Functional connectivity MRI in infants: exploration of the functional organization of the developing brain

Measuring and interpreting individual differences in fetal, infant, and toddler neurodevelopment

As scientists interested in fetal, infant, and toddler (FIT) neurodevelopment, our research questions often focus on how individual children differ in their neurodevelopment and the predictive value of those individual differences for long-term neural and behavioral outcomes. Measuring and interpreting individual differences in neurodevelopment can present challenges: Is there a "standard" way for the human brain to develop? How do the semantic, practical, or theoretical constraints that we place on studying "development" influence how we measure and interpret individual differences? While it is important to consider these questions across the lifespan, they are particularly relevant for conducting and interpreting research on individual differences in fetal, infant, and toddler neurodevelopment due to the rapid, profound, and heterogeneous changes happening during this period, which may be predictive of long-term outcomes. This article, therefore, has three goals: 1) to provide an overview about how individual differences in neurodevelopment are studied in the field of developmental cognitive neuroscience, 2) to identify challenges and considerations when studying individual differences in neurodevelopment, and 3) to discuss potential implications and solutions moving forward.

Tale of Two n-Backs: Diverging Associations of Dorsolateral Prefrontal Cortex Activation With n-Back Task Performance

In studying the neural correlates of working memory (WM) ability via functional magnetic resonance imaging (fMRI) in health and disease, it is relatively uncommon for investigators to report associations between brain activation and measures of task performance. Additionally, how the choice of WM task impacts observed activation-performance relationships is poorly understood. We sought to illustrate the impact of WM task on brain-behavior correlations using two large, publicly available datasets. We conducted between-participants analyses of task-based fMRI data from two publicly available datasets: The Human Connectome Project (HCP; n = 866) and the Queensland Twin Imaging (QTIM) Study (n = 459). Participants performed two distinct variations of the n-back WM task with different stimuli, timings, and response paradigms. Associations between brain activation ([2-back - 0-back] contrast) and task performance (2-back % correct) were investigated separately in each dataset, as well as across datasets, within the dorsolateral prefrontal cortex (dlPFC), medial prefrontal cortex, and whole cortex. Global patterns of activation to task were similar in both datasets. However, opposite associations between activation and task performance were observed in bilateral pre-supplementary motor area and left middle frontal gyrus. Within the dlPFC, HCP participants exhibited a significantly greater activation-performance relationship in bilateral middle frontal gyrus relative to QTIM Study participants. The observation of diverging activation-performance relationships between two large datasets performing variations of the n-back task serves as a critical reminder for investigators to exercise caution when selecting WM tasks and interpreting neural activation in response to a WM task.

Longitudinal functional brain connectivity maturation in premature newborn infants: Modulatory influence of early music enrichment

Premature birth affects brain maturation, illustrated by altered brain functional connectivity at term equivalent age (TEA) and alters neurobehavioral outcome. To correct early developmental differences and improve neurological outcome, music during the neonatal intensive care unit (NICU) stay has been proposed as an auditory enrichment with modulatory effects on functional and structural brain development, but longitudinal effects of such interventions have not been studied so far. We longitudinally investigated resting-state functional connectivity (RS-FC) maturation in preterm infants (n = 43). Data-driven Independent Component Analyses (ICA) were performed on scans obtained at 33- and 40-week gestational age (GA), determining the presence of distinct resting-state networks (RSNs). Connectome analysis "accordance measure" quantitively examined the RS-FC both at 33- and 40-week GA. Further comparing the internetwork RS-FC at 33- and 40-week GA provided a circuitry of interest (COI) for significant maturational changes in which the effects on the RS-FC of a music intervention were tested. The connectome analyses resulted in a COI of RS-FC connections significantly maturing from 33 to 40 weeks GA, namely between the thalamic/brainstem and prefrontal-limbic, salience, sensorimotor, auditory, and prefrontal cortical networks; between the prefrontal-limbic and cerebellar, visual and left hemispheric precuneus networks; between the salience and visual, and cerebellar networks; and between the sensorimotor and auditory, and posterior cingulate/precuneus networks. The infants exposed to music exhibited significantly increased maturation in RS-FC between the thalamic/brainstem and salience networks, compared with controls. This study exemplifies that preterm infant RS-FC maturation is modulated through NICU music exposure, highlighting the importance of environmental enrichment for neurodevelopment in premature newborns.

Functional connectivity of the pediatric brain

PURPOSE

This review highlights the importance of functional connectivity in pediatric neuroscience, focusing on its role in understanding neurodevelopment and potential applications in clinical practice. It discusses various techniques for analyzing brain connectivity and their implications for clinical interventions in neurodevelopmental disorders.

METHODS

The principles and applications of independent component analysis and seed-based connectivity analysis in pediatric brain studies are outlined. Additionally, the use of graph analysis to enhance understanding of network organization and topology is reviewed, providing a comprehensive overview of connectivity methods across developmental stages, from fetuses to adolescents.

RESULTS

Findings from the reviewed studies reveal that functional connectivity research has uncovered significant insights into the early formation of brain circuits in fetuses and neonates, particularly the prenatal origins of cognitive and sensory systems. Longitudinal research across childhood and adolescence demonstrates dynamic changes in brain connectivity, identifying critical periods of development and maturation that are essential for understanding neurodevelopmental trajectories and disorders.

CONCLUSION

Functional connectivity methods are crucial for advancing pediatric neuroscience. Techniques such as independent component analysis, seed-based connectivity analysis, and graph analysis offer valuable perspectives on brain development, creating new opportunities for early diagnosis and targeted interventions in neurodevelopmental disorders, thereby paving the way for personalized therapeutic strategies.

Functional Localization of the Human Auditory and Visual Thalamus Using a Thalamic Localizer Functional Magnetic Resonance Imaging Task

Functional magnetic resonance imaging (fMRI) of the auditory and visual sensory systems of the human brain is an active area of investigation in the study of human health and disease. The medial geniculate nucleus (MGN) and lateral geniculate nucleus (LGN) are key thalamic nuclei involved in the processing and relay of auditory and visual information, respectively, and are the subject of blood-oxygen-level-dependent (BOLD) fMRI studies of neural activation and functional connectivity in human participants. However, localization of BOLD fMRI signal originating from neural activity in MGN and LGN remains a technical challenge, due in part to the poor definition of boundaries of these thalamic nuclei in standard T1-weighted and T2-weighted magnetic resonance imaging sequences. Here, we report the development and evaluation of an auditory and visual sensory thalamic localizer (TL) fMRI task that produces participant-specific functionally-defined regions of interest (fROIs) of both MGN and LGN, using 3 Tesla multiband fMRI and a clustered-sparse temporal acquisition sequence, in less than 16 minutes of scan time. We demonstrate the use of MGN and LGN fROIs obtained from the TL fMRI task in standard resting-state functional connectivity (RSFC) fMRI analyses in the same participants. In RSFC analyses, we validated the specificity of MGN and LGN fROIs for signals obtained from primary auditory and visual cortex, respectively, and benchmark their performance against alternative atlas- and segmentation-based localization methods. The TL fMRI task and analysis code (written in Presentation and MATLAB, respectively) have been made freely available to the wider research community.

Temporal complexity of the BOLD-signal in preterm versus term infants

Preterm birth causes alterations in structural and functional cerebral development that are not fully understood. Here, we investigate whether basic characteristics of BOLD signal itself might differ across preterm, term equivalent, and term infants. Anatomical, fMRI, and diffusion weighted imaging data from 716 neonates born at 23-43 weeks gestational age were obtained from the Developing Human Connectome Project. Hurst exponent (H; a measure of temporal complexity of a time-series) was computed from the power spectral density of the BOLD signal within 13 resting state networks. Using linear mixed effects models to account for scan age and birth age, we found that H increased with age, that earlier birth age contributed to lower H values, and that H increased most in motor and sensory networks. We then tested for a relationship between temporal complexity and structural development using H and DTI-based estimates of myelination and found moderate but significant correlations. These findings suggest that the temporal complexity of BOLD signal in neonates relates to age and tracks with known developmental trajectories in the brain. Elucidating how these signal-based differences might relate to maturing hemodynamics in the preterm brain could yield new information about neurophysiological vulnerabilities during this crucial developmental period.

