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Brain Sciences
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Multimodal Imaging in Brain Development
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Multimodal Imaging in Brain Development

A special issue of Brain Sciences (ISSN 2076-3425). This special issue belongs to the section "Neurotechnology and Neuroimaging".

Deadline for manuscript submissions: 25 August 2025 | Viewed by 2425

Special Issue Editor

Dr. Antonio Napolitano

E-Mail Website
Guest Editor
Medical Physics Department, Bambino Gesù Children’s Hospital, IRCCS, 00165 Rome, Italy
Interests: machine learning; computer tomography (CT); magnetic resonance techniques; neu-roimaging applications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Brain development (BD) is a complex and dynamic process that begins in the early stages of prenatal life and continues into young adulthood. This intricate process encompasses the formation, growth, and refinement of neural structures and connections, making it a lifelong journey of neural adaptation and learning. BD is influenced by a combination of genetic, environmental, and experiential factors, which together contribute to the brain's remarkable plasticity and ability to acquire new skills and knowledge throughout life.

The need for effective biomarkers of cognitive functioning in brain development is increasingly recognized. Such biomarkers are essential for achieving a better understanding of the developmental process, enabling prompt diagnosis, guiding rehabilitation efforts, monitoring recovery, and aiding in prognostication. Neuroimaging techniques have emerged as ideal candidates to provide these biomarkers due to their widespread availability, noninvasive nature, relatively contained costs, and ability to depict both brain structure and function.

This Special Issue aims to identify biomarkers of brain development through neuroimaging by analyzing the structural and functional correlates of brain maturation. By doing so, it seeks to offer informative insights for diagnosis and prognostication. Despite extensive investigations over the past years, the precise cognitive dynamics underlying brain development remain to be fully elucidated. Neuroimaging is showing promising results in capturing these cognitive dynamics through advanced functional and structural techniques.

Modern neuroscience recognizes cognition as the result of the interplay between cortical areas wired in complex networks. These networks can be effectively studied through neuroimaging techniques, which allow for the visualization and analysis of brain connectivity and activity. This Special Issue seeks to integrate various neuroimaging approaches to characterize brain development and its associated conditions comprehensively. Preference will be given to articles that advance the characterization of brain development, discover new mechanisms of disease, develop innovative methods of imaging analysis, and create predictive models for disease onset and progression.

By focusing on the identification and validation of neuroimaging biomarkers, this research aims to bridge the gap between basic neuroscience and clinical application. The ultimate goal is to enhance our understanding of brain development, improve the early detection of developmental disorders, and refine therapeutic interventions to support optimal cognitive and neural outcomes. This integrated approach holds the promise of transforming our understanding of brain development and its implications for lifelong brain health.

Dr. Antonio Napolitano
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Brain Sciences is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • brain development (BD)
  • brain plasticity
  • neuroimaging technique
  • brain connectivity and activity

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Published Papers (3 papers)

