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Bioengineering
Special Issues
Neuroimaging Techniques and Applications in Neuroscience
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Neuroimaging Techniques and Applications in Neuroscience

A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biosignal Processing".

Deadline for manuscript submissions: 31 August 2026 | Viewed by 4404

Special Issue Editor

Dr. Md Nasir Uddin

E-Mail Website
Guest Editor
1. Department of Neurology, University of Rochester, Rochester, NY 14623, USA
2. Department of Biomedical Engineering, University of Rochester, Rochester, NY 14623, USA
3. Department of Electrical and Computer Engineering, University of Rochester, Rochester, NY 14623, USA
Interests: MRI; brain; neuroimaging; neuroinflammation; machine learning; deep learning; artificial intelligence

Special Issue Information

Dear Colleagues,

Advances in neuroimaging have transformed our understanding of the human brain, offering unprecedented insights into its structure, function, and connectivity. This Special Issue explores the latest developments in neuroimaging technologies, including magnetic resonance imaging (MRI), functional MRI (fMRI), diffusion MRI (dMRI), MR angiography (MRA), positron emission tomography (PET), and emerging multimodal approaches. We welcome contributions that showcase innovative imaging methodologies, computational tools, AI-driven applications, and analytical frameworks that enhance the resolution, sensitivity, and interpretability of neural data.

Beyond technical advances, this Special Issue highlights the diverse applications of neuroimaging across neuroscience, from mapping neural circuits and studying brain development to investigating neuroinflammatory and neurodegenerative disorders, psychiatric conditions, and cognitive processes. Submissions addressing methodological challenges, reproducibility, and best practices in neuroimaging research are also encouraged.

By bridging technological innovation with biological and clinical applications, this Special Issue seeks to foster interdisciplinary collaboration, accelerate translational research, and inform future therapeutic strategies. It provides a comprehensive platform for researchers, clinicians, and engineers to share cutting-edge findings and conceptual frameworks that advance our understanding of the human brain.

Dr. Md Nasir Uddin
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 250 words) can be sent to the Editorial Office for assessment.

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. Bioengineering 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 2700 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

  • neuroimaging
  • brain
  • MRI
  • MR angiography
  • fMRI
  • PET
  • machine learning
  • artificial intelligence
  • neurological disorders

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Published Papers (5 papers)