Assessing the impact of infantile hydrocephalus on visuomotor integration through behavioural and neuroimaging studies

Infantile hydrocephalus considerably impacts neurodevelopment, warranting attention to potential long-term consequences on visuomotor functions. The current study investigated the impact of infantile hydrocephalus on functional connectivity within the posterior cortex. Fourteen patients, who were treated for infantile hydrocephalus, were matched for age and sex with 14 typically-developing controls. Both groups had a mean age of 9 years old. Resting-state functional MRI was used to conduct a functional connectivity analysis within the visuomotor integration network, including the inferior frontal occipital fasciculus, superior longitudinal fasciculus, and frontal aslant tract. Patients had reduced functional connectivity in visuomotor pathways compared to typically-developing children with notable impact on the left and right fusiform gyrus and precuneus. Children with infantile hydrocephalus also performed significantly lower in tasks involving visuomotor integration, visual processing, visuospatial skills, motor coordination, and fine motor manipulation. This study enhances our understanding of the multifaceted impact of infantile hydrocephalus on both neural connectivity and considering behavioral outcomes.

Early Life Neuroimaging: The Generalizability of Cortical Area Parcellations Across Development

The cerebral cortex comprises discrete cortical areas that form during development. Accurate area parcellation in neuroimaging studies enhances statistical power and comparability across studies. The formation of cortical areas is influenced by intrinsic embryonic patterning as well as extrinsic inputs, particularly through postnatal exposure. Given the substantial changes in brain volume, microstructure, and functional connectivity during the first years of life, we hypothesized that cortical areas in 1-to-3-year-olds would exhibit major differences from those in neonates and progressively resemble adults as development progresses. Here, we parcellated the cerebral cortex into putative areas using local functional connectivity gradients in 92 toddlers at 2 years old. We demonstrated high reproducibility of these cortical regions across 1-to-3-year-olds in two independent datasets. The area boundaries in 1-to-3-year-olds were more similar to adults than neonates. While the age-specific group parcellation fitted better to the underlying functional connectivity in individuals during the first 3 years, adult area parcellations might still have some utility in developmental studies, especially in children older than 6 years. Additionally, we provided connectivity-based community assignments of the parcels, showing fragmented anterior and posterior components based on the strongest connectivity, yet alignment with adult systems when weaker connectivity was included.

Cortico-Cerebellar Monitoring of Speech Sequence Production

In a functional magnetic resonance imaging study, we examined speech error monitoring in a cortico-cerebellar network for two contrasts: (a) correct trials with high versus low articulatory error probability and (b) overtly committed errors versus correct trials. Engagement of the cognitive cerebellar region Crus I in both contrasts suggests that this region is involved in overarching performance monitoring. The activation of cerebellar motor regions (superior medial cerebellum, lobules VI and VIII) indicates the additional presence of a sensorimotor driven implementation of control. The combined pattern of pre-supplementary motor area (active across contrasts) and anterior cingulate cortex (only active in the contrast involving overt errors) activations suggests sensorimotor driven feedback monitoring in the medial frontal cortex, making use of proprioception and auditory feedback through overt errors. Differential temporal and parietal cortex activation across contrasts indicates involvement beyond sensorimotor driven feedback in line with speech production models that link these regions to auditory target processing and internal modeling-like mechanisms. These results highlight the presence of multiple, possibly hierarchically interdependent, mechanisms that support the optimizing of speech production.

Profiling cortical morphometric similarity in perinatal brains: Insights from development, sex difference, and inter-individual variation

The topological organization of the macroscopic cortical networks important for the development of complex brain functions. However, how the cortical morphometric organization develops during the third trimester and whether it demonstrates sexual and individual differences at this particular stage remain unclear. Here, we constructed the morphometric similarity network (MSN) based on morphological and microstructural features derived from multimodal MRI of two independent cohorts (cross-sectional and longitudinal) scanned at 30-44 postmenstrual weeks (PMW). Sex difference and inter-individual variations of the MSN were also examined on these cohorts. The cross-sectional analysis revealed that both network integration and segregation changed in a nonlinear biphasic trajectory, which was supported by the results obtained from longitudinal analysis. The community structure showed remarkable consistency between bilateral hemispheres and maintained stability across PMWs. Connectivity within the primary cortex strengthened faster than that within high-order communities. Compared to females, male neonates showed a significant reduction in the participation coefficient within prefrontal and parietal cortices, while their overall network organization and community architecture remained comparable. Furthermore, by using the morphometric similarity as features, we achieved over 65 % accuracy in identifying an individual at term-equivalent age from images acquired after birth, and vice versa. These findings provide comprehensive insights into the development of morphometric similarity throughout the perinatal cortex, enhancing our understanding of the establishment of neuroanatomical organization during early life.

Mapping brain function in adults and young children during naturalistic viewing with high-density diffuse optical tomography

Human studies of early brain development have been limited by extant neuroimaging methods. MRI scanners present logistical challenges for imaging young children, while alternative modalities like functional near-infrared spectroscopy have traditionally been limited by image quality due to sparse sampling. In addition, conventional tasks for brain mapping elicit low task engagement, high head motion, and considerable participant attrition in pediatric populations. As a result, typical and atypical developmental trajectories of processes such as language acquisition remain understudied during sensitive periods over the first years of life. We evaluate high-density diffuse optical tomography (HD-DOT) imaging combined with movie stimuli for high resolution optical neuroimaging in awake children ranging from 1 to 7 years of age. We built an HD-DOT system with design features geared towards enhancing both image quality and child comfort. Furthermore, we characterized a library of animated movie clips as a stimulus set for brain mapping and we optimized associated data analysis pipelines. Together, these tools could map cortical responses to movies and contained features such as speech in both adults and awake young children. This study lays the groundwork for future research to investigate response variability in larger pediatric samples and atypical trajectories of early brain development in clinical populations.

Cortical specialization associated with native speech category acquisition in early infancy

This study investigates neural processes in infant speech processing, with a focus on left frontal brain regions and hemispheric lateralization in Mandarin-speaking infants' acquisition of native tonal categories. We tested 2- to 6-month-old Mandarin learners to explore age-related improvements in tone discrimination, the role of inferior frontal regions in abstract speech category representation, and left hemisphere lateralization during tone processing. Using a block design, we presented four Mandarin tones via [ta] and measured oxygenated hemoglobin concentration with functional near-infrared spectroscopy. Results showed age-related improvements in tone discrimination, greater involvement of frontal regions in older infants indicating abstract tonal representation development and increased bilateral activation mirroring native adult Mandarin speakers. These findings contribute to our broader understanding of the relationship between native speech acquisition and infant brain development during the critical period of early language learning.

Altered resting-state functional connectivity in newborns with hypoxic ischemic encephalopathy assessed using high-density functional near-infrared spectroscopy

Hypoxic-ischemic encephalopathy (HIE) results from a lack of oxygen to the brain during the perinatal period. HIE can lead to mortality and various acute and long-term morbidities. Improved bedside monitoring methods are needed to identify biomarkers of brain health. Functional near-infrared spectroscopy (fNIRS) can assess resting-state functional connectivity (RSFC) at the bedside. We acquired resting-state fNIRS data from 21 neonates with HIE (postmenstrual age [PMA] = 39.96), in 19 neonates the scans were acquired post-therapeutic hypothermia (TH), and from 20 term-born healthy newborns (PMA = 39.93). Twelve HIE neonates also underwent resting-state functional magnetic resonance imaging (fMRI) post-TH. RSFC was calculated as correlation coefficients amongst the time courses for fNIRS and fMRI data, respectively. The fNIRS and fMRI RSFC maps were comparable. RSFC patterns were then measured with graph theory metrics and compared between HIE infants and healthy controls. HIE newborns showed significantly increased clustering coefficients, network efficiency and modularity compared to controls. Using a support vector machine algorithm, RSFC features demonstrated good performance in classifying the HIE and healthy newborns in separate groups. Our results indicate the utility of fNIRS-connectivity patterns as potential biomarkers for HIE and fNIRS as a new bedside tool for newborns with HIE.

