Cognitive control, otherwise known as executive function, refers to our ability to flexibly adjust or regulate habitual actions or behaviors. As a cluster of separable components, it depends heavily on the prefrontal cortex, one of the last brain regions to reach adult maturity. Cognitive control processes are thought to be among the key factors for scholastic success, and thus, underdeveloped cognitive control abilities might contribute to an achievement gap. In this chapter, we first discuss the prolonged maturation of the prefrontal cortex that leads to delayed emergence of cognitive control abilities in children. We briefly describe some of the functional effects of prolonged maturation of the prefrontal cortex. We then discuss how experience and environmental factors such as education and socioeconomic status may affect the development of cognitive control abilities, before turning to cognitive training interventions as a promising avenue for reducing this cognitive “gap” in both healthy children and those with developmental disabilities. Taken together, our hope is that by understanding the interaction of brain development, environmental factors, and the promise of cognitive interventions in children, this knowledge can help to both guide educational achievement and inform educational policy.
Value plays a central role in practically every aspect of human life that requires a decision: whether we choose between different consumer goods, whether we decide which person we marry or which political candidate gets our vote, we choose the...
JDM is applied psychology. The ultimate goal is to improve judgments and decisions, or keep them from getting worse. In order to achieve this goal we need to know what good judgments and decisions are. That is, we need criteria for evaluation, so that we can gather data on the goodness of judgments, find out what makes them better or worse, and test method for improving them when there is room for improvement. This is the main function of normative models.
One year after publishing "False-Positive Psychology," we propose a simple implementation of disclosure that requires but 21 words to achieve full transparency. This article is written in a casual tone. It includes phone-taken pictures of milk-jars and references to ice-cream and sardines.
Repeated measures analyses of variance are the method of choice in many studies from experimental psychology and the neurosciences. Data from these fields are often characterized by small sample sizes, high numbers of factor levels of the within-subjects factor(s), and nonnormally distributed response variables such as response times. For a design with a single within-subjects factor, we investigated Type I error control in univariate tests with corrected degrees of freedom, the multivariate approach, and a mixed-model (multilevel) approach (SAS PROC MIXED) with Kenward–Roger’s adjusted degrees of freedom. We simulated multivariate normal and nonnormal distributions with varied population variance–covariance structures (spherical and nonspherical), sample sizes (N), and numbers of factor levels (K). For normally distributed data, as expected, the univariate approach with Huynh–Feldt correction controlled the Type I error rate with only very few exceptions, even if samples sizes as low as three were combined with high numbers of factor levels. The multivariate approach also controlled the Type I error rate, but it requires N ≥ K. PROC MIXED often showed acceptable control of the Type I error rate for normal data, but it also produced several liberal or conservative results. For nonnormal data, all of the procedures showed clear deviations from the nominal Type I error rate in many conditions, even for sample sizes greater than 50. Thus, none of these approaches can be considered robust if the response variable is nonnormally distributed. The results indicate that both the variance heterogeneity and covariance heterogeneity of the population covariance matrices affect the error rates.
Probability matching in sequential decision making is a striking violation of rational choice that has been observed in hundreds of experiments. Recent studies have demonstrated that matching persists even in described tasks in which all the information required for identifying a superior alternative strategy—maximizing—is present before the first choice is made. These studies have also indicated that maximizing increases when (1) the asymmetry in the availability of matching and maximizing strategies is reduced and (2) normatively irrelevant outcome feedback is provided. In the two experiments reported here, we examined the joint influences of these factors, revealing that strategy availability and outcome feedback operate on different time courses. Both behavioral and modeling results showed that while availability of the maximizing strategy increases the choice of maximizing early during the task, feedback appears to act more slowly to erode misconceptions about the task and to reinforce optimal responding. The results illuminate the interplay between “top-down” identification of choice strategies and “bottom-up” discovery of those strategies via feedback.
Although many visual stimulus databases exist, none has data on item similarity levels for multiple items of each kind of stimulus. We present such data for 50 sets of grayscale object photographs. Similarity measures between pictures in each set (e.g., 25 different buttons) were collected using a similarity-sorting method (Goldstone, Behavior Research Methods Instruments & Computers, 26(4):381–386, 1994). A validation experiment used data from 1 picture set and compared responses from standard pairwise measures. This showed close agreement. The similarity-sorting measures were then standardized across picture sets, using pairwise ratings. Finally, the standardized similarity distances were validated in a recognition memory experiment; false alarms increased when targets and foils were more similar. These data will facilitate memory and perception research that needs to make comparisons between stimuli with a range of known target–foil similarities.
