Can information that is processed during sleep influence awake behavior? Recent research demonstrates that learning during sleep is possible, but that sleep-learning invariably produces memory traces that are consciously inaccessible in the awake state. Thus, sleep-learning can likely exert implicit, but not explicit, influences on awake behavior.

One of the most difficult and important decisions in power analysis involves specifying an effect size. Researchers frequently employ definitions of small, medium, and large that were proposed by Jacob Cohen. These definitions are problematic for two reasons. First, they are arbitrary, based on non-scientific criteria. Second, they are inconsistent, changing dramatically and illogically as a function of the statistical test a researcher plans to use (e.g., t-test versus regression). These problems may be unknown to many researchers, but they have a huge impact on power analyses. Estimates of the required n may be inappropriately doubled or cut in half. For power analyses to have any meaning, these definitions of effect size should be avoided.

What role does the hippocampus play in semantic memory? In a recent paper, Cutler et al. use a vector space model of semantics to characterize semantic search deficits in hippocampal amnesia. We relate their findings to properties of the hippocampal neural code and to controversies regarding hippocampal contributions to cognition.

People’s beliefs about others are often impervious to new evidence: we continue to cooperate with ingroup defectors and refuse to see outgroup enemies as rehabilitated. Resistance to updating beliefs with new information has historically been interpreted as reflecting bias or motivated cognition, but recent work in Bayesian inference suggests that belief maintenance can be compatible with procedural rationality. We propose a mentalizing account of belief maintenance, which holds that protecting strong priors by generating alternative explanations for surprising information involves more mentalizing about the target than nonrational discounting. We review the neuroscientific evidence supporting this approach, and discuss how both types of processing can lead to fitness benefits.

Sacrificial moral dilemmas are widely used to investigate when, how, and why people make judgments that are consistent with utilitarianism. However, to what extent can responses to sacrificial dilemmas shed light on utilitarian decision making? We consider two key questions. First, how meaningful is the relationship between responses to sacrificial dilemmas, and what is distinctive about a utilitarian approach to morality? Second, to what extent do findings about sacrificial dilemmas generalize to other moral contexts where there is tension between utilitarianism and common-sense intuitions? We argue that sacrificial dilemmas only capture one point of conflict between utilitarianism and common-sense morality, and new paradigms will be necessary to investigate other key aspects of utilitarianism, such as its radical impartiality.

Consciousness remains a formidable challenge. Different theories of consciousness have proposed vastly different mechanisms to account for phenomenal experience. Here, appealing to aspects of global workspace theory, higher-order theories, social theories, and predictive processing, we introduce a novel framework: the self-organizing metarerpresentational account (SOMA), in which consciousness is viewed as something that the brain learns to do. By this account, the brain continuously and unconsciously learns to redescribe its own activity to itself, so developing systems of metarepresentations that qualify target first-order representations. Thus, experiences only occur in experiencers that have learned to know they possess certain first-order states and that have learned to care more about certain states than about others. In this sense, consciousness is the brain’s (unconscious, embodied, enactive, nonconceptual) theory about itself.

The ratio of men to women in a given ecology can have profound influences on a range of interpersonal processes, from marriage and divorce rates to risk-taking and violent crime. Here, we organize such processes into two categories – intersexual choice and intrasexual competition – representing focal effects of imbalanced sex ratios.

There is ongoing debate regarding the robustness and credibility of published scientific research. We argue that these issues stem from two broad causal mechanisms: the cognitive biases of researchers and the incentive structures within which researchers operate. The UK Reproducibility Network (UKRN) is working with researchers, institutions, funders, publishers, and other stakeholders to address these issues.

Sometimes we accept propositions, sometimes we reject them, and sometimes we take propositions to be worth considering but not yet established, as merely possible. The result is a complex representation with logical structure. Is the ability to mark propositions as merely possible part of our innate representational toolbox or does it await development, perhaps relying on language acquisition? Several lines of inquiry show that preverbal infants manage possibilities in complex ways, while others find that preschoolers manage possibilities poorly. Here, we discuss how this apparent conflict can be resolved by distinguishing modal representations of possibility, which mark possibility symbolically, from minimal representations of possibility, which do not encode any modal status and need not have a logical structure.

