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Greene, D. J.

Publications and source records attributed to Greene, D. J..

At least 19 recordsLinked to original sources

Movie Watching for Individual Functional Brain Network Estimation in Adolescents

Precision functional mapping (PFM) reveals stable individual differences in brain functional network organization and holds promise for advancing neuropsychiatric clinical care. PFM requires sufficient high-quality and densely-sampled functional MRI data at the individual level that is typically acquired during the so-called resting state while passively fixating on a crosshair. However, crosshair fixation acquisitions can be challenging especially for pediatric or patient populations, where alternatives like movie watching might be used to improve data quality and reduce participant burden. Here, we compare the use of resting state crosshair fixation and movie watching fMRI data to derive individual-specific functional brain network topography using PFM data (28-38 minutes of low-motion fMRI data per-participant per-condition) in nineteen adolescents (12-18 years) with a range of transdiagnostic psychiatric diagnoses. Network assignments were largely conserved between crosshair fixation and movie watching, with a smaller subset of reproducible network reassignments which were overwhelmingly border shifts between neighboring networks. This suggests largely conserved global structure of functional network topography between crosshair fixation and movie watching, though border shifts can compound into variable estimates of cortical network size particularly for movie positive (language, salience, and parietal memory) and movie negative networks (default mode, action mode). Functional network assignments derived from movies and crosshair were also similarly individual-specific and consistent within common neuromodulation targets including dorsolateral prefrontal cortex and somatomotor cortex. Key results were replicated in independent pediatric consortia data (Healthy Brain Network, n = 466, 6-22 years) and reproduced across independent PFM data sessions. Acknowledging individual differences and level of analysis, we conclude that movies are a viable alternative to resting state crosshair fixation for individual network definitions.

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Functional Organization of the Neonatal Basal Ganglia and Thalamus

The basal ganglia and thalamus are key nodes in subcortico-cortical loops involved in sensory, motor, and cognitive function. In adults, posterior regions of the subcortex link to cortical sensorimotor networks and anterior regions link to association networks. Alterations in the size, strength, and selectivity of these subcortical regional network representations are implicated in several neuropsychiatric disorders, many of which originate early in development. However, the organization of these network representations at birth remains incompletely understood, limiting our ability to devise normative and atypical developmental models of subcortico-cortical interactions. Using resting-state fMRI, we characterized the size, strength, and selectivity of cortical network representations in the basal ganglia and thalamus in a set of neonates (n=261) and compared results to children (age range 9-11 years, n=69) and adults (n=120). We found that the broad anterior-posterior organization of the subcortex is present at birth, yet representations of somatomotor networks were larger at birth compared to children and adults (p<0.001). The strength and selectivity of subcortico-cortical functional connectivity (FC) exhibited interactions between age group and network (all p<0.001), such that subcortical representations of sensorimotor networks exhibited stronger FC and higher selectivity in neonates, while subcortical representations of association networks exhibited stronger FC and higher selectivity in older cohorts. In parallel, data-driven clustering revealed areas with integration of multiple networks in the neonatal subcortex. These results suggest that subcortico-cortical FC evolves over development largely in a sensorimotor-association manner and provide a baseline for normative and disordered subcortical development. HIGHLIGHTSO_LIThe basic anterior-posterior layout of association to sensorimotor network representation in the basal ganglia and thalamus is present at term birth. C_LIO_LISensorimotor systems are overrepresented in neonates compared to children and adults. C_LIO_LISensorimotor representations exhibit greater functional connectivity strength and selectivity than association representations at birth, while association representations are stronger and more selective than sensorimotor representations in adults. C_LIO_LIThe neonatal subcortex exhibits substantial integration of multiple cortical networks. C_LI GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=150 SRC="FIGDIR/small/736181v1_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@1d3bfa3org.highwire.dtl.DTLVardef@ca904dorg.highwire.dtl.DTLVardef@c7c219org.highwire.dtl.DTLVardef@983020_HPS_FORMAT_FIGEXP M_FIG C_FIG

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Functional brain organization is stable within individuals across years

