The uncertain brain: a co-ordinate based meta-analysis of the neural signatures supporting uncertainty during different contexts

Uncertainty is often inevitable in everyday life and can be both stressful and exciting. Given its relevance to psychopathology and wellbeing, recent research has begun to address the brain basis of uncertainty. In the current review we examined whether there are discrete and shared neural signatures for different uncertain contexts. From the literature we identified three broad categories of uncertainty currently empirically studied using functional MRI (fMRI): basic threat and reward uncertainty, decision-making under uncertainty, and associative learning under uncertainty. We examined the neural basis of each category by using a coordinate based metaanalysis, where brain activation foci from previously published fMRI experiments were drawn together (1998-2017; 87 studies). The analyses revealed shared and discrete patterns of neural activation for uncertainty, such as the insula and amygdala, depending on the category. Such findings will have relevance for researchers attempting to conceptualise uncertainty, as well as clinical researchers examining the neural basis of uncertainty in relation to psychopathology

Alterations in the functional neural circuitry supporting flexible choice behavior in autism spectrum disorders

Restricted and repetitive behaviors, and a pronounced preference for behavioral and environmental consistency, are distinctive characteristics of autism spectrum disorder (ASD). Alterations in frontostriatal circuitry that supports flexible behavior might underlie this behavioral impairment. In an functional magnetic resonance imaging study of 17 individuals with ASD, and 23 age-, gender- and IQ-matched typically developing control participants, reversal learning tasks were used to assess behavioral flexibility as participants switched from one learned response choice to a different response choice when task contingencies changed. When choice outcome after reversal was uncertain, the ASD group demonstrated reduced activation in both frontal cortex and ventral striatum, in the absence of task performance differences. When the outcomes of novel responses were certain, there was no difference in brain activation between groups. Reduced activation in frontal cortex and ventral striatum suggest problems in decision-making and response planning, and in processing reinforcement cues, respectively. These processes, and their integration, are essential for flexible behavior. Alterations in these systems may therefore contribute to a rigid adherence to preferred behavioral patterns in individuals with an ASD. These findings provide an additional impetus for the use of reversal learning paradigms as a translational model for treatment development targeting the domain of restricted and repetitive behaviors in ASD

Discounting of reward sequences: a test of competing formal models of hyperbolic discounting

Humans are known to discount future rewards hyperbolically in time. Nevertheless, a formal recursive model of hyperbolic discounting has been elusive until recently, with the introduction of the hyperbolically discounted temporal difference (HDTD) model. Prior to that, models of learning (especially reinforcement learning) have relied on exponential discounting, which generally provides poorer fits to behavioral data. Recently, it has been shown that hyperbolic discounting can also be approximated by a summed distribution of exponentially discounted values, instantiated in the μAgents model. The HDTD model and the μAgents model differ in one key respect, namely how they treat sequences of rewards. The μAgents model is a particular implementation of a Parallel discounting model, which values sequences based on the summed value of the individual rewards whereas the HDTD model contains a non-linear interaction. To discriminate among these models, we observed how subjects discounted a sequence of three rewards, and then we tested how well each candidate model fit the subject data. The results show that the Parallel model generally provides a better fit to the human data

Comment on Noll and Krier, "Some Implications of Cognitive Psychology for Risk Regulation"

We have known about systematic violations of the expected utility (EU) theory of choice for almost forty years, since Maurice Allais got Jimmie Savage to violate his own "sure-thing principle" (or "independence axiom") while making hypothetical choices over lunch in Paris. Savage was victimized by some combination of wine and intuition. The wine's effect is gone, but the intuition is not: devotion to EU sometimes produces unappealing choices

Neural activity associated with the passive prediction of ambiguity and risk for aversive events

In economic decision making, outcomes are described in terms of risk (uncertain outcomes with certain probabilities) and ambiguity (uncertain outcomes with uncertain probabilities). Humans are more averse to ambiguity than to risk, with a distinct neural system suggested as mediating this effect. However, there has been no clear disambiguation of activity related to decisions themselves from perceptual processing of ambiguity. In a functional magnetic resonance imaging (fMRI) experiment, we contrasted ambiguity, defined as a lack of information about outcome probabilities, to risk, where outcome probabilities are known, or ignorance, where outcomes are completely unknown and unknowable.Wemodified previously learned pavlovian CSstimuli such that they became an ambiguous cue and contrasted evoked brain activity both with an unmodified predictive CS(risky cue), and a cue that conveyed no information about outcome probabilities (ignorance cue). Compared with risk, ambiguous cues elicited activity in posterior inferior frontal gyrus and posterior parietal cortex during outcome anticipation. Furthermore, a similar set of regions was activated when ambiguous cues were compared with ignorance cues. Thus, regions previously shown to be engaged by decisions about ambiguous rewarding outcomes are also engaged by ambiguous outcome prediction in the context of aversive outcomes. Moreover, activation in these regions was seen even when no actual decision is made. Our findings suggest that these regions subserve a general function of contextual analysis when search for hidden information during outcome anticipation is both necessary and meaningful

Either, Or. Exploration of an Emerging Decision Theory.

