ABSTRACT
A single dose of psilocybin, a psychedelic that acutely causes distortions of space-time perception and ego dissolution, produces rapid and persistent therapeutic effects in human clinical trials1-4. In animal models, psilocybin induces neuroplasticity in cortex and hippocampus5-8. It remains unclear how human brain network changes relate to subjective and lasting effects of psychedelics. Here we tracked individual-specific brain changes with longitudinal precision functional mapping (roughly 18 magnetic resonance imaging visits per participant). Healthy adults were tracked before, during and for 3 weeks after high-dose psilocybin (25 mg) and methylphenidate (40 mg), and brought back for an additional psilocybin dose 6-12 months later. Psilocybin massively disrupted functional connectivity (FC) in cortex and subcortex, acutely causing more than threefold greater change than methylphenidate. These FC changes were driven by brain desynchronization across spatial scales (areal, global), which dissolved network distinctions by reducing correlations within and anticorrelations between networks. Psilocybin-driven FC changes were strongest in the default mode network, which is connected to the anterior hippocampus and is thought to create our sense of space, time and self. Individual differences in FC changes were strongly linked to the subjective psychedelic experience. Performing a perceptual task reduced psilocybin-driven FC changes. Psilocybin caused persistent decrease in FC between the anterior hippocampus and default mode network, lasting for weeks. Persistent reduction of hippocampal-default mode network connectivity may represent a neuroanatomical and mechanistic correlate of the proplasticity and therapeutic effects of psychedelics.
Subject(s)
Brain , Hallucinogens , Nerve Net , Psilocybin , Adolescent , Adult , Female , Humans , Male , Middle Aged , Young Adult , Brain/cytology , Brain/diagnostic imaging , Brain/drug effects , Brain/physiology , Brain Mapping , Default Mode Network/cytology , Default Mode Network/diagnostic imaging , Default Mode Network/drug effects , Default Mode Network/physiology , Hallucinogens/pharmacology , Hallucinogens/administration & dosage , Healthy Volunteers , Hippocampus/cytology , Hippocampus/diagnostic imaging , Hippocampus/drug effects , Hippocampus/physiology , Magnetic Resonance Imaging , Methylphenidate/pharmacology , Methylphenidate/administration & dosage , Nerve Net/cytology , Nerve Net/diagnostic imaging , Nerve Net/drug effects , Nerve Net/physiology , Psilocybin/pharmacology , Psilocybin/administration & dosage , Space Perception/drug effects , Time Perception/drug effects , EgoABSTRACT
Motor cortex (M1) has been thought to form a continuous somatotopic homunculus extending down the precentral gyrus from foot to face representations1,2, despite evidence for concentric functional zones3 and maps of complex actions4. Here, using precision functional magnetic resonance imaging (fMRI) methods, we find that the classic homunculus is interrupted by regions with distinct connectivity, structure and function, alternating with effector-specific (foot, hand and mouth) areas. These inter-effector regions exhibit decreased cortical thickness and strong functional connectivity to each other, as well as to the cingulo-opercular network (CON), critical for action5 and physiological control6, arousal7, errors8 and pain9. This interdigitation of action control-linked and motor effector regions was verified in the three largest fMRI datasets. Macaque and pediatric (newborn, infant and child) precision fMRI suggested cross-species homologues and developmental precursors of the inter-effector system. A battery of motor and action fMRI tasks documented concentric effector somatotopies, separated by the CON-linked inter-effector regions. The inter-effectors lacked movement specificity and co-activated during action planning (coordination of hands and feet) and axial body movement (such as of the abdomen or eyebrows). These results, together with previous studies demonstrating stimulation-evoked complex actions4 and connectivity to internal organs10 such as the adrenal medulla, suggest that M1 is punctuated by a system for whole-body action planning, the somato-cognitive action network (SCAN). In M1, two parallel systems intertwine, forming an integrate-isolate pattern: effector-specific regions (foot, hand and mouth) for isolating fine motor control and the SCAN for integrating goals, physiology and body movement.
