Read by QxMD icon Read

Behavioral and Brain Sciences

Christine Bastin, Gabriel Besson, Jessica Simon, Emma Delhaye, Marie Geurten, Sylvie Willems, Eric Salmon
Humans can recollect past events in details (recollection) and/or know that an object, person or place has been encountered before (familiarity). During the last two decades, there has been intense debate about how recollection and familiarity are organized in the brain. Here, we propose an Integrative Memory model which describes the distributed and interactive neurocognitive architecture of representations and operations underlying recollection and familiarity. In this architecture, the subjective experience of recollection and familiarity arises from the interaction between core systems storing particular kinds of representations shaped by specific computational mechanisms and an attribution system...
February 5, 2019: Behavioral and Brain Sciences
Falk Lieder, Thomas L Griffiths
Modeling human cognition is challenging because there are infinitely many mechanisms that can generate any given observation. Some researchers address this by constraining the hypothesis space through assumptions about what the human mind can and cannot do, while others constrain it through principles of rationality and adaptation. Recent work in economics, psychology, neuroscience, and linguistics has begun to integrate both approaches by augmenting rational models with cognitive constraints, incorporating rational principles into cognitive architectures, and applying optimality principles to understanding neural representations...
February 4, 2019: Behavioral and Brain Sciences
Romain Brette
"Neural coding" is a popular metaphor in neuroscience, where objective properties of the world are communicated to the brain in the form of spikes. Here I argue that this metaphor is often inappropriate and misleading. First, when neurons are said to encode experimental parameters, the neural code depends on experimental details that are not carried by the coding variable (e.g. the spike count). Thus, the representational power of neural codes is much more limited than generally implied. Second, neural codes carry information only by reference to things with known meaning...
February 4, 2019: Behavioral and Brain Sciences
Maria Babińska, Michal Bilewicz
No abstract text is available yet for this article.
January 2019: Behavioral and Brain Sciences
Nicolas Baumard
Since the Industrial Revolution, human societies have experienced high and sustained rates of economic growth. Recent explanations of this sudden and massive change in economic history have held that modern growth results from an acceleration of innovation. But it is unclear why the rate of innovation drastically accelerated in England in the 18th century. An important factor might be the alteration of individual preferences with regard to innovation due to the unprecedented living standards of the English during that period, for two reasons...
September 27, 2018: Behavioral and Brain Sciences
Christoph Hoerl, Teresa McCormack
We outline a dual systems approach to temporal cognition, which distinguishes between two cognitive systems for dealing with how things unfold over time - a temporal updating system and a temporal reasoning system - of which the former is both phylogenetically and ontogenetically more primitive than the latter, and which are at work alongside each other in adult human cognition. We describe the main features of each of the two systems, the types of behavior the more primitive temporal updating system can support, and the respects in which it is more limited than the temporal reasoning system...
September 25, 2018: Behavioral and Brain Sciences
Carsten K W De Dreu, Jörg Gross
Conflict can profoundly affect individuals and their groups. Oftentimes, conflict involves a clash between one side seeking change and increased gains through victory, and the other side defending the status quo and protecting against loss and defeat. However, theory and empirical research largely neglected these conflicts between attackers and defenders, and the strategic, social, and psychological consequences of attack and defense remain poorly understood. To fill this void, we model (i) the clashing of attack and defense as games of strategy, reveal that (ii) attack benefits from mismatching its target's level of defense, whereas defense benefits from matching the attacker's competitiveness, suggest that (iii) attack recruits neuro-endocrine pathways underlying behavioral activation and overconfidence, whereas defense invokes neural networks for behavioral inhibition, vigilant scanning and hostile attributions, and show that (iv) people invest less in attack than defense and attack often fails...
September 25, 2018: Behavioral and Brain Sciences
Katarzyna B Hooks, Jan Pieter Konsman, Maureen A O'Malley
Microbiota-gut-brain (MGB) research is a fast-growing field of inquiry with important implications for how human brain function and behaviour are understood. Researchers manipulate gut microbes ('microbiota') to reveal connections between intestinal microbiota and normal brain functions (e.g., cognition, emotion, memory) or pathological states (e.g., anxiety and mood disorders, neural developmental disorders such as autism). Many claims are made about causal relationships between gut microbiota and human behaviour...
September 12, 2018: Behavioral and Brain Sciences
Vikram K Jaswal, Nameera Akhtar
Progress in psychological science can be limited by a number of factors, not least of which are the starting assumptions of scientists themselves. We believe that some influential accounts of autism rest on a questionable assumption that many of its behavioral characteristics indicate a lack of social interest-an assumption that is flatly contradicted by the testimony of many autistic people themselves. In this paper, we challenge this assumption by describing alternative explanations for four such behaviors: (a) low levels of eye contact, (b) infrequent pointing, (c) motor stereotypies, and (d) echolalia...
