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Importance: The brain enters distinct activation states to support differential cognitive and emotional processes, but little is known about how brain activation states differ in youths with clinical anxiety., Objective: To characterize brain activation states during socioemotional processing (movie stimuli) and assess associations between state characteristics and movie features and anxiety symptoms., Design, Setting, and Participants: The Healthy Brain Network is an ongoing cross-sectional study of individuals aged 5 to 21 years experiencing difficulties in school, of whom approximately 45% met criteria for a lifetime anxiety disorder diagnosis. Data used in this study are from the first 9 releases (collected in a nonclinical research setting in the New York City metropolitan area from 2015 to 2020) and include 620 youths aged 5 to 15 years (53% of whom met criteria for a lifetime anxiety disorder diagnosis) who watched an emotional video during functional magnetic resonance imaging and completed questionnaires and clinical evaluation. Of those with functional magnetic resonance imaging data, 432 youths aged 7 to 15 years also self-reported on anxiety symptoms. Data were processed and analyzed between February 2020 and August 2024., Main Outcomes and Measures: A hidden Markov model was trained to identify brain activation states across participants during video watching. Time spent in each state and the moment-to-moment probability of being in each state were extracted. Videos were annotated for emotion-specific and nonspecific information using the EmoCodes system. Self-reported anxiety symptoms were assessed using the Screen for Child Anxiety Related Disorders. Time spent in each state across the video and during and outside of peaks in negative content correlated with generalized and social anxiety scores., Results: Among the 620 youths in the overall analysis, 369 were male and the mean (SD) age was 10.4 (2.8) years. In the anxiety symptom analysis, 263 of 432 youths were male and the mean (SD) age was 11.5 (2.2) years. Three brain activation states were identified: a high somatomotor activation state (state 1), a high cingulo-opercular network activation state (state 2), and a high ventral attention and default mode state (state 3). The probability of being in state 3 was correlated with video content that was more negative, quieter, and with less visual motion (ρ < 0.08; P < .001). Increased generalized anxiety was associated with greater time in state 3 (B, 0.10; 95% CI, 0.01 to 0.20; false discovery rate [FDR]-corrected P = .048) and less time in state 2 (B, -0.11; 95% CI, -0.21 to -0.02; FDR-corrected P = .048) when negative social cues were present., Conclusions and Relevance: Youths entered 3 distinct brain activation states during movie watching, and youths with anxiety spent more time in a state with high ventral attention and default activation during negative socioemotional processing. Youths high in generalized anxiety may be more engaged in deeply processing negative emotional content, which may influence self-regulation. Interventions that focus on changing physiological and psychological state during negative social interactions in youths with anxiety should be considered.

The characterization of individual functional brain organization with Precision Functional Mapping has provided important insights in recent years in adults. However, little is known about the ontogeny of inter-individual differences in brain functional organization during human development. Precise characterization of systems organization during periods of high plasticity is likely to be essential for discoveries promoting lifelong health. Obtaining precision fMRI data during development has unique challenges that highlight the importance of establishing new methods to improve data acquisition, processing, and analysis. Here, we investigate two methods that can facilitate attaining this goal: multi-echo (ME) data acquisition and thermal noise removal with Noise Reduction with Distribution Corrected (NORDIC) principal component analysis. We applied these methods to precision fMRI data from adults, children, and newborn infants. In adults, both ME acquisitions and NORDIC increased temporal signal to noise ratio (tSNR) as well as the split-half reliability of functional connectivity matrices, with the combination helping more than either technique alone. The benefits of NORDIC denoising replicated in both our developmental samples. ME acquisitions revealed longer and more variable T2* relaxation times across the brain in infants relative to older children and adults, leading to major differences in the echo weighting for optimally combining ME data. This result suggests ME acquisitions may be a promising tool for optimizing developmental fMRI, albeit application in infants needs further investigation. The present work showcases methodological advances that improve Precision Functional Mapping in adults and developmental populations and, at the same time, highlights the need for further improvements in infant specific fMRI., Competing Interests: 8.Declaration of Competing Interests Damien A. Fair is a patent holder on the Framewise Integrated Real-Time Motion Monitoring (FIRMM) software. He is also a co-founder of Turing Medical Inc that licenses this software. The nature of this financial interest and the design of the study have been reviewed by two committees at the University of Minnesota. They have put in place a plan to help ensure that this research study is not affected by the financial interest. Steven M. Nelson consults for Turing Medical, which commercializes FIRMM. This interest has been reviewed and managed by the University of Minnesota in accordance with its Conflict of Interest policies. Author Nico U. F. Dosenbach is a co-founder of Turing Medical Inc, has financial interest, and may benefit financially if the company is successful in marketing FIRMM motion monitoring software products. NUFD may receive royalty income based on FIRMM technology developed at Washington University School of Medicine (WUSOM) and licensed to Turing Medical Inc. Timothy O. Laumann holds a patent for taskless mapping of brain activity licensed to Sora Neurosciences and a patent for optimizing targets for neuromodulation, implant localization, and ablation is pending. TOL is also a consultant for Turing Medical Inc. Abraham Z. Snyder is a consultant for Sora Neurosciences. These potential conflicts of interest have been reviewed and are managed by Washington University School of Medicine. The other authors declare no competing interests.