Modeling the Predictive Social Mind Trends Cogn. Sci. (IF 15.402) Pub Date : 2018-01-18 Diana I. Tamir, Mark A. Thornton
The social mind is tailored to the problem of predicting the mental states and actions of other people. However, social cognition researchers have only scratched the surface of the predictive social mind. We discuss here a new framework for explaining how people organize social knowledge and use it for social prediction. Specifically, we propose a multilayered framework of social cognition in which two hidden layers – the mental states and traits of others – support predictions about the observable layer – the actions of others. A parsimonious set of psychological dimensions structures each layer, and proximity within and across layers guides social prediction. This simple framework formalizes longstanding intuitions from social cognition, and in doing so offers a generative model for deriving new hypotheses about predictive social cognition.
How Primate Brains Vary and Evolve Trends Cogn. Sci. (IF 15.402) Pub Date : 2018-01-18 Aida Gómez-Robles
Studies of brain evolution tend to focus on differences across species rather than on variation within species. A new study measures and compares intraspecific variation in macaque and human brain anatomy to explore the effect that short-term diversity has on long-term evolution.
Nature of Emotion Categories: Comment on Cowen and Keltner Trends Cogn. Sci. (IF 15.402) Pub Date : 2018-01-16 Lisa Feldman Barrett, Zulqarnain Khan, Jennifer Dy, Dana Brooks
Cowen and Keltner (2017) published the latest installment in a longstanding debate about whether measures of emotion organize themselves into categories or array themselves more continuously along affective dimensions. We discuss several notable features of the study and suggest future studies should consider asking questions more directly about physical and psychological variation within emotion categories as well as similarities between categories.
Memory as Perception of the Past: Compressed Time inMind and Brain Trends Cogn. Sci. (IF 15.402) Pub Date : 2018-01-16 Marc W. Howard
In the visual system retinal space is compressed such that acuity decreases further from the fovea. Different forms of memory may rely on a compressed representation of time, manifested as decreased accuracy for events that happened further in the past. Neurophysiologically, “time cells” show receptive fields in time. Analogous to the compression of visual space, time cells show less acuity for events further in the past. Behavioral evidence suggests memory can be accessed by scanning a compressed temporal representation, analogous to visual search. This suggests a common computational language for visual attention and memory retrieval. In this view, time functions like a scaffolding that organizes memories in much the same way that retinal space functions like a scaffolding for visual perception.
Beyond Functional Connectivity: Investigating Networks of Multivariate Representations Trends Cogn. Sci. (IF 15.402) Pub Date : 2018-01-02 Stefano Anzellotti, Marc N. Coutanche
For over two decades, interactions between brain regions have been measured in humans by asking how the univariate responses in different regions co-vary (‘Functional Connectivity’). Thousands of Functional Connectivity studies have been published investigating the healthy brain and how it is affected by neural disorders. The advent of multivariate fMRI analyses showed that patterns of responses within regions encode information that is lost by averaging. Despite this, connectivity methods predominantly continue to focus on univariate responses. In this review, we discuss the recent emergence of multivariate and nonlinear methods for studying interactions between brain regions. These new developments bring sensitivity to fluctuations in multivariate information, and offer the possibility to ask not only whether brain regions interact, but how they do so.
Individual Differences in Language Acquisition and Processing Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-12-23 Evan Kidd, Seamus Donnelly, Morten H. Christiansen
Humans differ in innumerable ways, with considerable variation observable at every level of description, from the molecular to the social. Traditionally, linguistic and psycholinguistic theory has downplayed the possibility of meaningful differences in language across individuals. However, it is becoming increasingly evident that there is significant variation among speakers at any age as well as across the lifespan. Here, we review recent research in psycholinguistics, and argue that a focus on individual differences (IDs) provides a crucial source of evidence that bears strongly upon core issues in theories of the acquisition and processing of language; specifically, the role of experience in language acquisition, processing, and attainment, and the architecture of the language system.
The Anatomy of Friendship Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-12-19 R.I.M. Dunbar
Friendship is the single most important factor influencing our health, well-being, and happiness. Creating and maintaining friendships is, however, extremely costly, in terms of both the time that has to be invested and the cognitive mechanisms that underpin them. Nonetheless, personal social networks exhibit many constancies, notably in their size and their hierarchical structuring. Understanding the processes that give rise to these patterns and their evolutionary origins requires a multidisciplinary approach that combines social and neuropsychology as well as evolutionary biology.
Forecasting Faces in the Cortex: Comment on ‘High-Level Prediction Signals in a Low-Level Area of the Macaque Face-Processing Hierarchy’, by Schwiedrzik and Freiwald, Neuron (2017) Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-12-18 Lucy S. Petro, Lars Muckli
Although theories of predictive coding in the brain abound, we lack key pieces of neuronal data to support these theories. Recently, Schwiedrzik and Freiwald found neurophysiological evidence for predictive codes throughout the face-processing hierarchy in macaque cortex. We highlight how these data enhance our knowledge of cortical information processing, and the impact of this more broadly.
