Correlations between measures of executive attention and cortical thickness of left posterior middle frontal gyrus - a dichotic listening study

Background: The frontal lobe has been associated to a wide range of cognitive control functions and is also vulnerable to degeneration in old age. A recent study by Thomsen and colleagues showed a difference between a young and old sample in grey matter density and activation in the left middle frontal cortex (MFC) and performance on a dichotic listening task. The present study investigated this brain behaviour association within a sample of healthy older individuals, and predicted a positive correlation between performance in a condition requiring executive attention and measures of grey matter structure of the posterior left MFC. Methods: A dichotic listening forced attention paradigm was used to measure attention control functions. Subjects were instructed to report only the left or the right ear syllable of a dichotically presented consonant-vowel syllable pair. A conflict situation appears when subjects are instructed to report the left ear stimulus, caused by the conflict with the bottom-up, stimulus-driven right ear advantage. Overcoming this processing conflict was used as a measure of executive attention. Thickness and volumes of frontal lobe regions were derived from automated segmentation of 3D magnetic resonance image acquisitions. Results: The results revealed a statistically significant positive correlation between the thickness measure of the left posterior MFC and performance on the dichotic listening measures of executive attention. Follow-up analyses showed that this correlation was only statistically significant in the subgroup that showed the typical bottom-up, stimulus-driven right ear advantage. Conclusion: The results suggest that the left MFC is a part of an executive attention network, and that the dichotic listening forced attention paradigm may be a feasible tool for assessing subtle attentional dysfunctions in older adults

Representative factor generation for the interactive visual analysis of high-dimensional data

Datasets with a large number of dimensions per data item (hundreds or more) are challenging both for computational and visual analysis. Moreover, these dimensions have different characteristics and relations that result in sub-groups and/or hierarchies over the set of dimensions. Such structures lead to heterogeneity within the dimensions. Although the consideration of these structures is crucial for the analysis, most of the available analysis methods discard the heterogeneous relations among the dimensions. In this paper, we introduce the construction and utilization of representative factors for the interactive visual analysis of structures in high-dimensional datasets. First, we present a selection of methods to investigate the sub-groups in the dimension set and associate representative factors with those groups of dimensions. Second, we introduce how these factors are included in the interactive visual analysis cycle together with the original dimensions. We then provide the steps of an analytical procedure that iteratively analyzes the datasets through the use of representative factors. We discuss how our methods improve the reliability and interpretability of the analysis process by enabling more informed selections of computational tools. Finally, we demonstrate our techniques on the analysis of brain imaging study results that are performed over a large group of subjects

Mental health services use predicted by number of mental health problems and gender in a total population study

We examined the relationship between service use and the number of problem areas as reported by parents and teachers on questionnaires among children aged 7–9 years old in the Bergen Child Study, a total population study including more than 9000 children. A problem area was counted as present if the child scored above the 95th percentile on parent and/or teacher questionnaire. A total number of 13 problem areas were included. Odd ratios (ORs) for contact with child and adolescent mental health services (CAMH), school psychology services (SPS), health visiting nurse/physician, and school support were calculated with gender as covariate. The number of symptom areas was highly predictive of service use, showing a dose-response relationship for all services. Children scoring on ≥4 problem areas had a more than hundredfold risk of being in contact with CAMH services compared to children without problems. The mean number of problem areas for children in CAMH and SPS was 6.1 and 4.4 respectively, strongly supporting the ESSENCE model predicting multisymptomatology in children in specialized services. Even after controlling for number of problem areas, boys were twice as likely as girls to be in contact with CAMH, replicating previous findings of female gender being a strong barrier to mental health services.publishedVersio

The attention network test: a characteristic pattern of deficits in children with ADHD

<p>Abstract</p> <p>Background</p> <p>The Attention Network test (ANT) gives measures of different aspects of the complex process of attention. We ask if children with Attention Deficit Hyperactivity Disorder (ADHD) will show a characteristic pattern of deficits on this test.</p> <p>Methods</p> <p>The sample included 157 children (M = 10 years) who performed the child version of ANT as participants of the Bergen Child Study. Children with an ADHD diagnosis (N = 45) were compared to a group of children with other diagnoses (N = 55) and a group of children without any diagnosis (N = 57).</p> <p>Results</p> <p>The group of children with ADHD showed low accuracy scores and a variable response set, indicating an inattentive response style. No differences were found between the groups on RT and accuracy measures of the alerting, orienting, and conflict networks. A high correlation between full scale IQ (FSIQ) and ANT measures was only found in the ADHD group. When FSIQ score was included as a covariate, the group differences were not statistically significant on any ANT measure.</p> <p>Conclusion</p> <p>The present study showed that accuracy and variability measures rather than measures of the three attention networks conveyed the characteristic pattern of deficits in children with ADHD. The results emphasized the importance of including these measures to extend the sensitivity of the ANT, and the importance of reporting results both with and without FSIQ as a covariate.</p