Brain regions exhibit dynamic yet highly coordinated activity patterns that form large-scale functional networks measurable through resting-state correlations. While their association with fluctuating activity may intuitively suggest functional networks to be temporally transient and dependent on state, a growing body of literature suggests that they are person-specific and stable across days. If truly person-specific, then functional networks should preserve unique characteristics over extended periods. To test this hypothesis, we collected longitudinal precision fMRI data ([&ge;]60 minutes per participant per time point) from 10 healthy young adults across 1-3 year intervals, as well as three adults over 8-13 years. We further replicated findings in the MyConnectome dataset and its 10-year follow-up. Functional network organization--when sufficient per-participant data were collected-- remained largely stable within individuals over prolonged periods of up to 13 years, suggesting that individualized brain organization constitutes persistent features of personal identity that may be supported by homeostatic mechanisms. SIGNIFICANCEWhile many aspects of brain function are portrayed as dynamic and malleable, our study provides evidence for the long-term preservation of functional organization of the healthy young adult brain. Whole-brain functional organization exhibited unique individual characteristics that were preserved for years, even over a decade. The stability of such individualized neural architecture suggests that the brain encodes features of personhood that may be invariant across contexts and temporal fluctuations. This observation reframes our understanding of brain resilience and plasticity by offering new insights into the extent that homeostatic mechanisms of brain organization can withstand stressors and environmental changes through time to maintain a constant functional organization. These insights pave the way for a more comprehensive understanding of the neural mechanisms behind this stability, with the possibility of pinpointing critical markers of healthy brain function and its disruptions.

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Individualized network topography in pre-adolescent children and adults using naturalistic precision fMRI

Group-averaged network definitions, commonly used in developmental functional connectivity research, limit our understanding of how network topography may change with age and can lead to inaccurate estimates of age effects on intra- and inter-network functional connectivity. Here, we collected a precision fMRI dataset from 24 parent-child pairs (children 6 to 8 years, 13 females; adults 33 to 47 years, 12 females) during passive video viewing and derived individual template-matched functional network maps from 60 minutes of motion-censored data per participant. Overall, large-scale network architecture was broadly shared between children and adults, with no age-effects observed for network-level surface area, few age differences in network boundaries and generally lower assignment confidence in children. Considering inter-individual similarity in network topography, association networks showed stronger within-family similarity and no overall effect of age on similarity of networks between pairs of individuals. We further asked how individualized network definitions might impact estimates of age effects on dense functional connectivity. While all approaches pointed to greater within-network functional connectivity in adults, we found that individualized approaches had larger age effects and lower sensitivity to head motion. Together, our results suggest that, relative to adults, pre-adolescent children show reduced network assignment confidence and weaker within-network connectivity, but limited differences in network borders and size, and underscore the value of individualized mapping for increasing sensitivity to age effects.

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Precision functional mapping reveals less inter-individual variability in the child vs. adult human brain

Human brain organization shares a common underlying structure, though recent studies have shown that features of this organization also differ significantly across individual adults. Understanding the developmental pathways that lead to individually unique brains is important for advancing models of cognitive development and neurodevelopmental disorders. Here we use highly personalized precision neuroimaging methods to map brain networks within 12 individual children, ages 8-12 years. We demonstrate fMRI functional connectivity maps that substantially exceed the reliability of traditional techniques, allowing us to measure individual differences after overcoming biases from measurement noise. Children share core functional network topography, with greatest inter-individual variability in association regions, consistent with adult findings. However, children show less between-subject variability than adults, suggesting increasing individual differentiation in brain networks with development. This pediatric precision neuroimaging dataset is publicly available to support future brain development research and provides a high-fidelity foundation for studying individual variation in atypical development.

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How much is 'enough'? Considerations for functional connectivity reliability in pediatric naturalistic fMRI

