in processing after repeated exposure to a syntactic structure – has been put forward as evidence for the psychological reality of constituent structures derived from grammar. However, converging evidence from memory research, large language models (LLMs), and structural priming itself challenges the validity of mapping structural representations onto grammatical constituents and demonstrates structural priming in the absence of such structure. Instead of autonomous representations specified by grammar, we propose that contextual representations emerging from multiple constraints (e.g., words, prosody, gesture) underlie structural priming. This perspective accounts for existing anomalous findings, is supported by the strong dependence on lexical cues observed in structural priming, and suggests that future research should prioritize studying linguistic representations in more naturalistic contexts.

Online Now: Context, not grammar, is key to structural priming

How rethinking difficulties can shape important life outcomes Difficulties are a common part of life, ranging from daily challenges to chronic adversity. While difficulties can undermine well-being, they can also promote growth and resilience. What determines whether difficulty harms or helps? A growing body of research points to the role of difficulty beliefs, that is, general beliefs about whether dealing with difficulty is harmful or beneficial. Prior work has examined these beliefs across domains such as task-level demand, life situation-level stress, and identity-level challenges, but these literatures remain disconnected. In this review, we synthesize these research streams, highlighting their shared principles. We propose a unifying mechanistic model and show how an integrative perspective can clarify how difficulty beliefs shape motivation, coping, and long-term outcomes across contexts.

Online Now: How rethinking difficulties can shape important life outcomes

Disagreement drives metacognitive development Metacognition improves significantly over childhood, but the mechanisms underlying this development are poorly understood. We first review recent research demonstrating that disagreement prompts competent responses by young children across several metacognitive domains (confidence monitoring, information search, and source monitoring). We then propose a mechanistic model of how disagreement facilitates metacognition. We localize one main source of children’s metacognitive limitations in their still-developing capacities to reason about alternative possibilities, which manifest in an overly narrow focus on one hypothesis. Disagreement increases the child’s likelihood of representing alternative hypotheses, thereby promoting improved metacognitive reasoning. The broader proposal is that, through repeated experiences of disagreement, children become better at representing alternative possibilities even when reasoning on their own, leading to metacognitive development.

Online Now: Disagreement drives metacognitive development

The value of ecologically irrelevant animal cognition research

Opinion by Scarlett Howard
tinyurl.com/37aedmfx

GenAI and the psychology of work

Opinion by Erik Hermann, Stefano Puntoni, & Carey Morewedge
tinyurl.com/uzj7pnup