Predicting conversion to Alzheimer’s disease in individuals with Mild Cognitive Impairment using clinically transferable features

Patients with Mild Cognitive Impairment (MCI) have an increased risk of Alzheimer’s disease (AD). Early identification of underlying neurodegenerative processes is essential to provide treatment before the disease is well established in the brain. Here we used longitudinal data from the ADNI database to investigate prediction of a trajectory towards AD in a group of patients defined as MCI at a baseline examination. One group remained stable over time (sMCI, n = 357) and one converted to AD (cAD, n = 321). By running two independent classification methods within a machine learning framework, with cognitive function, hippocampal volume and genetic APOE status as features, we obtained a cross-validation classification accuracy of about 70%. This level of accuracy was confirmed across different classification methods and validation procedures. Moreover, the sets of misclassified subjects had a large overlap between the two models. Impaired memory function was consistently found to be one of the core symptoms of MCI patients on a trajectory towards AD. The prediction above chance level shown in the present study should inspire further work to develop tools that can aid clinicians in making prognostic decisions.publishedVersio

Fractional anisotropy shows differential reduction in frontal-subcortical fiber bundles - A longitudinal MRI study of 76 middle-aged and older adults

Motivated by the frontal- and white matter (WM) retrogenesis hypotheses and the assumptions that fronto-striatal circuits are especially vulnerable in normal aging, the goal of the present study was to identify fiber bundles connecting subcortical nuclei and frontal areas and obtain site-specific information about age related fractional anisotropy (FA) changes. Multimodal magnetic resonance image acquisitions [3D T1-weighted and diffusion weighted imaging (DWI)] were obtained from healthy older adults (N = 76, range 49–80 years at inclusion) at two time points, 3 years apart. A subset of the participants (N = 24) was included at a third time-point. In addition to the frontal-subcortical fibers, the anterior callosal fiber (ACF) and the corticospinal tract (CST) was investigated by its mean FA together with tract parameterization analysis. Our results demonstrated fronto-striatal structural connectivity decline (reduced FA) in normal aging with substantial inter-individual differences. The tract parameterization analysis showed that the along tract FA profiles were characterized by piece-wise differential changes along their extension rather than being uniformly affected. To the best of our knowledge, this is the first longitudinal study detecting age-related changes in frontal-subcortical WM connections in normal aging.publishedVersio

Insomnia, Alcohol Consumption and ADHD Symptoms in Adults

Introduction Substance use disorders and insomnia are common in the general population, and particularly among adults with attention-deficit/hyperactivity disorder (ADHD). Here we investigated the relationship between insomnia, alcohol consumption and ADHD symptoms. Methods: Adults with an ADHD diagnosis (n = 235, 41.3% males) and controls (n = 184, 38% males) completed a questionnaire assessing insomnia (Bergen Insomnia Scale), alcohol consumption (Alcohol Use Disorders Identification Test), and current ADHD symptoms (Adult ADHD Self-report Scale). The majority of the sample (95%) gave additional information about childhood ADHD symptoms (Wender Utah Rating Scale), and information about lifetime occurrence of an internalizing disorder was included as part of background information. Results: Compared to controls, the ADHD group reported a higher frequency of insomnia, a higher quantity of consumed alcohol and a higher frequency of internalizing disorders. Current and childhood ADHD symptoms were more severe in those with than without insomnia. Scores on ADHD symptom scales were explained by the presence of insomnia and internalizing disorders, while the contribution from alcohol consumption was restricted to the control group. Discussion: The high functional impact of insomnia, alcohol misuse and internalizing disorders is well known. The present study contributed by focusing on their relations to ADHD symptoms, and by showing that strong relations were not restricted to adults with a clinical ADHD diagnosis. By this, the results put a critical light on a categorical delineation between adults with an ADHD diagnosis and population selected controls, and call for further studies including dimensional metrics of ADHD symptoms and co-occurring problems.publishedVersio

