Filling a gap in the semantic gradient: Color associates and response set effects in the Stroop task

In the Stroop task, incongruent color associates (e.g., LAKE) interfere more with color identification than neutral words do (e.g., SEAT). However, color associates have historically been related to colors in the response set. Response set membership is an important factor in Stroop interference, because color words in the response set interfere more than color words not in the response set. It has not been established whether response set membership plays a role in the ability of a colorassociate to interfere with color identification. This issue was addressed in two experiments (one using vocal responses and one using manual responses) by comparing the magnitude of interference caused by color associates related to colors in the response set with that of interference caused by color associates unrelated to colors in the response set. The results of both experiments show that color associates unrelated to colors in the response set interfered with color identification more than neutral words did. However, the amount of interference was less than that from color associates that were related to colors in the response set. In addition, this pattern was consistent across response modalities. These results are discussed with respect to various theoretical accounts of Stroop interference.     

Sleep deprivation impairs object recognition in mice

Many studies in animals and humans suggest that sleep facilitates learning, memory consolidation, and retrieval. Moreover, sleep deprivation (SD) incurred after learning, impaired memory in humans, mice, rats, and hamsters. We investigated the importance of sleep and its timing in an object recognition task in OF1 mice subjected to 6h SD either immediately after the acquisition phase (0-6 SD) or 6h later (7-12 SD), and in corresponding undisturbed controls. Motor activity was continuously recorded with infrared sensors. All groups explored two familiar, previously encountered objects to a similar extent, both at the end of the acquisition phase and 24h later during the test phase, indicating intact familiarity detection. During the test phase 0-6 SD mice failed to discriminate between the single novel and the two familiar objects. In contrast, the 7-12 SD group and the two control groups explored the novel object significantly longer than the two familiar objects. Plasma corticosterone levels determined after SD did not differ from time-matched undisturbed controls, but were significantly below the level measured after learning alone. ACTH did not differ between the groups. Therefore, it is unlikely that stress contributed to the memory impairment. We conclude that the loss of sleep and the activities the mice engaged in during the SD, impaired recognition memory retrieval, when they occurred immediately after acquisition. The delayed SD enabled memory consolidation during the 6h when the mice were allowed to sleep, and had no detrimental effect on memory. Neither SD schedule impaired object familiarity processing, suggesting that only specific cognitive abilities were sensitive to the intervention. Sleep may either actively promote memory formation, or alternatively, sleep may provide optimal conditions of non-interference for consolidation.     

Learning in the absence of experience-dependent regulation of NMDAR composition

Olfactory discrimination (OD) learning consists of two phases: an initial N-methyl-D-aspartate (NMDA) receptor-sensitive rule-learning phase, followed by an NMDA receptor (NMDAR)-insensitive pair-learning phase. The rule-learning phase is accompanied by changes in the composition and function of NMDARs at synapses in the piriform cortex, resulting in a high level of the NR2a subunit relative to NR2b. Here we show that the learning-induced changes in NMDAR composition in the adult piriform cortex are due to a decrease in the level of the NR2b subunit protein, rather than an increase in the level of NR2a. Chronic administration of an NMDAR open channel blocker during training delays OD learning and blocks learning-induced changes in NMDAR subunit composition. However, the animals still learn the OD task. Our data demonstrate that learning can occur in the absence of activity-dependent regulation of NMDAR composition, suggesting differences in the mechanism for long-term maintenance of NMDAR-dependent and NMDAR-independent learning.     

Amygdala or hippocampus inactivation after retrieval induces temporary memory deficit

The hypothesis that memory is stored through a single stage of consolidation that results in a stable and lasting long-term memory has been challenged by the proposition that reactivation of a memory induces reconsolidation of the memory. The reconsolidation hypothesis is supported by evidence that, under some conditions, post-retrieval treatments affecting amygdala and hippocampus functioning impair subsequent retention performance. We now report that repeated retention testing attenuates the performance impairment induced by post-retrieval reversible inactivation of the amygdala and hippocampus of rats induced by tetrodotoxin. These findings challenge the reconsolidation hypothesis and suggest that the post-retrieval retention performance impairment is best explained as due to temporary retrieval failure.     

