Outcome Prediction of Consciousness Disorders in the Acute Stage Based on a Complementary Motor Behavioural Tool.

Attaining an accurate diagnosis in the acute phase for severely brain-damaged patients presenting Disorders of Consciousness (DOC) is crucial for prognostic validity; such a diagnosis determines further medical management, in terms of therapeutic choices and end-of-life decisions. However, DOC evaluation based on validated scales, such as the Revised Coma Recovery Scale (CRS-R), can lead to an underestimation of consciousness and to frequent misdiagnoses particularly in cases of cognitive motor dissociation due to other aetiologies. The purpose of this study is to determine the clinical signs that lead to a more accurate consciousness assessment allowing more reliable outcome prediction. From the Unit of Acute Neurorehabilitation (University Hospital, Lausanne, Switzerland) between 2011 and 2014, we enrolled 33 DOC patients with a DOC diagnosis according to the CRS-R that had been established within 28 days of brain damage. The first CRS-R assessment established the initial diagnosis of Unresponsive Wakefulness Syndrome (UWS) in 20 patients and a Minimally Consciousness State (MCS) in the remaining13 patients. We clinically evaluated the patients over time using the CRS-R scale and concurrently from the beginning with complementary clinical items of a new observational Motor Behaviour Tool (MBT). Primary endpoint was outcome at unit discharge distinguishing two main classes of patients (DOC patients having emerged from DOC and those remaining in DOC) and 6 subclasses detailing the outcome of UWS and MCS patients, respectively. Based on CRS-R and MBT scores assessed separately and jointly, statistical testing was performed in the acute phase using a non-parametric Mann-Whitney U test; longitudinal CRS-R data were modelled with a Generalized Linear Model. Fifty-five per cent of the UWS patients and 77% of the MCS patients had emerged from DOC. First, statistical prediction of the first CRS-R scores did not permit outcome differentiation between classes; longitudinal regression modelling of the CRS-R data identified distinct outcome evolution, but not earlier than 19 days. Second, the MBT yielded a significant outcome predictability in the acute phase (p<0.02, sensitivity>0.81). Third, a statistical comparison of the CRS-R subscales weighted by MBT became significantly predictive for DOC outcome (p<0.02). The association of MBT and CRS-R scoring improves significantly the evaluation of consciousness and the predictability of outcome in the acute phase. Subtle motor behaviour assessment provides accurate insight into the amount and the content of consciousness even in the case of cognitive motor dissociation

Rivastigmine decreases brain damage in HIV patients with mild cognitive deficits.

Rivastigmine has been shown to improve cognition in HIV+ patients with minor neurocognitive disorders; however, the mechanisms underlying such beneficial effect are currently unknown. To assess whether rivastigmine therapy is associated with decreased brain inflammation and damage, we performed T1/T2* relaxometry and magnetization transfer imaging in 17 aviremic HIV+ patients with minor neurocognitive disorders enrolled on a crossed over randomized rivastigmine trial. Rivastigmine therapy was associated with changes in MRI metrics indicating a decrease in brain water content (i.e., edema reabsorption) and/or reduced demyelination/axonal damage. Furthermore, MRI changes correlated with cognitive improvement on rivastigmine therapy

Inter-hemispherical asymmetry in default-mode functional connectivity and BAIAP2 gene are associated with anger expression in ADHD adults