Subject(s)
Brain Mapping , Cognition , Motor Cortex , Brain Mapping/methods , Hand/physiology , Magnetic Resonance Imaging , Motor Cortex/anatomy & histology , Motor Cortex/physiology , Humans , Infant, Newborn , Infant , Child , Animals , Macaca/anatomy & histology , Macaca/physiology , Foot/physiology , Mouth/physiology , Datasets as TopicABSTRACT
Magnetic resonance imaging (MRI) has transformed our understanding of the human brain through well-replicated mapping of abilities to specific structures (for example, lesion studies) and functions1-3 (for example, task functional MRI (fMRI)). Mental health research and care have yet to realize similar advances from MRI. A primary challenge has been replicating associations between inter-individual differences in brain structure or function and complex cognitive or mental health phenotypes (brain-wide association studies (BWAS)). Such BWAS have typically relied on sample sizes appropriate for classical brain mapping4 (the median neuroimaging study sample size is about 25), but potentially too small for capturing reproducible brain-behavioural phenotype associations5,6. Here we used three of the largest neuroimaging datasets currently available-with a total sample size of around 50,000 individuals-to quantify BWAS effect sizes and reproducibility as a function of sample size. BWAS associations were smaller than previously thought, resulting in statistically underpowered studies, inflated effect sizes and replication failures at typical sample sizes. As sample sizes grew into the thousands, replication rates began to improve and effect size inflation decreased. More robust BWAS effects were detected for functional MRI (versus structural), cognitive tests (versus mental health questionnaires) and multivariate methods (versus univariate). Smaller than expected brain-phenotype associations and variability across population subsamples can explain widespread BWAS replication failures. In contrast to non-BWAS approaches with larger effects (for example, lesions, interventions and within-person), BWAS reproducibility requires samples with thousands of individuals.
Subject(s)
Brain Mapping , Brain , Magnetic Resonance Imaging , Brain Mapping/methods , Cognition , Datasets as Topic , Humans , Magnetic Resonance Imaging/methods , Neuroimaging , Phenotype , Reproducibility of ResultsABSTRACT
Identification of replicable neuroimaging correlates of attention-deficit hyperactivity disorder (ADHD) has been hindered by small sample sizes, small effects, and heterogeneity of methods. Given evidence that ADHD is associated with alterations in widely distributed brain networks and the small effects of individual brain features, a whole-brain perspective focusing on cumulative effects is warranted. The use of large, multisite samples is crucial for improving reproducibility and clinical utility of brain-wide MRI association studies. To address this, a polyneuro risk score (PNRS) representing cumulative, brain-wide, ADHD-associated resting-state functional connectivity was constructed and validated using data from the Adolescent Brain Cognitive Development (ABCD, N = 5,543, 51.5% female) study, and was further tested in the independent Oregon-ADHD-1000 case-control cohort (N = 553, 37.4% female). The ADHD PNRS was significantly associated with ADHD symptoms in both cohorts after accounting for relevant covariates (p < 0.001). The most predictive PNRS involved all brain networks, though the strongest effects were concentrated among the default mode and cingulo-opercular networks. In the longitudinal Oregon-ADHD-1000, non-ADHD youth had significantly lower PNRS (Cohen's d = -0.318, robust p = 5.5 × 10-4) than those with persistent ADHD (age 7-19). The PNRS, however, did not mediate polygenic risk for ADHD. Brain-wide connectivity was robustly associated with ADHD symptoms in two independent cohorts, providing further evidence of widespread dysconnectivity in ADHD. Evaluation in enriched samples demonstrates the promise of the PNRS approach for improving reproducibility in neuroimaging studies and unraveling the complex relationships between brain connectivity and behavioral disorders.
Subject(s)
Attention Deficit Disorder with Hyperactivity , Adolescent , Humans , Female , Child , Young Adult , Adult , Male , Attention Deficit Disorder with Hyperactivity/diagnostic imaging , Brain Mapping , Reproducibility of Results , Brain/diagnostic imaging , Cognition , Magnetic Resonance Imaging , Neural Pathways/diagnostic imagingABSTRACT
The cerebral cortex is organized into distinct but interconnected cortical areas, which can be defined by abrupt differences in patterns of resting state functional connectivity (FC) across the cortical surface. Such parcellations of the cortex have been derived in adults and older infants, but there is no widely used surface parcellation available for the neonatal brain. Here, we first demonstrate that existing parcellations, including surface-based parcels derived from older samples as well as volume-based neonatal parcels, are a poor fit for neonatal surface data. We next derive a set of 283 cortical surface parcels from a sample of n = 261 neonates. These parcels have highly homogenous FC patterns and are validated using three external neonatal datasets. The Infomap algorithm is used to assign functional network identities to each parcel, and derived networks are consistent with prior work in neonates. The proposed parcellation may represent neonatal cortical areas and provides a powerful tool for neonatal neuroimaging studies.