Functional activity level reported by an informant is an early predictor of Alzheimer’s disease

Background Loss of autonomy in day-to-day functioning is one of the feared outcomes of Alzheimer’s disease (AD), and relatives may have been worried by subtle behavioral changes in ordinary life situations long before these changes are given medical attention. In the present study, we ask if such subtle changes should be given weight as an early predictor of a future AD diagnosis. Methods Longitudinal data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) were used to define a group of adults with a mild cognitive impairment (MCI) diagnosis remaining stable across several visits (sMCI, n=360; 55-91 years at baseline), and a group of adults who over time converted from having an MCI diagnosis to an AD diagnosis (cAD, n=320; 55-88 years at baseline). Eleven features were used as input in a Random Forest (RF) binary classifier (sMCI vs. cAD) model. This model was tested on an unseen holdout part of the dataset, and further explored by three different permutation-driven importance estimates and a comprehensive post hoc machine learning exploration. Results The results consistently showed that measures of daily life functioning, verbal memory function, and a volume measure of hippocampus were the most important predictors of conversion from an MCI to an AD diagnosis. Results from the RF classification model showed a prediction accuracy of around 70% in the test set. Importantly, the post hoc analyses showed that even subtle changes in everyday functioning noticed by a close informant put MCI patients at increased risk for being on a path toward the major cognitive impairment of an AD diagnosis. Conclusion The results showed that even subtle changes in everyday functioning should be noticed when reported by relatives in a clinical evaluation of patients with MCI. Information of these changes should also be included in future longitudinal studies to investigate different pathways from normal cognitive aging to the cognitive decline characterizing different stages of AD and other neurodegenerative disorders.publishedVersio

A self-guided Internet-delivered intervention for adults with ADHD: a protocol for a randomized controlled trial

Background Attention-deficit/hyperactivity disorder (ADHD) in adulthood, with an estimated prevalence of 2–3%, is associated with several challenges in daily life functioning. The availability of evidence-based psychological interventions for adults with ADHD is still poor. Interventions delivered over the Internet on smartphones or personal computers may help to increase the availability of effective psychological interventions. The primary aim of this randomized controlled trial is to examine the efficacy of a self-guided Internet-delivered intervention on severity levels of ADHD symptomatology and quality of life. Methods We aim to include 118 participants with a self-reported ADHD diagnosis in a randomized controlled trial with two arms: 1) self-guided Internet-delivered intervention for coping with ADHD (N = 59); 2) self-guided online psychoeducation (control group, N = 59). After 3 months, the control group will be given access to the intervention. The primary clinical outcomes are inattention and quality of life. Secondary clinical outcomes are hyperactivity, stress and depression. Measures will be obtained at three time points: before (baseline), immediately after (8 weeks) and 3 months after the intervention. Uptake, usage, adherence and satisfaction will be explored. Discussion This RCT will provide valuable information on the clinical effectiveness of an Internet-delivered intervention for adults with ADHD. This study is, to our knowledge, one of the first randomized control trials that investigates the effects of a self-guided Internet-delivered psychological intervention in a fairly large group of adults with ADHD.publishedVersio

ASSERT - The Autism Symptom SElf-ReporT for adolescents and adults: Bifactor analysis and validation in a large adolescent population

With a view to developing a brief screening instrument for autism symptoms in a general population of adolescents, seven items from the Asperger syndrome (and high-functioning autism) diagnostic interview were adapted for use as self-report in an online questionnaire for youths aged 16–19 years (N = 10,220). The selected items target lack of social understanding (4 items) and rigid and repetitive behavior and interests (RRBI; 3 items). Factor analyses were performed, and the seven items were also validated against self-reported ASD diagnosis. Best statistical model fit was found for a bifactor model with one general factor and two domain specific factors tied to social difficulties and RRBI. Both the general and the domain specific factors were associated with self-reported ASD diagnoses. The scale (referred to as the Autism Symptom SElf-ReporT for Adolescents and Adults – ASSERT) had good screening properties with a receiver operating curve-area under the curve (ROC-AUC) of 0.87 and a diagnostic odds ratio (DOR) of 15.8. Applying a modified scoring of the scale further improved the screening properties leading to a ROC-AUC of 0.89 and a DOR of 24.9. The ASSERT holds promise as a brief self-report screen for autism symptoms in adolescents, and further studies should explore its usefulness for adults.publishedVersio