Attention deficit hyperactivity disorder (ADHD) is accompanied by resting-state alterations, including abnormal activity, connectivity and asymmetry of the default-mode network (DMN). Concurrently, recent studies suggested a link between ADHD and the presence of polymorphisms within the gene BAIAP2 (i.e., brain-specific angiogenesis inhibitor 1-associated protein 2), known to be differentially expressed in brain hemispheres. The clinical and neuroimaging correlates of this polymorphism are still unknown. We investigated the association between BAIAP2 polymorphisms and DMN functional connectivity (FC) asymmetry as well as behavioral measures in ADHD adults. Resting-state fMRI was acquired from 30 ADHD and 15 healthy adults. For each subject, rs7210438 and rs8079626 within the gene BAIAP2 were genotyped. ADHD severity, impulsiveness and anger were assessed for the ADHD group. Using multivariate analysis of variance, we found that genetic features do have an impact on DMN FC asymmetry. In particular, polymorphism rs8079626 affects medial frontal gyrus and inferior parietal lobule connectivity asymmetry, lower for AA than AG/GG carriers. Further, when combining FC asymmetry and the presence of the rs8079626 variant, we successfully predicted increased externalization of anger in ADHD. In conclusion, a complex interplay between genetic vulnerability and inter-hemispherical DMN FC asymmetry plays a role in emotion regulation in adult ADHD

Adaptive Strategy for the Statistical Analysis of Connectomes

We study an adaptive statistical approach to analyze brain networks represented by brain connection matrices of interregional connectivity (connectomes). Our approach is at a middle level between a global analysis and single connections analysis by considering subnetworks of the global brain network. These subnetworks represent either the inter-connectivity between two brain anatomical regions or by the intra-connectivity within the same brain anatomical region. An appropriate summary statistic, that characterizes a meaningful feature of the subnetwork, is evaluated. Based on this summary statistic, a statistical test is performed to derive the corresponding p-value. The reformulation of the problem in this way reduces the number of statistical tests in an orderly fashion based on our understanding of the problem. Considering the global testing problem, the p-values are corrected to control the rate of false discoveries. Finally, the procedure is followed by a local investigation within the significant subnetworks. We contrast this strategy with the one based on the individual measures in terms of power. We show that this strategy has a great potential, in particular in cases where the subnetworks are well defined and the summary statistics are properly chosen. As an application example, we compare structural brain connection matrices of two groups of subjects with a 22q11.2 deletion syndrome, distinguished by their IQ scores

Inter-hemispherical asymmetry in default-mode functional connectivity and BAIAP2 gene are associated with anger expression in ADHD adults

Attention deficit hyperactivity disorder (ADHD) is accompanied by resting-state alterations, including abnormal activity, connectivity and asymmetry of the default-mode network (DMN). Concurrently, recent studies suggested a link between ADHD and the presence of polymorphisms within the gene BAIAP2 (i.e., brain-specific angiogenesis inhibitor 1-associated protein 2), known to be differentially expressed in brain hemispheres. The clinical and neuroimaging correlates of this polymorphism are still unknown. We investigated the association between BAIAP2 polymorphisms and DMN functional connectivity (FC) asymmetry as well as behavioral measures in ADHD adults. Resting-state fMRI was acquired from 30 ADHD and 15 healthy adults. For each subject, rs7210438 and rs8079626 within the gene BAIAP2 were genotyped. ADHD severity, impulsiveness and anger were assessed for the ADHD group. Using multivariate analysis of variance, we found that genetic features do have an impact on DMN FC asymmetry. In particular, polymorphism rs8079626 affects medial frontal gyrus and inferior parietal lobule connectivity asymmetry, lower for AA than AG/GG carriers. Further, when combining FC asymmetry and the presence of the rs8079626 variant, we successfully predicted increased externalization of anger in ADHD. In conclusion, a complex interplay between genetic vulnerability and inter-hemispherical DMN FC asymmetry plays a role in emotion regulation in adult ADHD

Electrical Brain Responses to an Auditory Illusion and the Impact of Musical Expertise

