Network connectivity abnormality profile supports a categorical-dimensional hybrid model of ADHD: Categorical-Dimensional Hybrid Model of ADHD

Attention-deficit/hyperactivity disorder (ADHD) is characterized by inattention, hyperactivity and impulsivity, but there is no consensus regarding whether ADHD exists on the extreme end of a continuum of normal behavior or represents a discrete disorder. In this study, we sought to characterize both the categorical and dimensional variations in network functional connectivity in order to identify neural connectivity mechanisms of ADHD. Functional connectivity analyses of resting-state fMRI data from 155 children with ADHD and 145 typically-developing children (TDC) defined the dorsal attention network (DA), default mode network (DM), salience processing network (SAL) and executive control network (CON). Regional alterations in connectivity associated with categorical diagnoses and dimensional symptom measures (inattention and hyperactivity/impulsivity) as well as their interaction were systematically characterized. Dimensional relationships between symptom severity measures and functional connectivity that did not differ between TDC and children with ADHD were observed for each network, supporting a dimensional characterization of ADHD. However, categorical differences in functional connectivity magnitude between TDC and children with ADHD were detected after accounting for dimensional relationships, indicating the existence of categorical mechanisms independent of dimensional effects. Additionally, differential dimensional relationships for TDC versus ADHD children demonstrated categorical differences in brain-behavior relationships. The patterns of network functional organization associated with categorical versus dimensional measures of ADHD accentuate the complexity of this disorder and support a dual characterization of ADHD etiology featuring both dimensional and categorical mechanisms

Fronto-parietal homotopy in resting-state functional connectivity predicts task-switching performance

Homotopic functional connectivity reflects the degree of synchrony in spontaneous activity between homologous voxels in the two hemispheres. Previous studies have associated increased brain homotopy and decreased white matter integrity with performance decrements on different cognitive tasks across the life-span. Here, we correlated functional homotopy, both at the whole-brain level and specifically in fronto-parietal network nodes, with task-switching performance in young adults. Cue-to-target intervals (CTI: 300 vs. 1200 ms) were manipulated on a trial-by-trial basis to modulate cognitive demands and strategic control. We found that mixing costs, a measure of task-set maintenance and monitoring, were significantly correlated to homotopy in different nodes of the fronto-parietal network depending on CTI. In particular, mixing costs for short CTI trials were smaller with lower homotopy in the superior frontal gyrus, whereas mixing costs for long CTI trials were smaller with lower homotopy in the supramarginal gyrus. These results were specific to the fronto-parietal network, as similar voxel-wise analyses within a control language network did not yield significant correlations with behavior. These findings extend previous literature on the relationship between homotopy and cognitive performance to task-switching, and show a dissociable role of homotopy in different fronto-parietal nodes depending on task-demands

Development of human brain cortical network architecture during infancy

The brain’s mature functional network architecture has been extensively studied but the early emergence of the brain’s network organization remains largely unknown. In this study, leveraging a large sample (143 subjects) with longitudinal rsfMRI scans (333 datasets), we aimed to characterize the important developmental process of the brain’s functional network architecture during the first two years of life. Based on spatial independent component analysis and longitudinal linear mixed effect modeling, our results unveiled the detailed topology and growth trajectories of nine cortical functional networks. Within networks, our findings clearly separated the brains networks into two categories: primary networks were topologically adult-like in neonates while higher-order networks were topologically incomplete and isolated in neonates but demonstrated consistent synchronization during the first two years of life (connectivity increases 0.13~0.35). Between networks, our results demonstrated both network-level connectivity decreases (−0.02~−0.64) and increases (0.05~0.18) but decreasing connections (n=14) dominated increasing ones (n=5). Finally, significant sex differences were observed with boys demonstrating faster network-level connectivity increases among the two frontoparietal networks (growth rate was 1.63e-4 per day for girls and 2.69e-4 per day for boys, p<1e-4). Overall, our study delineated the development of the whole brain functional architecture during the first two years of life featuring significant changes of both within- and between-network interactions

Consistent Anterior–Posterior Segregation of the Insula During the First 2 Years of Life