Early life stress moderates the relation between systemic inflammation and neural activation to reward in adolescents both cross-sectionally and longitudinally

Elevated levels of systemic inflammation are associated with altered reward-related brain function in ventral striatal areas of the brain like the nucleus accumbens (NAcc). In adolescents, cross-sectional research indicates that exposure to early life stress (ELS) can moderate the relation between inflammation and neural activation, which may contribute to atypical reward function; however, no studies have tested whether this moderation by ELS of neuroimmune associations persists over time. Here, we conducted a cross-sectional analysis and the first exploratory longitudinal analysis testing whether cumulative severity of ELS moderates the association of systemic inflammation with reward-related processing in the NAcc in adolescents (n = 104; 58F/46M; M[SD] age = 16.00[1.45] years; range = 13.07-19.86 years). For the cross-sectional analysis, we modeled a statistical interaction between ELS and levels of C-reactive protein (CRP) predicting NAcc activation during the anticipation and outcome phases of a monetary reward task. We found that higher CRP was associated with blunted NAcc activation during the outcome of reward in youth who experienced higher levels of ELS (β = -0.31; p = 0.006). For the longitudinal analysis, we modeled an interaction between ELS and change in CRP predicting change in NAcc activation across 2 years. This analysis similarly showed that increasing CRP over time was associated with decreasing NAcc during reward outcomes in youth who experienced higher levels of ELS (β = -0.47; p = 0.022). Both findings support contemporary theoretical frameworks involving associations among inflammation, reward-related brain function, and ELS exposure, and suggest that experiencing ELS can have significant and enduring effects on neuroimmune function and adolescent neurodevelopment.

A high-density diffuse optical tomography dataset of naturalistic viewing

Traditional laboratory tasks offer tight experimental control but lack the richness of our everyday human experience. As a result many cognitive neuroscientists have been motivated to adopt experimental paradigms that are more natural, such as stories and movies. Here we describe data collected from 58 healthy adult participants (aged 18-76 years) who viewed 10 minutes of a movie (The Good, the Bad, and the Ugly, 1966). Most (36) participants viewed the clip more than once, resulting in 106 sessions of data. Cortical responses were mapped using high-density diffuse optical tomography (first- through fourth nearest neighbor separations of 1.3, 3.0, 3.9, and 4.7 cm), covering large portions of superficial occipital, temporal, parietal, and frontal lobes. Consistency of measured activity across subjects was quantified using intersubject correlation analysis. Data are provided in both channel format (SNIRF) and projected to standard space (NIfTI), using an atlas-based light model. These data are suitable for methods exploration as well as investigating a wide variety of cognitive phenomena.

Structural and functional connectome relationships in early childhood

There is strong evidence that the functional connectome is highly related to the white matter connectome in older children and adults, though little is known about structure-function relationships in early childhood. We investigated the development of cortical structure-function coupling in children longitudinally scanned at 1, 2, 4, and 6 years of age (N = 360) and in a comparison sample of adults (N = 89). We also applied a novel graph convolutional neural network-based deep learning model with a new loss function to better capture inter-subject heterogeneity and predict an individual's functional connectivity from the corresponding structural connectivity. We found regional patterns of structure-function coupling in early childhood that were consistent with adult patterns. In addition, our deep learning model improved the prediction of individual functional connectivity from its structural counterpart compared to existing models.

Maternal pre-pregnancy obesity affects the uncinate fasciculus white matter tract in preterm infants

Background

A growing body of evidence suggests an association between a higher maternal pre-pregnancy body mass index (BMI) and adverse long-term neurodevelopmental outcomes for their offspring. Despite recent attention to the effects of maternal obesity on fetal and neonatal brain development, changes in the brain microstructure of preterm infants born to mothers with pre-pregnancy obesity are still not well understood. This study aimed to detect the changes in the brain microstructure of obese mothers in pre-pregnancy and their offspring born as preterm infants using diffusion tensor imaging (DTI).

Methods

A total of 32 preterm infants (born to 16 mothers with normal BMI and 16 mothers with a high BMI) at <32 weeks of gestation without brain injury underwent brain magnetic resonance imaging at term-equivalent age (TEA). The BMI of all pregnant women was measured within approximately 12 weeks before pregnancy or the first 2 weeks of gestation. We analyzed the brain volume using a morphologically adaptive neonatal tissue segmentation toolbox and calculated the major white matter (WM) tracts using probabilistic maps of the Johns Hopkins University neonatal atlas. We investigated the differences in brain volume and WM microstructure between preterm infants of mothers with normal and high BMI. The DTI parameters were compared among groups using analysis of covariance adjusted for postmenstrual age at scan and multiple comparisons.

Results

Preterm infants born to mothers with a high BMI showed significantly increased cortical gray matter volume (p = 0.001) and decreased WM volume (p = 0.003) after controlling for postmenstrual age and multiple comparisons. We found a significantly lower axial diffusivity in the uncinate fasciculus (UNC) in mothers with high BMI than that in mothers with normal BMI (1.690 ± 0.066 vs. 1.762 ± 0.101, respectively; p = 0.005).

Conclusion

Our study is the first to demonstrate that maternal obesity impacts perinatal brain development patterns in preterm infants at TEA, even in the absence of apparent brain injury. These findings provide evidence for the detrimental effects of maternal obesity on brain developmental trajectories in offspring and suggest potential neurodevelopmental outcomes based on an altered UNC WM microstructure, which is known to be critical for language and social-emotional functions.

Gestational and postnatal age associations for striatal tissue iron deposition in early infancy

Striatal development is crucial for later motor, cognitive, and reward behavior, but age-related change in striatal physiology during the neonatal period remains understudied. An MRI-based measure of tissue iron deposition, T2*, is a non-invasive way to probe striatal physiology neonatally, linked to dopaminergic processing and cognition in children and adults. Striatal subregions have distinct functions that may come online at different time periods in early life. To identify if there are critical periods before or after birth, we measured if striatal iron accrued with gestational age at birth [range= 34.57-41.85 weeks] or postnatal age at scan [range= 5-64 days], using MRI to probe the T2* signal in N = 83 neonates in three striatal subregions. We found iron increased with postnatal age in the pallidum and putamen but not the caudate. No significant relationship between iron and gestational age was observed. Using a subset of infants scanned at preschool age (N = 26), we show distributions of iron shift between time points. In infants, the pallidum had the least iron of the three regions but had the most by preschool age. Together, this provides evidence of distinct change for striatal subregions, a possible differentiation between motor and cognitive systems, identifying a mechanism that may impact future trajectories.

Longitudinal developmental trajectories of functional connectivity reveal regional distribution of distinct age effects in infancy

Prior work has shown that different functional brain networks exhibit different maturation rates, but little is known about whether and how different brain areas may differ in the exact shape of longitudinal functional connectivity growth trajectories during infancy. We used resting-state functional magnetic resonance imaging (fMRI) during natural sleep to characterize developmental trajectories of different regions using a longitudinal cohort of infants at 3 weeks (neonate), 1 year, and 2 years of age (n = 90; all with usable data at three time points). A novel whole brain heatmap analysis was performed with four mixed-effect models to determine the best fit of age-related changes for each functional connection: (i) growth effects: positive-linear-age, (ii) emergent effects: positive-log-age, (iii) pruning effects: negative-quadratic-age, and (iv) transient effects: positive-quadratic-age. Our results revealed that emergent (logarithmic) effects dominated developmental trajectory patterns, but significant pruning and transient effects were also observed, particularly in connections centered on inferior frontal and anterior cingulate areas that support social learning and conflict monitoring. Overall, unique global distribution patterns were observed for each growth model indicating that developmental trajectories for different connections are heterogeneous. All models showed significant effects concentrated in association areas, highlighting the dominance of higher-order social/cognitive development during the first 2 years of life.