Humans can imagine what happened in the past and what will happen in the future, but also what did not happen and what might happen. We reflect on envisioned events from alternative timelines, while knowing that we only ever live on one timeline. Considering alternative timelines rests on representations of temporal junctures, or points in time at which possible versions of reality diverge. These representations become increasingly sophisticated over childhood, first enabling preparation for mutually exclusive future possibilities and later the experience of counterfactual emotions like regret. By contrast, it remains unclear whether non-human animals represent temporal junctures at all. The emergence of these representations may have been a prime mover in human evolution.

In the visual world, attention is guided by perceptual goals activated in visual working memory (VWM). However, planning multiple-task sequences also requires VWM to store representations for future goals. These future goals need to be prevented from interfering with the current perceptual task. Recent findings have implicated neural oscillations as a control mechanism serving the implementation and switching of different states of prioritization of VWM representations. We review recent evidence that posterior alpha-band oscillations underlie the flexible activation and deactivation of VWM representations and that frontal delta-to-theta-band oscillations play a role in the executive control of this process. That is, frontal delta-to-theta appears to orchestrate posterior alpha through long-range oscillatory networks to flexibly set up and change VWM states during multitask sequences.

How and when infants and young children begin to develop emotion categories is not yet well understood. Research has largely treated the learning problem as one of identifying perceptual similarities among exemplars (typically posed, stereotyped facial configurations). However, recent meta-analyses and reviews converge to suggest that emotion categories are abstract, involving high-dimensional and situationally variable instances. In this paper we consult research on the development of abstract object categorization to guide hypotheses about how infants might learn abstract emotion categories because the two domains present infants with similar learning challenges. In particular, we consider how a developmental cascades framework offers opportunities to understand how and when young children develop emotion categories.

From the noisy information bombarding our senses, our brains must construct percepts that are veridical – reflecting the true state of the world – and informative – conveying what we did not already know. Influential theories suggest that both challenges are met through mechanisms that use expectations about the likely state of the world to shape perception. However, current models explaining how expectations render perception either veridical or informative are mutually incompatible. While the former propose that perceptual experiences are dominated by events we expect, the latter propose that perception of expected events is suppressed. To solve this paradox we propose a two-process model in which probabilistic knowledge initially biases perception towards what is likely and subsequently upweights events that are particularly surprising.

Sleep is a basic need. Mounting evidence suggests this is particularly true during adolescence, a developmental period involving substantial changes in the brain regions supporting cognition, learning, and emotion. Although sleep loss is a normative psychosocially and biologically driven developmental process, it occurs alongside behaviors that characterize adolescence, including deepening cognitive sophistication, improved emotion regulation, and intensifying social cognition, calling into question how sleep may impact these developmental milestones. This review synthesizes growing research aimed at addressing this timely question. It presents evidence that neurodevelopmental changes in brain structure, function, and sleep physiology mechanistically link the relationship between sleep and cognitive ability.

Is how we control our thoughts similar to how we control our movements? Egger et al. show that the neural dynamics underlying the control of internal states exhibit similar algorithmic properties as those that control movements. This experiment reveals a promising connection between how we control our brain and our body.

Two recent studies (Farashahi et al. and Rouault et al.) provide compelling evidence refuting the Subjective Expected Utility (SEU) hypothesis as a ground model describing human decision-making. Together, these studies pave the way towards a new model that subsumes the notion of decision-making and adaptive behavior into a single account.

Fast Science is bad for scientists and bad for science. Slow Science may actually help us to make faster progress, but how can we slow down? Here, I offer preliminary suggestions for how we can transition to a healthier and more sustainable research culture.

The efficacy and reliability of using intranasal oxytocin (OT) to clinically enhance social functions remains undependable. We discuss the potential benefit of concurrent administration of OT and naloxone (NAL) to robustly modulate social behavior. We further suggest that combinatorial neuropharmacology approaches should exploit the interactions between OT and serotonin to regulate social functions.