Subject(s)
Brain , Magnetic Resonance Imaging , Adult , Infant, Newborn , Humans , Magnetic Resonance Imaging/methods , Neuroimaging , Cerebral Cortex/diagnostic imaging , Algorithms , Image Processing, Computer-Assisted/methodsABSTRACT
Prior work has shown that there is substantial interindividual variation in the spatial distribution of functional networks across the cerebral cortex, or functional topography. However, it remains unknown whether there are sex differences in the topography of individualized networks in youth. Here, we leveraged an advanced machine learning method (sparsity-regularized non-negative matrix factorization) to define individualized functional networks in 693 youth (ages 8 to 23 y) who underwent functional MRI as part of the Philadelphia Neurodevelopmental Cohort. Multivariate pattern analysis using support vector machines classified participant sex based on functional topography with 82.9% accuracy (P < 0.0001). Brain regions most effective in classifying participant sex belonged to association networks, including the ventral attention, default mode, and frontoparietal networks. Mass univariate analyses using generalized additive models with penalized splines provided convergent results. Furthermore, transcriptomic data from the Allen Human Brain Atlas revealed that sex differences in multivariate patterns of functional topography were spatially correlated with the expression of genes on the X chromosome. These results highlight the role of sex as a biological variable in shaping functional topography.
Subject(s)
Cerebral Cortex , Neural Pathways , Sex Characteristics , Adolescent , Adult , Brain Mapping , Cerebral Cortex/physiology , Child , Female , Humans , Machine Learning , Magnetic Resonance Imaging , Male , Young AdultABSTRACT
Perinatal exposure to a high-fat, high-sugar Western-style diet (WSD) is associated with altered neural circuitry in the melanocortin system. This association may have an underlying inflammatory component, as consumption of a WSD during pregnancy can lead to an elevated inflammatory environment. Our group previously demonstrated that prenatal WSD exposure was associated with increased markers of inflammation in the placenta and fetal hypothalamus in Japanese macaques. In this follow-up study, we sought to determine whether this heightened inflammatory state persisted into the postnatal period, as prenatal exposure to inflammation has been shown to reprogram offspring immune function and long-term neuroinflammation would present a potential means for prolonged disruptions to microglia-mediated neuronal circuit formation. Neuroinflammation was approximated in 1-yr-old offspring by counting resident microglia and peripherally derived macrophages in the region of the hypothalamus examined in the fetal study, the arcuate nucleus (ARC). Microglia and macrophages were immunofluorescently stained with their shared marker, ionized calcium-binding adapter molecule 1 (Iba1), and quantified in 11 regions along the rostral-caudal axis of the ARC. A mixed-effects model revealed main effects of perinatal diet (P = 0.011) and spatial location (P = 0.003) on Iba1-stained cell count. Perinatal WSD exposure was associated with a slight decrease in the number of Iba1-stained cells, and cells were more densely located in the center of the ARC. These findings suggest that the heightened inflammatory state experienced in utero does not persist postnatally. This inflammatory response trajectory could have important implications for understanding how neurodevelopmental disorders progress.NEW & NOTEWORTHY Prenatal Western-style diet exposure is associated with increased microglial activity in utero. However, we found a potentially neuroprotective reduction in microglia count during early postnatal development. This trajectory could inform the timing of disruptions to microglia-mediated neuronal circuit formation. Additionally, this is the first study in juvenile macaques to characterize the distribution of microglia along the rostral-caudal axis of the arcuate nucleus of the hypothalamus. Nearby neuronal populations may be greater targets during inflammatory insults.
