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BACKGROUND: Air pollution is ubiquitous, yet questions remain regarding its impact on the developing brain. Large changes occur in white matter microstructure across adolescence, with notable differences by sex. METHODS: We investigate sex-stratified effects of annual exposure to fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3) at ages 9-10 years on longitudinal patterns of white matter microstructure over a 2-year period. Diffusion-weighted imaging was collected on 3T MRI scanners for 8182 participants (1-2 scans per subject; 45% with two scans) from the Adolescent Brain Cognitive Development (ABCD) Study®. Restriction spectrum imaging was performed to quantify intracellular isotropic (RNI) and directional (RND) diffusion. Ensemble-based air pollution concentrations were assigned to each child's primary residential address. Multi-pollutant, sex-stratified linear mixed-effect models assessed associations between pollutants and RNI/RND with age over time, adjusting for sociodemographic factors. RESULTS: Here we show higher PM2.5 exposure is associated with higher RND at age 9 in both sexes, with no significant effects of PM2.5 on RNI/RND change over time. Higher NO2 exposure is associated with higher RNI at age 9 in both sexes, as well as attenuating RNI over time in females. Higher O3 exposure is associated with differences in RND and RNI at age 9, as well as changes in RND and RNI over time in both sexes. CONCLUSIONS: Criteria air pollutants influence patterns of white matter maturation between 9-13 years old, with some sex-specific differences in the magnitude and anatomical locations of affected tracts. This occurs at concentrations that are below current U.S. standards, suggesting exposure to low-level pollution during adolescence may have long-term consequences.
Air pollution is known to affect health, but it is unclear whether it affects the growing human brain. We investigated whether there were differences in the development of white matter connections, which allow for faster communication between different brain regions, in children aged 9-13 years living in areas with relatively low or high air pollution in the USA. In a large group of U.S. teens, we find that polluted air is linked to differences in white matter at ages 9-10 years old and over the next two years. In some cases, males and females showed differences in the part of the brain showing changes and the amount of white matter change. Our study suggests that air pollution levels that are deemed acceptable under current regulations in the USA could have long-term effects on how a child's brain grows. Further studies are needed to better understand the impact of these changes.
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Humans and nonhuman primate studies suggest that timing and tempo of cortical development varies neuroanatomically along a sensorimotor-to-association (S-A) axis. Prior human studies have reported a principal S-A axis across various modalities, but largely rely on cross-sectional samples with wide age-ranges. Here, we investigate developmental changes and individual variability in cortical organization along the S-A axis between the ages of 9-13 years using a large, longitudinal sample (N = 2487-3747, 46-50% female) from the Adolescent Brain Cognitive Development Study (ABCD Study®). This work assesses multiple aspects of neurodevelopment indexed by changes in cortical thickness, cortical microarchitecture, and resting-state functional fluctuations. First, we evaluated S-A organization in age-related changes and, then, computed individual-level S-A alignment in brain changes and assessing differences therein due to age, sex, and puberty. Varying degrees of linear and quadratic age-related brain changes were identified along the S-A axis. Yet, these patterns of cortical development were overshadowed by considerable individual variability in S-A alignment. Even within individuals, there was little correspondence between S-A patterning across the different aspects of neurodevelopment investigated (i.e., cortical morphology, microarchitecture, function). Some of the individual variation in developmental patterning of cortical morphology and microarchitecture was explained by age, sex, and pubertal development. Altogether, this work contextualizes prior findings that regional age differences do progress along an S-A axis at a group level, while highlighting broad variation in developmental change between individuals and between aspects of cortical development, in part due to sex and puberty. Significance Statement: Understanding normative patterns of adolescent brain change, and individual variability therein, is crucial for disentangling healthy and abnormal development. We used longitudinal human neuroimaging data to study several aspects of neurodevelopment during early adolescence and assessed their organization along a sensorimotor-to-association (S-A) axis across the cerebral cortex. Age differences in brain changes were linear and curvilinear along this S-A axis. However, individual-level sensorimotor-association alignment varied considerably, driven in part by differences in age, sex, and pubertal development.