Are We Face Experts? Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-12-15 Andrew W. Young, A. Mike Burton
According to a widely used theoretical perspective, our everyday experiences lead us to become natural experts at perceiving and recognising human faces. However, there has been considerable debate about this view. We discuss criteria for expertise and show how the debate over face expertise has often missed key points concerning the role and nature of face familiarity. For identity recognition, most of us show only limited expertise with unfamiliar faces. Carefully evaluating the senses in which it is appropriate or inappropriate to assert that we are face experts leads to the conclusion that we are, in effect, familiar face experts.
Negotiating the Traffic: Can Cognitive Science Help Make Autonomous Vehicles a Reality? Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-12-14 Nick Chater, Jennifer Misyak, Derrick Watson, Nathan Griffiths, Alex Mouzakitis
To drive safely among human drivers, cyclists and pedestrians, autonomous vehicles will need to mimic, or ideally improve upon, humanlike driving. Yet, driving presents us with difficult problems of joint action: ‘negotiating’ with other users over shared road space. We argue that autonomous driving provides a test case for computational theories of social interaction, with fundamental implications for the development of autonomous vehicles.
Frontal Cortex and the Hierarchical Control of Behavior Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-12-08 David Badre, Derek Evan Nee
The frontal lobes are important for cognitive control, yet their functional organization remains controversial. An influential class of theory proposes that the frontal lobes are organized along their rostrocaudal axis to support hierarchical cognitive control. Here, we take an updated look at the literature on hierarchical control, with particular focus on the functional organization of lateral frontal cortex. Our review of the evidence supports neither a unitary model of lateral frontal function nor a unidimensional abstraction gradient. Rather, separate frontal networks interact via local and global hierarchical structure to support diverse task demands.
Consciousness, Representation, Action: The Importance of Being Goal-Directed Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-12-07 Cyriel M.A. Pennartz
Recent years have witnessed fierce debates on the dependence of consciousness on interactions between a subject and the environment. Reviewing neuroscientific, computational, and clinical evidence, I will address three questions. First, does conscious experience necessarily depend on acute interactions between a subject and the environment? Second, does it depend on specific perception–action loops in the longer run? Third, which types of action does consciousness cohere with, if not with all of them? I argue that conscious contents do not necessarily depend on acute or long-term brain–environment interactions. Instead, consciousness is proposed to be specifically associated with, and subserve, deliberate, goal-directed behavior (GDB). Brain systems implied in conscious representation are highly connected to, but distinct from, neural substrates mediating GDB and declarative memory.
Large-Scale Gradients in Human Cortical Organization Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-12-01 Julia M. Huntenburg, Pierre-Louis Bazin, Daniel S. Margulies
Recent advances in mapping cortical areas in the human brain provide a basis for investigating the significance of their spatial arrangement. Here we describe a dominant gradient in cortical features that spans between sensorimotor and transmodal areas. We propose that this gradient constitutes a core organizing axis of the human cerebral cortex, and describe an intrinsic coordinate system on its basis. Studying the cortex with respect to these intrinsic dimensions can inform our understanding of how the spectrum of cortical function emerges from structural constraints.
The Role of Inhibition in Avoiding Distraction by Salient Stimuli Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-11-27 Nicholas Gaspelin, Steven J. Luck
Researchers have long debated whether salient stimuli can involuntarily ‘capture’ visual attention. We review here evidence for a recently discovered inhibitory mechanism that may help to resolve this debate. This evidence suggests that salient stimuli naturally attempt to capture attention, but capture can be avoided if the salient stimulus is suppressed before it captures attention. Importantly, the suppression process can be more or less effective as a result of changing task demands or lapses in cognitive control. Converging evidence for the existence of this suppression mechanism comes from multiple sources, including psychophysics, eye-tracking, and event-related potentials (ERPs). We conclude that the evidence for suppression is strong, but future research will need to explore the nature and limits of this mechanism.
Predicting Violent Behavior: What Can Neuroscience Add? Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-11-25 Russell A. Poldrack, John Monahan, Peter B. Imrey, Valerie Reyna, Marcus E. Raichle, David Faigman, Joshua W. Buckholtz
The ability to accurately predict violence and other forms of serious antisocial behavior would provide important societal benefits, and there is substantial enthusiasm for the potential predictive accuracy of neuroimaging techniques. Here, we review the current status of violence prediction using actuarial and clinical methods, and assess the current state of neuroprediction. We then outline several questions that need to be addressed by future studies of neuroprediction if neuroimaging and other neuroscientific markers are to be successfully translated into public policy.
Network Neuroscience Theory of Human Intelligence Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-11-20 Aron K. Barbey
An enduring aim of research in the psychological and brain sciences is to understand the nature of individual differences in human intelligence, examining the stunning breadth and diversity of intellectual abilities and the remarkable neurobiological mechanisms from which they arise. This Opinion article surveys recent neuroscience evidence to elucidate how general intelligence, g, emerges from individual differences in the network architecture of the human brain. The reviewed findings motivate new insights about how network topology and dynamics account for individual differences in g, represented by the Network Neuroscience Theory. According to this framework, g emerges from the small-world topology of brain networks and the dynamic reorganization of its community structure in the service of system-wide flexibility and adaptation.
