Hydroxyurea maintains working memory function in pediatric sickle cell disease.

Sickle cell disease (SCD) decreases the oxygen-carrying capacity of red blood cells. Children with SCD have reduced/restricted cerebral blood flow, resulting in neurocognitive deficits. Hydroxyurea is the standard treatment for SCD; however, whether hydroxyurea influences such effects is unclear. A key area of SCD-associated neurocognitive impairment is working memory, which is implicated in other cognitive and academic skills. The neural correlates of working memory can be tested using n-back tasks. We analyzed functional magnetic resonance imaging (fMRI) data of patients with SCD (20 hydroxyurea-treated patients and 11 controls, aged 7-18 years) while they performed n-back tasks. Blood-oxygenation level-dependent (BOLD) signals were assessed during working memory processing at 2 time points: before hydroxyurea treatment and ~1 year after treatment was initiated. Neurocognitive measures were also assessed at both time points. Our results suggested that working memory was stable in the treated group. We observed a treatment-by-time interaction in the right cuneus and angular gyrus for the 2- >0-back contrast. Searchlight-pattern classification of the 2 time points of the 2-back tasks identified greater changes in the pattern and magnitude of BOLD signals, especially in the posterior regions of the brain, in the control group than in the treated group. In the control group at 1-year follow-up, 2-back BOLD signals increased across time points in several clusters (e.g., right inferior temporal lobe, right angular gyrus). We hypothesize that these changes resulted from increased cognitive effort during working memory processing in the absence of hydroxyurea. In the treated group, 0- to 2-back BOLD signals in the right angular gyrus and left cuneus increased continuously with increasing working memory load, potentially related to a broader dynamic range in response to task difficulty and cognitive effort. These findings suggest that hydroxyurea treatment helps maintain working memory function in SCD.

Hydroxyurea maintains working memory function in pediatric sickle cell disease.

Pediatric patients with sickle cell disease (SCD) have decreased oxygen-carrying capacity in the blood and reduced or restricted cerebral blood flow resulting in neurocognitive deficits and cerebral infarcts. The standard treatment for children with SCD is hydroxyurea; however, the treatment-related neurocognitive effects are unclear. A key area of impairment in SCD is working memory, which is implicated in other cognitive and academic skills. N-back tasks are commonly used to investigate neural correlates of working memory. We analyzed functional magnetic resonance imaging (fMRI) of patients with SCD while they performed n-back tasks by assessing the blood-oxygenation level-dependent (BOLD) signals during working memory processing. Twenty hydroxyurea-treated and 11 control pediatric patients with SCD (7-18 years old) performed 0-, 1-, and 2-back tasks at 2 time points, once before hydroxyurea treatment (baseline) and ~1 year after treatment (follow-up). Neurocognitive measures (e.g., verbal comprehension, processing speed, full-scale intelligence quotient, etc.) were assessed at both time points. Although no significant changes in behavior performance of n-back tasks and neurocognitive measures were observed in the treated group, we observed a treatment-by-time interaction in the right cuneus and angular gyrus for the 2- > 0-back contrast. Through searchlight-pattern classifications in the treated and control groups to identify changes in brain activation between time points during the 2-back task, we found more brain areas, especially the posterior region, with changes in the pattern and magnitude of BOLD signals in the control group compared to the treated group. In the control group, increases in 2-back BOLD signals were observed in the right crus I cerebellum, right inferior parietal lobe, right inferior temporal lobe, right angular gyrus, left cuneus and left middle frontal gyrus at 1-year follow-up. Moreover, BOLD signals elevated as the working memory load increased from 0- to 1-back but did not increase further from 1- to 2-back in the right inferior temporal lobe, right angular gyrus, and right superior frontal gyrus. These observations may result from increased cognitive effort during working memory processing with no hydroxyurea treatment. In contrast, we found fewer changes in the pattern and magnitude of BOLD signals across time points in the treated group. Furthermore, BOLD signals in the left crus I cerebellum, right angular gyrus, left cuneus and right superior frontal gyrus of the treated group increased continuously with increasing working memory load from 0- to 2-back, potentially related to a broader dynamic range in response to task difficulty and cognitive effort. Collectively, these findings suggest that hydroxyurea treatment helped maintain working memory function in SCD.