Understanding neurocognitive computations will require not just localizing cognitive information distributed throughout the brain but also determining how that information got there. We review recent advances in linking empirical and simulated brain network organization with cognitive information processing. Building on these advances, we offer a new framework for understanding the role of connectivity in cognition: network coding (encoding/decoding) models. These models utilize connectivity to specify the transfer of information via neural activity flow processes, successfully predicting the formation of cognitive representations in empirical neural data. The success of these models supports the possibility that localized neural functions mechanistically emerge (are computed) from distributed activity flow processes that are specified primarily by connectivity patterns.

Curiosity plays a fundamental role for learning and memory, but the neural mechanisms that stimulate curiosity and its effect on memory are poorly understood. Accumulating evidence suggests that curiosity states are related to modulations in activity in the dopaminergic circuit and that these modulations impact memory encoding and consolidation for both targets of curiosity and incidental information encountered during curiosity states. To account for this evidence, we propose the Prediction, Appraisal, Curiosity, and Exploration (PACE) framework, which attempts to explain curiosity and memory in terms of cognitive processes, neural circuits, behavior, and subjective experience. The PACE framework generates testable predictions that can stimulate future investigation of the mechanisms underlying curiosity-related memory enhancements.

The standard systems consolidation account posits that recently formed memories are initially dependent on the hippocampus and only gradually become instantiated in neocortical networks over a period of weeks to years. However, recent animal and human research has identified rapid formation of cortical engrams at the time of learning that can support hippocampal-independent memories within hours or days. Conditions that promote rapid cortical learning include relatedness to prior knowledge, activation of knowledge in the service of action selection or active discovery, and repeated retrieval. Here, we propose that cortical hubs can support rapid learning through synchronous activation of sensorimotor representational cortices. Candidate neurobiological mechanisms include unmasking of latent synaptic connections and rapid synaptic remodeling driven by disinhibitory processes.

A new study by Kano and colleagues shows that great apes use their own visual experience to attribute perceptions and beliefs to another agent. Their results suggest that the way apes understand behavior is more similar to human understanding than was previously thought, and may be driven by representations of mental states.

Jonasson et al. investigated whether individual differences in human dopamine receptors (D2R) were related to cognitive performance before and after a 6-month aerobic exercise intervention (compared with active control). While D2R decreased (perhaps counterintuitively) with exercise, there was no relationship between D2R and working memory at baseline or following exercise.

A central goal in cognitive science is to parse the series of processing stages underlying a cognitive task. A powerful yet simple behavioral method that can resolve this problem is finger trajectory tracking: by continuously tracking the finger position and speed as a participant chooses a response, and by analyzing which stimulus features affect the trajectory at each time point during the trial, we can estimate the absolute timing and order of each processing stage, and detect transient effects, changes of mind, serial versus parallel processing, and real-time fluctuations in subjective confidence. We suggest that trajectory tracking, which provides considerably more information than mere response times, may provide a comprehensive understanding of the fast temporal dynamics of cognitive operations.

Humans often represent and reason about unrealized possible actions – the vast infinity of things that were not (or have not yet been) chosen. This capacity is central to the most impressive of human abilities: causal reasoning, planning, linguistic communication, moral judgment, etc. Nevertheless, how do we select possible actions that are worth considering from the infinity of unrealized actions that are better left ignored? We review research across the cognitive sciences, and find that the possible actions considered by default are those that are both likely to occur and generally valuable. We then offer a unified theory of why. We propose that (i) across diverse cognitive tasks, the possible actions we consider are biased towards those of general practical utility, and (ii) a plausible primary function for this mechanism resides in decision making.

Is consciousness based in prefrontal circuits involved in cognitive processes like thought, reasoning, and memory or is it based in sensory areas in the back of the neocortex? The no-report paradigm has been crucial to this debate because it aims to separate the neural basis of the cognitive processes underlying post-perceptual decision and report from the neural basis of conscious perception itself. However, the no-report paradigm is problematic because, even in the absence of report, subjects might engage in post-perceptual cognitive processing. Therefore, to isolate the neural basis of consciousness, a no-cognition paradigm is needed. Here, I describe a no-cognition approach to binocular rivalry and outline how this approach can help to resolve debates about the neural basis of consciousness.