The use of functional near-infrared spectroscopy in tracking neurodevelopmental trajectories in infants and children with or without developmental disorders: a systematic review

Understanding the neurodevelopmental trajectories of infants and children is essential for the early identification of neurodevelopmental disorders, elucidating the neural mechanisms underlying the disorders, and predicting developmental outcomes. Functional Near-Infrared Spectroscopy (fNIRS) is an infant-friendly neuroimaging tool that enables the monitoring of cerebral hemodynamic responses from the neonatal period. Due to its advantages, fNIRS is a promising tool for studying neurodevelopmental trajectories. Although many researchers have used fNIRS to study neural development in infants/children and have reported important findings, there is a lack of synthesized evidence for using fNIRS to track neurodevelopmental trajectories in infants and children. The current systematic review summarized 84 original fNIRS studies and showed a general trend of age-related increase in network integration and segregation, interhemispheric connectivity, leftward asymmetry, and differences in phase oscillation during resting-state. Moreover, typically developing infants and children showed a developmental trend of more localized and differentiated activation when processing visual, auditory, and tactile information, suggesting more mature and specialized sensory networks. Later in life, children switched from recruiting bilateral auditory to a left-lateralized language circuit when processing social auditory and language information and showed increased prefrontal activation during executive functioning tasks. The developmental trajectories are different in children with developmental disorders, with infants at risk for autism spectrum disorder showing initial overconnectivity followed by underconnectivity during resting-state; and children with attention-deficit/hyperactivity disorders showing lower prefrontal cortex activation during executive functioning tasks compared to their typically developing peers throughout childhood. The current systematic review supports the use of fNIRS in tracking the neurodevelopmental trajectories in children. More longitudinal studies are needed to validate the neurodevelopmental trajectories and explore the use of these neurobiomarkers for the early identification of developmental disorders and in tracking the effects of interventions.

Real-time feedback reduces participant motion during task-based fMRI

The potential negative impact of head movement during fMRI has long been appreciated. Although a variety of prospective and retrospective approaches have been developed to help mitigate these effects, reducing head movement in the first place remains the most appealing strategy for optimizing data quality. Real-time interventions, in which participants are provided feedback regarding their scan-to-scan motion, have recently shown promise in reducing motion during resting state fMRI. However, whether feedback might similarly reduce motion during task-based fMRI is an open question. In particular, it is unclear whether participants can effectively monitor motion feedback while attending to task-related demands. Here we assessed whether a combination of real-time and between-run feedback could reduce head motion during task-based fMRI. During an auditory word repetition task, 78 adult participants (aged 19-81) were pseudorandomly assigned to receive feedback or not. Feedback was provided FIRMM software that used real-time calculation of realignment parameters to estimate participant motion. We quantified movement using framewise displacement (FD). We found that motion feedback resulted in a statistically significant reduction in participant head motion, with a small-to-moderate effect size (reducing average FD from 0.347 to 0.282). Reductions were most apparent in high-motion events. We conclude that under some circumstances real-time feedback may reduce head motion during task-based fMRI, although its effectiveness may depend on the specific participant population and task demands of a given study.

Reliability of resting-state functional connectivity in the human spinal cord: Assessing the impact of distinct noise sources

The investigation of spontaneous fluctuations of the blood-oxygen-level-dependent (BOLD) signal has recently been extended from the brain to the spinal cord, where it has stimulated interest from a clinical perspective. A number of resting-state functional magnetic resonance imaging (fMRI) studies have demonstrated robust functional connectivity between the time series of BOLD fluctuations in bilateral dorsal horns and between those in bilateral ventral horns, in line with the functional neuroanatomy of the spinal cord. A necessary step prior to extension to clinical studies is assessing the reliability of such resting-state signals, which we aimed to do here in a group of 45 healthy young adults at the clinically prevalent field strength of 3T. When investigating connectivity in the entire cervical spinal cord, we observed fair to good reliability for dorsal-dorsal and ventral-ventral connectivity, whereas reliability was poor for within- and between-hemicord dorsal-ventral connectivity. Considering how prone spinal cord fMRI is to noise, we extensively investigated the impact of distinct noise sources and made two crucial observations: removal of physiological noise led to a reduction in functional connectivity strength and reliability - due to the removal of stable and participant-specific noise patterns - whereas removal of thermal noise considerably increased the detectability of functional connectivity without a clear influence on reliability. Finally, we also assessed connectivity within spinal cord segments and observed that while the pattern of connectivity was similar to that of whole cervical cord, reliability at the level of single segments was consistently poor. Taken together, our results demonstrate the presence of reliable resting-state functional connectivity in the human spinal cord even after thoroughly accounting for physiological and thermal noise, but at the same time urge caution if focal changes in connectivity (e.g. due to segmental lesions) are to be studied, especially in a longitudinal manner.

Gestational and postnatal age associations for striatal tissue iron deposition in early infancy

Striatal development is crucial for later motor, cognitive, and reward behavior, but age-related change in striatal physiology during the neonatal period remains understudied. An MRI-based measure of tissue iron deposition, T2*, is a non-invasive way to probe striatal physiology neonatally, linked to dopaminergic processing and cognition in children and adults. Striatal subregions have distinct functions that may come online at different time periods in early life. To identify if there are critical periods before or after birth, we measured if striatal iron accrued with gestational age at birth [range=34.57-41.85 weeks] or postnatal age at scan [range=5-64 days], using MRI to probe the T2* signal in N=83 neonates in three striatal subregions. We found iron increased with postnatal age in the pallidum and putamen but not the caudate. No significant relationship between iron and gestational age was observed. Using a subset of infants scanned at preschool age (N=26), we show distributions of iron shift between timepoints. In infants, the pallidum had the least iron of the three regions but had the most by preschool age. Together, this provides evidence of distinct change for striatal subregions, a possible differentiation between motor and cognitive systems, identifying a mechanism that may impact future trajectories.

Highlights

Neonatal striatal tissue iron can be measured using the T2* signal from rsfMRInT2* changed with postnatal age in the pallidum and putamen but not in the caudatenT2* did not change with gestational age in any of the three regionsPatterns of iron deposition (nT2*) among regions shift from infancy to preschool.

Brief mock-scan training reduces head motion during real scanning for children: A growth curve study

Pediatric neuroimaging datasets are rapidly increasing in scales. Despite strict protocols in data collection and preprocessing focused on improving data quality, the presence of head motion still impedes our understanding of neurodevelopmental mechanisms. Large head motion can lead to severe noise and artifacts in magnetic resonance imaging (MRI) studies, inflating correlations between adjacent brain areas and decreasing correlations between spatial distant territories, especially in children and adolescents. Here, by leveraging mock-scans of 123 Chinese children and adolescents, we demonstrated the presence of increased head motion in younger participants. Critically, a 5.5-minute training session in an MRI mock scanner was found to effectively suppress the head motion in the children and adolescents. Therefore, we suggest that mock scanner training should be part of the quality assurance routine prior to formal MRI data collection, particularly in large-scale population-level neuroimaging initiatives for pediatrics.

Systematic evaluation of head motion on resting-state functional connectivity MRI in the neonate

Reliability and robustness of resting state functional connectivity MRI (rs-fcMRI) relies, in part, on minimizing the influence of head motion on measured brain signals. The confounding effects of head motion on functional connectivity have been extensively studied in adults, but its impact on newborn brain connectivity remains unexplored. Here, using a large newborn data set consisting of 159 rs-fcMRI scans acquired in the Developing Brain Institute at Children's National Hospital and 416 scans from The Developing Human Connectome Project (dHCP), we systematically investigated associations between head motion and rs-fcMRI. Head motion during the scan significantly affected connectivity at sensory-related networks and default mode networks, and at the whole brain scale; the direction of motion effects varied across the whole brain. Comparing high- versus low-head motion groups suggested that head motion can impact connectivity estimates across the whole brain. Censoring of high-motion volumes using frame-wise displacement significantly reduced the confounding effects of head motion on neonatal rs-fcMRI. Lastly, in the dHCP data set, we demonstrated similar persistent associations between head motion and network connectivity despite implementing a standard denoising strategy. Collectively, our results highlight the importance of using rigorous head motion correction in preprocessing neonatal rs-fcMRI to yield reliable estimates of brain activity.