functional connectivity (FC) measurements are important for robust and reproducible findings, yet pediatric functional magnetic resonance imaging (fMRI) faces unique challenges due to head motion and bias toward shorter scans. Passive viewing conditions during fMRI offer advantages for scanning pediatric populations, but FC reliability under these conditions remains underexplored. Here, we used precision fMRI data collected across three passive viewing conditions to directly compare FC reliability profiles between 25 pre-adolescent children and 25 adults, with each participant providing over 2.8 hours of data over four sessions. We found that FC test-retest correlations increased asymptotically with scan length, with children requiring nearly twice the post-censored scan time (24.6 minutes) compared to adults (14.4 minutes) to achieve comparable reliability, and that this effect was only partly attributable to head motion. Reliability differences between lower-motion adults and higher-motion children were spatially non-uniform and largest in ventral anterior temporal and frontal regions. While averaging features within functional networks improved intraclass correlation coefficient (ICC) reliability, values for higher-motion children remained in the poor-to-fair ICC range even with 48 minutes of total scan time. Viewing conditions with greater engagement reduced head motion in children but had lower FC reliability compared to less engaging low-demand videos, suggesting complex state- or condition-related trade-offs. These findings have important implications for developmental neuroimaging study design, particularly for higher motion pediatric populations.

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Substructure of the brain's Cingulo-Opercular network

The Cingulo-Opercular network (CON) is an executive network of the human brain that regulates actions. CON is composed of many widely distributed cortical regions that are involved in top-down control over both lower-level (i.e., motor) and higher-level (i.e., cognitive) functions, as well as in processing of painful stimuli. Given the topographical and functional heterogeneity of the CON, we investigated whether subnetworks within the CON support separable aspects of action control. Using precision functional mapping (PFM) in 15 participants with > 5 hours of resting state functional connectivity (RSFC) and task data, we identified three anatomically and functionally distinct CON subnetworks within each individual. These three distinct subnetworks were linked to Decisions, Actions, and Feedback (including pain processing), respectively, in convergence with a meta-analytic task database. These Decision, Action and Feedback subnetworks represent pathways by which the brain establishes top-down goals, transforms those goals into actions, implemented as movements, and processes critical action feedback such as pain.

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Structure-Function Coupling in Highly Sampled Individual Brains

Structural connections (SC) between distant regions of the brain support synchronized function known as functional connectivity (FC) and give rise to the large-scale brain networks that enable cognition and behavior. Understanding how SC enables FC is important to understand how injuries to structural connections may alter brain function and cognition. Previous work evaluating whole-brain SC-FC relationships showed that SC explained FC well in unimodal visual and motor areas, but only weakly in association areas, suggesting a unimodal-heteromodal gradient organization of SC-FC coupling. However, this work was conducted in group-averaged SC/FC data. Thus, it could not account for inter-individual variability in the locations of cortical areas and white matter tracts. We evaluated the correspondence of SC and FC within three highly sampled healthy participants. For each participant, we collected 78 minutes of diffusion-weighted MRI for SC and 360 minutes of resting state fMRI for FC. We found that FC was best explained by SC in visual and motor systems, as well as in anterior and posterior cingulate regions. A unimodal-to-heteromodal gradient could not fully explain SC-FC coupling. We conclude that the SC-FC coupling of the anterior-posterior cingulate circuit is more similar to unimodal areas than to heteromodal areas. SIGNIFICANCE STATEMENTStructural connections between distant regions of the human brain support networked function that enables cognition and behavior. Improving our understanding of how structure enables function could allow better insight into how brain disconnection injuries impair brain function. Previous work using neuroimaging suggested that structure-function relationships vary systematically across the brain, with structure better explaining function in basic visual/motor areas than in higher-order areas. However, this work was conducted in group-averaged data, which may obscure details of individual-specific structure-function relationships. Using individual-specific densely sampled neuroimaging data, we found that in addition to visual/motor regions, structure strongly predicts function in specific circuits of the higher-order cingulate gyrus. The cingulates structure-function relationship suggests that its organization may be unique among higher-order cortical regions.

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A mind-body interface alternates with effector-specific regions in motor cortex