The human insula is a complex region characterized by heterogeneous cytoarchitecture, connectivity, and function. Subregional parcellation of the insula in adults has revealed an interesting anterior–posterior subdivision pattern that is highly consistent with its functional differentiation. However, the development of the insula's subregional segregation during the first 2 years of life remains unknown. The aim of this study was to test the hypothesis that similar segregation of the insula exists during this critical time period based on the resting-state functional magnetic resonance imaging study of a large cohort of infants (n = 143) with longitudinal scans. Our results confirmed a consistent anterior–posterior subdivision of the insula during the first 2 years of life with dissociable connectivity patterns associated with each cluster. Specifically, the anterior insula coupled more with frontal association areas, whereas the posterior insula integrated more with sensorimotor-related regions. More importantly, dramatic development of each subregion's functional network was observed, providing important neuronal correlates for the rapid advancement of its related functions during this time period

Functional Network Development During the First Year: Relative Sequence and Socioeconomic Correlations

The first postnatal year is characterized by the most dramatic functional network development of the human lifespan. Yet, the relative sequence of the maturation of different networks and the impact of socioeconomic status (SES) on their development during this critical period remains poorly characterized. Leveraging a large, normally developing infant sample with multiple longitudinal resting-state functional magnetic resonance imaging scans during the first year (N = 65, scanned every 3 months), we aimed to delineate the relative maturation sequence of 9 key brain functional networks and examine their SES correlations. Our results revealed a maturation sequence from primary sensorimotor/auditory to visual to attention/default-mode, and finally to executive control networks. Network-specific critical growth periods were also identified. Finally, marginally significant positive SES–brain correlations were observed at 6 months of age for both the sensorimotor and default-mode networks, indicating interesting SES effects on functional brain maturation. To the best of our knowledge, this is the first study delineating detailed longitudinal growth trajectories of all major functional networks during the first year of life and their SES correlations. Insights from this study not only improve our understanding of early brain development, but may also inform the critical periods for SES expression during infancy

Intersubject Variability of and Genetic Effects on the Brain's Functional Connectivity during Infancy

Infancy is a period featuring a high level of intersubject variability but the brain basis for such variability and the potential genetic/environmental contributions remain largely unexplored. The assessment of the brain's functional connectivity during infancy by the resting state functional magnetic resonance imaging (rsfMRI) technique (Biswal et al., 1995) provides a unique means to probe the brain basis of intersubject variability during infancy. In this study, an unusually large typically developing human infant sample including 58 singletons, 132 dizygotic twins, and 98 monozygotic twins with rsfMRI scans during the first 2 years of life was recruited to delineate the spatial and temporal developmental patterns of both the intersubject variability of and genetic effects on the brain's functional connectivity. Through systematic voxelwise functional connectivity analyses, our results revealed that the intersubject variability at birth features lower variability in primary functional areas but higher values in association areas. Although the relative pattern remains largely consistent, the magnitude of intersubject variability undergoes an interesting U-shaped growth during the first 2 years of life. Overall, the intersubject variability patterns during infancy show both adult-like and infant-specific characteristics (Mueller et al., 2013). On the other hand, age-dependent genetic effects were observed showing significant but bidirectional relationships with intersubject variability. The temporal and spatial patterns of the intersubject variability of and genetic contributions to the brain's functional connectivity documented in this study shed light on the largely uncharted functional development of the brain during infancy

Frequency of spontaneous BOLD signal shifts during infancy and correlates with cognitive performance

Numerous studies have been conducted to delineate the early development of different functional networks, based on measuring the temporal synchronization of spontaneous blood oxygenation level-dependent (BOLD) signals acquired using resting state functional MRI (rsfMRI). However, little attention has been paid to the change of the frequency properties of these signals during early brain development. Such frequency properties may reflect important physiological changes and potentially have significant cognitive consequences. In this study, leveraging a large (N=86 subjects), longitudinal sample of human infants scanned during the first two years of life, we aimed to specifically delineate the developmental changes of the frequency characteristics of spontaneous BOLD signals. Both whole-brain and network-level examinations were carried out and the frequency-behavior relationship was explored. Our results revealed a clear right-ward shift of BOLD signal frequency during the first year of life. Moreover, the power at the peak-frequency for sensorimotor and lateral visual networks correlates with domain-specific Mullen Scales in 1-year-olds, suggesting the behavioral significance of the BOLD signal frequency during infancy. Findings from this study shed light into early functional brain development and provide a new perspective for future searches for functional developmental abnormalities