The nervous system promotes adaptive responding to myriad environmental stimuli by ascribing emotion to specific stimulus domains. This affects the salience of different stimuli, facilitates learning, and likely involves the amygdala. Recent studies suggest a strong homology between adaptive responses that result from learning and those that emerge during development. As in motivated learning, developmental studies have found the salience of different classes of stimulus (e.g., peers) undergoes marked fluctuation across maturation and may involve differential amygdala engagement. In this review, by highlighting the importance of particular stimulus categories during sensitive periods of development, we suggest that variability in amygdala response to different stimulus domains has an active and functional role in shaping emerging cortical circuits across development.

Since the original characterization of the ventral visual pathway, our knowledge of its neuroanatomy, functional properties, and extrinsic targets has grown considerably. Here we synthesize this recent evidence and propose that the ventral pathway is best understood as a recurrent occipitotemporal network containing neural representations of object quality both utilized and constrained by at least six distinct cortical and subcortical systems. Each system serves its own specialized behavioral, cognitive, or affective function, collectively providing the raison d'être for the ventral visual pathway. This expanded framework contrasts with the depiction of the ventral visual pathway as a largely serial staged hierarchy culminating in singular object representations and more parsimoniously incorporates attentional, contextual, and feedback effects.

Comparative neuroimaging can identify unique features of the human brain and teach us about human brain evolution. Comparisons with chimpanzees, our closest living primate relative, are critical in this endeavor. Structural magnetic resonance imaging (MRI) has been used to compare brain size development, brain structure proportions and brain aging. Positron emission tomography (PET) imaging has been used to compare resting brain glucose metabolism. Functional MRI (fMRI) has been used to compare auditory and visual system pathways, as well as resting-state networks of connectivity. Finally, diffusion-weighted imaging (DWI) has been used to compare structural connectivity. Collectively, these methods have revealed human brain specializations with respect to development, cortical organization, connectivity, and aging. These findings inform our knowledge of the evolutionary changes responsible for the special features of the modern human mind.

Extraordinary evidence generates extraordinary claims. I discuss the remarkable memory skills of chimpanzees tested in the Kyoto Primate Laboratory, and suggest a novel – but deflationary – hypothesis to explain them. Could the chimpanzees, who have been highly trained to learn the sequence of Arabic numerals, have developed number–colour synaesthesia?

by Steven Pinker, W.W. Norton & Co., 1997. $29.95 (xii+660 pages) ISBN 0 393 04535 8.

Although only humans use spoken language, the vocal communication of many animals shares some features with language. Within the context of their family, normal children and young non-human primates develop proficiency in the nuances of their species-specific vocal communication system. Engaging in speech-like phonetic activity, or babbling, occurs in all normal children regardless of their native language. Similar periods of vocal development have not been described previously for non-human primates. However, in the pygmy marmoset, a South American monkey, we found that the primary vocal behavior of infants parallels many characteristics of human infant babbling. These analogous features include universality, repetition, use of a subset of the adult vocal repertoire, recognizably adult-like vocal structure and lack of a clear vocal referent. Also, like human infants, young marmosets develop in a closely knit family unit that includes both parents and often older siblings. In this context, the babbling-like behavior of the marmoset infant stimulates interaction with caregivers, thereby serving a key role in the infant's own development. These developmental and social processes indicate that the study of vocal development in non-human primate species can provide insights into the function of babbling in humans.

Vision is our most powerful sense and, arguably, it gives us our most vivid sensory and imaginal experiences. It is also one of the best understood systems in contemporary neuroscience. Yet, contrary to both traditional assumptions and our phenomenological intuition, recent research has shown that vision is not a monolithic system that creates a single general-purpose representation in the brain. For example, selective brain damage can compromise visuomotor control while leaving perception intact, and damage elsewhere can compromise visual perception while leaving visuomotor control intact. Thus, it is becoming apparent that we have two (largely) separate visual systems. One of them is dedicated to the rapid and accurate guidance of our movements: it is a complex and powerful system, and yet it lies outside the realm of our conscious visual awareness. The other seems to provide our perceptual phenomenology, although its primary purpose is probably to provide suitably coded visual inputs for storage in and retrieval from memory. According to this conceptualization, both systems can be seen as serving our behaviour, but each does so on a different time scale. Recent studies suggest that neuropsychological research in humans can play a central role in bridging the gap between neurobiological studies of the monkey's visual system and the search to narrow down the brain mechanisms that mediate our visual awareness.

