Mark A. Elliott

An improved framework for confound regression and filtering for control of motion artifact in the preprocessing of resting-state functional connectivity data.

Several recent reports in large, independent samples have demonstrated the influence of motion artifact on resting-state functional connectivity MRI (rsfc-MRI). Standard rsfc-MRI preprocessing typically includes regression of confounding signals and band-pass filtering. However, substantial heterogeneity exists in how these techniques are implemented across studies, and no prior study has examined the effect of differing approaches for the control of motion-induced artifacts. To better understand how in-scanner head motion affects rsfc-MRI data, we describe the spatial, temporal, and spectral characteristics of motion artifacts in a sample of 348 adolescents. Analyses utilize a novel approach for describing head motion on a voxelwise basis. Next, we systematically evaluate the efficacy of a range of confound regression and filtering techniques for the control of motion-induced artifacts. Results reveal that the effectiveness of preprocessing procedures on the control of motion is heterogeneous, and that improved preprocessing provides a substantial benefit beyond typical procedures. These results demonstrate that the effect of motion on rsfc-MRI can be substantially attenuated through improved preprocessing procedures, but not completely removed.

Impact of In-Scanner Head Motion on Multiple Measures of Functional Connectivity: Relevance for Studies of Neurodevelopment in Youth

It has recently been reported (Van Dijk et al., 2011) that in-scanner head motion can have a substantial impact on MRI measurements of resting-state functional connectivity. This finding may be of particular relevance for studies of neurodevelopment in youth, confounding analyses to the extent that motion and subject age are related. Furthermore, while Van Dijk et al. demonstrated the effect of motion on seed-based connectivity analyses, it is not known how motion impacts other common measures of connectivity. Here we expand on the findings of Van Dijk et al. by examining the effect of motion on multiple types of resting-state connectivity analyses in a large sample of children and adolescents (n=456). Following replication of the effect of motion on seed-based analyses, we examine the influence of motion on graphical measures of network modularity, dual-regression of independent component analysis, as well as the amplitude and fractional amplitude of low frequency fluctuation. In the entire sample, subject age was highly related to motion. Using a subsample where age and motion were unrelated, we demonstrate that motion has marked effects on connectivity in every analysis examined. While subject age was associated with increased within-network connectivity even when motion was accounted for, controlling for motion substantially attenuated the strength of this relationship. The results demonstrate the pervasive influence of motion on multiple types functional connectivity analysis, and underline the importance of accounting for motion in studies of neurodevelopment.

Sex differences in the structural connectome of the human brain

Significance Sex differences are of high scientific and societal interest because of their prominence in behavior of humans and nonhuman species. This work is highly significant because it studies a very large population of 949 youths (8–22 y, 428 males and 521 females) using the diffusion-based structural connectome of the brain, identifying novel sex differences. The results establish that male brains are optimized for intrahemispheric and female brains for interhemispheric communication. The developmental trajectories of males and females separate at a young age, demonstrating wide differences during adolescence and adulthood. The observations suggest that male brains are structured to facilitate connectivity between perception and coordinated action, whereas female brains are designed to facilitate communication between analytical and intuitive processing modes. Sex differences in human behavior show adaptive complementarity: Males have better motor and spatial abilities, whereas females have superior memory and social cognition skills. Studies also show sex differences in human brains but do not explain this complementarity. In this work, we modeled the structural connectome using diffusion tensor imaging in a sample of 949 youths (aged 8–22 y, 428 males and 521 females) and discovered unique sex differences in brain connectivity during the course of development. Connection-wise statistical analysis, as well as analysis of regional and global network measures, presented a comprehensive description of network characteristics. In all supratentorial regions, males had greater within-hemispheric connectivity, as well as enhanced modularity and transitivity, whereas between-hemispheric connectivity and cross-module participation predominated in females. However, this effect was reversed in the cerebellar connections. Analysis of these changes developmentally demonstrated differences in trajectory between males and females mainly in adolescence and in adulthood. Overall, the results suggest that male brains are structured to facilitate connectivity between perception and coordinated action, whereas female brains are designed to facilitate communication between analytical and intuitive processing modes.

Neuroimaging of the Philadelphia neurodevelopmental cohort.

