While the provided sources offer rich insights into the developmental trajectory of naturalistic processing and the clinical utility of movie-fMRI, they do not contain the specific papers you referenced by Cohen (2022), Tripathy (2024), or the AI-based developmental simulations (NeuroGPT, etc.). However, the corpus does include extensive data on infant event segmentation (from Yates, Ellis, et al., 2022), developmental changes in story/movie-evoked responses, and the use of naturalistic fMRI in atypical development.
Here is a synthesis of the developmental trajectory of naturalistic processing based on the available sources:
(a) Infant, Child, and Adolescent Naturalistic fMRI
- Infant Visual Cortex and Event Segmentation: A study of awake infants (3.6 to 12.7 months) and adults watching a continuous cartoon investigated how the brain segments naturalistic experience into discrete events [1, 2]. The adult brain exhibits a well-documented hierarchical gradient of event timescales: early sensory regions process shorter events (e.g., sudden visual changes), while higher-order associative regions process longer events (e.g., narrative plot points) [1, 3, 4]. In contrast, the infant brain does not yet possess this hierarchy [4, 5]. Instead, infants demonstrate a "flattened hierarchy," consistently segmenting experience into fewer, longer events across the entire brain, including early visual cortex [1, 4, 6]. This coarser event structure suggests that infants may have greater temporal integration, reduced temporal precision, or attentional limitations that restrict their processing of rapid sensory transients [5, 7, 8].
- Child and Adolescent Development: During early childhood, functional connectivity (FC) undergoes steep and dynamic changes. In cross-sectional and longitudinal studies of children aged 2 to 7, naturalistic viewing reveals that both sensory and higher-order networks develop rapidly [9, 10]. Furthermore, as children mature, their brain networks become more integrated internally while simultaneously exhibiting greater anti-correlation with other networks. For example, during movies that require Theory of Mind (mentalizing) or pain perception, network anti-correlation was found to change dynamically with age, and the degree of this anti-correlation strongly predicted the integration and maturity of the network [11, 12].
- Inter-Subject Correlations (ISCs) over Time: By comparing children’s neural responses during movies to an averaged "adult" time course, researchers map the maturation of specific regions. For instance, child-adult ISCs in the temporoparietal junction (TPJ) predict age and attentional development [13, 14]. In general, ISCs during complex processing appear to follow a "diffuse to focal" developmental pattern as children grow into adolescence [14].
(b) Early Biomarkers for Atypical Development and Age-of-Detection Naturalistic fMRI fundamentally lowers the barrier to scanning young and atypical populations, providing a mechanism for earlier detection and study of developmental disorders compared to traditional resting-state or cognitive tasks [15-17].
- Compliance and Early Detection: Children under the age of 7, as well as pediatric patients with autism spectrum disorder (ASD) or ADHD, have historically high scan failure rates due to excessive head motion [16, 18, 19]. Movie-watching paradigms significantly improve compliance and reduce head motion, particularly in children under 10 and those who struggle most with task-free resting states [20-22]. This enables the acquisition of robust functional data in clinical populations at much younger ages than was previously possible [17].
- Autism and ADHD: Movie-watching fMRI has successfully revealed idiosyncratic functional integration and segregation in individuals with ASD [23]. Connectome-based predictive modeling derived from these naturalistic scans has also been used to predict behavioral and social abilities in children with ASD and ADHD [24].
- Depression and Anxiety: Naturalistic paradigms appear to elicit symptom-related neural characteristics that remain hidden during traditional resting states [25]. For example, when watching emotional movies, individuals with depression show diminished ISCs in sensory and higher-order areas [26]. Regarding age-of-detection, research on adolescents viewing movies found that those with more severe depressive symptoms exhibited more atypical neural responses; however, this relationship between symptom severity and brain response typicality was not found in younger children, suggesting that some biomarkers for depression may be age-specific and emerge only during adolescence [26, 27].
- Language and Sensory Delays: In children with cochlear implants, naturalistic viewing of movies has been used to detect early cross-modal neural reorganization. Rather than deactivating auditory cortices during visual tasks like their typically hearing peers, deaf children exhibit altered responses, providing early biomarkers for why some children struggle with literacy and language development despite early implantation [28, 29].
(c) AI-Based Simulation of Neural Development Note: The provided sources do not discuss NeuroGPT, lifespan-trained brain foundation models, or the use of generative AI to predict developmental milestones.
The sources do, however, confirm the utility of artificial intelligence in modeling mature naturalistic processing. Deep neural networks (DNNs) and advanced language models (like GPT-2) have been successfully used to decode brain activity in adults processing naturalistic audiovisual events and speech [30-32]. For example, researchers have mapped the activations of multi-layer language algorithms directly onto human fMRI responses to show that both the brain and algorithms utilize a predictive coding hierarchy [32, 33]. Similarly, two-branch audiovisual DNNs have been compared to human fMRI/EEG data to prove that early cross-modal connections are necessary for biologically plausible models of perception [30, 34]. While these AI models currently illuminate the spatial and temporal dynamics of the adult brain, the corpus does not extend their application to the simulation of neural maturation or the prediction of pediatric developmental milestones.