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Exposure to outdoor air pollution has been linked to adverse health effects, including potential widespread impacts on the CNS. Ongoing brain development may render children and adolescents especially vulnerable to neurotoxic effects of air pollution. While mechanisms remain unclear, promising advances in human neuroimaging can help elucidate both sensitive periods and neurobiological consequences of exposure to air pollution. Herein we review the potential influences of air pollution exposure on neurodevelopment, drawing from animal toxicology and human neuroimaging studies. Due to ongoing cellular and system-level changes during childhood and adolescence, the developing brain may be more sensitive to pollutants' neurotoxic effects, as a function of both timing and duration, with relevance to cognition and mental health. Building on these foundations, the emerging field of environmental neuroscience is poised to further decipher which air toxicants are most harmful and to whom.
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Contaminación del Aire , Encéfalo , Humanos , Encéfalo/crecimiento & desarrollo , Contaminación del Aire/efectos adversos , Niño , Adolescente , Animales , Exposición a Riesgos Ambientales/efectos adversos , Contaminantes Atmosféricos/efectos adversos , Contaminantes Atmosféricos/toxicidadRESUMEN
Exposure to outdoor particulate matter (PM2.5) represents a ubiquitous threat to human health, and particularly the neurotoxic effects of PM2.5 from multiple sources may disrupt neurodevelopment. Studies addressing neurodevelopmental implications of PM exposure have been limited by small, geographically limited samples and largely focus either on macroscale cortical morphology or postmortem histological staining and total PM mass. Here, we leverage residentially assigned exposure to six, data-driven sources of PM2.5 and neuroimaging data from the longitudinal Adolescent Brain Cognitive Development Study (ABCD Study®), collected from 21 different recruitment sites across the United States. To contribute an interpretable and actionable assessment of the role of air pollution in the developing brain, we identified alterations in cortical microstructure development associated with exposure to specific sources of PM2.5 using multivariate, partial least squares analyses. Specifically, average annual exposure (i.e., at ages 8-10 years) to PM2.5 from biomass burning was related to differences in neurite development across the cortex between 9 and 13 years of age.
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Contaminantes Atmosféricos , Contaminación del Aire , Biomasa , Material Particulado , Adolescente , Material Particulado/toxicidad , Humanos , Contaminación del Aire/efectos adversos , Niño , Masculino , Femenino , Contaminantes Atmosféricos/toxicidad , Exposición a Riesgos Ambientales/efectos adversos , Estados Unidos , Corteza Cerebral/efectos de los fármacos , Estudios LongitudinalesRESUMEN
Background: Transparency can build trust in the scientific process, but scientific findings can be undermined by poor and obscure data use and reporting practices. The purpose of this work is to report how data from the Adolescent Brain Cognitive Development (ABCD) Study has been used to date, and to provide practical recommendations on how to improve the transparency and reproducibility of findings. Methods: Articles published from 2017 to 2023 that used ABCD Study data were reviewed using more than 30 data extraction items to gather information on data use practices. Total frequencies were reported for each extraction item, along with computation of a Level of Completeness (LOC) score that represented overall endorsement of extraction items. Univariate linear regression models were used to examine the correlation between LOC scores and individual extraction items. Post hoc analysis included examination of whether LOC scores were correlated with the logged 2-year journal impact factor. Results: There were 549 full-length articles included in the main analysis. Analytic scripts were shared in 30% of full-length articles. The number of participants excluded due to missing data was reported in 60% of articles, and information on missing data for individual variables (e.g., household income) was provided in 38% of articles. A table describing the analytic sample was included in 83% of articles. A race and/or ethnicity variable was included in 78% of reviewed articles, while its inclusion was justified in only 41% of these articles. LOC scores were highly correlated with extraction items related to examination of missing data. A bottom 10% of LOC score was significantly correlated with a lower logged journal impact factor when compared to the top 10% of LOC scores (ß=-0.77, 95% -1.02, -0.51; p-value < 0.0001). Conclusion: These findings highlight opportunities for improvement in future papers using ABCD Study data to readily adapt analytic practices for better transparency and reproducibility efforts. A list of recommendations is provided to facilitate adherence in future research.