Inflammation in white matter: clinical and pathophysiological aspects

While the central nervous system (CNS) is generally thought of as an immunopriviledged site, immune-mediated CNS white matter damage can occur in both the perinatal period and in adults, and can result in severe and persistent neurological deficits. Periventricular leukomalacia (PVL) is an inflammatory white matter disease of premature infants that frequently results in cerebral palsy (CP). Clinical and experimental studies show that both hypoxic/ischemic and innate immune mechanisms contribute to the destruction of immature oligodendroglia and of axons in the deep cerebral white matter in PVL. No data are yet available as to whether there is any genetic predisposition to PVL or to its neurological sequelae. Multiple sclerosis (MS) is an inflammatory white matter disease that often begins in young adulthood, causes multifocal destruction of mature oligodendroglia and of axons, and eventually leads to substantial cumulative neurological disability. Certain genetic polymorphisms contribute to susceptibility to MS, and adaptive immune responses to myelin-associated self antigens, or to exogenous antigens that mimic these self antigens, play a central role in the pathophysiology of this disease.     

Making the case for objective performance metrics in newborn screening by tandem mass spectrometry

The expansion of newborn screening programs to include multiplex testing by tandem mass spectrometry requires understanding and close monitoring of performance metrics. This is not done consistently because of lack of defined targets, and interlaboratory comparison is almost nonexistent. Between July 2004 and April 2006 (N=176,185 cases), the overall performance metrics of the Minnesota program, limited to MS/MS testing, were as follows: detection rate 1:1,816, positive predictive value 37% (54% in 2006 till date), and false positive rate 0.09%. The repeat rate and the proportion of cases with abnormal findings actually been reported are new metrics proposed here as an objective mean to express the overall noise in a program, where noise is defined as the total number of abnormal results obtained using a given set of cut-off values. On the basis of our experience, we propose the following targets as evidence of adequate analytical and postanalytical performance: detection rate 1:3,000 or higher, positive predictive value>20%, and false positive rate<0.3%.     

Defining and diagnosing involuntary emotional expression disorder

Uncontrollable episodes of emotional expression occur in a variety of neurological conditions. This emotional disinhibition syndrome is characterized by episodes of crying or laughing that are unrelated to or out of proportion to the eliciting stimulus. This syndrome is common among patients with amyotrophic lateral sclerosis, multiple sclerosis, stroke, and traumatic brain injury and a variety of terms and definitions have been used to describe it. The confusing nomenclature has been a barrier to understanding, diagnosis, and treatment of this disorder. The authors propose a unifying term, involuntary emotional expression disorder (IEED), and provide diagnostic criteria for this disorder.     

Adjustments to the correction for attenuation

With respect to the often-present covariance between error terms of correlated variables, D. W. Zimmerman and R. H. Williams's (1977) adjusted correction for attenuation estimates the strength of the pairwise correlation between true scores without assuming independence of error scores. This article focuses on the derivation and analysis of formulas that perform the same function for partial and part correlation coefficients. Values produced by these formulas lie closer to the actual true-score coefficient than do the observed-score coefficients or those obtained by using C. Spearman's (1904) correction for attenuation. The new versions of the formulas thus allow analysts to use hypothetical values for error-score correlations to estimate values for the partial and part correlations between true scores while disregarding the independence-of-errors assumption.     

Profiling local optima in K-means clustering: developing a diagnostic technique

Using the cluster generation procedure proposed by D. Steinley and R. Henson (2005), the author investigated the performance of K-means clustering under the following scenarios: (a) different probabilities of cluster overlap; (b) different types of cluster overlap; (c) varying samples sizes, clusters, and dimensions; (d) different multivariate distributions of clusters; and (e) various multidimensional data structures. The results are evaluated in terms of the Hubert-Arabie adjusted Rand index, and several observations concerning the performance of K-means clustering are made. Finally, the article concludes with the proposal of a diagnostic technique indicating when the partitioning given by a K-means cluster analysis can be trusted. By combining the information from several observable characteristics of the data (number of clusters, number of variables, sample size, etc.) with the prevalence of unique local optima in several thousand implementations of the K-means algorithm, the author provides a method capable of guiding key data-analysis decisions.