[1] (src:80911ca8) Neural event segmentation of continuous experience in human infants Tristan S. Yatesa, Lena J. Skalabana, Cameron T. Ellisb , Angelika J. Bracherc,d , Christopher Baldassanoe, and Nicholas B. Turk-Brownea,f,1 Edited by Linda Smith, Indiana University Bloomington, Bloomington, IN; received January 9,...
[2] (src:80911ca8) Results Intersubject Correlation Reveals Reliable Neural Responses in Infants. We scanned infants (n = 24; 3.6 to 12.7 mo) and adults (n = 24; 18 to 32 y) while they watched a short, silent movie (“Aeronaut”) that had a complete narrative arc. To investigate the consistency of infants’ neural respon...
[3] (src:80911ca8) In this study, we collected movie-watching fMRI data from infants in their first year to investigate the early development of event perception during continuous, naturalistic experience. We also collected fMRI data from adults watching the same movie. We first asked whether the movie was processed r...
[4] (src:80911ca8) In adults, we replicated previous work showing a hierarchical gradient of event timescales across cortex, with more/shorter events in early visual compared to higher-order associative regions (Fig. 2A). Qualitative inspection revealed that boundaries in EVC seemed to correspond to multiple types of ...
[5] (src:80911ca8) With this adult comparison in hand, we tested three hypotheses about event segmentation in the infant brain. The first hypothesis is that infants possess an adult-like hierarchy of event timescales across the brain. This would fit with findings that aspects of adult brain function, including resting...
[6] (src:80911ca8) Event Structure in an Additional Infant Cohort. To provide additional evidence of coarser event structure in infancy, we applied our analyses to a more heterogeneous sample of in-fants who watched a different, short cartoon movie (“Mickey”) during breaks between tasks for other studies. We first ask...
[7] (src:80911ca8) Different mechanisms could be responsible for longer event timescales in infant visual regions. One account involves which in-puts are processed by the infant brain. Developmental differences in sensation (e.g., acuity), perception (e.g., object recognition), and/or attention (e.g., selection, vigil...
[8] (src:80911ca8) that shifts of attention can decrease the temporal resolution of perception (53) and that working-memory limitations can be associated with coarser event segmentation in some cases (54). By this account, the architecture for hierarchical event processing may be ready in infancy but not fully engaged...
[9] (src:43b9cbf0) 10. FC and age in preschool children In the first study of its kind in preschool children, Long et al. in-vestigated the relationship between basic FC measures and age in this pivotal developmental period. Using movies as an acquisition state enabled them to collect both cross-sectional and longitud...
[10] (src:43b9cbf0) As did the frontoparietal and default network regions in the Long et al. study, other data also show an overall pattern of FC increasing with age at a dynamic pace during early childhood. This has been de-monstrated for pain and Theory of Mind networks from ages 3–12 years (Richardson et al., 2018),...
[11] (src:43b9cbf0) (i.e., pain). Their data show that as a network matures and becomes more integrated, it also exhibits more anti-correlated interactions with other networks (Richardson et al., 2018) (see Fig. 6). In their sample, network interactions were the measure that changed most dynamically, going from uncorre...
[12] (src:43b9cbf0) Fig. 6. Inter-region correlation analysis using Theory of Mind (ToM) and Pain networks in children and adults. As intra-network correlations increased, anti-correlations between networks also increased. The degree of integration within a network was also found to predict the degree of anti-correlati...
[13] (src:43b9cbf0) adult time course at each voxel (Cantlon and Li, 2013; Moraczewski et al., 2018; Richardson et al., 2018). The advantage of generating an averaged adult time course is that it provides a model for what mature neural responses in dynamic, complex conditions might look like at each voxel. Each child’s...
[14] (src:43b9cbf0) 13.2. Intersubject correlations ISCs could also be studied longitudinally to delineate trajectories of functional brain development of complex processing. It remains unclear how intersubject correlations during movie-watching change with de-velopment. Some data indicate that ISCs become stronger wit...
[15] (src:43b9cbf0) Despite these challenges, a major reason for the growing use of naturalistic paradigms in developmental fMRI has been the effect of movie-watching on head motion during scanning. With conventional task-based fMRI, scanning young awake children was possible because child-friendly tasks maintained int...
[16] (src:43b9cbf0) from awake children under the age of 7 years has remained a formid-able challenge.1 Even now, more than 20 years after the advent of resting state, only a few studies have used task-free conditions with substantial numbers of awake children under the age of 6 years (e.g., de Bie et al., 2012; Langes...
[17] (src:43b9cbf0) Much has been learned about the development of FC organization using task-free rest, sleep studies, and conventional tasks (for review, see Grayson and Fair, 2017). To date, studies of FC during movie-watching are making unique contributions to the developmental lit-erature in three main ways: first...