Subject(s)
Arcuate Nucleus of Hypothalamus , Macaca fuscata , Pregnancy , Animals , Female , Microglia , Neuroinflammatory Diseases , Follow-Up Studies , Hypothalamus , Diet, High-Fat/adverse effects , MacacaABSTRACT
Preclinical evidence suggests that inter-individual variation in the structure of the hypothalamus at birth is associated with variation in the intrauterine environment, with downstream implications for future disease susceptibility. However, scientific advancement in humans is limited by a lack of validated methods for the automatic segmentation of the newborn hypothalamus. N = 215 healthy full-term infants with paired T1-/T2-weighted MR images across four sites were considered for primary analyses (mean postmenstrual age = 44.3 ± 3.5 weeks, nmale /nfemale = 110/106). The outputs of FreeSurfer's hypothalamic subunit segmentation tools designed for adults (segFS) were compared against those of a novel registration-based pipeline developed here (segATLAS) and against manually edited segmentations (segMAN) as reference. Comparisons were made using Dice Similarity Coefficients (DSCs) and through expected associations with postmenstrual age at scan. In addition, we aimed to demonstrate the validity of the segATLAS pipeline by testing for the stability of inter-individual variation in hypothalamic volume across the first year of life (n = 41 longitudinal datasets available). SegFS and segATLAS segmentations demonstrated a wide spread in agreement (mean DSC = 0.65 ± 0.14 SD; range = {0.03-0.80}). SegATLAS volumes were more highly correlated with postmenstrual age at scan than segFS volumes (n = 215 infants; RsegATLAS 2 = 65% vs. RsegFS 2 = 40%), and segATLAS volumes demonstrated a higher degree of agreement with segMAN reference segmentations at the whole hypothalamus (segATLAS DSC = 0.89 ± 0.06 SD; segFS DSC = 0.68 ± 0.14 SD) and subunit levels (segATLAS DSC = 0.80 ± 0.16 SD; segFS DSC = 0.40 ± 0.26 SD). In addition, segATLAS (but not segFS) volumes demonstrated stability from near birth to ~1 years age (n = 41; R2 = 25%; p < 10-3 ). These findings highlight segATLAS as a valid and publicly available (https://github.com/jerodras/neonate_hypothalamus_seg) pipeline for the segmentation of hypothalamic subunits using human newborn MRI up to 3 months of age collected at resolutions on the order of 1 mm isotropic. Because the hypothalamus is traditionally understudied due to a lack of high-quality segmentation tools during the early life period, and because the hypothalamus is of high biological relevance to human growth and development, this tool may stimulate developmental and clinical research by providing new insight into the unique role of the hypothalamus and its subunits in shaping trajectories of early life health and disease.
Subject(s)
Image Processing, Computer-Assisted , Magnetic Resonance Imaging , Adult , Infant, Newborn , Infant , Humans , Male , Female , Image Processing, Computer-Assisted/methods , Magnetic Resonance Imaging/methods , Hypothalamus/diagnostic imagingABSTRACT
Diffusion Spectrum Imaging (DSI) using dense Cartesian sampling of q-space has been shown to provide important advantages for modeling complex white matter architecture. However, its adoption has been limited by the lengthy acquisition time required. Sparser sampling of q-space combined with compressed sensing (CS) reconstruction techniques has been proposed as a way to reduce the scan time of DSI acquisitions. However prior studies have mainly evaluated CS-DSI in post-mortem or non-human data. At present, the capacity for CS-DSI to provide accurate and reliable measures of white matter anatomy and microstructure in the living human brain remains unclear. We evaluated the accuracy and inter-scan reliability of 6 different CS-DSI schemes that provided up to 80% reductions in scan time compared to a full DSI scheme. We capitalized on a dataset of 26 participants who were scanned over eight independent sessions using a full DSI scheme. From this full DSI scheme, we subsampled images to create a range of CS-DSI images. This allowed us to compare the accuracy and inter-scan reliability of derived measures of white matter structure (bundle segmentation, voxel-wise scalar maps) produced by the CS-DSI and the full DSI schemes. We found that CS-DSI estimates of both bundle segmentations and voxel-wise scalars were nearly as accurate and reliable as those generated by the full DSI scheme. Moreover, we found that the accuracy and reliability of CS-DSI was higher in white matter bundles that were more reliably segmented by the full DSI scheme. As a final step, we replicated the accuracy of CS-DSI in a prospectively acquired dataset (n = 20, scanned once). Together, these results illustrate the utility of CS-DSI for reliably delineating in vivo white matter architecture in a fraction of the scan time, underscoring its promise for both clinical and research applications.