Primary motor cortex (M1) has been thought to form a continuous somatotopic homunculus extending down precentral gyrus from foot to face representations1,2. The motor homunculus has remained a textbook pillar of functional neuroanatomy, despite evidence for concentric functional zones3 and maps of complex actions4. Using our highest precision functional magnetic resonance imaging (fMRI) data and methods, we discovered that the classic homunculus is interrupted by regions with sharpy distinct connectivity, structure, and function, alternating with effector-specific (foot, hand, mouth) areas. These inter-effector regions exhibit decreased cortical thickness and strong functional connectivity to each other, and to prefrontal, insular, and subcortical regions of the Cingulo-opercular network (CON), critical for executive action5 and physiological control6, arousal7, and processing of errors8 and pain9. This interdigitation of action control-linked and motor effector regions was independently verified in the three largest fMRI datasets. Macaque and pediatric (newborn, infant, child) precision fMRI revealed potential cross-species analogues and developmental precursors of the inter-effector system. An extensive battery of motor and action fMRI tasks documented concentric somatotopies for each effector, separated by the CON-linked inter-effector regions. The inter-effector regions lacked movement specificity and co-activated during action planning (coordination of hands and feet), and axial body movement (e.g., abdomen, eyebrows). These results, together with prior work demonstrating stimulation-evoked complex actions4 and connectivity to internal organs (e.g., adrenal medulla)10, suggest that M1 is punctuated by an integrative system for implementing whole-body action plans. Thus, two parallel systems intertwine in motor cortex to form an integrate-isolate pattern: effector-specific regions (foot, hand, mouth) for isolating fine motor control, and a mind-body interface (MBI) for the integrative whole-organism coordination of goals, physiology, and body movement.

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Real-time motion monitoring improves functional MRI data quality in infants

Imaging the infant brain with MRI has improved our understanding of early stages of neurodevelopment. However, head motion during MRI acquisition is detrimental to both functional and structural MRI scan quality. Though infants are commonly scanned while asleep, they commonly exhibit motion during scanning, causing data loss. Our group has shown that providing MRI technicians with real-time motion estimates via Framewise Integrated Real-Time MRI Monitoring (FIRMM) software helps obtain high-quality, low motion fMRI data. By estimating head motion in real time and displaying motion metrics to the MR technician during an fMRI scan, FIRMM can improve scanning efficiency. Hence, we compared average framewise displacement (FD), a proxy for head motion, and the amount of usable fMRI data (FD [&le;] 0.2mm) in infants scanned with (n = 407) and without FIRMM (n = 295). Using a mixed-effects model, we found that the addition of FIRMM to current state-of-the-art infant scanning protocols significantly increased the amount of usable fMRI data acquired per infant, demonstrating its value for research and clinical infant neuroimaging.

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Human Fronto-Striatal Connectivity is Organized into Discrete Functional Subnetworks

The striatum is interconnected with the cerebral cortex via multiple recurrent loops that play a major role in many neuropsychiatric conditions. Primate cortico-striatal connections can be precisely mapped using invasive tract-tracing. However, noninvasive human research has not mapped these connections with anatomical precision, limited by the practice of averaging neuroimaging data across individuals. Here we utilized highly-sampled resting-state functional connectivity MRI for individually-specific precision functional mapping of cortico-striatal connections. We identified ten discrete, individual-specific subnetworks linking cortex--predominately frontal cortex--to striatum. These subnetworks included previously unknown striatal connections to the human language network. The discrete subnetworks formed a stepped rostral-caudal gradient progressing from nucleus accumbens to posterior putamen; this organization was strongest for projections from medial frontal cortex. The stepped gradient organization fit patterns of fronto-striatal connections better than a smooth, continuous gradient. Thus, precision subnetworks identify detailed, individual-specific stepped gradients of cortico-striatal connectivity that include human-specific language networks.

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Using synthetic MR images for field map-less distortion correction

Functional MRI (fMRI) data acquired using echo-planar imaging (EPI) are highly distorted by magnetic field inhomogeneities. Distortion combined with underlying differences in image contrast between EPI and T1-weighted and T2-weighted (T1w/T2w) structural images makes the alignment of functional and anatomical images a challenge. Typically, separately acquired field map data are used to correct fMRI distortions and a flexible cost function insensitive to cross-modal differences in image contrast and intensity is used for aligning fMRI and anatomical images. The quality of alignment achieved with this approach can vary greatly and depends on the quality of field map data. In addition, many publicly available datasets lack field map data entirely. To address this issue, we developed Synth, a software package for distortion correction and cross-modal image registration that does not require separately acquired field map data. Synth combines information from T1w and T2w anatomical images to construct an idealized undistorted synthetic image that has similar contrast properties to fMRI data. The undistorted synthetic image then serves as an effective reference for individual-specific nonlinear unwarping to correct fMRI distortions. We demonstrate, in both pediatric (ABCD: Adolescent Brain Cognitive Development) and adult (MSC: Midnight Scan Club) data that Synth performs comparably well to other leading distortion correction approaches that utilize field map data, and often outperforms them. Field map-less distortion correction with Synth allows accurate and precise registration of fMRI data with missing or corrupted field map information.