Computational Complexity and Human Decision-Making Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-11-14 Peter Bossaerts, Carsten Murawski
The rationality principle postulates that decision-makers always choose the best action available to them. It underlies most modern theories of decision-making. The principle does not take into account the difficulty of finding the best option. Here, we propose that computational complexity theory (CCT) provides a framework for defining and quantifying the difficulty of decisions. We review evidence showing that human decision-making is affected by computational complexity. Building on this evidence, we argue that most models of decision-making, and metacognition, are intractable from a computational perspective. To be plausible, future theories of decision-making will need to take into account both the resources required for implementing the computations implied by the theory, and the resource constraints imposed on the decision-maker by biology.
Expansion and Renormalization of Human Brain Structure During Skill Acquisition Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-11-14 Elisabeth Wenger, Claudio Brozzoli, Ulman Lindenberger, Martin Lövdén
Research on human brain changes during skill acquisition has revealed brain volume expansion in task-relevant areas. However, the large number of skills that humans acquire during ontogeny militates against plasticity as a perpetual process of volume growth. Building on animal models and available theories, we promote the expansion–renormalization model for plastic changes in humans. The model predicts an initial increase of gray matter structure, potentially reflecting growth of neural resources like neurons, synapses, and glial cells, which is followed by a selection process operating on this new tissue leading to a complete or partial return to baseline of the overall volume after selection has ended. The model sheds new light on available evidence and current debates and fosters the search for mechanistic explanations.
Towards a Unitary Approach to Human Action Control Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-11-14 Bernhard Hommel, Reinout W. Wiers
From its academic beginnings the theory of human action control has distinguished between endogenously driven, intentional action and exogenously driven, habitual, or automatic action. We challenge this dual-route model and argue that attempts to provide clear-cut and straightforward criteria to distinguish between intentional and automatic action have systematically failed. Specifically, we show that there is no evidence for intention-independent action, and that attempts to use the criterion of reward sensitivity and rationality to differentiate between intentional and automatic action are conceptually unsound. As a more parsimonious, and more feasible, alternative we suggest a unitary approach to action control, according to which actions are (i) represented by codes of their perceptual effects, (ii) selected by matching intention-sensitive selection criteria, and (ii) moderated by metacontrol states.
Constraints on Statistical Learning Across Species Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-11-14 Chiara Santolin, Jenny R. Saffran
Both human and nonhuman organisms are sensitive to statistical regularities in sensory inputs that support functions including communication, visual processing, and sequence learning. One of the issues faced by comparative research in this field is the lack of a comprehensive theory to explain the relevance of statistical learning across distinct ecological niches. In the current review we interpret cross-species research on statistical learning based on the perceptual and cognitive mechanisms that characterize the human and nonhuman models under investigation. Considering statistical learning as an essential part of the cognitive architecture of an animal will help to uncover the potential ecological functions of this powerful learning process.
Data-Driven Methods to Diversify Knowledge of Human Psychology Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-11-07 Rachael E. Jack, Carlos Crivelli, Thalia Wheatley
Psychology aims to understand real human behavior. However, cultural biases in the scientific process can constrain knowledge. We describe here how data-driven methods can relax these constraints to reveal new insights that theories can overlook. To advance knowledge we advocate a symbiotic approach that better combines data-driven methods with theory.
Segregated Systems of Human Brain Networks Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-10-31 Gagan S. Wig
The organization of the brain network enables its function. Evaluation of this organization has revealed that large-scale brain networks consist of multiple segregated subnetworks of interacting brain areas. Descriptions of resting-state network architecture have provided clues for understanding the functional significance of these segregated subnetworks, many of which correspond to distinct brain systems. The present report synthesizes accumulating evidence to reveal how maintaining segregated brain systems renders the human brain network functionally specialized, adaptable to task demands, and largely resilient following focal brain damage. The organizational properties that support system segregation are harmonious with the properties that promote integration across the network, but confer unique and important features to the brain network that are central to its function and behavior.
Single-Neuron Correlates of Awareness during Attentional Blinks Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-10-31 Zhongzheng Fu, Ueli Rutishauser
A recent single-neuron study revealed an anatomical anterior-to-posterior gradient of awareness-related responses by ‘concept neurons’ in the human medial temporal lobe (MTL). Delayed and weaker responses were indicative of the failure of a stimulus to reach awareness, suggesting that reliable fast responses are a critical aspect of the neural mechanisms of consciousness.
Parallel Distributed Processing Theory in the Age of Deep Networks Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-10-31 Jeffrey S. Bowers
Parallel distributed processing (PDP) models in psychology are the precursors of deep networks used in computer science. However, only PDP models are associated with two core psychological claims, namely that all knowledge is coded in a distributed format and cognition is mediated by non-symbolic computations. These claims have long been debated in cognitive science, and recent work with deep networks speaks to this debate. Specifically, single-unit recordings show that deep networks learn units that respond selectively to meaningful categories, and researchers are finding that deep networks need to be supplemented with symbolic systems to perform some tasks. Given the close links between PDP and deep networks, it is surprising that research with deep networks is challenging PDP theory.