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BACKGROUND: Transparency can build trust in the scientific process, but scientific findings can be undermined by poor and obscure data use and reporting practices. The purpose of this work is to report how data from the Adolescent Brain Cognitive Development (ABCD) Study has been used to date, and to provide practical recommendations on how to improve the transparency and reproducibility of findings. METHODS: Articles published from 2017 to 2023 that used ABCD Study data were reviewed using more than 30 data extraction items to gather information on data use practices. Total frequencies were reported for each extraction item, along with computation of a Level of Completeness (LOC) score that represented overall endorsement of extraction items. Univariate linear regression models were used to examine the correlation between LOC scores and individual extraction items. Post hoc analysis included examination of whether LOC scores were correlated with the logged 2-year journal impact factor. RESULTS: There were 549 full-length articles included in the main analysis. Analytic scripts were shared in 30â¯% of full-length articles. The number of participants excluded due to missing data was reported in 60â¯% of articles, and information on missing data for individual variables (e.g., household income) was provided in 38â¯% of articles. A table describing the analytic sample was included in 83â¯% of articles. A race and/or ethnicity variable was included in 78â¯% of reviewed articles, while its inclusion was justified in only 41â¯% of these articles. LOC scores were highly correlated with extraction items related to examination of missing data. A bottom 10â¯% of LOC score was significantly correlated with a lower logged journal impact factor when compared to the top 10â¯% of LOC scores (ß=-0.77, 95â¯% -1.02, -0.51; p-value < 0.0001). CONCLUSION: These findings highlight opportunities for improvement in future papers using ABCD Study data to readily adapt analytic practices for better transparency and reproducibility efforts. A list of recommendations is provided to facilitate adherence in future research.
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Desarrollo del Adolescente , Humanos , Reproducibilidad de los Resultados , Adolescente , Desarrollo del Adolescente/fisiología , Cognición/fisiología , Encéfalo/crecimiento & desarrolloRESUMEN
Exposure to outdoor particulate matter (PM 2.5 ) represents a ubiquitous threat to human health, and particularly the neurotoxic effects of PM 2.5 from multiple sources may disrupt neurodevelopment. Studies addressing neurodevelopmental implications of PM exposure have been limited by small, geographically limited samples and largely focus either on macroscale cortical morphology or postmortem histological staining and total PM mass. Here, we leverage residentially assigned exposure to six, data-driven sources of PM 2.5 and neuroimaging data from the longitudinal Adolescent Brain Cognitive Development Study (ABCD Study®), collected from 21 different recruitment sites across the United States. To contribute an interpretable and actionable assessment of the role of air pollution in the developing brain, we identified alterations in cortical microstructure development associated with exposure to specific sources of PM 2.5 using multivariate, partial least squares analyses. Specifically, average annual exposure (i.e., at ages 8-10 years) to PM 2.5 from biomass burning was related to differences in neurite development across the cortex between 9 and 13 years of age.
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This cohort study explores variability in neurodevelopment across sociodemographic factors among youths.
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Desarrollo del Adolescente , Humanos , Adolescente , Femenino , Masculino , Trastornos del Neurodesarrollo/epidemiología , Clase SocialRESUMEN
Recent studies have linked air pollution to increased risk for behavioral problems during development, albeit with inconsistent findings. Additional longitudinal studies are needed that consider how emotional behaviors may be affected when exposure coincides with the transition to adolescence - a vulnerable time for developing mental health difficulties. This study investigates if annual average PM2.5 and NO2 exposure at ages 9-10 years moderates age-related changes in internalizing and externalizing behaviors over a 2-year follow-up period in a large, nationwide U.S. sample of participants from the Adolescent Brain Cognitive Development (ABCD) Study®. Air pollution exposure was estimated based on the residential address of each participant using an ensemble-based modeling approach. Caregivers answered questions from the Child Behavior Checklist (CBCL) at the baseline, 1-year follow-up, and 2-year follow-up visits, for a total of 3 waves of data; from the CBCL we obtained scores on internalizing and externalizing problems plus 5 syndrome scales (anxious/depressed, withdrawn/depressed, rule-breaking behavior, aggressive behavior, and attention problems). Zero-inflated negative binomial models were used to examine both the main effect of age as well as the interaction of age with each pollutant on behavior while adjusting for various socioeconomic and demographic characteristics. Against our hypothesis, there was no evidence that greater air pollution exposure was related to more behavioral problems with age over time.