A Discriminative Characterization of Heschl's Gyrus Morphology using Spectral Graph Features.

Heschl's Gyrus (HG), which hosts the primary auditory cortex, exhibits large variability not only in size but also in its gyrification patterns, within (i.e., between hemispheres) and between individuals. Conventional structural measures such as volume, surface area and thickness do not capture the full morphological complexity of HG, in particular, with regards to its shape. We present a method for characterizing the morphology of HG in terms of Laplacian eigenmodes of surface-based and volume-based graph representations of its structure, and derive a set of spectral graph features that can be used to discriminate HG subtypes. We applied this method to a dataset of 177 adults previously shown to display considerable variability in the shape of their HG, including data from amateur and professional musicians, as well as non-musicians. Results show the superiority of the proposed spectral graph features over conventional ones in differentiating HG subtypes, in particular, single HG versus Common Stem Duplications (CSDs). We anticipate the proposed shape features to be found beneficial in the domains of language, music and associated pathologies, in which variability of HG morphology has previously been established.

Ensemble Classification of Alzheimer's Disease and Mild Cognitive Impairment Based on Complex Graph Measures from Diffusion Tensor Images.

The human brain is a complex network of interacting regions. The gray matter regions of brain are interconnected by white matter tracts, together forming one integrative complex network. In this article, we report our investigation about the potential of applying brain connectivity patterns as an aid in diagnosing Alzheimer's disease and Mild Cognitive Impairment (MCI). We performed pattern analysis of graph theoretical measures derived from Diffusion Tensor Imaging (DTI) data representing structural brain networks of 45 subjects, consisting of 15 patients of Alzheimer's disease (AD), 15 patients of MCI, and 15 healthy subjects (CT). We considered pair-wise class combinations of subjects, defining three separate classification tasks, i.e., AD-CT, AD-MCI, and CT-MCI, and used an ensemble classification module to perform the classification tasks. Our ensemble framework with feature selection shows a promising performance with classification accuracy of 83.3% for AD vs. MCI, 80% for AD vs. CT, and 70% for MCI vs. CT. Moreover, our findings suggest that AD can be related to graph measures abnormalities at Brodmann areas in the sensorimotor cortex and piriform cortex. In this way, node redundancy coefficient and load centrality in the primary motor cortex were recognized as good indicators of AD in contrast to MCI. In general, load centrality, betweenness centrality, and closeness centrality were found to be the most relevant network measures, as they were the top identified features at different nodes. The present study can be regarded as a "proof of concept" about a procedure for the classification of MRI markers between AD dementia, MCI, and normal old individuals, due to the small and not well-defined groups of AD and MCI patients. Future studies with larger samples of subjects and more sophisticated patient exclusion criteria are necessary toward the development of a more precise technique for clinical diagnosis.

A toolbox for real-time subject-independent and subject-dependent classification of brain states from fMRI signals.

There is a recent increase in the use of multivariate analysis and pattern classification in prediction and real-time feedback of brain states from functional imaging signals and mapping of spatio-temporal patterns of brain activity. Here we present MANAS, a generalized software toolbox for performing online and offline classification of fMRI signals. MANAS has been developed using MATLAB, LIBSVM, and SVMlight packages to achieve a cross-platform environment. MANAS is targeted for neuroscience investigations and brain rehabilitation applications, based on neurofeedback and brain-computer interface (BCI) paradigms. MANAS provides two different approaches for real-time classification: subject dependent and subject independent classification. In this article, we present the methodology of real-time subject dependent and subject independent pattern classification of fMRI signals; the MANAS software architecture and subsystems; and finally demonstrate the use of the system with experimental results.