Network Design and the Brain Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-10-17 Saket Navlakha, Ziv Bar-Joseph, Alison L. Barth
Neural circuits have evolved to accommodate similar information processing challenges as those faced by engineered systems. Here, we compare neural versus engineering strategies for constructing networks. During circuit development, synapses are overproduced and then pruned back over time, whereas in engineered networks, connections are initially sparse and are then added over time. We provide a computational perspective on these two different approaches, including discussion of how and why they are used, insights that one can provide the other, and areas for future joint investigation. By thinking algorithmically about the goals, constraints, and optimization principles used by neural circuits, we can develop brain-derived strategies for enhancing network design, while also stimulating experimental hypotheses about circuit development and function.
Advances in fMRI Real-Time Neurofeedback Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-10-12 Takeo Watanabe, Yuka Sasaki, Kazuhisa Shibata, Mitsuo Kawato
Functional magnetic resonance imaging (fMRI) neurofeedback is a type of biofeedback in which real-time online fMRI signals are used to self-regulate brain function. Since its advent in 2003 significant progress has been made in fMRI neurofeedback techniques. Specifically, the use of implicit protocols, external rewards, multivariate analysis, and connectivity analysis has allowed neuroscientists to explore a possible causal involvement of modified brain activity in modified behavior. These techniques have also been integrated into groundbreaking new neurofeedback technologies, specifically decoded neurofeedback (DecNef) and functional connectivity-based neurofeedback (FCNef). By modulating neural activity and behavior, DecNef and FCNef have substantially advanced both basic and clinical research.
Smiles as Multipurpose Social Signals Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-09-27 Jared Martin, Magdalena Rychlowska, Adrienne Wood, Paula Niedenthal
The human smile is highly variable in both its form and the social contexts in which it is displayed. A social-functional account identifies three distinct smile expressions defined in terms of their effects on the perceiver: reward smiles reinforce desired behavior; affiliation smiles invite and maintain social bonds; and dominance smiles manage hierarchical relationships. Mathematical modeling uncovers the appearance of the smiles, and both human and Bayesian classifiers validate these distinctions. New findings link laughter to reward, affiliation, and dominance, and research suggests that these functions of smiles are recognized across cultures. Taken together, this evidence suggests that the smile can be productively investigated according to how it assists the smiler in meeting the challenges and opportunities inherent in human social living.
Disruption of Conscious Access in Schizophrenia Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-09-26 Lucie Berkovitch, Stanislas Dehaene, Raphaël Gaillard
Schizophrenia is a severe and complex psychiatric disorder resulting in delusions, hallucinations, and cognitive impairments. Across a variety of paradigms, an elevated threshold for conscious perception has been repeatedly observed in persons with schizophrenia. Remarkably, even subtle measures of subliminal processing appear to be preserved. We argue here that the dissociation between impaired conscious access and intact unconscious processing may be due to a specific disruption of top-down attentional amplification. This proposal is compatible with the neurophysiological disturbances observed in schizophrenia, including dysconnectivity, abnormal neural oscillations, and glutamatergic and cholinergic dysregulation. Therefore, placing impaired conscious access as a central feature of schizophrenia can help researchers develop a coherent and parsimonious pathophysiological framework of the disease.
The Split-Brain Phenomenon Revisited: A Single Conscious Agent with Split Perception Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-09-25 Yair Pinto, Edward H.F de Haan, Victor A.F. Lamme
The split-brain phenomenon is caused by the surgical severing of the corpus callosum, the main route of communication between the cerebral hemispheres. The classical view of this syndrome asserts that conscious unity is abolished. The left hemisphere consciously experiences and functions independently of the right hemisphere. This view is a cornerstone of current consciousness research. In this review, we first discuss the evidence for the classical view. We then propose an alternative, the ‘conscious unity, split perception’ model. This model asserts that a split brain produces one conscious agent who experiences two parallel, unintegrated streams of information. In addition to changing our view of the split-brain phenomenon, this new model also poses a serious challenge for current dominant theories of consciousness.
Reading Faces: From Features to Recognition Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-09-19 J. Swaroop Guntupalli, M. Ida Gobbini
Chang and Tsao recently reported that the monkey face patch system encodes facial identity in a space of facial features as opposed to exemplars. Here, we discuss how such coding might contribute to face recognition, emphasizing the critical role of learning and interactions with other brain areas for optimizing the recognition of familiar faces.
Flexible Planning in Ravens? Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-09-15 Jonathan Redshaw, Alex H. Taylor, Thomas Suddendorf
Across two different contexts, Kabadayi and Osvath found that ravens preferentially selected items that could be used to obtain future rewards. Do these results demand a rethink of the evolution of flexible planning, or are there leaner alternative explanations for the performance of ravens?
An Integrative Interdisciplinary Perspective on Social Dominance Hierarchies Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-09-12 Chen Qu, Romain Ligneul, Jean-Baptiste Van der Henst, Jean-Claude Dreher
In the course of evolution, social dominance has been a strong force shaping the organization of social systems in many species. Individuals with a better ability to represent social dominance relationships and to adapt their behavior accordingly usually achieve better access to resources, hence providing benefits in terms of reproduction, health, and wellbeing. Understanding how and to what extent our brains are affected by social dominance requires interdisciplinary efforts. Here, we integrate findings from social neuroscience, evolutionary biology, and developmental psychology to highlight how social hierarchies are learned and represented in primates. We also review neuropharmacological findings showing how dopamine, serotonin, and testosterone influence social hierarchies and we emphasize their key clinical implications on vulnerabilities to neuropsychiatric disorders.
Constructing Experience: Event Models from Perception to Action Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-09-09 Lauren L. Richmond, Jeffrey M. Zacks
Mental representations of everyday experience are rich, structured, and multimodal. In this article we consider the adaptive pressures that led to human construction of such representations, arguing that structured event representations enable cognitive systems to more effectively predict the trajectory of naturalistic everyday activity. We propose an account of how cortical systems and the hippocampus (HPC) interact to construct, maintain, and update event representations. This analysis throws light on recent research on story comprehension, event segmentation, episodic memory, and action planning. It also suggests how the growing science base can be deployed to diagnose impairments in event perception and memory, and to improve memory for everyday events.
Why Do the Children (Pretend) Play? Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-08-29 Angeline S. Lillard
Pretend play appears to be an evolved behavior because it is universal and appears on a set schedule. However, no specific functions have been determined for pretend play and empirical tests for its functions in humans are elusive. Yet animal play fighting can serve as an analog, as both activities involve as-if, metacommunicative signaling and symbolism. In the rat and some other animals, adaptive functions of play fighting include assisting social behavior and emotion regulation. Research is presented suggesting that pretend play might serve similar functions for humans.
Origins of the Belief in Good True Selves Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-06-07 Julian De Freitas, Mina Cikara, Igor Grossmann, Rebecca Schlegel
Despite differences in beliefs about the self across cultures and relevant individual differences, recent evidence suggests that people universally believe in a ‘true self’ that is morally good. We propose that this belief arises from a general tendency: psychological essentialism (PE).
Evidence from Blindness for a Cognitively Pluripotent Cortex Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-08-16 Marina Bedny
Cognitive neuroscience seeks to discover how cognitive functions are implemented in neural circuits. Studies of plasticity in blindness suggest that this mind–brain mapping is highly flexible during development. In blindness, ‘visual’ cortices take on higher-cognitive functions, including language and mathematics, becoming sensitive to the grammatical structure of spoken sentences and the difficulty of math equations. Visual cortex activity at rest becomes synchronized with higher-cognitive networks. Such repurposing is striking in light of the cognitive and evolutionary differences between vision, language, and mathematics. We propose that human cortices are cognitively pluripotent, that is, capable of assuming a wide range of cognitive functions. Specialization is driven by input during development, which is itself constrained by connectivity and experience.‘The child who methodically adds two numbers from right to left, carrying a digit when necessary, may be using the same algorithm that is implemented by the wires and transistors of the cash register in the neighborhood supermarket…’▓▓Vision, 1982, David Marr
Mind Games: Game Engines as an Architecture for Intuitive Physics Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-06-24 Tomer D. Ullman, Elizabeth Spelke, Peter Battaglia, Joshua B. Tenenbaum
We explore the hypothesis that many intuitive physical inferences are based on a mental physics engine that is analogous in many ways to the machine physics engines used in building interactive video games. We describe the key features of game physics engines and their parallels in human mental representation, focusing especially on the intuitive physics of young infants where the hypothesis helps to unify many classic and otherwise puzzling phenomena, and may provide the basis for a computational account of how the physical knowledge of infants develops. This hypothesis also explains several ‘physics illusions’, and helps to inform the development of artificial intelligence (AI) systems with more human-like common sense.
Sex-Linked Behavior: Evolution, Stability, and Variability Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-08-15 Cordelia Fine, John Dupré, Daphna Joel
Common understanding of human sex-linked behaviors is that proximal mechanisms of genetic and hormonal sex, ultimately shaped by the differential reproductive challenges of ancestral males and females, act on the brain to transfer sex-linked predispositions across generations. Here, we extend the debate on the role of nature and nurture in the development of traits in the lifetime of an individual, to their role in the cross-generation transfer of traits. Advances in evolutionary theory that posit the environment as a source of trans-generational stability, and new understanding of sex effects on the brain, suggest that the cross-generation stability of sex-linked patterns of behavior are sometimes better explained in terms of inherited socioenvironmental conditions, with biological sex fostering intrageneration variability.
Brain and Social Networks: Fundamental Building Blocks of Human Experience Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-07-20 Emily B. Falk, Danielle S. Bassett
How do brains shape social networks, and how do social ties shape the brain? Social networks are complex webs by which ideas spread among people. Brains comprise webs by which information is processed and transmitted among neural units. While brain activity and structure offer biological mechanisms for human behaviors, social networks offer external inducers or modulators of those behaviors. Together, these two axes represent fundamental contributors to human experience. Integrating foundational knowledge from social and developmental psychology and sociology on how individuals function within dyads, groups, and societies with recent advances in network neuroscience can offer new insights into both domains. Here, we use the example of how ideas and behaviors spread to illustrate the potential of multilayer network models.
