Intervention Models in Functional Connectivity Identification Applied to fMRI

Recent advances in neuroimaging techniques have provided precise spatial localization of brain activation applied in several neuroscience subareas. The development of functional magnetic resonance imaging (fMRI), based on the BOLD signal, is one of the most popular techniques related to the detection of neuronal activation. However, understanding the interactions between several neuronal modules is also an important task, providing a better comprehension about brain dynamics. Nevertheless, most connectivity studies in fMRI are based on a simple correlation analysis, which is only an association measure and does not provide the direction of information flow between brain areas. Other proposed methods like structural equation modeling (SEM) seem to be attractive alternatives. However, this approach assumes prior information about the causality direction and stationarity conditions, which may not be satisfied in fMRI experiments. Generally, the fMRI experiments are related to an activation task; hence, the stimulus conditions should also be included in the model. In this paper, we suggest an intervention analysis, which includes stimulus condition, allowing a nonstationary modeling. Furthermore, an illustrative application to real fMRI dataset from a simple motor task is presented

Resting state functional connectivity in the default mode network and aerobic exercise in young adults

Around the world Alzheimer’s Disease (AD) is on the rise. Previous studies have shown the default mode network (DMN) sees changes with AD progression as the disease erodes away cortical areas. Aerobic exercise with significant increases to cardiorespiratory fitness could show neuro-protective changes to delay AD. This study will explore if functional connectivity changes in the DMN can be seen in a young adult sample by using group independent component analysis through FSL MELODIC. The young adult sample of 19 were selected from a larger study at the Brain Plasticity and Neuroimaging Laboratory at Boston University. The participants engaged in a twelve-week exercise intervention in either a strength training or aerobic training group. They also completed pre-intervention and post-intervention resting-state fMRI scans to evaluate change in functional connectivity in the default mode network. Cardiorespiratory fitness was assessed using a modified Balke protocol with pre-intervention and post-intervention VO2 max percentiles being used. Through two repeated-measure ANOVA analyses, this study found no significant increase in mean functional connectivity or cardiorespiratory fitness in the young adult sample. While improvements in mean VO2 max percentile and functional connectivity would have been seen with a larger sample size, this study adds to the literature by suggesting if fitness does not improve significantly, neither will functional connectivity in the default mode network

Functional connectivity in relation to motor performance and recovery after stroke.

Plasticity after stroke has traditionally been studied by observing changes only in the spatial distribution and laterality of focal brain activation during affected limb movement. However, neural reorganization is multifaceted and our understanding may be enhanced by examining dynamics of activity within large-scale networks involved in sensorimotor control of the limbs. Here, we review functional connectivity as a promising means of assessing the consequences of a stroke lesion on the transfer of activity within large-scale neural networks. We first provide a brief overview of techniques used to assess functional connectivity in subjects with stroke. Next, we review task-related and resting-state functional connectivity studies that demonstrate a lesion-induced disruption of neural networks, the relationship of the extent of this disruption with motor performance, and the potential for network reorganization in the presence of a stroke lesion. We conclude with suggestions for future research and theories that may enhance the interpretation of changing functional connectivity. Overall findings suggest that a network level assessment provides a useful framework to examine brain reorganization and to potentially better predict behavioral outcomes following stroke

Safety and efficacy of cognitive training plus epigallocatechin-3-gallate in young adults with Down's syndrome (TESDAD): a double-blind, randomised, placebo-controlled, phase 2 trial

Background Early cognitive intervention is the only routine therapeutic approach used for amelioration of intellectual deficits in individuals with Down's syndrome, but its effects are limited. We hypothesised that administration of a green tea extract containing epigallocatechin-3-gallate (EGCG) would improve the effects of non-pharmacological cognitive rehabilitation in young adults with Down's syndrome.; Methods We enrolled adults (aged 16-34 years) with Down's syndrome from outpatient settings in Catalonia, Spain, with any of the Down's syndrome genetic variations (trisomy 21, partial trisomy, mosaic, or translocation) in a double-blind, placebo-controlled, phase 2, single centre trial (TESDAD). Participants were randomly assigned at the IMIM-Hospital del Mar Medical Research Institute to receive EGCG (9 mg/kg per day) or placebo and cognitive training for 12 months. We followed up participants for 6 months after treatment discontinuation. We randomly assigned participants using random-number tables and balanced allocation by sex and intellectual quotient. Participants, families, and researchers assessing the participants were masked to treatment allocation. The primary endpoint was cognitive improvement assessed by neuropsychologists with a battery of cognitive tests for episodic memory, executive function, and functional measurements. Analysis was on an intention-to-treat basis. This trial is registered with ClinicalTrials.gov, number NCT01699711.; Findings The study was done between June 5, 2012, and June 6, 2014. 84 of 87 participants with Down's syndrome were included in the intention-to-treat analysis at 12 months (43 in the EGCG and cognitive training group and 41 in the placebo and cognitive training group). Differences between the groups were not significant on 13 of 15 tests in the TESDAD battery and eight of nine adaptive skills in the Adaptive Behavior Assessment System II (ABAS-II). At 12 months, participants treated with EGCG and cognitive training had significantly higher scores in visual recognition memory (Pattern Recognition Memory test immediate recall, adjusted mean difference: 6.23 percentage points [95% CI 0.31 to 12.14], p=0.039; d 0.4 [0.05 to 0.84]), inhibitory control (Cats and Dogs total score, adjusted mean difference: 0.48 [0.02 to 0.93], p=0.041; d 0.28 [0.19 to 0.74]; Cats and Dogs total response time, adjusted mean difference: -4.58 s [-8.54 to -0.62], p=0.024; d -0.27 [-0.72 to -0.20]), and adaptive behaviour (ABAS-II functional academics score, adjusted mean difference: 5.49 [2.13 to 8.86], p=0.002; d 0.39 [-0.06 to 0.84]). No differences were noted in adverse effects between the two treatment groups.; Interpretation EGCG and cognitive training for 12 months was significantly more effective than placebo and cognitive training at improving visual recognition memory, inhibitory control, and adaptive behaviour. Phase 3 trials with a larger population of individuals with Down's syndrome will be needed to assess and confirm the long-term efficacy of EGCG and cognitive training.; Funding Jerome Lejeune Foundation, Instituto de Salud Carlos III FEDER, MINECO, Generalitat de Catalunya.Peer ReviewedPostprint (author's final draft