Maturation of large-scale brain systems over the first month of life

The period immediately after birth is a critical developmental window, capturing rapid maturation of brain structure and a child's earliest experiences. Large-scale brain systems are present at delivery, but how these brain systems mature during this narrow window (i.e. first weeks of life) marked by heightened neuroplasticity remains uncharted. Using multivariate pattern classification techniques and functional connectivity magnetic resonance imaging, we detected robust differences in brain systems related to age in newborns (n = 262; R2 = 0.51). Development over the first month of life occurred brain-wide, but differed and was more pronounced in brain systems previously characterized as developing early (i.e. sensorimotor networks) than in those characterized as developing late (i.e. association networks). The cingulo-opercular network was the only exception to this organizing principle, illuminating its early role in brain development. This study represents a step towards a normative brain "growth curve" that could be used to identify atypical brain maturation in infancy.

The Lateralization of Spatial Cognition in Table Tennis Players: Neuroplasticity in the Dominant Hemisphere

Spatial cognition facilitates the successful completion of specific cognitive tasks through lateral processing and neuroplasticity. Long-term training in table tennis induces neural processing efficiency in the visuospatial cognitive processing cortex of athletes. However, the lateralization characteristics and neural mechanisms of visual−spatial cognitive processing in table tennis players in non-sport domains are unclear. This study utilized event-related potentials to investigate differences in the spatial cognition abilities of regular college students (controls) and table tennis players. A total of 48 participants (28 controls; 20 s-level national table tennis players) completed spatial cognitive tasks while electroencephalography data were recorded. Task performance was better in the table tennis group than in the control group (reaction time: P < 0.001; correct number/sec: P = 0.043), P3 amplitude was greater in the table tennis group (P = 0.040), spatial cognition showed obvious lateralization characteristics (P < 0.001), table tennis players showed a more obvious right-hemisphere advantage, and the P3 amplitude in the right hemisphere was significantly greater in table tennis athletes than in the control group. (P = 0.044). Our findings demonstrate a right-hemisphere advantage in spatial cognition. Long-term training strengthened the visual−spatial processing ability of table tennis players, and this advantage effect was reflected in the neuroplasticity of the right hemisphere (the dominant hemisphere for spatial processing).

Altered development of structural MRI connectome hubs at near-term age in very and moderately preterm infants

Preterm infants may exhibit altered developmental patterns of the brain structural network by endogenous and exogenous stimuli, which are quantifiable through hub and modular network topologies that develop in the third trimester. Although preterm brain networks can compensate for white matter microstructural abnormalities of core connections, less is known about how the network developmental characteristics of preterm infants differ from those of full-term infants. We identified 13 hubs and 4 modules and revealed subtle differences in edgewise connectivity and local network properties between 134 preterm and 76 full-term infants, identifying specific developmental patterns of the brain structural network in preterm infants. The modules of preterm infants showed an imbalanced composition. The edgewise connectivity in preterm infants showed significantly decreased long- and short-range connections and local network properties in the dorsal superior frontal gyrus. In contrast, the fusiform gyrus and several nonhub regions showed significantly increased wiring of short-range connections and local network properties. Our results suggested that decreased local network in the frontal lobe and excessive development in the occipital lobe may contribute to the understanding of brain developmental deviances in preterm infants.

Early life stress, systemic inflammation, and neural correlates of implicit emotion regulation in adolescents

Exposure to early life stress (ELS) increases the risk for developing psychopathology; however, the mechanisms underlying this association are not clear. In this study we examined systemic inflammation as a pathway that may link exposure to stress to altered neural correlates of implicit emotion regulation in adolescents with varying levels of exposure to ELS (n = 83; 52 females, 31 males; 15.63 ± 1.10 years). We measured ventrolateral prefrontal cortex (vlPFC) activation and functional connectivity (FC) between the bilateral amygdala and the vlPFC as adolescents completed an affect labeling task in the scanner and assessed concentrations of C-reactive protein (CRP) using a dried blood spot protocol. We found that CRP levels were negatively associated with vlPFC activation during implicit regulation of negatively-valenced stimuli, and that cumulative severity of ELS exposure moderated this neuroimmune association. Severity of ELS also significantly moderated the association between CRP levels and FC between the bilateral amygdala and l-vlPFC during implicit emotion regulation: in adolescents who had been exposed to more severe ELS, higher CRP was associated with more negative frontoamygdala FC during implicit regulation of negatively-valenced stimuli. Thus, ELS may disrupt the normative association between the immune system and the neural processes that underlie socioemotional functioning potentially increasing adolescents' risk for maladaptive outcomes.

Retained Primitive Reflexes and Potential for Intervention in Autistic Spectrum Disorders

We provide evidence to support the contention that many aspects of Autistic Spectrum Disorder (ASD) are related to interregional brain functional disconnectivity associated with maturational delays in the development of brain networks. We think a delay in brain maturation in some networks may result in an increase in cortical maturation and development in other networks, leading to a developmental asynchrony and an unevenness of functional skills and symptoms. The paper supports the close relationship between retained primitive reflexes and cognitive and motor function in general and in ASD in particular provided to indicate that the inhibition of RPRs can effect positive change in ASD.

Functional individual variability development of the neonatal brain

Individual variability in cognition and behavior results from the differences in brain structure and function that have already emerged before birth. However, little is known about individual variability in brain functional architecture at local level in neonates which is of great significance to explore owing to largely undeveloped long-range functional connectivity and segregated functions in early brain development. To address this, resting-state fMRI data of 163 neonates ranged from 32 to 45 postconceptional weeks (PCW) were used in this study, and various functional features including functional parcellation similarity, local brain activity and local functional connectivity were used to characterize individual functional variability. We observed significantly higher local functional individual variability in superior parietal, sensorimotor, and visual cortex, and lower variability in the frontal, insula and cingulate cortex relative to other regions within each hemisphere. The mean local functional individual variability significantly increased with age, and the age effect was found larger in brain regions such as the occipital, temporal, prefrontal and parietal cortex. Our findings promote the understanding of brain plasticity and regional differential maturation in the early stage.

Evaluating denoising strategies in resting-state functional magnetic resonance in traumatic brain injury (EpiBioS4Rx)

Resting-state functional MRI is increasingly used in the clinical setting and is now included in some diagnostic guidelines for severe brain injury patients. However, to ensure high-quality data, one should mitigate fMRI-related noise typical of this population. Therefore, we aimed to evaluate the ability of different preprocessing strategies to mitigate noise-related signal (i.e., in-scanner movement and physiological noise) in functional connectivity (FC) of traumatic brain injury (TBI) patients. We applied nine commonly used denoising strategies, combined into 17 pipelines, to 88 TBI patients from the Epilepsy Bioinformatics Study for Anti-epileptogenic Therapy clinical trial. Pipelines were evaluated by three quality control (QC) metrics across three exclusion regimes based on the participant's head movement profile. While no pipeline eliminated noise effects on FC, some pipelines exhibited relatively high effectiveness depending on the exclusion regime. Once high-motion participants were excluded, the choice of denoising pipeline becomes secondary - although this strategy leads to substantial data loss. Pipelines combining spike regression with physiological regressors were the best performers, whereas pipelines that used automated data-driven methods performed comparatively worse. In this study, we report the first large-scale evaluation of denoising pipelines aimed at reducing noise-related FC in a clinical population known to be highly susceptible to in-scanner motion and significant anatomical abnormalities. If resting-state functional magnetic resonance is to be a successful clinical technique, it is crucial that procedures mitigating the effect of noise be systematically evaluated in the most challenging populations, such as TBI datasets.

Prefrontal cortex supports speech perception in listeners with cochlear implants

Cochlear implants are neuroprosthetic devices that can restore hearing in people with severe to profound hearing loss by electrically stimulating the auditory nerve. Because of physical limitations on the precision of this stimulation, the acoustic information delivered by a cochlear implant does not convey the same level of acoustic detail as that conveyed by normal hearing. As a result, speech understanding in listeners with cochlear implants is typically poorer and more effortful than in listeners with normal hearing. The brain networks supporting speech understanding in listeners with cochlear implants are not well understood, partly due to difficulties obtaining functional neuroimaging data in this population. In the current study, we assessed the brain regions supporting spoken word understanding in adult listeners with right unilateral cochlear implants (n=20) and matched controls (n=18) using high-density diffuse optical tomography (HD-DOT), a quiet and non-invasive imaging modality with spatial resolution comparable to that of functional MRI. We found that while listening to spoken words in quiet, listeners with cochlear implants showed greater activity in the left prefrontal cortex than listeners with normal hearing, specifically in a region engaged in a separate spatial working memory task. These results suggest that listeners with cochlear implants require greater cognitive processing during speech understanding than listeners with normal hearing, supported by compensatory recruitment of the left prefrontal cortex.