Subject(s)
Diffusion Magnetic Resonance Imaging , White Matter , Humans , Reproducibility of Results , Diffusion Magnetic Resonance Imaging/methods , Brain/diagnostic imaging , Brain/anatomy & histology , White Matter/diagnostic imaging , White Matter/anatomy & histology , Autopsy , AlgorithmsABSTRACT
Diffusion-weighted magnetic resonance imaging (dMRI) is the primary method for noninvasively studying the organization of white matter in the human brain. Here we introduce QSIPrep, an integrative software platform for the processing of diffusion images that is compatible with nearly all dMRI sampling schemes. Drawing on a diverse set of software suites to capitalize on their complementary strengths, QSIPrep facilitates the implementation of best practices for processing of diffusion images.
Subject(s)
Brain/diagnostic imaging , Diffusion Magnetic Resonance Imaging/methods , Image Processing, Computer-Assisted/methods , Software , Humans , Programming Languages , WorkflowABSTRACT
The adult human brain is organized into functional brain networks, groups of functionally connected segregated brain regions. A key feature of adult functional networks is long-range selectivity, the property that spatially distant regions from the same network have higher functional connectivity than spatially distant regions from different networks. Although it is critical to establish the status of functional networks and long-range selectivity during the neonatal period as a foundation for typical and atypical brain development, prior work in this area has been mixed. Although some studies report distributed adult-like networks, other studies suggest that neonatal networks are immature and consist primarily of spatially isolated regions. Using a large sample of neonates (n = 262), we demonstrate that neonates have long-range selective functional connections for the default mode, fronto-parietal, and dorsal attention networks. An adult-like pattern of functional brain networks is evident in neonates when network-detection algorithms are tuned to these long-range connections, when using surface-based registration (versus volume-based registration), and as per-subject data quantity increases. These results help clarify factors that have led to prior mixed results, establish that key adult-like functional network features are evident in neonates, and provide a foundation for studies of typical and atypical brain development.
Subject(s)
Brain Mapping , Magnetic Resonance Imaging , Adult , Infant, Newborn , Humans , Brain Mapping/methods , Magnetic Resonance Imaging/methods , Neural Pathways , Brain , Image Processing, Computer-Assisted , Nerve NetABSTRACT
The thalamus is a critical relay center for neural pathways involving sensory, motor, and cognitive functions, including cortico-striato-thalamo-cortical and cortico-ponto-cerebello-thalamo-cortical loops. Despite the importance of these circuits, their development has been understudied. One way to investigate these pathways in human development in vivo is with functional connectivity MRI, yet few studies have examined thalamo-cortical and cerebello-cortical functional connectivity in development. Here, we used resting-state functional connectivity to measure functional connectivity in the thalamus and cerebellum with previously defined cortical functional networks in 2 separate data sets of children (7-12 years old) and adults (19-40 years old). In both data sets, we found stronger functional connectivity between the ventral thalamus and the somatomotor face cortical functional network in children compared with adults, extending previous cortico-striatal functional connectivity findings. In addition, there was more cortical network integration (i.e. strongest functional connectivity with multiple networks) in the thalamus in children than in adults. We found no developmental differences in cerebello-cortical functional connectivity. Together, these results suggest different maturation patterns in cortico-striato-thalamo-cortical and cortico-ponto-cerebellar-thalamo-cortical pathways.
Subject(s)
Cerebellum , Magnetic Resonance Imaging , Adult , Child , Humans , Young Adult , Cerebellum/diagnostic imaging , Neural Pathways/diagnostic imaging , Thalamus/diagnostic imaging , Corpus StriatumABSTRACT
Race is a social construct that contributes to group membership and heightens emotional arousal in intergroup contexts. Little is known about how emotional arousal, specifically uncertain threat, influences behavior and brain processes in response to race information. We investigated the effects of experimentally manipulated uncertain threat on impulsive actions to Black versus White faces in a community sample (n = 106) of Black and White adults. While undergoing fMRI, participants performed an emotional go/no-go task under three conditions of uncertainty: 1) anticipation of an uncertain threat (i.e., unpredictable loud aversive sound); 2) anticipation of an uncertain reward (i.e., unpredictable receipt of money); and 3) no anticipation of an uncertain event. Representational similarity analysis was used to examine the neural representations of race information across functional brain networks between conditions of uncertainty. Participants-regardless of their own race-showed greater impulsivity and neural dissimilarity in response to Black versus White faces across all functional brain networks in conditions of uncertain threat relative to other conditions. This pattern of greater neural dissimilarity under threat was enhanced in individuals with high implicit racial bias. Our results illustrate the distinct and important influence of uncertain threat on global differentiation in how race information is represented in the brain, which may contribute to racially biased behavior.