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Research

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18 pages, 4837 KiB  
Article
White-Matter Connectivity and General Movements in Infants with Perinatal Brain Injury
by Ellen N. Sutter, Jose Guerrero-Gonzalez, Cameron P. Casey, Douglas C. Dean III, Andrea de Abreu e Gouvea, Colleen Peyton, Ryan M. McAdams and Bernadette T. Gillick
Brain Sci. 2025, 15(4), 341; https://doi.org/10.3390/brainsci15040341 - 26 Mar 2025
Viewed by 614
Abstract
Background/Objectives: Cerebral palsy (CP), often caused by early brain injury such as perinatal stroke or hemorrhage, is the most common lifelong motor disability. Early identification of at-risk infants and timely access to rehabilitation interventions are essential for improving long-term outcomes. The General Movements [...] Read more.
Background/Objectives: Cerebral palsy (CP), often caused by early brain injury such as perinatal stroke or hemorrhage, is the most common lifelong motor disability. Early identification of at-risk infants and timely access to rehabilitation interventions are essential for improving long-term outcomes. The General Movements Assessment (GMA), performed in the first months of life, has high sensitivity and specificity to predict CP; however, the neurological correlates of general movements remain unclear. This analysis aimed to investigate the relationship between white matter integrity and general movements in infants with perinatal brain injury using advanced neuroimaging techniques. Methods: Diffusion-weighted MRI data were analyzed in 17 infants, 12 with perinatal brain injury and 5 typically developing infants. Tractography was used to identify the corticospinal tract, a key motor pathway often affected by perinatal brain injury, and tract-based spatial statistics (TBSS) were used to examine broader white matter networks. Diffusion parameters from the diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) models were compared between infants with and without typical general movements. Results: Corticospinal tract integrity did not differ between groups when averaged across hemispheres. However, infants with asymmetric general movements exhibited greater corticospinal tract asymmetries. A subset of infants with atypical general movement trajectories at <6 weeks and 3–5 months of age showed reduced corticospinal tract integrity compared to those with typical general movements. TBSS revealed significant differences in white matter integrity between infants with typical and atypical general movements in several white matter pathways, including the corpus callosum, the right posterior corona radiata, bilateral posterior thalamic radiations, the left fornix/stria terminalis, and bilateral tapetum. Conclusions: These findings support and expand upon previous research suggesting that white matter integrity across multiple brain regions plays a role in the formation of general movements. Corticospinal integrity alone was not strongly associated with general movements; interhemispheric and cortical-subcortical connectivity appear critical. These findings underscore the need for further research in larger, diverse populations to refine early biomarkers of neurodevelopmental impairment and guide targeted interventions. Full article
(This article belongs to the Special Issue Multimodal Imaging in Brain Development)
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14 pages, 693 KiB  
Article
Multimodal Morphometric Similarity Network Analysis of Autism Spectrum Disorder
by Antonio Del Casale, Darvin Shehu, Maria Camilla Rossi-Espagnet, Clarissa Zocchi, Irene Bilotta, Jan Francesco Arena, Alessandro Alcibiade, Barbara Adriani, Daniela Longo, Carlo Gandolfo, Andrea Romano, Stefano Ferracuti, Alessandro Bozzao and Antonio Napolitano
Brain Sci. 2025, 15(3), 247; https://doi.org/10.3390/brainsci15030247 - 26 Feb 2025
Viewed by 593
Abstract
Background: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by persistent difficulties in social interaction, communication, and repetitive behaviors. Neuroimaging studies have revealed structural and functional neural changes in individuals with ASD compared to healthy subjects. Objectives: This study aimed [...] Read more.
Background: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by persistent difficulties in social interaction, communication, and repetitive behaviors. Neuroimaging studies have revealed structural and functional neural changes in individuals with ASD compared to healthy subjects. Objectives: This study aimed to investigate brain network structural connectivity in ASD using Morphometric Similarity Network (MSN) analysis. Methods: Data from the Autism Brain Imaging Data Exchange (ABIDE) were analyzed, comprising 597 individuals with ASD and 644 healthy controls. Structural connectivity was assessed using cortical morphometric features. Global and regional network indices, including the density index, node degree, node strength, and clustering coefficients, were evaluated. Results: Among the global network indices, when using a threshold value of 0.4, ASD patients compared to HCs showed a lower density (p = 0.041) and higher negative clustering (p = 0.0051) coefficients. For regional network indices, ASD patients showed a lower bilateral superior frontal cortices degree (left hemisphere: p = 0.014; right hemisphere: p = 0.0038) and strength (left: p = 0.017; right: p = 0.018). Additionally, they showed higher negative clustering coefficients in the bilateral superior frontal cortices (left, p = 0.0088; right, p = 0.0056) and bilateral pars orbitalis (left, p = 0.016; right, p = 0.0006), as well as lower positive clustering in the bilateral frontal pole (left, p = 0.03; right, p = 0.044). Conclusions: These findings highlight significant alterations in both global and regional brain network organization in ASD, which may contribute to the disorder’s cognitive and behavioral manifestations. Future studies are needed to investigate the pathophysiological mechanisms underlying these structural connectivity changes, to inform the development of more targeted and individualized therapeutic interventions for individuals with ASD. Full article
(This article belongs to the Special Issue Multimodal Imaging in Brain Development)
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Other

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28 pages, 4195 KiB  
Systematic Review
Brain Markers of Resilience to Psychosis in High-Risk Individuals: A Systematic Review and Label-Based Meta-Analysis of Multimodal MRI Studies
by Guusje Collin, Joshua E. Goldenberg, Xiao Chang, Zhenghan Qi, Susan Whitfield-Gabrieli, Wiepke Cahn, Jijun Wang, William S. Stone, Matcheri S. Keshavan and Martha E. Shenton
Brain Sci. 2025, 15(3), 314; https://doi.org/10.3390/brainsci15030314 - 17 Mar 2025
Viewed by 669
Abstract
Background/Objectives: Most individuals who have a familial or clinical risk of developing psychosis remain free from psychopathology. Identifying neural markers of resilience in these at-risk individuals may help clarify underlying mechanisms and yield novel targets for early intervention. However, in contrast to [...] Read more.
Background/Objectives: Most individuals who have a familial or clinical risk of developing psychosis remain free from psychopathology. Identifying neural markers of resilience in these at-risk individuals may help clarify underlying mechanisms and yield novel targets for early intervention. However, in contrast to studies on risk biomarkers, studies on neural markers of resilience to psychosis are scarce. The current study aimed to identify potential brain markers of resilience to psychosis. Methods: A systematic review of the literature yielded a total of 43 MRI studies that reported resilience-associated brain changes in individuals with an elevated risk for psychosis. Label-based meta-analysis was used to synthesize findings across MRI modalities. Results: Resilience-associated brain changes were significantly overreported in the default mode and language network, and among highly connected and central brain regions. Conclusions: These findings suggest that the DMN and language-associated areas and central brain hubs may be hotspots for resilience-associated brain changes. These neural systems are thus of key interest as targets of inquiry and, possibly, intervention in at-risk populations. Full article
(This article belongs to the Special Issue Multimodal Imaging in Brain Development)
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