A Descriptive Review of the Impact of Patient Motion in Early Childhood Resting-State Functional Magnetic Resonance Imaging

Resting-state functional magnetic images (rs-fMRIs) can be used to map and delineate the brain activity occurring while the patient is in a task-free state. These resting-state activity networks can be informative when diagnosing various neurodevelopmental diseases, but only if the images are high quality. The quality of an rs-fMRI rapidly degrades when the patient moves during the scan. Herein, we describe how patient motion impacts an rs-fMRI on multiple levels. We begin with how the electromagnetic field and pulses of an MR scanner interact with a patient’s physiology, how movement affects the net signal acquired by the scanner, and how motion can be quantified from rs-fMRI. We then present methods for preventing motion through educational and behavioral interventions appropriate for different age groups, techniques for prospectively monitoring and correcting motion during the acquisition process, and pipelines for mitigating the effects of motion in existing scans.

Social-Cognitive Network Connectivity in Preterm Children and Relations With Early Nutrition and Developmental Outcomes

Infants born very low birth weight (VLBW, < 1,500 g) are at a heightened risk for structural brain abnormalities and social-cognitive deficits, which can impair behavioural functioning. Resting-state fMRI, reflecting a baseline level of brain activity and underlying social-cognitive processes, has also been reported to be altered in children born VLBW. Yet very little is known about the functional networks underlying social cognition using magnetoencephalography (MEG) and how it relates to neonatal factors and developmental outcomes. Thus, we investigated functional connectivity at rest in VLBW children and the associations with early nutrition and IQ and behavioural problems. We collected resting-state MEG recordings and measures of IQ and social-cognitive behaviour, as well as macronutrient/energy intakes during initial hospitalisation in 5-year-old children born VLBW (n = 37) compared to full-term (FT; n = 27) controls. We examined resting-state network differences controlling for sex and age at scan. Functional connectivity was estimated using the weighted phase lag index. Associations between functional connectivity with outcome measures and postnatal nutrition were also assessed using regression analyses. We found increased resting-state functional connectivity in VLBW compared to FT children in the gamma frequency band (65–80 Hz). This hyper-connected network was primarily anchored in frontal regions known to underlie social-cognitive functions such as emotional processing. In VLBW children, increased functional connectivity was related to higher IQ scores, while reduced connectivity was related to increased behavioural problems at 5 years of age. These within-group associations were found in the slower frequency bands of theta (4–7 Hz) and alpha (8–12 Hz), frequently linked to higher-order cognitive functions. We also found significant associations between macronutrient (protein and lipid) and energy intakes during the first postnatal month with functional connectivity at preschool-age, highlighting the long-term impacts of postnatal nutrition on preterm brain development. Our findings demonstrate that at preschool-age, VLBW children show altered resting-state connectivity despite IQ and behaviour being in the average range, possibly reflecting functional reorganisation of networks to support social-cognitive and behavioural functioning. Further, our results highlight an important role of early postnatal nutrition in the development of resting-state networks, which in turn may improve neurodevelopmental outcomes in this vulnerable population.

Functional Connectivity of the Developing Mouse Cortex

Cross-sectional studies have established a variety of structural, synaptic, and cell physiological changes corresponding to critical periods in cortical development. However, the emergence of functional connectivity (FC) in development has not been fully characterized, and hemodynamic-based measures are vulnerable to any neurovascular coupling changes occurring in parallel. We therefore used optical fluorescence imaging to trace longitudinal calcium FC in the awake, resting-state mouse cortex at 5 developmental timepoints beginning at postnatal day 15 (P15) and ending in early adulthood at P60. Calcium FC displayed coherent functional maps as early as P15, and FC significantly varied in connections between many regions across development, with the developmental trajectory's shape specific to the functional region. Evaluating 325 seed-seed connections, we found that there was a significant increase in FC between P15 and P22 over the majority of the cortex as well as bilateral connectivity and node degree differences in frontal, motor, and retrosplenial cortices after P22. A rebalancing of inter- and intrahemispheric FC and local-distal FC dominance was also observed during development. This longitudinal developmental calcium FC study therefore provides a resource dataset to the field and identifies periods of dynamic change which cross-sectional studies may target for examination of disease states.

Individual variability in functional organization of the neonatal brain

The adult brain is organized into distinct functional networks, forming the basis of information processing and determining individual differences in behavior. Is this network organization genetically determined and present at birth? And what is the individual variability in this organization in neonates? Here, we use unsupervised learning to uncover intrinsic functional brain organization using resting-state connectivity from a large cohort of neonates (Developing Human Connectome Project). We identified a set of symmetric, hierarchical, and replicable networks: sensorimotor, visual, default mode, ventral attention, and high-level vision. We quantified individual variability across neonates, and found the most individual variability in the ventral attention networks. Crucially, the variability of these networks was not driven by SNR differences or differences from adult networks (Yeo et al., 2011). Finally, differential gene expression provided a potential explanation for the emergence of these distinct networks and identified potential genes of interest for future developmental and individual variability research. Overall, we found neonatal connectomes (even at the voxel-level) can reveal broad individual-specific information processing units. The presence of individual differences in neonates and the framework for personalized parcellations demonstrated here has the potential to improve prediction of behavior and future outcomes from neonatal and infant brain data.

Existence of Functional Connectome Fingerprint during Infancy and Its Stability over Months

The functional connectome fingerprint is a cluster of individualized brain functional connectivity patterns that are capable of distinguishing one individual from others. Although its existence has been demonstrated in adolescents and adults, whether such individualized patterns exist during infancy is barely investigated despite its importance in identifying the origin of the intrinsic connectome patterns that potentially mirror distinct behavioral phenotypes. To fill this knowledge gap, capitalizing on a longitudinal high-resolution structural and resting-state functional MRI dataset with 104 human infants (53 females) with 806 longitudinal scans (age, 16-876 d) and infant-specific functional parcellation maps, we observe that the brain functional connectome fingerprint may exist since infancy and keeps stable over months during early brain development. Specifically, we achieve an ∼78% individual identification rate by using ∼5% selected functional connections, compared with the best identification rate of 60% without connection selection. The frontoparietal networks recognized as the most contributive networks in adult functional connectome fingerprinting retain their superiority in infants despite being widely acknowledged as rapidly developing systems during childhood. The existence and stability of the functional connectome fingerprint are further validated on adjacent age groups. Moreover, we show that the infant frontoparietal networks can reach similar accuracy in predicting individual early learning composite scores as the whole-brain connectome, again resembling the observations in adults and highlighting the relevance of functional connectome fingerprint to cognitive performance. For the first time, these results suggest that each individual may retain a unique and stable marker of functional connectome during early brain development.SIGNIFICANCE STATEMENT Functional connectome fingerprinting during infancy featuring rapid brain development remains almost uninvestigated even though it is essential for understanding the early individual-level intrinsic pattern of functional organization and its relationship with distinct behavioral phenotypes. With an infant-tailored functional connection selection and validation strategy, we strive to provide the delineation of the infant functional connectome fingerprint by examining its existence, stability, and relationship with early cognitive performance. We observe that the brain functional connectome fingerprint may exist since early infancy and remains stable over months during the first 2 years. The identified key contributive functional connections and networks for fingerprinting are also verified to be highly predictive for cognitive score prediction, which reveals the association between infant connectome fingerprint and cognitive performance.

ciftiTools: A package for reading, writing, visualizing, and manipulating CIFTI files in R

There is significant interest in adopting surface- and grayordinate-based analysis of MR data for a number of reasons, including improved whole-cortex visualization, the ability to perform surface smoothing to avoid issues associated with volumetric smoothing, improved inter-subject alignment, and reduced dimensionality. The CIFTI grayordinate file format introduced by the Human Connectome Project further advances grayordinate-based analysis by combining gray matter data from the left and right cortical hemispheres with gray matter data from the subcortex and cerebellum into a single file. Analyses performed in grayordinate space are well-suited to leverage information shared across the brain and across subjects through both traditional analysis techniques and more advanced statistical methods, including Bayesian methods. The R statistical environment facilitates use of advanced statistical techniques, yet little support for grayordinates analysis has been previously available in R Indeed, few comprehensive programmatic tools for working with CIFTI files have been available in any language Here, we present the ciftiTools R package, which provides a unified environment for reading, writing, visualizing and manipulating CIFTI files and related data formats. We illustrate ciftiTools’ convenient and user-friendly suite of tools for working with grayordinates and surface geometry data in R, and we describe how ciftiTools is being utilized to advance the statistical analysis of grayordinate-based functional MRI data.