Subject(s)
Brain , Emotions , Impulsive Behavior , Adult , Humans , Black People , Brain/diagnostic imaging , Brain/physiology , Uncertainty , White PeopleABSTRACT
BACKGROUND: Clinical studies suggest that anaesthesia exposure early in life affects neurobehavioural development. We designed a non-human primate (NHP) study to evaluate cognitive, behavioural, and brain functional and structural alterations after isoflurane exposure during infancy. These NHPs displayed decreased close social behaviour and increased astrogliosis in specific brain regions, most notably in the amygdala. Here we hypothesise that resting-state functional connectivity MRI can detect alterations in connectivity of brain areas that relate to these social behaviours and astrogliosis. METHODS: Imaging was performed in 2-yr-old NHPs under light anaesthesia, after early-in-life (postnatal days 6-12) exposure to 5 h of isoflurane either one or three times, or to room air. Brain images were segmented into 82 regions of interest; the amygdala and the posterior cingulate cortex were chosen for a seed-based resting-state functional connectivity MRI analysis. RESULTS: We found differences between groups in resting-state functional connectivity of the amygdala and the auditory cortices, medial premotor cortex, and posterior cingulate cortex. There were also alterations in resting-state functional connectivity between the posterior cingulate cortex and secondary auditory, polar prefrontal, and temporal cortices, and the anterior insula. Relationships were identified between resting-state functional connectivity alterations and the decrease in close social behaviour and increased astrogliosis. CONCLUSIONS: Early-in-life anaesthesia exposure in NHPs is associated with resting-state functional connectivity alterations of the amygdala and the posterior cingulate cortex with other brain regions, evident at the juvenile age of 2 yr. These changes in resting-state functional connectivity correlate with the decrease in close social behaviour and increased astrogliosis. Using resting-state functional connectivity MRI to study the neuronal underpinnings of early-in-life anaesthesia-induced behavioural alterations could facilitate development of a biomarker for anaesthesia-induced developmental neurotoxicity.
Subject(s)
Isoflurane , Animals , Isoflurane/adverse effects , Gliosis , Brain/diagnostic imaging , Gyrus Cinguli/diagnostic imaging , Magnetic Resonance Imaging/methods , Primates , Brain Mapping/methods , Neural Pathways/diagnostic imaging , Neural Pathways/physiologyABSTRACT
The importance of motion correction when processing resting state functional magnetic resonance imaging (rs-fMRI) data is well-established in adult cohorts. This includes adjustments based on self-limited, large amplitude subject head motion, as well as factitious rhythmic motion induced by respiration. In adults, such respiration artifact can be effectively removed by applying a notch filter to the motion trace, resulting in higher amounts of data retained after frame censoring (e.g., "scrubbing") and more reliable correlation values. Due to the unique physiological and behavioral characteristics of infants and toddlers, rs-fMRI processing pipelines, including methods to identify and remove colored noise due to subject motion, must be appropriately modified to accurately reflect true neuronal signal. These younger cohorts are characterized by higher respiration rates and lower-amplitude head movements than adults; thus, the presence and significance of comparable respiratory artifact and the subsequent necessity of applying similar techniques remain unknown. Herein, we identify and characterize the consistent presence of respiratory artifact in rs-fMRI data collected during natural sleep in infants and toddlers across two independent cohorts (aged 8-24 months) analyzed using different pipelines. We further demonstrate how removing this artifact using an age-specific notch filter allows for both improved data quality and data retention in measured results. Importantly, this work reveals the critical need to identify and address respiratory-driven head motion in fMRI data acquired in young populations through the use of age-specific motion filters as a mechanism to optimize the accuracy of measured results in this population.