Three dual-task experiments were designed to assess the contribution of executive cognitive functions to the perception of time. Each experiment combined a serial temporal production timing task with an executive task emphasizing either shifting, updating, or inhibition. The experiments uncovered evidence of bidirectional interference between the concurrent tasks, such that the executive tasks interfered with timing performance and the timing task interfered with executive performance. Each experiment also included 3 dual-task conditions in which subjects allocated attention to the concurrent tasks in specified proportions. The results showed a reciprocal tradeoff in performance on each task: More attention allocated to timing caused timing performance to improve and executive performance to decline, whereas more attention allocated to the executive task produced the opposite pattern. The findings suggest that timing relies on the same processing resources that support basic executive functions.
Humans are able to flexibly devise and implement rules to reach their desired goals. For simple situations, we can use single rules, such as “if traffic light is green then cross the street.” In most cases, however, more complex rule sets are required, involving the integration of multiple layers of control. Although it has been shown that prefrontal cortex is important for rule representation, it has remained unclear how the brain encodes more complex rule sets. Here, we investigate how the brain represents the order in which different parts of a rule set are evaluated. Participants had to follow compound rule sets that involved the concurrent application of two single rules in a specific order, where one of the rules always had to be evaluated first. The rules and their assigned order were independently manipulated. By applying multivariate decoding to fMRI data, we found that the identity of the current rule was encoded in a frontostriatal network involving right ventrolateral prefrontal cortex, right superior frontal gyrus, and dorsal striatum. In contrast, rule order could be decoded in the dorsal striatum and in the right premotor cortex. The nonhomogeneous distribution of information across brain areas was confirmed by follow-up analyses focused on relevant regions of interest. We argue that the brain encodes complex rule sets by “decomposing” them in their constituent features, which are represented in different brain areas, according to the aspect of information to be maintained.
Neural activity in orbitofrontal cortex has been linked to flexible representations of stimulus-outcome associations. Such value representations are known to emerge with learning, but the neural mechanisms supporting this phenomenon are not well understood. Here, we provide evidence for a causal role for NMDA receptors (NMDARs) in mediating spike pattern discriminability, neural plasticity, and rhythmic synchronization in relation to evaluative stimulus processing and decision making. Using tetrodes, single-unit spike trains and local field potentials were recorded during local, unilateral perfusion of an NMDAR blocker in rat OFC. In the absence of behavioral effects, NMDAR blockade severely hampered outcome-selective spike pattern formation to olfactory cues, relative to control perfusions. Moreover, NMDAR blockade shifted local rhythmic synchronization to higher frequencies and degraded its linkage to stimulus-outcome selective coding. These results demonstrate the importance of NMDARs for cue-outcome associative coding in OFC during learning and illustrate how NMDAR blockade disrupts network dynamics.
This article seeks to establish a rapprochement between explicitly Bayesian models of contextual effects in perception and neural network models of such effects, particularly the connectionist interactive activation (IA) model of perception.
Current views of semantic memory share the assumption that conceptual representations are based on multimodal experience, which activates distinct modality-specific brain regions. This proposition is widely accepted, yet little is known about how each modality contributes to conceptual knowledge and how the structure of this contribution varies across these multiple information sources. We used verbal feature lists, features from drawings, and verbal co-occurrence statistics from latent semantic analysis to examine the informational structure in four domains of knowledge: perceptual, functional, encyclopedic, and verbal. The goals of the analysis were three-fold: (1) to assess the structure within individual modalities; (2) to compare structures between modalities; and (3) to assess the degree to which concepts organize categorically or randomly. Our results indicated significant and unique structure in all four modalities: perceptually, concepts organize based on prominent features such as shape, size, color, and parts; functionally, they group based on use and interaction; encyclopedically, they arrange based on commonality in location or behavior; and verbally, they group associatively or relationally. Visual/perceptual knowledge gives rise to the strongest hierarchical organization and is closest to classic taxonomic structure. Information is organized somewhat similarly in the perceptual and encyclopedic domains, which differs significantly from the structure in the functional and verbal domains. Notably, the verbal modality has the most unique organization, which is not at all categorical but also not random. The idiosyncrasy and complexity of conceptual structure across modalities raise the question of how all of these modality-specific experiences are fused together into coherent, multifaceted yet unified concepts. Accordingly, both methodological and theoretical implications of the present findings are discussed.
The present paper builds on the idea that attention is largely in service of our actions. A framework and model which captures the allocation of attention for learning of goal-directed actions is proposed and developed. This framework highlights an evolutionary model based on the notion that rudimentary functions of the basal ganglia have become embedded into increasingly higher levels of networks which all contribute to adaptive learning. Supporting the proposed model, background literature is presented alongside key evidence based on experimental studies in the so-called “split-brain” (surgically divided cerebral hemispheres), and selected evidence from related areas of research. Although overlap with other existing findings and models is acknowledged, the proposed framework is an original synthesis of cognitive experimental findings with supporting evidence of a neural system and a carefully formulated model of attention. It is the hope that this new synthesis will be informative in fields of cognition and other fields of brain sciences and will lead to new avenues for experimentation across domains.