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Contaminación del Aire , Niño , Humanos , Adolescente , Contaminación del Aire/efectos adversos , Estudios Longitudinales , Agresión , AnsiedadRESUMEN
Background: Population-based neuroscience offers opportunities to examine important but understudied sociocultural factors such as acculturation. Acculturation refers to the extent to which an individual retains their cultural heritage and/or adopts the receiving society's culture and is particularly salient among Hispanic/Latinx immigrants. Specific acculturative orientations have been linked to vulnerability to substance use, depression, and suicide and are known to influence family dynamics between caregivers and their children. Methods: Using data from first- and second-generation Hispanic/Latinx caregivers in the Adolescent Brain Cognitive Development (ABCD) Study (N = 1057), we examined how caregivers' acculturative orientation affects their mental health, as well as the mental health and brain function of their children. Neuroimaging analyses focused on regions associated with self- and affiliation-based social processing (ventromedial prefrontal cortex, insula, and temporoparietal junction). Results: We identified 2 profiles of caregiver acculturation: bicultural (retains heritage culture while adopting U.S. culture) and detached (discards heritage culture and rejects U.S. culture). Bicultural caregivers exhibited fewer internalizing and externalizing problems than detached caregivers; furthermore, youth exhibited similar internalizing effects across caregiver profiles. In addition, youth with bicultural caregivers displayed increased resting-state brain activity (i.e., fractional amplitude of low-frequency fluctuations and regional homogeneity) in the left insula, which has been linked to psychopathology; however, differences in long-range functional connectivity were not significant. Conclusions: Caregiver acculturation is an important familial factor that has been linked to significant differences in youth mental health and insula activity. Future work should examine sociocultural and neurodevelopmental changes across adolescence to assess health outcomes and determine whether localized, corticolimbic brain effects are ultimately translated into long-range connectivity differences.
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PURPOSE: Attentional control theory (ACT) posits that elevated anxiety increases the probability of re-allocating cognitive resources needed to complete a task to processing anxiety-related stimuli. This process impairs processing efficiency and can lead to reduced performance effectiveness. Science, technology, engineering, and math (STEM) students frequently experience anxiety about their coursework, which can interfere with learning and performance and negatively impact student retention and graduation rates. The objective of this study was to extend the ACT framework to investigate the neurobiological associations between science and math anxiety and cognitive performance among 123 physics undergraduate students. PROCEDURES: Latent profile analysis (LPA) identified four profiles of science and math anxiety among STEM students, including two profiles that represented the majority of the sample (Low Science and Math Anxiety; 59.3% and High Math Anxiety; 21.9%) and two additional profiles that were not well represented (High Science and Math Anxiety; 6.5% and High Science Anxiety; 4.1%). Students underwent a functional magnetic resonance imaging (fMRI) session in which they performed two tasks involving physics cognition: the Force Concept Inventory (FCI) task and the Physics Knowledge (PK) task. FINDINGS: No significant differences were observed in FCI or PK task performance between High Math Anxiety and Low Science and Math Anxiety students. During the three phases of the FCI task, we found no significant brain connectivity differences during scenario and question presentation, yet we observed significant differences during answer selection within and between the dorsal attention network (DAN), ventral attention network (VAN), and default mode network (DMN). Further, we found significant group differences during the PK task were limited to the DAN, including DAN-VAN and within-DAN connectivity. CONCLUSIONS: These results highlight the different cognitive processes required for physics conceptual reasoning compared to physics knowledge retrieval, provide new insight into the underlying brain dynamics associated with anxiety and physics cognition, and confirm the relevance of ACT theory for science and math anxiety.
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Trastornos de Ansiedad , Ansiedad , Humanos , Universidades , Física , EstudiantesRESUMEN
Macroscale gradients have emerged as a central principle for understanding functional brain organization. Previous studies have demonstrated that a principal gradient of connectivity in the human brain exists, with unimodal primary sensorimotor regions situated at one end and transmodal regions associated with the default mode network and representative of abstract functioning at the other. The functional significance and interpretation of macroscale gradients remains a central topic of discussion in the neuroimaging community, with some studies demonstrating that gradients may be described using meta-analytic functional decoding techniques. However, additional methodological development is necessary to fully leverage available meta-analytic methods and resources and quantitatively evaluate their relative performance. Here, we conducted a comprehensive series of analyses to investigate and improve the framework of data-driven, meta-analytic methods, thereby establishing a principled approach for gradient segmentation and functional decoding. We found that a two-segment solution determined by a k-means segmentation approach and an LDA-based meta-analysis combined with the NeuroQuery database was the optimal combination of methods for decoding functional connectivity gradients. Finally, we proposed a method for decoding additional components of the gradient decomposition. The current work aims to provide recommendations on best practices and flexible methods for gradient-based functional decoding of fMRI data.