Among our most fundamental capacities are those that allow us to perceive, categorize and name objects. Recently, controversy has surrounded the question of how young children learn names for objects, in particular, the relative roles of perception and higher-level world knowledge. It is well known that adults depend strongly on conceptual knowledge in a variety of categorization tasks, including object naming. We argue, however, that perception may play a special role in early object naming and, in particular, that certain kinds of world knowledge known to guide adult naming may come to guide naming only rather late in development. Building early mechanisms of naming on a perceptual foundation that may be encapsulated, and thus shut off from more reflective processes, may explain in part why young children can easily and rapidly learn names for things from the adults around them, despite the fact that adults and children may possess very different conceptual organizations.

The study of object cognition over the past 25 years has proceeded in two largely non-interacting camps. One camp has studied object-based visual attention in adults, while the other has studied the object concept in infants. We briefly review both sets of literature and distill from the adult research a theoretical model that we apply to findings from the infant studies. The key notion in our model of object representation is the `sticky' index, a mechanism of selective attention that points at a physical object in a location. An object index does not represent any of the properties of the entity at which it points. However, once an index is pointing to an object, the properties of that object can be examined and featural information can be associated with, or `bound' to, its index. The distinction between indexing and feature binding underwrites the distinction between object individuation and object identification, a distinction that turns out to be crucial in both the adult attention and the infant object-concept literature. By developing the indexing model, we draw together two disparate sets of literature and suggest new ways to study object-based attention in infancy.

Artificial neural networks (ANNs) are widely used to model low-level neural activities and high-level cognitive functions. In this article, we review the applications of statistical inference for learning in ANNs. Statistical inference provides an objective way to derive learning algorithms both for training and for evaluation of the performance of trained ANNs. Solutions to the over-fitting problem by model-selection methods, based on either conventional statistical approaches or on a Bayesian approach, are discussed. The use of supervised and unsupervised learning algorithms for ANNs are reviewed. Training a multilayer ANN by supervised learning is equivalent to nonlinear regression. The ensemble methods, bagging and arching, described here, can be applied to combine ANNs to form a new predictor with improved performance. Unsupervised learning algorithms that are derived either by the Hebbian law for bottom-up self-organization, or by global objective functions for top-down self-organization are also discussed.

Dyslexia: Advances in theory and practice, Dyslexia Research Foundation and Center for Reading Research, 20-23 November 1997, Stavanger, Norway.

A new class of visuomotor neuron has been recently discovered in the monkey's premotor cortex: mirror neurons. These neurons respond both when a particular action is performed by the recorded monkey and when the same action, performed by another individual, is observed. Mirror neurons appear to form a cortical system matching observation and execution of goal-related motor actions. Experimental evidence suggests that a similar matching system also exists in humans. What might be the functional role of this matching system? One possible function is to enable an organism to detect certain mental states of observed conspecifics. This function might be part of, or a precursor to, a more general mind-reading ability. Two different accounts of mind-reading have been suggested. According to `theory theory', mental states are represented as inferred posits of a naive theory. According to `simulation theory', other people's mental states are represented by adopting their perspective: by tracking or matching their states with resonant states of one's own. The activity of mirror neurons, and the fact that observers undergo motor facilitation in the same muscular groups as those utilized by target agents, are findings that accord well with simulation theory but would not be predicted by theory theory.

Behavioral studies of memory and learning in both humans and animals support a role for sleep in the consolidation and integration of memories. Physiological studies of hippocampal and cortical activity as well as of brainstem neuromodulatory systems demonstrate the state-dependence of communication both between and within the neocortex and hippocampus. These findings are consonant with observed cognition during sleep and immediately following awakening.