A theoretical landmark in the growing literature comparing language and music is the shared syntactic integration resource hypothesis (SSIRH; e.g., Patel, 2008), which posits that the successful processing of linguistic and musical materials relies, at least partially, on the mastery of a common syntactic processor. Supporting the SSIRH, Slevc, Rosenberg, and Patel (Psychonomic Bulletin & Review 16(2):374–381, 2009) recently reported data showing enhanced syntactic garden path effects when the sentences were paired with syntactically unexpected chords, whereas the musical manipulation had no reliable effect on the processing of semantic violations. The present experiment replicated Slevc et al.’s (2009) procedure, except that syntactic garden paths were replaced with semantic garden paths. We observed the very same interactive pattern of results. These findings suggest that the element underpinning interactions is the garden path configuration, rather than the implication of an alleged syntactic module. We suggest that a different amount of attentional resources is recruited to process each type of linguistic manipulations, hence modulating the resources left available for the processing of music and, consequently, the effects of musical violations.
Kornell and Bjork (Psychological Science 19:585–592, 2008) found that interleaving exemplars of different categories enhanced inductive learning of the concepts based on those exemplars. They hypothesized that the benefit of mixing exemplars from different categories is that doing so highlights differences between the categories. Kang and Pashler (Applied Cognitive Psychology 26:97–103, 2012) obtained results consistent with this discriminative-contrast hypothesis: Interleaving enhanced inductive learning, but temporal spacing, which does not highlight category differences, did not. We further tested the discriminative-contrast hypothesis by examining the effects of interleaving and spacing, as well as their combined effects. In three experiments, using photographs of butterflies and birds as the stimuli, temporal spacing was harmful when it interrupted the juxtaposition of interleaved categories, even when total spacing was held constant, supporting the discriminative-contrast hypothesis. Temporal spacing also had value, however, when it did not interrupt discrimination processing.
Huge amounts of money are spent every year on unlearning programs—in drug-treatment facilities, prisons, psychotherapy clinics, and schools. Yet almost all of these programs fail, since recidivism rates are high in each of these fields. Progress on this problem requires a better understanding of the mechanisms that make unlearning so difficult. Much cognitive neuroscience evidence suggests that an important component of these mechanisms also dictates success on categorization tasks that recruit procedural learning and depend on synaptic plasticity within the striatum. A biologically detailed computational model of this striatal-dependent learning is described (based on Ashby & Crossley, 2011). The model assumes that a key component of striatal-dependent learning is provided by interneurons in the striatum called the tonically active neurons (TANs), which act as a gate for the learning and expression of striatal-dependent behaviors. In their tonically active state, the TANs prevent the expression of any striatal-dependent behavior. However, they learn to pause in rewarding environments and thereby permit the learning and expression of striatal-dependent behaviors. The model predicts that when rewards are no longer contingent on behavior, the TANs cease to pause, which protects striatal learning from decay and prevents unlearning. In addition, the model predicts that when rewards are partially contingent on behavior, the TANs remain partially paused, leaving the striatum available for unlearning. The results from 3 human behavioral studies support the model predictions and suggest a novel unlearning protocol that shows promising initial signs of success.
The superior capability of cognitive experts largely depends on automatic, quick information processing, which is often referred to as intuition. Intuition develops following extensive long-term training. There are many cognitive models on intuition development, but its neural basis is not known. Here we trained novices for 15 weeks to learn a simple board game and measured their brain activities in early and end phases of the training while they quickly generated the best next-move to a given board pattern. We found that the activation in the head of caudate nucleus developed over the course of training, in parallel to the development of the capability to quickly generate the best next-move, and the magnitude of the caudate activity was correlated with the subject's performance. In contrast, cortical activations, which already appeared in the early phase of training, did not further change. Thus, neural activation in the caudate head, but not those in cortical areas, tracked the development of capability to quickly generate the best next-move, indicating that circuitries including the caudate head may automate cognitive computations.
Organization of behavior into a nested hierarchy of tasks and subtasks is characteristic of purposive cognition in humans. While frontoparietal regions have been shown to represent many kinds of task events, their representation of task/subtask structure has not been directly investigated. On each trial of the current study, participants carried out a sequence of four visual target detections organized by task context into subtasks of different structure (three and one or two and two). Through extended regions of frontoparietal cortex, activity elicited by target detections depended upon the hierarchical level of the episode completed. Target detections completing the entire trial elicited greatest activity, followed by targets completing a subtask, and finally targets within one subtask. Results depended on task and subtask completion, rather than the complexity of the next task stage to be established. We suggest that, through large regions of frontoparietal cortex, control representations direct each step of a behavioral program. Completion of a subtask revises control representations related just to this subtask, leaving those related to the overarching task episode intact, while completion of the entire task revises the entire assembly of representations.
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