[18] (src:74e989c9) 2Center for Autism Spectrum Disorders, Children’s National Medical Center, Washington, DC 3Department of Psychology, Georgetown University, Washington, DC 4Department of Neurology, Johns Hopkins Hospital, Washington, DC 5Clinical Epilepsy Section, NINDS, NIH, Washington, DC 6Neurology Department, Ge...
[19] (src:74e989c9) Scan Failures Among children who entered the MRI scanner, 155 of 409 (38%) children failed at least one run. There were six reasons for failed runs: (1) excessive head motion; (2) re-fusal to begin or finish a run after entering the MRI scan-ner; (3) inattention (e.g., forgetting task rules or falli...
[20] (src:43b9cbf0) The idea of using movies to improve compliance is not new; labs and hospitals have been showing cartoons during structural MRI se-quences to improve image quality and avoid sedation during pediatric scans for years (Raschle et al., 2012, 2009). In 2013, Cantlon and Li published an elegant study usin...
[21] (src:43b9cbf0) limiting as different ages demonstrate different levels of compliance. A recent examination of head motion in a sample of 24 healthy children (mean age 11.1 years) found that movies conferred a significant ad-vantage in children ages 5–10, but not for children older than age 10 (Greene et al., 2018)...
[22] (src:43b9cbf0) (20.3 ± 6.3) with Down Syndrome and healthy participants ReHo= regional homogeneity, ALFF= amplitude of low frequency fluctuations, FC= functional connectivity, ISCs= intersubject correlations, ToM=Theory of Mind, GLM=general linear model, DAN=dorsal attention network, ICA= independent component ana...
[23] (src:43b9cbf0) (i.e., time-locked) signal changes, but are also model-free and whole-brain. ISCs can be examined in groups of different developmental stages (see Fig. 5), or across clinical groups such as individuals with autism spectrum disorder (Bolton et al., 2018; Hasson et al., 2009) or Down Syndrome and heal...
[24] (src:43b9cbf0) Additionally, recent approaches using FC-based predictive modeling to truly predict (as opposed to correlating) a behavioral score of interest in individual subjects seem to work best when more volumes of data are used, and when more varied acquisition states are used (Rosenberg et al., 2016; Shen e...
[25] (src:864419ff) The naturalistic paradigm combined with fMRI shows substan-tial potential in advancing research on emotional dysregulation of psychiatric disorders. For example, movie-fMRI, employing films with feature-rich content, can robustly induce genuine mood states (Hasson et al. 2008), enhance higher-order ...
[26] (src:864419ff) With the emergence of the naturalistic paradigm, two methods have been proposed: inter-subject correlation (ISC) and inter-subject functional connectivity (ISFC). The ISC analysis is com-monly used to measure the shared neural response across sub-jects under conditions with complex information (Hass...
[27] (src:864419ff) Gruskin et al. (2020) discovered that adolescents with more atypical fMRI responses during movie viewing experienced greater depressive symptom severity. As functional typicality analysis is not suitable for this study due to the equal sample sizes of the two groups, we performed partial correction ...
[28] (src:ab5fa37d) Summary of fNIRS findings As expected, the visual task generated strong occipital activ-ity revealed both by HbO and HbR signals. Unfortunately, group differences were not significant over V1/V2 (but are perhaps better appreciated in terms of spread— Supplementary Appendix B). The same applied to V3...
[29] (src:ab5fa37d) Conclusion To this day, some children with CI struggle at school, des-pite early implantation and continuous rehabilitation ef-forts.29,30 Here, we provided converging evidence—using non-simultaneous EEG and fNIRS—that one reason for these ongoing difficulties is that the brain of these children has...
[30] (src:b0437311) https://doi.org/10.1038/s42003-024-07434-5 Neural processing of naturalistic audiovisual events in space and time Check for updates Yu Hu 1,2 & Yalda Mohsenzadeh 1,2,3 Our brain seamlessly integrates distinct sensory information to form a coherent percept. However, when real-world audiovisual events...
[31] (src:b0437311) Previousfindings show that cross-modal interactions occur at different processing stages and can be observed as early as primary sensory Fig. 4 | Comparisons between fMRI voxel searchlight RDMs and two-branch deep neural network (DNN) pre-trained on audiovisual video stimuli. a Schematic illustratio...
[32] (src:a24af881) nature human behaviour Article https://doi.org/10.1038/s41562-022-01516-2 Evidence of a predictive coding hierarchy in the human brain listening to speech Charlotte Caucheteux 1,2 , Alexandre Gramfort1,2 & Jean-Rémi King 1,3 Considerable progress has recently been made in natural language proc...
[33] (src:a24af881) of the next token. Consequently, the nature of the predicted representa-tions and their temporal scope are largely unknown. In this study, we address these issues by analysing the brain signals of 304 individuals listening to short stories while their brain activity is recorded with fMRI39. After co...
[34] (src:b0437311) visual and acoustic features and high-level categorical and semantic infor-mation as well as when they were processed. By examining neural processes involved for different types of information, our results suggest two different stages of cross-modal interactions, with their associated brain areas, t...
Sources used: 7 documents
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