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As we move toward population-level developmental neuroscience, understanding intra- and inter-individual variability in brain maturation and sources of neurodevelopmental heterogeneity becomes paramount. Large-scale, longitudinal neuroimaging studies have uncovered group-level neurodevelopmental trajectories, and while recent work has begun to untangle intra- and inter-individual differences, they remain largely unclear. Here, we aim to quantify both intra- and inter-individual variability across facets of neurodevelopment across early adolescence (ages 8.92 to 13.83 years) in the Adolescent Brain Cognitive Development (ABCD) Study and examine inter-individual variability as a function of age, sex, and puberty. Our results provide novel insight into differences in annualized percent change in macrostructure, microstructure, and functional brain development from ages 9-13 years old. These findings reveal moderate age-related intra-individual change, but age-related differences in inter-individual variability only in a few measures of cortical macro- and microstructure development. Greater inter-individual variability in brain development were seen in mid-pubertal individuals, except for a few aspects of white matter development that were more variable between prepubertal individuals in some tracts. Although both sexes contributed to inter-individual differences in macrostructure and functional development in a few regions of the brain, we found limited support for hypotheses regarding greater male-than-female variability. This work highlights pockets of individual variability across facets of early adolescent brain development, while also highlighting regional differences in heterogeneity to facilitate future investigations in quantifying and probing nuances in normative development, and deviations therefrom.
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Individualidad , Sustancia Blanca , Humanos , Masculino , Adolescente , Femenino , Niño , Encéfalo/diagnóstico por imagen , Sustancia Blanca/diagnóstico por imagen , Neuroimagen/métodos , CogniciónRESUMEN
Recent studies have linked air pollution to increased risk for behavioral problems during development, albeit with inconsistent findings. Additional longitudinal studies are needed that consider how emotional behaviors may be affected when exposure coincides with the transition to adolescence - a vulnerable time for developing mental health difficulties. This study examines how annual average PM2.5 and NO2 exposure at ages 9-10 years relates to internalizing and externalizing behaviors over a 2-year follow-up period in a large, nationwide U.S. sample of participants from the Adolescent Brain Cognitive Development (ABCD) Study®. Air pollution exposure was estimated based on the residential address of each participant using an ensemble-based modeling approach. Caregivers answered questions from the Child Behavior Checklist (CBCL) at baseline and annually for two follow-up sessions for a total of 3 waves of data; from the CBCL we obtained scores on internalizing and externalizing problems plus 5 syndrome scales (anxious/depressed, withdrawn/depressed, rule-breaking behavior, aggressive behavior, and attention problems). Zero-inflated negative binomial models were used to examine both the main effect of age as well as the interaction of age with each pollutant on behavior while adjusting for various socioeconomic and demographic characteristics. Overall, the pollution effects moderated the main effects of age with higher levels of PM2.5 and NO2 leading to an even greater likelihood of having no behavioral problems (i.e., score of zero) with age over time, as well as fewer problems when problems are present as the child ages. Albeit this was on the order equal to or less than a 1-point change. Thus, one year of annual exposure at 9-10 years is linked with very small change in emotional behaviors in early adolescence, which may be of little clinical relevance.
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Neuroimaging studies showing the adverse effects of air pollution on neurodevelopment have largely focused on smaller samples from limited geographical locations and have implemented univariant approaches to assess exposure and brain macrostructure. Herein, we implement restriction spectrum imaging and a multivariate approach to examine how one year of annual exposure to daily fine particulate matter (PM2.5), daily nitrogen dioxide (NO2), and 8-h maximum ozone (O3) at ages 9-10 years relates to subcortical gray matter microarchitecture in a geographically diverse subsample of children from the Adolescent Brain Cognitive Development (ABCD) Studyâ . Adjusting for confounders, we identified a latent variable representing 66% of the variance between one year of air pollution and subcortical gray matter microarchitecture. PM2.5 was related to greater isotropic intracellular diffusion in the thalamus, brainstem, and accumbens, which related to cognition and internalizing symptoms. These findings may be indicative of previously identified air pollution-related risk for neuroinflammation and early neurodegenerative pathologies.