The Philadelphia Neurodevelopmental Cohort (PNC) is a large-scale, NIMH funded initiative to understand how brain maturation mediates cognitive development and vulnerability to psychiatric illness, and understand how genetics impacts this process. As part of this study, 1445 adolescents ages 8-21 at enrollment underwent multimodal neuroimaging. Here, we highlight the conceptual basis for the effort, the study design, and the measures available in the dataset. We focus on neuroimaging measures obtained, including T1-weighted structural neuroimaging, diffusion tensor imaging, perfusion neuroimaging using arterial spin labeling, functional imaging tasks of working memory and emotion identification, and resting state imaging of functional connectivity. Furthermore, we provide characteristics regarding the final sample acquired. Finally, we describe mechanisms in place for data sharing that will allow the PNC to become a freely available public resource to advance our understanding of normal and pathological brain development.

Longitudinal study of skeletal muscle adaptations during immobilization and rehabilitation.

This study describes the metabolic, morphologic, neurologic, and functional adaptations observed in the plantar flexors during 8 weeks of lower leg immobilization and 10 weeks of physical therapy following ankle surgery. A combination of magnetic resonance imaging and spectroscopy, isokinetic and isometric muscle testing, and simple functional tests revealed many adaptive changes due to immobilization, including atrophy, loss of muscle strength, reduced central activation, increase in fatigue resistance, and an increase in inorganic phosphate content. After 10 weeks of physical therapy all alterations were reversed, with the exception of a remaining 5.5% deficit in total muscle cross‐sectional area.

Heterogeneous impact of motion on fundamental patterns of developmental changes in functional connectivity during youth

Several independent studies have demonstrated that small amounts of in-scanner motion systematically bias estimates of resting-state functional connectivity. This confound is of particular importance for studies of neurodevelopment in youth because motion is strongly related to subject age during this period. Critically, the effects of motion on connectivity mimic major findings in neurodevelopmental research, specifically an age-related strengthening of distant connections and weakening of short-range connections. Here, in a sample of 780 subjects ages 8-22, we re-evaluate patterns of change in functional connectivity during adolescent development after rigorously controlling for the confounding influences of motion at both the subject and group levels. We find that motion artifact inflates both overall estimates of age-related change as well as specific distance-related changes in connectivity. When motion is more fully accounted for, the prevalence of age-related change as well as the strength of distance-related effects is substantially reduced. However, age-related changes remain highly significant. In contrast, motion artifact tends to obscure age-related changes in connectivity associated with segregation of functional brain modules; improved preprocessing techniques allow greater sensitivity to detect increased within-module connectivity occurring with development. Finally, we show that subjects age can still be accurately estimated from the multivariate pattern of functional connectivity even while controlling for motion. Taken together, these results indicate that while motion artifact has a marked and heterogeneous impact on estimates of connectivity change during adolescence, functional connectivity remains a valuable phenotype for the study of neurodevelopment.

Alterations of fronto-temporal connectivity during word encoding in schizophrenia

Cognitive deficits, including impaired verbal memory, are prominent in schizophrenia and lead to increased disability. Functional neuroimaging of patients with schizophrenia performing memory tasks has revealed abnormal activation patterns in prefrontal cortex and temporo-limbic regions. Aberrant fronto-temporal interactions thus represent a potential pathophysiological mechanism underlying verbal memory deficits, yet this hypothesis of disturbed connectivity is not tested directly with standard activation studies. We performed within-subject correlations of frontal and temporal timeseries to measure functional connectivity during verbal encoding. Our results confirm earlier findings of aberrant fronto-temporal connectivity in schizophrenia, and extend them by identifying distinct alterations within dorsal and ventral prefrontal cortex. Relative to healthy controls, patients with schizophrenia had reduced connectivity between the dorsolateral prefrontal cortex (DLPFC) and temporal lobe areas including parahippocampus and superior temporal gyrus. In contrast, patients showed increased connectivity between a region of ventrolateral prefrontal cortex (VLPFC) and these same temporal lobe regions. Higher temporal-DLPFC connectivity during encoding was associated with better subsequent recognition accuracy in controls, but not patients. Temporal-VLPFC connectivity was uncorrelated with recognition accuracy in either group. The results suggest that reduced temporal-DLPFC connectivity in schizophrenia could underlie encoding deficits, and increased temporal-VLPFC connectivity may represent an ineffective compensatory effort.