June 19, 2018: Behavioral and Brain Sciences
Patrick Anselme, Onur Güntürkün
Food uncertainty has the effect of invigorating food-related responses. Psychologists have noted that mammals and birds respond more to a conditioned stimulus that unreliably predicts food delivery, and ecologists have shown that animals (especially small passerines) consume and/or hoard more food and can get fatter when access to that resource is unpredictable. Are these phenomena related? We think they are. Psychologists have proposed several mechanistic interpretations, while ecologists have suggested a functional interpretation: the effect of unpredictability on fat reserves and hoarding behavior is an evolutionary strategy acting against the risk of starvation when food is in short supply...
March 8, 2018: Behavioral and Brain Sciences
Dobromir Rahnev, Rachel N Denison
Human perceptual decisions are often described as optimal. Critics of this view have argued that claims of optimality are overly flexible and lack explanatory power. Meanwhile, advocates for optimality have countered that such criticisms single out a few selected papers. To elucidate the issue of optimality in perceptual decision making, we review the extensive literature on suboptimal performance in perceptual tasks. We discuss eight different classes of suboptimal perceptual decisions, including improper placement, maintenance, and adjustment of perceptual criteria, inadequate tradeoff between speed and accuracy, inappropriate confidence ratings, misweightings in cue combination, and findings related to various perceptual illusions and biases...
February 27, 2018: Behavioral and Brain Sciences
Harvey Whitehouse
Whether upheld as heroic or reviled as terrorism, throughout history people have been willing to lay down their lives for the sake of their groups. Why? Previous theories of extreme self-sacrifice have highlighted a range of seemingly disparate factors such as collective identity, outgroup hostility, and kin psychology. This paper attempts to integrate many of these factors into a single overarching theory based on several decades of collaborative research with a range of special populations, from tribes in Papua New Guinea to Libyan insurgents, and from Muslim fundamentalists in Indonesia to Brazilian football hooligans...
February 7, 2018: Behavioral and Brain Sciences
Denny Borsboom, Angélique Cramer, Annemarie Kalis
In the past decades, reductionism has dominated both research directions and funding policies in clinical psychology and psychiatry. However, the intense search for the biological basis of mental disorders has not resulted in conclusive reductionist explanations of psychopathology. Recently, network models have been proposed as an alternative framework for the analysis of mental disorders, in which mental disorders arise from the causal interplay between symptoms. In this paper, we show that this conceptualization can help understand why reductionist approaches in psychiatry and clinical psychology are on the wrong track...
January 24, 2018: Behavioral and Brain Sciences
Bradley C Love
Systematically comparing models that vary across components can be more informative and explanatory than determining whether behaviour is optimal, however defined. The process of model comparison has a number of benefits, including the possibility of integrating seemingly disparate empirical findings, understanding individual and group differences, and drawing theoretical connections between model proposals.
January 2018: Behavioral and Brain Sciences
Emilio Salinas, Joshua A Seideman, Terrence R Stanford
Rahnev & Denison (R&D) catalog numerous experiments in which performance deviates, often in subtle ways, from the theoretical ideal. We discuss an extreme case, an elementary behavior (reactive saccades to single targets) for which a simple contextual manipulation results in responses that are dramatically different from those expected based on reward maximization - and yet are highly informative and amenable to mechanistic examination.
January 2018: Behavioral and Brain Sciences
Andrew Howes, Richard L Lewis
We argue that a radically increased emphasis on (bounded) optimality can contribute to cognitive science by supporting prediction. Bounded optimality (computational rationality), an idea that borrowed from artificial intelligence, supports a priori behavioral prediction from constrained generative models of cognition. Bounded optimality thereby addresses serious failings with the logic and testing of descriptive models of perception and action.
January 2018: Behavioral and Brain Sciences
Valentin Wyart
Although the suboptimality of perceptual decision making is indisputable in its strictest sense, characterizing the nature of suboptimalities constitutes a valuable drive for future research. I argue that decision consistency offers a rarely measured, yet important behavioral metric for decomposing suboptimality (or, more generally, deviations from any candidate model of decision making) into ultimately predictable and inherently unpredictable components.
January 2018: Behavioral and Brain Sciences
Mintao Zhao, William H Warren
We highlight that optimal cue combination does not represent a general principle of cue interaction during navigation, extending Rahnev & Denison's (R&D) summary of nonoptimal perceptual decisions to the navigation domain. However, we argue that the term "suboptimality" does not capture the way visual and nonvisual cues interact in navigational decisions.
January 2018: Behavioral and Brain Sciences
Johannes Schultz, René Hurlemann
Current perspectives propose that observer models accounting for both optimal and suboptimal behaviour may yield real progress in understanding perception. We propose that such models could, in addition, be very useful for precisely characterising the variation in perception across healthy participants and those affected by psychiatric disorders, as well as the effects of neuromodulators such as oxytocin.
January 2018: Behavioral and Brain Sciences
Joachim Meyer
Optimality of any decision, including perceptual decisions, depends on the criteria used to evaluate outcomes and on the assumptions about available alternatives and information. In research settings, these are often difficult to define, and therefore, claims about optimality are equivocal. However, optimality is important in applied settings when evaluating, for example, the detection of abnormalities in medical images.
January 2018: Behavioral and Brain Sciences
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"