Human brain development over the early years

Recent studies of the structural and functional development of the human brain over the early years have highlighted the rapid development of brain structures and their interconnectivity. Some regional functional specializations emerge within the first months after birth, while others have a more protracted course of development spanning over the first decade or longer. While some anatomical changes enable the emergence of new functions, evidence also points to the importance of resting state oscillations in sculpting neural architecture during development. In atypical development differences in brain structure, function and task-related activity in infancy often precede the emergence of later diagnostic behavioural symptoms

Development of Thalamocortical Connectivity during Infancy and Its Cognitive Correlations

Although commonly viewed as a sensory information relay center, the thalamus has been increasingly recognized as an essential node in various higher-order cognitive circuits, and the underlying thalamocortical interaction mechanism has attracted increasing scientific interest. However, the development of thalamocortical connections and how such development relates to cognitive processes during the earliest stages of life remain largely unknown. Leveraging a large human pediatric sample (N = 143) with longitudinal resting-state fMRI scans and cognitive data collected during the first 2 years of life, we aimed to characterize the age-dependent development of thalamocortical connectivity patterns by examining the functional relationship between the thalamus and nine cortical functional networks and determine the correlation between thalamocortical connectivity and cognitive performance at ages 1 and 2 years. Our results revealed that the thalamus–sensorimotor and thalamus–salience connectivity networks were already present in neonates, whereas the thalamus–medial visual and thalamus–default mode network connectivity emerged later, at 1 year of age. More importantly, brain–behavior analyses based on the Mullen Early Learning Composite Score and visual–spatial working memory performance measured at 1 and 2 years of age highlighted significant correlations with the thalamus–salience network connectivity. These results provide new insights into the understudied early functional brain development process and shed light on the behavioral importance of the emerging thalamocortical connectivity during infancy

Frequency drift in MR spectroscopy at 3T

Purpose: Heating of gradient coils and passive shim components is a common cause of instability in the B0 field, especially when gradient intensive sequences are used. The aim of the study was to set a benchmark for typical drift encountered during MR spectroscopy (MRS) to assess the need for real-time field-frequency locking on MRI scanners by comparing field drift data from a large number of sites. Method: A standardized protocol was developed for 80 participating sites using 99 3T MR scanners from 3 major vendors. Phantom water signals were acquired before and after an EPI sequence. The protocol consisted of: minimal preparatory imaging; a short pre-fMRI PRESS; a ten-minute fMRI acquisition; and a long post-fMRI PRESS acquisition. Both pre- and post-fMRI PRESS were non-water suppressed. Real-time frequency stabilization/adjustment was switched off when appropriate. Sixty scanners repeated the protocol for a second dataset. In addition, a three-hour post-fMRI MRS acquisition was performed at one site to observe change of gradient temperature and drift rate. Spectral analysis was performed using MATLAB. Frequency drift in pre-fMRI PRESS data were compared with the first 5:20 minutes and the full 30:00 minutes of data after fMRI. Median (interquartile range) drifts were measured and showed in violin plot. Paired t-tests were performed to compare frequency drift pre- and post-fMRI. A simulated in vivo spectrum was generated using FID-A to visualize the effect of the observed frequency drifts. The simulated spectrum was convolved with the frequency trace for the most extreme cases. Impacts of frequency drifts on NAA and GABA were also simulated as a function of linear drift. Data from the repeated protocol were compared with the corresponding first dataset using Pearson\u27s and intraclass correlation coefficients (ICC). Results: Of the data collected from 99 scanners, 4 were excluded due to various reasons. Thus, data from 95 scanners were ultimately analyzed. For the first 5:20 min (64 transients), median (interquartile range) drift was 0.44 (1.29) Hz before fMRI and 0.83 (1.29) Hz after. This increased to 3.15 (4.02) Hz for the full 30 min (360 transients) run. Average drift rates were 0.29 Hz/min before fMRI and 0.43 Hz/min after. Paired t-tests indicated that drift increased after fMRI, as expected (p \u3c 0.05). Simulated spectra convolved with the frequency drift showed that the intensity of the NAA singlet was reduced by up to 26%, 44 % and 18% for GE, Philips and Siemens scanners after fMRI, respectively. ICCs indicated good agreement between datasets acquired on separate days. The single site long acquisition showed drift rate was reduced to 0.03 Hz/min approximately three hours after fMRI. Discussion: This study analyzed frequency drift data from 95 3T MRI scanners. Median levels of drift were relatively low (5-min average under 1 Hz), but the most extreme cases suffered from higher levels of drift. The extent of drift varied across scanners which both linear and nonlinear drifts were observed