In vivo ATP synthesis rates in single human muscles during high intensity exercise

1 In vivo ATP synthesis rates were measured in the human medial gastrocnemius muscle during high intensity exercise using localized 31P‐magnetic resonance spectroscopy (31P‐MRS). Six‐second localized spectra were acquired during and following a 30 s maximal voluntary rate exercise using a magnetic resonance image‐guided spectral localization technique. 2 During 30 s maximal voluntary rate exercise, ATPase fluxes were predominantly met by anaerobic ATP sources. Maximal in vivo glycogenolytic rates of 207 ± 48 mM ATP min−1 were obtained within 15 s, decreasing to 72 ± 34 mM ATP min−1 by the end of 30 s. In contrast, aerobic ATP synthesis rates achieved 85 ± 2 % of their maximal capacity within 9 s and did not change throughout the exercise. The ratio of peak glycolytic ATP synthesis rate to maximal oxidative ATP synthesis was 2.9 ± 0.9. 3 The non‐Pi, non‐CO2 buffer capacity was calculated to be 27.0 ± 6.2 slykes (millimoles acid added per unit change in pH). At the cessation of exercise, Pi, phosphomonoesters and CO2 were predicted to account for 17.2 ± 1.5, 5.57 ± 0.97 and 2.24 ± 0.34 slykes of the total buffer capacity. 4 Over the approximately linear range of intracellular pH recovery following the post‐exercise acidification, pHi recovered at a rate of 0.19 ± 0.03 pH units min−1. Proton transport capacity was determined to be 16.4 ± 4.1 mM (pH unit)−1 min−1 and corresponded to a maximal proton efflux rate of 15.3 ± 2.7 mM min−1. 5 These data support the observation that glycogenolytic and glycolytic rates are elevated in vivo in the presence of elevated Pi levels. The data do not support the hypothesis that glycogenolysis follows Michealis‐Menten kinetics with an apparent Km for [Pi]in vivo. 6 In vivo ‐measured ATP utilization rates and the initial dependence on PCr and glycolysis were similar to those previously reported in in situ studies involving short duration, high intensity exercise. This experimental approach presents a non‐invasive, quantitative measure of peak glycolytic rates in human skeletal muscle.

Benchmarking of participant-level confound regression strategies for the control of motion artifact in studies of functional connectivity.

&NA; Since initial reports regarding the impact of motion artifact on measures of functional connectivity, there has been a proliferation of participant‐level confound regression methods to limit its impact. However, many of the most commonly used techniques have not been systematically evaluated using a broad range of outcome measures. Here, we provide a systematic evaluation of 14 participant‐level confound regression methods in 393 youths. Specifically, we compare methods according to four benchmarks, including the residual relationship between motion and connectivity, distance‐dependent effects of motion on connectivity, network identifiability, and additional degrees of freedom lost in confound regression. Our results delineate two clear trade‐offs among methods. First, methods that include global signal regression minimize the relationship between connectivity and motion, but result in distance‐dependent artifact. In contrast, censoring methods mitigate both motion artifact and distance‐dependence, but use additional degrees of freedom. Importantly, less effective de‐noising methods are also unable to identify modular network structure in the connectome. Taken together, these results emphasize the heterogeneous efficacy of existing methods, and suggest that different confound regression strategies may be appropriate in the context of specific scientific goals. HighlightsWe evaluate 14 participant‐level de‐noising pipelines for functional connectivity.Pipeline performance is markedly heterogeneous.GSR minimizes the impact of motion but introduces distance dependence.Censoring reduces motion and improves network identifiability.

Functional Maturation of the Executive System during Adolescence

Adolescence is characterized by rapid development of executive function. Working memory (WM) is a key element of executive function, but it is not known what brain changes during adolescence allow improved WM performance. Using a fractal n-back fMRI paradigm, we investigated brain responses to WM load in 951 human youths aged 8–22 years. Compared with more limited associations with age, WM performance was robustly associated with both executive network activation and deactivation of the default mode network. Multivariate patterns of brain activation predicted task performance with a high degree of accuracy, and also mediated the observed age-related improvements in WM performance. These results delineate a process of functional maturation of the executive system, and suggest that this process allows for the improvement of cognitive capability seen during adolescence.