Advancing motion denoising of multiband resting-state functional connectivity fMRI data

Simultaneous multi-slice (multiband) accelerated functional magnetic resonance imaging (fMRI) provides dramatically improved temporal and spatial resolution for resting-state functional connectivity (RSFC) studies of the human brain in health and disease. However, multiband acceleration also poses unique challenges for denoising of subject motion induced data artifacts, the presence of which is a major confound in RSFC research that substantively diminishes reliability and reproducibility. We comprehensively evaluated existing and novel approaches to volume censoring-based motion denoising in the Human Connectome Project (HCP) dataset. We show that assumptions underlying common metrics for evaluating motion denoising pipelines, especially those based on quality control-functional connectivity (QC-FC) correlations and differences between high- and low-motion participants, are problematic, and appear to be inappropriate in their current widespread use as indicators of comparative pipeline performance and as targets for investigators to use when tuning pipelines for their own datasets. We further develop two new quantitative metrics that are instead agnostic to QC-FC correlations and other measures that rely upon the null assumption that no true relationships exist between trait measures of subject motion and functional connectivity, and demonstrate their use as benchmarks for comparing volume censoring methods. Finally, we develop and validate quantitative methods for determining dataset-specific optimal volume censoring parameters prior to the final analysis of a dataset, and provide straightforward recommendations and code for all investigators to apply this optimized approach to their own RSFC datasets.

Linking irritability and functional brain networks: A transdiagnostic case for expanding consideration of development and environment in RDoC

The National Institute of Mental Health Research Domain Criteria (RDoC) framework promotes the dimensional and transdiagnostic operationalization of psychopathology, but consideration of the neurodevelopmental foundations of mental health problems requires deeper examination. Irritability, the dispositional tendency to angry emotion that has both mood and behavioral elements, is dimensional, transdiagnostic, and observable early in life-a promising target for the identification of early neural indicators or risk factors for psychopathology. Here, we examine functional brain networks linked to irritability from preschool to adulthood and discuss how development and early experience may influence these neural substrates. Functional connectivity measured with fMRI varies according to irritability and indicates the atypical coordination of several functional networks involved in emotion generation, emotion perception, attention, internalization, and cognitive control. We lay out an agenda to improve our understanding and detection of atypical brain:behavior patterns through advances in the characterization of both functional networks and irritability as well as the consideration and operationalization of developmental and early life environmental influences on this pathway.

A Pilot Trial Examining the Merits of Combining Amantadine and Repetitive Transcranial Magnetic Stimulation as an Intervention for Persons With Disordered Consciousness After TBI

OBJECTIVE

Report pilot findings of neurobehavioral gains and network changes observed in persons with disordered consciousness (DoC) who received repetitive transcranial magnetic stimulation (rTMS) or amantadine (AMA), and then rTMS+AMA.

PARTICIPANTS

Four persons with DoC 1 to 15 years after traumatic brain injury (TBI).

DESIGN

Alternate treatment-order, within-subject, baseline-controlled trial.

MAIN MEASURES

For group and individual neurobehavioral analyses, predetermined thresholds, based on mixed linear-effects models and conditional minimally detectable change, were used to define meaningful neurobehavioral change for the Disorders of Consciousness Scale-25 (DOCS) total and Auditory-Language measures. Resting-state functional connectivity (rsFC) of the default mode and 6 other networks was examined.

RESULTS

Meaningful gains in DOCS total measures were observed for 75% of treatment segments and auditory-language gains were observed after rTMS, which doubled when rTMS preceded rTMS+AMA. Neurobehavioral changes were reflected in rsFC for language, salience, and sensorimotor networks. Between networks interactions were modulated, globally, after all treatments.

CONCLUSIONS

For persons with DoC 1 to 15 years after TBI, meaningful neurobehavioral gains were observed after provision of rTMS, AMA, and rTMS+AMA. Sequencing and combining of treatments to modulate broad-scale neural activity, via differing mechanisms, merits investigation in a future study powered to determine efficacy of this approach to enabling neurobehavioral recovery.

What have we really learned from functional connectivity in clinical populations?

Functional connectivity (FC), or the statistical interdependence of blood-oxygen dependent level (BOLD) signals between brain regions using fMRI, has emerged as a widely used tool for probing functional abnormalities in clinical populations due to the promise of the approach across conceptual, technical, and practical levels. With an already vast and steadily accumulating neuroimaging literature on neurodevelopmental, psychiatric, and neurological diseases and disorders in which FC is a primary measure, we aim here to provide a high-level synthesis of major concepts that have arisen from FC findings in a manner that cuts across different clinical conditions and sheds light on overarching principles. We highlight that FC has allowed us to discover the ubiquity of intrinsic functional networks across virtually all brains and clarify typical patterns of neurodevelopment over the lifespan. This understanding of typical FC maturation with age has provided important benchmarks against which to evaluate divergent maturation in early life and degeneration in late life. This in turn has led to the important insight that many clinical conditions are associated with complex, distributed, network-level changes in the brain, as opposed to solely focal abnormalities. We further emphasize the important role that FC studies have played in supporting a dimensional approach to studying transdiagnostic clinical symptoms and in enhancing the multimodal characterization and prediction of the trajectory of symptom progression across conditions. We highlight the unprecedented opportunity offered by FC to probe functional abnormalities in clinical conditions where brain function could not be easily studied otherwise, such as in disorders of consciousness. Lastly, we suggest high priority areas for future research and acknowledge critical barriers associated with the use of FC methods, particularly those related to artifact removal, data denoising and feasibility in clinical contexts.

Structural and functional neuroimaging changes associated with cognitive impairment and dementia in Parkinson's disease

This study seeks a better understanding of possible pathophysiological mechanisms associated with cognitive impairment and dementia in Parkinson's disease using structural and functional MRI. We investigated resting-state functional connectivity of important subdivisions of the caudate nucleus, putamen and thalamus, and also how the morphology of these structures are impacted in the disorder. We found cognitively unimpaired Parkinson's disease subjects (n = 33), compared to controls (n = 26), display increased functional connectivity of the dorsal caudate, anterior putamen and mediodorsal thalamic subdivisions with areas across the frontal lobe, as well as reduced functional connectivity of the dorsal caudate with posterior cortical and cerebellar regions. Compared to cognitively unimpaired subjects, those with mild cognitive impairment (n = 22) demonstrated reduced functional connectivity of the mediodorsal thalamus with the paracingulate cortex, while also demonstrating increased functional connectivity of the mediodorsal thalamus with the posterior cingulate cortex, compared to subjects with dementia (n = 17). Extensive volumetric and surface-based deflation was found in subjects with dementia compared to cognitively unimpaired Parkinson's disease participants and controls. Our research suggests that structures within basal ganglia-thalamocortical circuits are implicated in cognitive impairment and dementia in Parkinson's disease, with cognitive impairment and dementia associated with a breakdown in functional connectivity of the mediodorsal thalamus with para- and posterior cingulate regions of the brain respectively.