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Neuroscientists have sought to identify the underlying neural systems supporting social processing that allow interaction and communication, forming social relationships, and navigating the social world. Through the use of NIMH's Research Domain Criteria (RDoC) framework, we evaluated consensus among studies that examined brain activity during social tasks to elucidate regions comprising the "social brain". We examined convergence across tasks corresponding to the four RDoC social constructs, including Affiliation and Attachment, Social Communication, Perception and Understanding of Self, and Perception and Understanding of Others. We performed a series of coordinate-based meta-analyses using the activation likelihood estimate (ALE) method. Meta-analysis was performed on whole-brain coordinates reported from 864 fMRI contrasts using the NiMARE Python package, revealing convergence in medial prefrontal cortex, anterior cingulate cortex, posterior cingulate cortex, temporoparietal junction, bilateral insula, amygdala, fusiform gyrus, precuneus, and thalamus. Additionally, four separate RDoC-based meta-analyses revealed differential convergence associated with the four social constructs. These outcomes highlight the neural support underlying these social constructs and inform future research on alterations among neurotypical and atypical populations.
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Mapeo Encefálico , Encéfalo , Humanos , Funciones de Verosimilitud , Encéfalo/diagnóstico por imagen , Encéfalo/fisiología , Lóbulo Temporal , Imagen por Resonancia MagnéticaRESUMEN
Altered activity within and between large-scale brain networks has been implicated across various neuropsychiatric conditions. However, patterns of network dysregulation associated with human immunodeficiency virus (HIV), and further impacted by cannabis (CB) use, remain to be delineated. We examined the impact of HIV and CB on resting-state functional connectivity (rsFC) between brain networks and associations with error awareness and error-related network responsivity. Participants (N = 106), stratified into four groups (HIV+/CB+, HIV+/CB-, HIV-/CB+, HIV-/CB-), underwent fMRI scanning while completing a resting-state scan and a modified Go/NoGo paradigm assessing brain responsivity to errors and explicit error awareness. We examined separate and interactive effects of HIV and CB on resource allocation indexes (RAIs), a measure quantifying rsFC strength between the default mode network (DMN), central executive network (CEN), and salience network (SN). We observed reduced RAIs among HIV+ (vs. HIV-) participants, which was driven by increased SN-DMN rsFC. No group differences were detected for SN-CEN rsFC. Increased SN-DMN rsFC correlated with diminished error awareness, but not with error-related network responsivity. These outcomes highlight altered network interactions among participants with HIV and suggest such rsFC dysregulation may persist during task performance, reflecting an inability to disengage irrelevant mental operations, ultimately hindering error processing.
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As the global health crisis unfolded, many academic conferences moved online in 2020. This move has been hailed as a positive step towards inclusivity in its attenuation of economic, physical, and legal barriers and effectively enabled many individuals from groups that have traditionally been underrepresented to join and participate. A number of studies have outlined how moving online made it possible to gather a more global community and has increased opportunities for individuals with various constraints, e.g., caregiving responsibilities. Yet, the mere existence of online conferences is no guarantee that everyone can attend and participate meaningfully. In fact, many elements of an online conference are still significant barriers to truly diverse participation: the tools used can be inaccessible for some individuals; the scheduling choices can favour some geographical locations; the set-up of the conference can provide more visibility to well-established researchers and reduce opportunities for early-career researchers. While acknowledging the benefits of an online setting, especially for individuals who have traditionally been underrepresented or excluded, we recognize that fostering social justice requires inclusivity to actively be centered in every aspect of online conference design. Here, we draw from the literature and from our own experiences to identify practices that purposefully encourage a diverse community to attend, participate in, and lead online conferences. Reflecting on how to design more inclusive online events is especially important as multiple scientific organizations have announced that they will continue offering an online version of their event when in-person conferences can resume.
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Brainhack is an innovative meeting format that promotes scientific collaboration and education in an open, inclusive environment. This NeuroView describes the myriad benefits for participants and the research community and how Brainhacks complement conventional formats to augment scientific progress.
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Comunicación , Internet , Neurociencias/organización & administración , Congresos como Asunto , Guías de Práctica Clínica como AsuntoRESUMEN
Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses1. The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset2-5. Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed.