Amygdala oscillations and the consolidation of emotional memories

The amygdala receives multi-modal sensory inputs and projects to virtually all levels of the central nervous system. Via these widespread projections, the amygdala facilitates consolidation of emotionally arousing memories. How the amygdala promotes synaptic plasticity elsewhere in the brain remains unknown, however. Recent work indicates that amygdala neurons show theta activity during emotional arousal, and various types of oscillations during sleep. These synchronized neuronal events could promote synaptic plasticity by facilitating interactions between neocortical storage sites and temporal lobe structures involved in declarative memory.     

Seventh-Day Adventist Teachers’ Perceptions of Inclusion Classrooms and Identification of Challenges to Their Implementation

This qualitative study investigated the perceptions and challenges of Seventh-day Adventist teachers towards inclusion classrooms in the United States. For this study, 17 participants were interviewed using two 12-item interview protocols. The analysis of the teachers’ responses revealed five key perceptions. First, teachers have positive attitudes towards inclusion. Second, accommodations help students who are mildly disabled succeed in the regular classroom. Third, inclusion classrooms can be Christian based. Fourth, school personnel need to develop policies for accepting students with disabilities. Finally, Adventist teachers can identify children with special needs. Participants identified two challenges for implementing inclusion classrooms, first, developing policies and resources for use by teachers, and second, providing needed training to help teachers succeed in an inclusive classroom. The article concludes with recommendations for developing a successful inclusive educational program in Christian schools and recommendations future study.     

Lost ability to automatize task performance in old age

Can elderly adults automatize a new task? To address this question, 10 older adults each performed 10,080 training trials over 12 sessions on an easy but novel task. The psychological refractory period (PRP) procedure was then used to evaluate whether this highly practiced task, when presented as task 2 along with an unpracticed task 1, could proceed automatically. If automatic, task 2 processing should bypass the bottleneck and, therefore, not be delayed while central attention is devoted to task 1, yielding little dual-task interference. This is exactly what Maquestiaux, Laguë-Beauvais, Ruthruff, and Bherer (Memory and Cognition 36:1262-1282, 2008) previously observed for almost all younger adults, even with half the training on a more difficult task. Although extensive training reduced older adults’ reaction times to only 307 ms, a value virtually identical to that attained by Maquestiaux et al.’s (Memory and Cognition 36:1262-1282, 2008) younger adults, the highly practiced task 2 was slowed by 485 ms in the dual-task PRP procedure. Such a large slowing in older adults is striking given the easy tasks and massive amounts of practice. These findings demonstrate a qualitative change with age, in which older adults lose the ability to automatize novel tasks, which cannot be attributed merely to generalized cognitive slowing.     

Stepwise Latent Class Models for Explaining Group-Level Outcomes Using Discrete Individual-Level Predictors

Explaining group-level outcomes from individual-level predictors requires aggregating the individual-level scores to the group level and correcting the group-level estimates for measurement errors in the aggregated scores. However, for discrete variables it is not clear how to perform the aggregation and correction. It is shown how stepwise latent class analysis can be used to do this. First, a latent class model is estimated in which the scores on a discrete individual-level predictor are used to construct group-level latent classes. Second, this latent class model is used to aggregate the individual-level predictor by assigning the groups to the latent classes. Third, a group-level analysis is performed in which the aggregated measures are related to the remaining group-level variables while correcting for the measurement error in the class assignments. This stepwise approach is introduced in a multilevel mediation model with a single individual-level mediator, and compared to existing methods in a simulation study. We also show how a mediation model with multiple group-level latent variables can be used with multiple individual-level mediators and this model is applied to explain team productivity (group level) as a function of job control (individual level), job satisfaction (individual level), and enriched job design (group level).     

Explanatory,Multilevel Person-Fit Analysis of Response Consistency on the Spielberger State-Trait Anxiety Inventory

Self-report measures are vulnerable to concentration and motivation problems, leading to responses that may be inconsistent with the respondent's latent trait value. We investigated response consistency in a sample (N = 860) of cardiac patients with an implantable cardioverter defibrillator and their partners who completed the Spielberger State-Trait Anxiety Inventory on five measurement occasions. For each occasion and for both the state and trait subscales, we used the l ^p _z person-fit statistic to assess response consistency. We used multilevel analysis to model the between-person and within-person differences in the repeated observations of response consistency using time-dependent (e.g., mood states) and time-invariant explanatory variables (e.g., demographic characteristics). Respondents with lower education, undergoing psychological treatment, and with more post-traumatic stress disorder symptoms tended to respond less consistently. The percentages of explained variance in response consistency were small. Hence, we conclude that the results give insight into the causes of response inconsistency but that the identified explanatory variables are of limited practical value for identifying respondents at risk of producing invalid test results. We discuss explanations for the small percentage of explained variance and suggest alternative methods for studying causes of response inconsistency.     

Quelques remarques sur les ‘Tableaux de Beth’

Sans résumé     

Jean Wahl’s unassailable heritage

Continental Philosophy Review - Despite his unassailable heritage, the passionate thinker to whom Levinas dedicated Totalité et infini has today nearly been forgotten outside France. This...     

Can Children with Autism Recover? If So, How?

Although Autism Spectrum Disorders (ASD) are generally assumed to be lifelong, we review evidence that between 3% and 25% of children reportedly lose their ASD diagnosis and enter the normal range of cognitive, adaptive and social skills. Predictors of recovery include relatively high intelligence, receptive language, verbal and motor imitation, and motor development, but not overall symptom severity. Earlier age of diagnosis and treatment, and a diagnosis of Pervasive Developmental Disorder-Not Otherwise Specified are also favorable signs. The presence of seizures, mental retardation and genetic syndromes are unfavorable signs, whereas head growth does not predict outcome. Controlled studies that report the most recovery came about after the use of behavioral techniques. Residual vulnerabilities affect higher-order communication and attention. Tics, depression and phobias are frequent residual co-morbidities after recovery. Possible mechanisms of recovery include: normalizing input by forcing attention outward or enriching the environment; promoting the reinforcement value of social stimuli; preventing interfering behaviors; mass practice of weak skills; reducing stress and stabilizing arousal. Improving nutrition and sleep quality is non-specifically beneficial.