The brains of higher mammals are extraordinary integrative devices. Signals from large numbers of functionally specialized groups of neurons distributed over many brain regions are integrated to generate a coherent, multimodal scene. Signals from the environment are integrated with ongoing, patterned neural activity that provides them with a meaningful context. We review recent advances in neurophysiology and neuroimaging that are beginning to reveal the neural mechanisms of integration. In addition, we discuss concepts and measures derived from information theory that lend a theoretical basis to the notion of complexity as integration of information and suggest new experimental tests of these concepts.

Attention and Performance XVIII: Control of Cognitive Processes, 13-17 July 1998, Windsor, UK.

Cognitive Neuroscience: The Biology of the Mind by Michael Gazzaniga, Richard Ivry and George Mangun, W.W. Norton, 1998. £24.95 (xv+587 pages) ISBN 0 393 97219 4 Findings and Current Opinion in Cognitive Neuroscience by Larry Squire and Stephen Kosslyn, MIT Press, 1998. $35.00 (vii+381 pages) ISBN 0 262 69204 X.

This review describes and motivates six principles for computational cognitive neuroscience models: biological realism, distributed representations, inhibitory competition, bidirectional activation propagation, error-driven task learning, and Hebbian model learning. Although these principles are supported by a number of cognitive, computational and biological motivations, the prototypical neural-network model (a feedforward back-propagation network) incorporates only two of them, and no widely used model incorporates all of them. It is argued here that these principles should be integrated into a coherent overall framework, and some potential synergies and conflicts in doing so are discussed.

There is a wealth of empirical data pertaining to the issue of neuropsychological impairment in depression. However, a coherent and comprehensive framework for understanding the disorder remains elusive. This review will briefly consider some of the important issues on which recent research has focused. It would be premature to derive firm conclusions in an area characterized by considerable confusion, so the aim of this review is to highlight the key areas that must be addressed. Three distinct questions are considered. The first concerns the neuropsychological specificity of the deficits associated with depression; whether they represent selective deficits or a more general profile of impairment. The second question is to determine how cognitive deficits might relate to clinical and demographic factors, including symptom severity, hospitalization, medication and ageing. Finally, a comprehensive theory of depression must also relate impairments to neuropathology, and evidence is now available from imaging studies that have attempted to elucidate neural substrates of neuropsychological deficits.

The prefrontal cortex (PFC) utilizes working memory to guide behavior and to release the organism from dependence on environmental cues and is commonly disrupted in neuropsychiatric disorders, normal aging, or exposure to uncontrollable stress. This review posits that the PFC is very sensitive to changes in the neuromodulatory inputs it receives from norepinephrine (NE) and dopamine (DA) systems and that this sensitivity can lead to marked changes in the working-memory functions of the PFC. While NE and DA have important beneficial influences on processing in this area, very high levels of catecholamine release, for example, during exposure to uncontrollable stress, disrupt the cognitive functions of the PFC. This fresh understanding of the neurochemical influences on PFC function has led to new treatments for cognitive disorders such as Attention Deficit Hyperactivity Disorder (ADHD), and may help to elucidate the prevalence of PFC dysfunction in other mental disorders.

The significance of the English past tense in current cognitive science is that it offers a clear contrast between a potentially rule-based system-the procedures for forming the regular past tense-and an unpredictable and idiosyncratic set of irregular forms. This contrast has become a focus for a wide-ranging debate about whether mental computation requires the use of symbols. Highly regular combinatorial phenomena, such as the regular past tense, are prime candidates for rule-based symbolic computation. Earlier research concentrated on the evidence for this during language acquisition, looking at how children learned the English regular and irregular verb systems. Over the last five years attention has shifted towards the properties of the adult system, and we review here some recent research into the neural correlates of the two types of procedure. The evidence suggests that there are divergences in the neural systems underlying the generation and perception of regular and irregular forms. Regular inflected forms seem to involve primarily combinatorial processes, while irregular forms appear to have a hybrid status, sharing their semantic properties with the regular forms but diverging in the phonological domain, where their form representations are stored as complete units. This indicates that the regular and irregular past tenses may not, after all, provide a clean contrast in the types of mental computation they implicate.