Female advantage in verbal learning revisited: a HUNT study.

The argument for a female advantage in word list learning is often based on partial observations that focus on a single component of the task. Using a large sample (N = 4403) of individuals 13-97 years of age from the general population, we investigated whether this advantage is consistently reflected in learning, recall, and recognition and how other cognitive abilities differentially support word list learning. A robust female advantage was found in all subcomponents of the task. Semantic clustering mediated the effects of short-term and working memory on long-delayed recall and recognition, and serial clustering on short-delayed recall. These indirect effects were moderated by sex, with men benefiting more from reliance on each clustering strategy than women. Auditory attention span mediated the effect of pattern separation on true positives in word recognition, and this effect was stronger in men than in women. Men had better short-term and working memory scores, but lower auditory attention span and were more vulnerable to interference both in delayed recall and recognition. Thus, our data suggest that auditory attention span and interference control (inhibition), rather than short-term or working memory scores, semantic and/or serial clustering on their own, underlie better performance on word list learning in women.

Poor Response Inhibition and Symptoms of Inattentiveness Are Core Characteristics of Lifetime Illicit Substance Use among Young Adults in the General Norwegian Population: The HUNT Study.

BACKGROUND: Impairments in neurocognitive functioning are associated with substance use behavior. Previous studies in neurocognitive predictors of substance use typically use self-report measures rather than neuropsychological performance measures and suffer from low sample sizes and use of clinical diagnostic cut offs. METHODS: Crossectional data from the HUNT4 Study (Helseundersøkelsen i Trøndelag) was used to study executive neuropsychological performance and self-reported measures of neurocognitive function associated with a history of illicit substance use in a general population sample of young adults in Norway. We performed both between group comparisons and logistic regression modeling and controlled for mental health symptomatology. RESULTS: Subjects in our cohort with a self-reported use of illicit substances had significantly higher self-reported mental health and neurocognitive symptom load. A logistic regression model with substance use as response included sex, commission errors and self-reported inattentiveness and anxiety as significant predictors. After 10-fold cross-validation this model achieved a moderate area under the receiver-operator curve of 0.63. To handle the class imbalance typically found in such population data, we also calculated balanced accuracy with a optimal model cut off of 0.234 with a sensitivity of 0.50 and specificity of 0.76 as well as precision recall-area under the curve of 0.28. CONCLUSIONS: Subtle cognitive dysfunction differentiates subjects with and without a history of illicit substance use. Neurocognitive factors outperformed the effects of depressive symptoms on substance use behavior in this cohort. We highlight the need for using adequate statistical tools for evaluating the performance of models in unbalanced datasets.

How Does the Accuracy of Intracranial Volume Measurements Affect Normalized Brain Volumes? Sample Size Estimates Based on 966 Subjects from the HUNT MRI Cohort.

BACKGROUND AND PURPOSE: The intracranial volume is commonly used for correcting regional brain volume measurements for variations in head size. Accurate intracranial volume measurements are important because errors will be propagated to the corrected regional brain volume measurements, possibly leading to biased data or decreased power. Our aims were to describe a fully automatic SPM-based method for estimating the intracranial volume and to explore the practical implications of different methods for obtaining the intracranial volume and normalization methods on statistical power. MATERIALS AND METHODS: We describe a method for calculating the intracranial volume that can use either T1-weighted or both T1- and T2-weighted MR images. The accuracy of the method was compared with manual measurements and automatic estimates by FreeSurfer and SPM-based methods. Sample size calculations on intracranial volume-corrected regional brain volumes with intracranial volume estimates from FreeSurfer, SPM, and our proposed method were used to explore the benefits of accurate intracranial volume estimates. RESULTS: The proposed method for estimating the intracranial volume compared favorably with the other methods evaluated here, with mean and absolute differences in manual measurements of -0.1% and 2.2%, respectively, and an intraclass correlation coefficient of 0.97 when using T1-weighted images. Using both T1- and T2-weighted images for estimating the intracranial volume slightly improved the accuracy. Sample size calculations showed that both the accuracy of intracranial volume estimates and the method for correcting the regional volume measurements affected the sample size. CONCLUSIONS: Accurate intracranial volume estimates are most important for ratio-corrected regional brain volumes, for which our proposed method can provide increased power in intracranial volume-corrected regional brain volume data.