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Precision Diffusion Imaging

Diffusion tensor imaging (DTI) aims to non-invasively characterize the anatomy and integrity of the brains white matter fibers. To establish individual-specific precision approaches for DTI, we defined its reliability and accuracy as a function of data quantity and analysis method, using both simulations and highly sampled individual-specific data (927-1442 diffusion weighted images [DWIs] per individual). DTI methods that allow for crossing fibers (BedpostX [BPX], Q-Ball Imaging [QBI]) estimated excess fibers when insufficient data was present and when the data did not match the model priors. To reduce such overfitting, we developed a novel crossing-fiber diffusion imaging method, Bayesian Multi-tensor Model-selection (BaMM), that is designed for high-quality repeated sampling data sets. BaMM was robust to overfitting, showing high reliability and the relatively best crossing-fiber accuracy with increasing amounts of diffusion data. Thus, the choice of diffusion imaging analysis method is important for the success of individual-specific diffusion imaging. Importantly, for potential clinical applications of individual-specific precision DTI, such as deep brain stimulation (DBS), other forms of neuromodulation or neurosurgical planning, the data quantities required to achieve DTI reliability are lower than for functional MRI measures.

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Parallel Hippocampal-Parietal Circuits for Self- and Goal-oriented Processing

The hippocampus is critically important for a diverse range of cognitive processes, such as episodic memory, prospective memory, affective processing, and spatial navigation. The human hippocampus has been thought of as being solely functionally connected to a set of neocortical regions known as the default mode network (DMN), which supports self-referential cognition. Using individual-specific precision functional mapping of resting state fMRI data, we found the anterior hippocampus (head and body) to be preferentially connected to the DMN as expected. The hippocampal tail, however, was strongly preferentially connected to the parietal memory network (PMN), which supports goal-oriented cognition and stimulus recognition. This resting state functional connectivity (RSFC) anterior-posterior dichotomy was well-matched by differences in task deactivations and anatomical segmentations of the hippocampus. Task deactivations were localized to the head and body of the hippocampus (DMN), relatively sparing the tail (PMN). Anterior and posterior hippocampal connectivity was network-specific even though the DMN and PMN are interdigitated in medial parietal cortex. The functional dichotomization of the hippocampus into anterior DMN-connected and posterior PMN-connected parcels suggests parallel, but distinct circuits between the hippocampus and medial parietal cortex for self vs. goal-oriented processing.

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Cingulo-Opercular Control Network Supports Disused Motor Circuits in Standby Mode

Whole-brain resting-state functional MRI (rs-fMRI) during two weeks of limb constraint revealed that disused motor regions became more strongly connected to the cingulo-opercular network (CON), an executive control network that includes regions of the dorsal anterior cingulate cortex (dACC) and insula (1). Disuse-driven increases in functional connectivity (FC) were specific to the CON and somatomotor networks and did not involve any other networks, such as the salience, frontoparietal, or default mode networks. Censoring and modeling analyses showed that FC increases during casting were mediated by large, spontaneous activity pulses that appeared in the disused motor regions and CON control regions. During limb constraint, disused motor circuits appear to enter a standby mode characterized by spontaneous activity pulses and strengthened connectivity to CON executive control regions. SignificanceMany studies have examined plasticity in the primary somatosensory and motor cortex during disuse, but little is known about how disuse impacts the brain outside of primary cortical areas. We leveraged the whole-brain coverage of resting-state functional MRI (rs-fMRI) to discover that disuse drives plasticity of distant executive control regions in the cingulo-opercular network (CON). Two complementary analyses, pulse censoring and pulse addition, demonstrated that increased functional connectivity between the CON and disused motor regions was driven by large, spontaneous pulses of activity in the CON and disused motor regions. These results point to a previously unknown role for the CON in supporting motor plasticity and reveal spontaneous activity pulses as a novel mechanism for reorganizing the brains functional connections.