Handedness Development: A Model for Investigating the Development of Hemispheric Specialization and Interhemispheric Coordination

The author presents his perspective on the character of science, development, and handedness and relates these to his investigations of the early development of handedness. After presenting some ideas on what hemispheric specialization of function might mean for neural processing and how handedness should be assessed, the neuroscience of control of the arms/hands and interhemispheric communication and coordination are examined for how developmental processes can affect these mechanisms. The author’s work on the development of early handedness is reviewed and placed within a context of cascading events in which different forms of handedness emerge from earlier forms but not in a deterministic manner. This approach supports a continuous rather than categorical distribution of handedness and accounts for the predominance of right-handedness while maintaining a minority of left-handedness. Finally, the relation of the development of handedness to the development of several language and cognitive skills is examined.

MRI of the Neonatal Brain: A Review of Methodological Challenges and Neuroscientific Advances

In recent years, exploration of the developing brain has become a major focus for researchers and clinicians in an attempt to understand what allows children to acquire amazing and unique abilities, as well as the impact of early disruptions (eg, prematurity, neonatal insults) that can lead to a wide range of neurodevelopmental disorders. Noninvasive neuroimaging methods such as MRI are essential to establish links between the brain and behavioral changes in newborns and infants. In this review article, we aim to highlight recent and representative studies using the various techniques available: anatomical MRI, quantitative MRI (relaxometry, diffusion MRI), multiparametric approaches, and functional MRI. Today, protocols use 1.5 or 3T MRI scanners, and specialized methodologies have been put in place for data acquisition and processing to address the methodological challenges specific to this population, such as sensitivity to motion. MR sequences must be adapted to the brains of newborns and infants to obtain relevant good soft-tissue contrast, given the small size of the cerebral structures and the incomplete maturation of tissues. The use of age-specific image postprocessing tools is also essential, as signal and contrast differ from the adult brain. Appropriate methodologies then make it possible to explore multiple neurodevelopmental mechanisms in a precise way, and assess changes with age or differences between groups of subjects, particularly through large-scale projects. Although MRI measurements only indirectly reflect the complex series of dynamic processes observed throughout development at the molecular and cellular levels, this technique can provide information on brain morphology, structural connectivity, microstructural properties of gray and white matter, and on the functional architecture. Finally, MRI measures related to clinical, behavioral, and electrophysiological markers have a key role to play from a diagnostic and prognostic perspective in the implementation of early interventions to avoid long-term disabilities in children. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY STAGE: 1.

Hippocampal functional connectivity development during the first two years indexes 4-year working memory performance

The hippocampus is a key limbic region involved in higher-order cognitive processes including learning and memory. Although both typical and atypical functional connectivity patterns of the hippocampus have been well-studied in adults, the developmental trajectory of hippocampal connectivity during infancy and how it relates to later working memory performance remains to be elucidated. Here we used resting state fMRI (rsfMRI) during natural sleep to examine the longitudinal development of hippocampal functional connectivity using a large cohort (N = 202) of infants at 3 weeks (neonate), 1 year, and 2 years of age. Next, we used multivariate modeling to investigate the relationship between both cross-sectional and longitudinal growth in hippocampal connectivity and 4-year working memory outcome. Results showed robust local functional connectivity of the hippocampus in neonates with nearby limbic and subcortical regions, with dramatic maturation and increasing connectivity with key default mode network (DMN) regions resulting in adult-like topology of the hippocampal functional connectivity by the end of the first year. This pattern was stabilized and further consolidated by 2 years of age. Importantly, cross-sectional and longitudinal measures of hippocampal connectivity in the first year predicted subsequent behavioral measures of working memory at 4 years of age. Taken together, our findings provide insight into the development of hippocampal functional circuits underlying working memory during this early critical period.

Structural and functional brain network alterations in prenatal alcohol exposed neonates

Prenatal alcohol exposure leads to alterations in cognition, behavior and underlying brain architecture. However, prior studies have not integrated structural and functional imaging data in children with prenatal alcohol exposure. The aim of this study was to characterize disruptions in both structural and functional brain network organization after prenatal alcohol exposure in very early life. A group of 11 neonates with prenatal alcohol exposure and 14 unexposed controls were investigated using diffusion weighted structural and resting state functional magnetic resonance imaging. Covariance networks were created using graph theoretical analyses for each data set, controlling for age and sex. Group differences in global hub arrangement and regional connectivity were determined using nonparametric permutation tests. Neonates with prenatal alcohol exposure and controls exhibited similar global structural network organization. However, global functional networks of neonates with prenatal alcohol exposure comprised of temporal and limbic hubs, while hubs were more distributed in controls representing an early default mode network. On a regional level, controls showed prominent structural and functional connectivity in parietal and occipital regions. Neonates with prenatal alcohol exposure showed regionally, predominant structural and functional connectivity in several subcortical regions and occipital regions. The findings suggest early functional disruption on a global and regional level after prenatal alcohol exposure and indicate suboptimal organization of functional networks. These differences likely underlie sensory dysregulation and behavioral difficulties in prenatal alcohol exposure.

Biomarkers in Panic Disorder

Background:

Panic disorder (PD) is a kind of anxiety disorder that impacts the life quality and functional perspectives in patients. However, the pathophysiological study of PD seems still inadequate and many unresolved issues need to be clarified.

Objectives:

In this review article of biomarkers in PD, the investigator will focus on the findings of magnetic resonance imaging (MRI) of the brain in the pathophysiology study. The MRI biomarkers would be divided into several categories, on the basis of structural and functional perspectives.

Methods:

The structural category would include the gray matter and white matter tract studies. The functional category would consist of functional MRI (fMRI), resting-state fMRI (Rs-fMRI), and magnetic resonance spectroscopy (MRS). The PD biomarkers revealed by the above methodologies would be discussed in this article.

Results:

For the gray matter perspectives, the PD patients would have alterations in the volumes of fear network structures, such as the amygdala, parahippocampal gyrus, thalamus, anterior cingulate cortex, insula, and frontal regions. For the white matter tract studies, the PD patients seemed to have alterations in the fasciculus linking the fear network regions, such as the anterior thalamic radiation, uncinate fasciculus, fronto-occipital fasciculus, and superior longitudinal fasciculus. For the fMRI studies in PD, the significant results also focused on the fear network regions, such as the amygdala, hippocampus, thalamus, insula, and frontal regions. For the Rs-fMRI studies, PD patients seemed to have alterations in the regions of the default mode network and fear network model. At last, the MRS results showed alterations in neuron metabolites of the hippocampus, amygdala, occipital cortex, and frontal regions.

Conclusion:

The MRI biomarkers in PD might be compatible with the extended fear network model hypothesis in PD, which included the amygdala, hippocampus, thalamus, insula, frontal regions, and sensory-related cortex.

Behavior and Regional Cortical BOLD Signal Fluctuations Are Altered in Adult Rabbits After Neonatal Volatile Anesthetic Exposure

Neonatal and infant exposure to volatile anesthetics has been associated with long-term learning, memory, and behavioral deficits. Although early anesthesia exposure has been linked to a number of underlying structural abnormalities, functional changes associated with these impairments remain poorly understood. To investigate the relationship between functional alteration in neuronal circuits and learning deficiency, resting state functional MRI (rsfMRI) connectivity was examined in adolescent rabbits exposed to general anesthesia as neonates (1 MAC isoflurane for 2 h on postnatal days P8, P11, and P14) and unanesthetized controls before and after training with a trace eyeblink classical conditioning (ECC) paradigm. Long-range connectivity was measured between several key regions of interest (ROIs), including primary and secondary somatosensory cortices, thalamus, hippocampus, and cingulate. In addition, metrics of regional BOLD fluctuation amplitudes and coherence, amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), and regional homogeneity (ReHo) were calculated. Our results showed that the trace ECC learning rate was significantly lower in the anesthesia-exposed group. No anesthesia-related changes in long-range connectivity, fALFF, or ReHo were found between any ROIs. However, ALFF was significantly higher in anesthesia-exposed rabbits in the primary and secondary somatosensory cortices, and ALFF in those areas was a significant predictor of the learning performance for trace ECC. The absence of anesthesia-related changes in long-range thalamocortical connectivity indicates that functional thalamocortical input is not affected. Higher ALFF in the somatosensory cortex may indicate the developmental disruption of cortical neuronal circuits after neonatal anesthesia exposure, including excessive neuronal synchronization that may underlie the observed cognitive deficits.