Disentangling causal webs in the brain using functional Magnetic Resonance Imaging: A review of current approaches

In the past two decades, functional Magnetic Resonance Imaging has been used to relate neuronal network activity to cognitive processing and behaviour. Recently this approach has been augmented by algorithms that allow us to infer causal links between component populations of neuronal networks. Multiple inference procedures have been proposed to approach this research question but so far, each method has limitations when it comes to establishing whole-brain connectivity patterns. In this work, we discuss eight ways to infer causality in fMRI research: Bayesian Nets, Dynamical Causal Modelling, Granger Causality, Likelihood Ratios, LiNGAM, Patel's Tau, Structural Equation Modelling, and Transfer Entropy. We finish with formulating some recommendations for the future directions in this area

Neuroimaging of structural pathology and connectomics in traumatic brain injury: Toward personalized outcome prediction.

Recent contributions to the body of knowledge on traumatic brain injury (TBI) favor the view that multimodal neuroimaging using structural and functional magnetic resonance imaging (MRI and fMRI, respectively) as well as diffusion tensor imaging (DTI) has excellent potential to identify novel biomarkers and predictors of TBI outcome. This is particularly the case when such methods are appropriately combined with volumetric/morphometric analysis of brain structures and with the exploration of TBI-related changes in brain network properties at the level of the connectome. In this context, our present review summarizes recent developments on the roles of these two techniques in the search for novel structural neuroimaging biomarkers that have TBI outcome prognostication value. The themes being explored cover notable trends in this area of research, including (1) the role of advanced MRI processing methods in the analysis of structural pathology, (2) the use of brain connectomics and network analysis to identify outcome biomarkers, and (3) the application of multivariate statistics to predict outcome using neuroimaging metrics. The goal of the review is to draw the community's attention to these recent advances on TBI outcome prediction methods and to encourage the development of new methodologies whereby structural neuroimaging can be used to identify biomarkers of TBI outcome

Understanding Interest And Self-Efficacy In The Reading And Writing Of Students With Persisting Specific Learning Disabilities During Middle Childhood And Early Adolescence

Three methodological approaches were applied to understand the role of interest and self-efficacy in reading and/or writing in students without and with persisting specific learning disabilities (SLDs) in literacy. For each approach students in grades 4 to 9 completed a survey in which they rated 10 reading items and 10 writing items on a Scale 1 to 5; all items were the same but domain varied. The first approach applied Principal Component Analysis with Varimax Rotation to a sample that varied in specific kinds of literacy achievement. The second approach applied bidirectional multiple regressions in a sample of students with diagnosed SLDs-WL to (a) predict literacy achievement from ratings on interest and self-efficacy survey items; and (b) predict ratings on interest and self-efficacy survey items from literacy achievement. The third approach correlated ratings on the surveys with BOLD activation on an fMRI word reading/spelling task in a brain region associated with approach/avoidance and affect in a sample with diagnosed SLDs-WL. The first approach identified two components for the reading items (each correlated differently with reading skills) and two components for the writing items (each correlated differently with writing skills), but the components were not the same for both domains. Multiple regressions supported predicting interest and self-efficacy ratings from current reading achievement, rather than predicting reading achievement from interest and self-efficacy ratings, but also bidirectional relationships between interest or self-efficacy in writing and writing achievement. The third approach found negative correlations with amygdala connectivity for 2 reading items, but 5 positive and 2 negative correlations with amygdala connectivity for writing items; negative correlations may reflect avoidance and positive correlations approach. Collectively results show the relevance and domain-specificity of interest and self-efficacy in reading and writing for students with persisting SLDs in literacy