Foraging Cognition: Reviving the Ecological Intelligence Hypothesis Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-06-15 Alexandra G. Rosati
What are the origins of intelligent behavior? The demands associated with living in complex social groups have been the favored explanation for the evolution of primate cognition in general and human cognition in particular. However, recent comparative research indicates that ecological variation can also shape cognitive abilities. I synthesize the emerging evidence that ‘foraging cognition’ – skills used to exploit food resources, including spatial memory, decision-making, and inhibitory control – varies adaptively across primates. These findings provide a new framework for the evolution of human cognition, given our species’ dependence on costly, high-value food resources. Understanding the origins of the human mind will require an integrative theory accounting for how humans are unique in both our sociality and our ecology.
Mechanisms of Connectome Development Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-06-10 Marcus Kaiser
At the centenary of D’Arcy Thompson’s seminal work ‘On Growth and Form’, pioneering the description of principles of morphological changes during development and evolution, recent experimental advances allow us to study change in anatomical brain networks. Here, we outline potential principles for connectome development. We will describe recent results on how spatial and temporal factors shape connectome development in health and disease. Understanding the developmental origins of brain diseases in individuals will be crucial for deciding on personalized treatment options. We argue that longitudinal studies, experimentally derived parameters for connection formation, and biologically realistic computational models are needed to better understand the link between brain network development, network structure, and network function.
Crowdsourcing Samples in Cognitive Science Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-08-10 Neil Stewart, Jesse Chandler, Gabriele Paolacci
Crowdsourcing data collection from research participants recruited from online labor markets is now common in cognitive science. We review who is in the crowd and who can be reached by the average laboratory. We discuss reproducibility and review some recent methodological innovations for online experiments. We consider the design of research studies and arising ethical issues. We review how to code experiments for the web, what is known about video and audio presentation, and the measurement of reaction times. We close with comments about the high levels of experience of many participants and an emerging tragedy of the commons.
Comparing Parietal Quantity-Processing Mechanisms between Humans and Macaques Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-08-09 Ben M. Harvey, Stefania Ferri, Guy A. Orban
Quantity processing studies typically assume functional homology between regions within macaque and human intraparietal sulcus (IPS), where apparently similar locations respond to broadly similar tasks. However, macaque single cell neurophysiology is difficult to compare to human functional magnetic resonance imaging (fMRI); particularly in multivoxel pattern analysis and adaptation paradigms, or where different tasks are used. fMRI approaches incorporating neural tuning models allow closer comparison, revealing human numerosity-selective responses only outside the IPS. Extensive functional similarities support this novel homology of physical quantity processing. Human IPS instead houses a network responding to comparisons of physical quantities, symbolic numbers, and other stimulus features. This network likely reflects interactions between physical quantity processing, spatial processing, and (in humans) linguistic processing.
How Linguistic Metaphor Scaffolds Reasoning Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-08-05 Paul H. Thibodeau, Rose K. Hendricks, Lera Boroditsky
Language helps people communicate and think. Precise and accurate language would seem best suited to achieve these goals. But a close look at the way people actually talk reveals an abundance of apparent imprecision in the form of metaphor: ideas are ‘light bulbs’, crime is a ‘virus’, and cancer is an ‘enemy’ in a ‘war’. In this article, we review recent evidence that metaphoric language can facilitate communication and shape thinking even though it is literally false. We first discuss recent experiments showing that linguistic metaphor can guide thought and behavior. Then we explore the conditions under which metaphors are most influential. Throughout, we highlight theoretical and practical implications, as well as key challenges and opportunities for future research.
Retrieval as a Fast Route to Memory Consolidation Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-06-02 James W. Antony, Catarina S. Ferreira, Kenneth A. Norman, Maria Wimber
Retrieval-mediated learning is a powerful way to make memories last, but its neurocognitive mechanisms remain unclear. We propose that retrieval acts as a rapid consolidation event, supporting the creation of adaptive hippocampal–neocortical representations via the ‘online’ reactivation of associative information. We describe parallels between online retrieval and offline consolidation and offer testable predictions for future research.
A Closer Look at the Hippocampus and Memory Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-06-15 Joel L. Voss, Donna J. Bridge, Neal J. Cohen, John A. Walker
Current interpretations of hippocampal memory function are blind to the fact that viewing behaviors are pervasive and complicate the relationships among perception, behavior, memory, and brain activity. For example, hippocampal activity and associative memory demands increase with stimulus complexity. Stimulus complexity also strongly modulates viewing. Associative processing and viewing thus are often confounded, rendering interpretation of hippocampal activity ambiguous. Similar considerations challenge many accounts of hippocampal function. To explain relationships between memory and viewing, we propose that the hippocampus supports the online memory demands necessary to guide visual exploration. The hippocampus thus orchestrates memory-guided exploration that unfolds over time to build coherent memories. This new perspective on hippocampal function harmonizes with the fact that memory formation and exploratory viewing are tightly intertwined.