The presentation of two sinusoidal tones, one to each ear, with a slight frequency mismatch yields an auditory illusion of a beating frequency equal to the frequency difference between the two tones; this is known as binaural beat (BB). The effect of brief BB stimulation on scalp EEG is not conclusively demonstrated. Further, no studies have examined the impact of musical training associated with BB stimulation, yet musicians' brains are often associated with enhanced auditory processing. In this study, we analysed EEG brain responses from two groups, musicians and non-musicians, when stimulated by short presentation (1 min) of binaural beats with beat frequency varying from 1 Hz to 48 Hz. We focused our analysis on alpha and gamma band EEG signals, and they were analysed in terms of spectral power, and functional connectivity as measured by two phase synchrony based measures, phase locking value and phase lag index. Finally, these measures were used to characterize the degree of centrality, segregation and integration of the functional brain network. We found that beat frequencies belonging to alpha band produced the most significant steady-state responses across groups. Further, processing of low frequency (delta, theta, alpha) binaural beats had significant impact on cortical network patterns in the alpha band oscillations. Altogether these results provide a neurophysiological account of cortical responses to BB stimulation at varying frequencies, and demonstrate a modulation of cortico-cortical connectivity in musicians' brains, and further suggest a kind of neuronal entrainment of a linear and nonlinear relationship to the beating frequencies

Improved statistical evaluation of group differences in connectomes by screening-filtering strategy with application to study maturation of brain connections between childhood and adolescence.

Detecting local differences between groups of connectomes is a great challenge in neuroimaging, because the large number of tests that have to be performed and the impact on multiplicity correction. Any available information should be exploited to increase the power of detecting true between-group effects. We present an adaptive strategy that exploits the data structure and the prior information concerning positive dependence between nodes and connections, without relying on strong assumptions. As a first step, we decompose the brain network, i.e., the connectome, into subnetworks and we apply a screening at the subnetwork level. The subnetworks are defined either according to prior knowledge or by applying a data driven algorithm. Given the results of the screening step, a filtering is performed to seek real differences at the node/connection level. The proposed strategy could be used to strongly control either the family-wise error rate or the false discovery rate. We show by means of different simulations the benefit of the proposed strategy, and we present a real application of comparing connectomes of preschool children and adolescents

Longitudinal study of neonatal brain tissue volumes in preterm infants and their ability to predict neurodevelopmental outcome

Premature birth has been associated with poor neurodevelopmental outcomes. However, the relation between such outcomes and brain growth in the neonatal period has not yet been fully elucidated. This study investigates longitudinal brain development between birth and term-equivalent age (TEA) by quantitative imaging in a cohort of premature infants born between 26 and 36 weeks gestational age (GA), to provide insight into the relation of brain growth with later neurodevelopmental outcomes.Longitudinal T2-weighted magnetic resonance images (MRI) of 84 prematurely born infants acquired shortly after birth and TEA were automatically segmented into cortical gray matter (CGM), unmyelinated white matter (UWM), subcortical gray matter (SGM), cerebellum (CB) and cerebrospinal fluid (CSF). General linear models and correlation analysis were used to study the relation between brain volumes and their growth, and perinatal variables. To investigate the ability of the brain volumes to predict children's neurodevelopmental outcome at 18-24 months and at 5 years of age, a linear discriminant analysis classifier was tested and several general linear models were fitted and compared by statistical tests.From birth to TEA, relative volumes of CGM, CB and CSF with respect to total intracranial volume increased, while relative volumes of UWM and SGM decreased. The fastest growing tissues between birth and TEA were found to be the CB and the CGM. Lower GA at birth was associated with lower growth rates of CGM, CB and total tissue. Among perinatal factors, persistent ductus arteriosus was associated with lower SGM, CB and IC growth rates, while sepsis was associated with lower CSF and intracranial volume growth rates.Model comparisons showed that brain tissue volumes at birth and at TEA contributed to the prediction of motor outcomes at 18-24 months, while volumes at TEA and volume growth rates contributed to the prediction of cognitive scores at 5 years of age. The family socio-economic status (SES) was not correlated with brain volumes at birth or at TEA, but was strongly associated with the cognitive outcomes at 18-24 months and 5 years of age.This study provides information about brain growth between birth and TEA in premature children with no focal brain lesions, and investigates their association with subsequent neurodevelopmental outcome. Parental SES was found to be a major determinant of neurodevelopmental outcome, unrelated to brain growth. However, further research is necessary in order to fully explain the variability of neurodevelopmental outcomes in this population