A novel decision theory is emerging out of sparse findings in economics, mathematics and, most importantly, psychology and computational cognitive science. It rejects a fundamental assumption of the theory of rational decision-making, namely, that uncertain belief rests on independent assessment of utility and probability, and includes envisioning possibilities within its scope. Several researchers working with these premises, independently of one another, arrived at the conclusion that decision is made by highlighting the positive features of the alternative that will be chosen while opposing it to a loosing alternative, whose unpleasant aspects have been stressed. This article frames together contributions from different disciplines, often unknown to one another, with the hope of improving the coordination of research efforts. Furthermore, it discusses the status of the novel theory with respect to our current idea of rationality.Rationality; Shackle; Shafer; Search for Dominant Structure; Differentiation -- Consolidation; Constraint Satisfaction Networks; Construction of Narratives

Early maternal separation impacts cognitive flexibility at the age of first independence in mice.

Early life adversity is associated with increased risk for mental and physical health problems, including substance abuse. Changes in neural development caused by early life insults could cause or complicate these conditions. Maternal separation (MS) is a model of early adversity for rodents. Clear effects of MS have been shown on behavioral flexibility in rats, but studies of effects of MS on cognition in mice have been mixed. We hypothesized that previous studies focused on adult mice may have overlooked a developmental transition point when juvenile mice exhibit greater flexibility in reversal learning. Here, using a 4-choice reversal learning task we find that early MS leads to decreased flexibility in post-weaning juvenile mice, but no significant effects in adults. In a further study of voluntary ethanol consumption, we found that adult mice that had experienced MS showed greater cumulative 20% ethanol consumption in an intermittent access paradigm compared to controls. Our data confirm that the MS paradigm can reduce cognitive flexibility in mice and may enhance risk for substance abuse. We discuss possible interpretations of these data as stress-related impairment or adaptive earlier maturation in response to an adverse environment

Student attitudes to games-based skills development: learning from video games in higher education

Qualitative interview data is presented in support of previously-published quantitative evidence that suggests commercial video games may be used to develop useful skills and competencies in undergraduate students. The purpose of the work described here was to document the attitudes of those students involved in the quantitative study and to explore how the game-based intervention was perceived. To this end, student attitudes to the use of specified games to develop communication skill, resourcefulness and adaptability are examined. A broadly positive perception of the games' efficacy for skills development is revealed, and the aspects of game play that students believe contribute to skills development are discussed. These aspects include the need to communicate with team mates in order to succeed, and the fluid, unpredictable nature of in-game challenges. It is suggested that while the games played an important role in skills development, interaction between students, facilitated by game play, was also a significant factor

Attention and associative learning in humans: An integrative review

This article presents a comprehensive survey of research concerning interactions between associative learning and attention in humans. Four main findings are described. First, attention is biased toward stimuli that predict their consequences reliably (learned predictiveness). This finding is consistent with the approach taken by Mackintosh (1975) in his attentional model of associative learning in nonhuman animals. Second, the strength of this attentional bias is modulated by the value of the outcome (learned value). That is, predictors of high-value outcomes receive especially high levels of attention. Third, the related but opposing idea that uncertainty may result in increased attention to stimuli (Pearce & Hall, 1980), receives less support. This suggests that hybrid models of associative learning, incorporating the mechanisms of both the Mackintosh and Pearce-Hall theories, may not be required to explain data from human participants. Rather, a simpler model, in which attention to stimuli is determined by how strongly they are associated with significant outcomes, goes a long way to account for the data on human attentional learning. The last main finding, and an exciting area for future research and theorizing, is that learned predictiveness and learned value modulate both deliberate attentional focus, and more automatic attentional capture. The automatic influence of learning on attention does not appear to fit the traditional view of attention as being either goal-directed or stimulus-driven. Rather, it suggests a new kind of “derived” attention

Measuring cognitive load and cognition: metrics for technology-enhanced learning

This critical and reflective literature review examines international research published over the last decade to summarise the different kinds of measures that have been used to explore cognitive load and critiques the strengths and limitations of those focussed on the development of direct empirical approaches. Over the last 40 years, cognitive load theory has become established as one of the most successful and influential theoretical explanations of cognitive processing during learning. Despite this success, attempts to obtain direct objective measures of the theory's central theoretical construct – cognitive load – have proved elusive. This obstacle represents the most significant outstanding challenge for successfully embedding the theoretical and experimental work on cognitive load in empirical data from authentic learning situations. Progress to date on the theoretical and practical approaches to cognitive load are discussed along with the influences of individual differences on cognitive load in order to assess the prospects for the development and application of direct empirical measures of cognitive load especially in technology-rich contexts