The Dorsal Frontoparietal Network: A Core System for Emulated Action Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-06-01 Radek Ptak, Armin Schnider, Julia Fellrath
The dorsal frontoparietal network (dFPN) of the human brain assumes a puzzling variety of functions, including motor planning and imagery, mental rotation, spatial attention, and working memory. How can a single network engage in such a diversity of roles? We propose that cognitive computations relying on the dFPN can be pinned down to a core function underlying offline motor planning: action emulation. Emulation creates a dynamic representation of abstract movement kinematics, sustains the internal manipulation of this representation, and ensures its maintenance over short time periods. Based on these fundamental characteristics, the dFPN has evolved from a pure motor control network into a domain-general system supporting various cognitive and motor functions.
Default Rules Are Better Than Active Choosing (Often) Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-05-25 Cass R. Sunstein
In recent years, governments have become keenly interested in behavioral science; new findings in psychology and behavioral economics have led to bold initiatives in areas that involve poverty, consumer protection, savings, health, the environment, and much more. Private institutions have used behavioral findings as well. But there is a pervasive and insufficiently explored question: when is it best to ask people to make active choices, and when is it best to use a default rule, which means that people need not make any choice at all? The answer depends on a form of cost–benefit analysis, which means that it is necessary to investigate whether choosing is a burden or a pleasure, whether learning is important, and whether a default rule would satisfy the informed preferences or all of most people.
Meta-Reasoning: Monitoring and Control of Thinking and Reasoning Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-06-15 Rakefet Ackerman, Valerie A. Thompson
Meta-Reasoning refers to the processes that monitor the progress of our reasoning and problem-solving activities and regulate the time and effort devoted to them. Monitoring processes are usually experienced as feelings of certainty or uncertainty about how well a process has, or will, unfold. These feelings are based on heuristic cues, which are not necessarily reliable. Nevertheless, we rely on these feelings of (un)certainty to regulate our mental effort. Most metacognitive research has focused on memorization and knowledge retrieval, with little attention paid to more complex processes, such as reasoning and problem solving. In that context, we recently developed a Meta-Reasoning framework, used here to review existing findings, consider their consequences, and frame questions for future research.
Neurobiology of Schemas and Schema-Mediated Memory Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-05-24 Asaf Gilboa, Hannah Marlatte
Schemas are superordinate knowledge structures that reflect abstracted commonalities across multiple experiences, exerting powerful influences over how events are perceived, interpreted, and remembered. Activated schema templates modulate early perceptual processing, as they get populated with specific informational instances (schema instantiation). Instantiated schemas, in turn, can enhance or distort mnemonic processing from the outset (at encoding), impact offline memory transformation and accelerate neocortical integration. Recent studies demonstrate distinctive neurobiological processes underlying schema-related learning. Interactions between the ventromedial prefrontal cortex (vmPFC), hippocampus, angular gyrus (AG), and unimodal associative cortices support context-relevant schema instantiation and schema mnemonic effects. The vmPFC and hippocampus may compete (as suggested by some models) or synchronize (as suggested by others) to optimize schema-related learning depending on the specific operationalization of schema memory. This highlights the need for more precise definitions of memory schemas.
Reevaluating the Sensory Account of Visual Working Memory Storage Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-07-31 Yaoda Xu
Recent human fMRI pattern-decoding studies have highlighted the involvement of sensory areas in visual working memory (VWM) tasks and argue for a sensory account of VWM storage. In this review, evidence is examined from human behavior, fMRI decoding, and transcranial magnetic stimulation (TMS) studies, as well as from monkey neurophysiology studies. Contrary to the prevalent view, the available evidence provides little support for the sensory account of VWM storage. Instead, when the ability to resist distraction and the existence of top-down feedback are taken into account, VWM-related activities in sensory areas seem to reflect feedback signals indicative of VWM storage elsewhere in the brain. Collectively, the evidence shows that prefrontal and parietal regions, rather than sensory areas, play more significant roles in VWM storage.
Mapping the Consequences of Impaired Synaptic Plasticity in Schizophrenia through Development: An Integrative Model for Diverse Clinical Features Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-07-25 Jennifer K. Forsyth, David A. Lewis
Schizophrenia is associated with alterations in sensory, motor, and cognitive functions that emerge before psychosis onset; identifying pathogenic processes that can account for this multi-faceted phenotype remains a challenge. Accumulating evidence suggests that synaptic plasticity is impaired in schizophrenia. Given the role of synaptic plasticity in learning, memory, and neural circuit maturation, impaired plasticity may underlie many features of the schizophrenia syndrome. Here, we summarize the neurobiology of synaptic plasticity, review evidence that plasticity is impaired in schizophrenia, and explore a framework in which impaired synaptic plasticity interacts with brain maturation to yield the emergence of sensory, motor, cognitive, and psychotic features at different times during development in schizophrenia. Key gaps in the literature and future directions for testing this framework are discussed.