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Towards Reproducible Brain-Wide Association Studies

Magnetic resonance imaging (MRI) continues to drive many important neuroscientific advances. However, progress in uncovering reproducible associations between individual differences in brain structure/function and behavioral phenotypes (e.g., cognition, mental health) may have been undermined by typical neuroimaging sample sizes (median N=25)1,2. Leveraging the Adolescent Brain Cognitive Development (ABCD) Study3 (N=11,878), we estimated the effect sizes and reproducibility of these brain-wide associations studies (BWAS) as a function of sample size. The very largest, replicable brain-wide associations for univariate and multivariate methods were r=0.14 and r=0.34, respectively. In smaller samples, typical for brain-wide association studies (BWAS), irreproducible, inflated effect sizes were ubiquitous, no matter the method (univariate, multivariate). Until sample sizes started to approach consortium-levels, BWAS were underpowered and statistical errors assured. Multiple factors contribute to replication failures4-6; here, we show that the pairing of small brain-behavioral phenotype effect sizes with sampling variability is a key element in wide-spread BWAS replication failure. Brain-behavioral phenotype associations stabilize and become more reproducible with sample sizes of N{gap}2,000. While investigator-initiated brain-behavior research continues to generate hypotheses and propel innovation, large consortia are needed to usher in a new era of reproducible human brain-wide association studies.

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Hippocampal volume in Provisional Tic Disorder predicts tic severity at 12-month follow-up

BackgroundPrevious studies have investigated differences in the volumes of subcortical structures (e.g., caudate nucleus, putamen, thalamus, amygdala, hippocampus) between individuals with and without Tourette syndrome (TS), as well as the relationships between these volumes and tic symptom severity. These volumes may also predict clinical outcome in Provisional Tic Disorder (PTD), but that hypothesis has never been tested. ObjectiveThis study aimed to examine whether the volumes of subcortical structures measured shortly after tic onset can predict tic symptom severity at one year post tic onset, when TS can first be diagnosed. MethodsWe obtained T1-weighted structural MRI scans from 41 children with PTD (25 with prospective motion correction [vNavs]) whose tics had begun less than 9 months (median 3.7 months) prior to the first study visit (baseline). We re-examined them at the 12-month anniversary of their first tic (follow-up), assessing tic severity using the Yale Global Tic Severity Scale. We quantified the volumes of subcortical structures using volBrain software. ResultsBaseline hippocampal volume was correlated with tic severity at the 12-month follow-up, with a larger hippocampus at baseline predicting worse tic severity at follow-up. This result was confirmed in the subgroup scanned with prospective motion correction. The volumes of other subcortical structures did not significantly predict tic severity at follow-up. ConclusionThese findings suggest that hippocampal volume may be an important marker in predicting prognosis in Provisional Tic Disorder.

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Atypical functional connectivity in Tourette syndrome differs between children and adults

BackgroundTourette syndrome (TS) is a neuropsychiatric disorder characterized by motor and vocal tics that typically change over development. Whether and how brain function in TS also differs across development has been largely understudied. Here, we used functional connectivity MRI to examine whole brain functional networks in children and adults with TS.\n\nMethodsMultivariate classification methods were used to find patterns among functional connections that distinguish TS from controls separately for children and adults (total N = 202). We tested whether the patterns of connections that classify diagnosis in one age group (e.g., children) could classify diagnosis in another age group (e.g., adults). We also tested whether the developmental trajectory of these connections were altered in TS.\n\nResultsPatterns of functional connections that distinguished TS from controls were generalizable to an age-matched independent test set, but not to other age groups. While diagnostic classification was successful in children and adults separately, the connections that best distinguished TS from controls were age-specific. When contextualized with typical development, some functional connections exhibited accelerated maturation in childhood TS, while others exhibited delayed maturation in adulthood TS.\n\nConclusionsOur results demonstrate that brain networks are differentially altered in children and adults with TS, and that the developmental trajectory of affected connections is disrupted. These findings further our understanding of neurodevelopmental trajectories in TS and carry implications for future applications aimed at predicting the clinical course of TS in individuals over development.

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