Subject(s)
Image Processing, Computer-Assisted/methods , Magnetic Resonance Imaging/methods , Motion , Neuroimaging/methods , Artifacts , Connectome/methods , Female , Head Movements , Humans , Infant , Male , Respiration , SleepABSTRACT
As public access to longitudinal developmental datasets like the Adolescent Brain Cognitive Development StudySM (ABCD Study®) increases, so too does the need for resources to benchmark time-dependent effects. Scan-to-scan changes observed with repeated imaging may reflect development but may also reflect practice effects, day-to-day variability in psychological states, and/or measurement noise. Resources that allow disentangling these time-dependent effects will be useful in quantifying actual developmental change. We present an accelerated adult equivalent of the ABCD Study dataset (a-ABCD) using an identical imaging protocol to acquire magnetic resonance imaging (MRI) structural, diffusion-weighted, resting-state and task-based data from eight adults scanned five times over five weeks. We report on the task-based imaging data (n = 7). In-scanner stop-signal (SST), monetary incentive delay (MID), and emotional n-back (EN-back) task behavioral performance did not change across sessions. Post-scan recognition memory for emotional n-back stimuli, however, did improve as participants became more familiar with the stimuli. Functional MRI analyses revealed that patterns of task-based activation reflecting inhibitory control in the SST, reward success in the MID task, and working memory in the EN-back task were more similar within individuals across repeated scan sessions than between individuals. Within-subject, activity was more consistent across sessions during the EN-back task than in the SST and MID task, demonstrating differences in fMRI data reliability as a function of task. The a-ABCD dataset provides a unique testbed for characterizing the reliability of brain function, structure, and behavior across imaging modalities in adulthood and benchmarking neurodevelopmental change observed in the open-access ABCD Study.
Subject(s)
Brain , Neuroimaging , Adolescent , Adult , Brain/physiology , Humans , Magnetic Resonance Imaging/methods , Memory, Short-Term/physiology , Reproducibility of ResultsABSTRACT
T1- and T2-weighted (T1w and T2w) images are essential for tissue classification and anatomical localization in Magnetic Resonance Imaging (MRI) analyses. However, these anatomical data can be challenging to acquire in non-sedated neonatal cohorts, which are prone to high amplitude movement and display lower tissue contrast than adults. As a result, one of these modalities may be missing or of such poor quality that they cannot be used for accurate image processing, resulting in subject loss. While recent literature attempts to overcome these issues in adult populations using synthetic imaging approaches, evaluation of the efficacy of these methods in pediatric populations and the impact of these techniques in conventional MR analyses has not been performed. In this work, we present two novel methods to generate pseudo-T2w images: the first is based in deep learning and expands upon previous models to 3D imaging without the requirement of paired data, the second is based in nonlinear multi-atlas registration providing a computationally lightweight alternative. We demonstrate the anatomical accuracy of pseudo-T2w images and their efficacy in existing MR processing pipelines in two independent neonatal cohorts. Critically, we show that implementing these pseudo-T2w methods in resting-state functional MRI analyses produces virtually identical functional connectivity results when compared to those resulting from T2w images, confirming their utility in infant MRI studies for salvaging otherwise lost subject data.
Subject(s)
Magnetic Resonance Imaging , Neuroimaging , Adult , Child , Humans , Image Processing, Computer-Assisted/methods , Infant, Newborn , Magnetic Resonance Imaging/methodsABSTRACT
The Brain Imaging Data Structure (BIDS) is a specification accompanied by a software ecosystem that was designed to create reproducible and automated workflows for processing neuroimaging data. BIDS Apps flexibly build workflows based on the metadata detected in a dataset. However, even BIDS valid metadata can include incorrect values or omissions that result in inconsistent processing across sessions. Additionally, in large-scale, heterogeneous neuroimaging datasets, hidden variability in metadata is difficult to detect and classify. To address these challenges, we created a Python-based software package titled "Curation of BIDS" (CuBIDS), which provides an intuitive workflow that helps users validate and manage the curation of their neuroimaging datasets. CuBIDS includes a robust implementation of BIDS validation that scales to large samples and incorporates DataLad--a version control software package for data--as an optional dependency to ensure reproducibility and provenance tracking throughout the entire curation process. CuBIDS provides tools to help users perform quality control on their images' metadata and identify unique combinations of imaging parameters. Users can then execute BIDS Apps on a subset of participants that represent the full range of acquisition parameters that are present, accelerating pipeline testing on large datasets.