Do Intelligent Robots Need Emotion? Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-07-20 Luiz Pessoa
What is the place of emotion in intelligent robots? Researchers have advocated the inclusion of some emotion-related components in the information-processing architecture of autonomous agents. It is argued here that emotion needs to be merged with all aspects of the architecture: cognitive–emotional integration should be a key design principle.
Intuitive Physics: Current Research and Controversies Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-07-12 James R. Kubricht, Keith J. Holyoak, Hongjing Lu
Early research in the field of intuitive physics provided extensive evidence that humans succumb to common misconceptions and biases when predicting, judging, and explaining activity in the physical world. Recent work has demonstrated that, across a diverse range of situations, some biases can be explained by the application of normative physical principles to noisy perceptual inputs. However, it remains unclear how knowledge of physical principles is learned, represented, and applied to novel situations. In this review we discuss theoretical advances from heuristic models to knowledge-based, probabilistic simulation models, as well as recent deep-learning models. We also consider how recent work may be reconciled with earlier findings that favored heuristic models.
Agency and the Calibration of Motivated Behavior Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-07-07 Justin M. Moscarello, Catherine A. Hartley
The controllability of positive or negative environmental events has long been recognized as a critical factor determining their impact on an organism. In studies across species, controllable and uncontrollable reinforcement have been found to yield divergent effects on subsequent behavior. Here we present a model of the organizing influence of control, or a lack thereof, on the behavioral repertoire. We propose that individuals derive a generalizable estimate of agency from controllable and uncontrollable outcomes, which serves to calibrate their behavioral strategies in a manner that is most likely to be adaptive given their prior experience.
Continuous Flash Suppression: Stimulus Fractionation rather than Integration Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-07-06 Pieter Moors, Guido Hesselmann, Johan Wagemans, Raymond van Ee
Recent studies using continuous flash suppression suggest that invisible stimuli are processed as integrated, semantic entities. We challenge the viability of this account, given recent findings on the neural basis of interocular suppression and replication failures of high-profile CFS studies. We conclude that CFS reveals stimulus fractionation in visual cortex.
Serial Dependence across Perception, Attention, and Memory Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-05-23 Anastasia Kiyonaga, Jason M. Scimeca, Daniel P. Bliss, David Whitney
Information that has been recently perceived or remembered can bias current processing. This has been viewed as both a corrupting (e.g., proactive interference in short-term memory) and stabilizing (e.g., serial dependence in perception) phenomenon. We hypothesize that this bias is a generally adaptive aspect of brain function that leads to occasionally maladaptive outcomes.
The Coding Question Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-05-15 C.R. Gallistel
Recent electrophysiological results imply that the duration of the stimulus onset asynchrony in eyeblink conditioning is encoded by a mechanism intrinsic to the cerebellar Purkinje cell. This raises the general question – how is quantitative information (durations, distances, rates, probabilities, amounts, etc.) transmitted by spike trains and encoded into engrams? The usual assumption is that information is transmitted by firing rates. However, rate codes are energetically inefficient and computationally awkward. A combinatorial code is more plausible. If the engram consists of altered synaptic conductances (the usual assumption), then we must ask how numbers may be written to synapses. It is much easier to formulate a coding hypothesis if the engram is realized by a cell-intrinsic molecular mechanism.
Metastability in Senescence Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-05-09 Shruti Naik, Arpan Banerjee, Raju S. Bapi, Gustavo Deco, Dipanjan Roy
The brain during healthy aging exhibits gradual deterioration of structure but maintains a high level of cognitive ability. These structural changes are often accompanied by reorganization of functional brain networks. Existing neurocognitive theories of aging have argued that such changes are either beneficial or detrimental. Despite numerous empirical investigations, the field lacks a coherent account of the dynamic processes that occur over our lifespan. Taking advantage of the recent developments in whole-brain computational modeling approaches, we hypothesize that the continuous process of aging can be explained by the concepts of metastability − a theoretical framework that gives a systematic account of the variability of the brain. This hypothesis can bridge the gap between existing theories and the empirical findings on age-related changes.
Evolution in Mind: Evolutionary Dynamics, Cognitive Processes, and Bayesian Inference Trends Cogn. Sci. (IF 15.402) Pub Date : 2017-05-24 Jordan W. Suchow, David D. Bourgin, Thomas L. Griffiths
Evolutionary theory describes the dynamics of population change in settings affected by reproduction, selection, mutation, and drift. In the context of human cognition, evolutionary theory is most often invoked to explain the origins of capacities such as language, metacognition, and spatial reasoning, framing them as functional adaptations to an ancestral environment. However, evolutionary theory is useful for understanding the mind in a second way: as a mathematical framework for describing evolving populations of thoughts, ideas, and memories within a single mind. In fact, deep correspondences exist between the mathematics of evolution and of learning, with perhaps the deepest being an equivalence between certain evolutionary dynamics and Bayesian inference. This equivalence permits reinterpretation of evolutionary processes as algorithms for Bayesian inference and has relevance for understanding diverse cognitive capacities, including memory and creativity.
Some contents have been Reproduced by permission of The Royal Society of Chemistry.
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