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Research

19 pages, 11764 KB  
Article
HIV-Associated Microstructural Abnormalities in Default Mode, Executive Control, and Salience Networks: Insights from Tensor-Valued Diffusion Encoding
by Md Nasir Uddin, Abrar Faiyaz, Chase R. Figley, Xing Qiu, Miriam T. Weber and Giovanni Schifitto
Bioengineering 2026, 13(4), 413; https://doi.org/10.3390/bioengineering13040413 - 1 Apr 2026
Viewed by 579
Abstract
Cognitive impairment persists in people with HIV (PWH) despite effective combination antiretroviral therapy, possibly as a result of persistent alterations in white matter microstructural abnormalities in the brain. Noninvasive tensor-valued diffusion MRI (dMRI) is sensitive to microstructural integrity; thus, it may contribute to [...] Read more.
Cognitive impairment persists in people with HIV (PWH) despite effective combination antiretroviral therapy, possibly as a result of persistent alterations in white matter microstructural abnormalities in the brain. Noninvasive tensor-valued diffusion MRI (dMRI) is sensitive to microstructural integrity; thus, it may contribute to the understanding of HIV-associated cognitive impairment. In this exploratory cross-sectional study, 31 healthy controls (HCs) and 24 PWH underwent 3T MRI and neurocognitive assessment. Tensor-valued dMRI metrics, including microscopic fractional anisotropy (µFA) and isotropic, anisotropic, and total mean kurtosis (MKi, MKa, MKt), and conventional DTI and DKI metrics (FA, MD, and MK) were evaluated across six functionally defined brain networks. Compared with HCs, PWH exhibited reduced FA, µFA, and MKa in the dorsal default mode and anterior salience networks, along with increased MKi in the salience network and decreased MKi in the executive control network, with moderate effect sizes. Compared with HCs, PWH performed significantly worse on measures of learning, memory, and language, but showed no differences in executive function, attention, or processing speed. Additionally, significant associations and interactions between dMRI metrics and HIV status were observed, particularly for MKi and attention, executive function, and processing speed across the default mode, salience, and executive control networks. These preliminary findings underscore tensor-valued dMRI as a sensitive biomarker of network-specific neurocognitive vulnerability in HIV. Full article
(This article belongs to the Special Issue Neuroimaging Techniques and Applications in Neuroscience)
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4 pages, 162 KB  
Communication
Divergent Myelination or Divergent Trajectories? Insights from MPF Mapping in Bipolar Disorder and Recurrent Depressive Disorder
by Remigiusz Recław and Anna Grzywacz
Bioengineering 2026, 13(2), 243; https://doi.org/10.3390/bioengineering13020243 - 19 Feb 2026
Viewed by 474
Abstract
Quantitative magnetic resonance imaging has increasingly highlighted white matter abnormalities as a key component of affective disorders. Fast macromolecular proton fraction (MPF) mapping, a myelin-sensitive technique, recently revealed divergent patterns of white matter myelination in bipolar disorder (BD) and recurrent depressive disorder (RDD), [...] Read more.
Quantitative magnetic resonance imaging has increasingly highlighted white matter abnormalities as a key component of affective disorders. Fast macromolecular proton fraction (MPF) mapping, a myelin-sensitive technique, recently revealed divergent patterns of white matter myelination in bipolar disorder (BD) and recurrent depressive disorder (RDD), with reduced MPF in RDD but elevated MPF in BD. These findings challenge uniform hypomyelination models of mood disorders. In this Communication, we propose a trajectory-oriented reinterpretation of these results, suggesting that MPF differences may reflect distinct neurodevelopmental and lifespan-related myelination trajectories rather than a simple marker of tissue damage. Elevated MPF in BD—observed particularly in relatively young patients—may indicate accelerated or dysregulated white matter maturation or activity-dependent myelin plasticity, whereas reduced MPF in RDD may reflect impaired maintenance of myelin integrity. We emphasize that MPF should not be interpreted as a unidirectional index of pathology and argue that it may serve as a phenotype-differentiating biomarker between BD and RDD, warranting further longitudinal and multimodal studies. Full article
(This article belongs to the Special Issue Neuroimaging Techniques and Applications in Neuroscience)
14 pages, 1165 KB  
Article
Lean-NET-Based Local Brain Connectome Analysis for Autism Spectrum Disorder Classification
by Aoumria Chelef, Demet Yuksel Dal, Mahmut Ozturk, Mosab A. A. Yousif and Gokce Koc
Bioengineering 2026, 13(1), 99; https://doi.org/10.3390/bioengineering13010099 - 15 Jan 2026
Viewed by 764
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by impairments in social interaction and communication, along with atypical behavioral patterns. Affected individuals often seem isolated in their inner world and exhibit particular sensory reactions. The World Health Organization has indicated a persistent [...] Read more.
Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by impairments in social interaction and communication, along with atypical behavioral patterns. Affected individuals often seem isolated in their inner world and exhibit particular sensory reactions. The World Health Organization has indicated a persistent increase in the global prevalence of autism, with approximately 1 in 127 persons affected worldwide. This study contributes to the growing research effort by presenting a comprehensive analysis of functional connectivity patterns for ASD prediction using rs-fMRI datasets. A novel approach was used for ASD identification using the ABIDE II dataset, based on functional networks derived from BOLD signals. The sparse functional brain connectome (Lean-NET) model is employed to construct subject-specific connectomes, from which local graph metrics are extracted to quantify regional network properties. Statistically significant features are selected using Welch’s t-test, then subjected to False Discovery Rate (FDR) correction and classified using a Support Vector Machine (SVM). Our experimental results demonstrate that locally derived graph metrics effectively discriminate ASD from typically developing (TD) subjects and achieve accuracy ranging from 70% up to 91%, highlighting the potential of graph learning approaches for functional connectivity analysis and ASD characterization. Full article
(This article belongs to the Special Issue Neuroimaging Techniques and Applications in Neuroscience)
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14 pages, 2048 KB  
Article
Macromolecular Proton Fraction Reveals Divergent White Matter Myelination in Bipolar Disorder and Unipolar Recurrent Depression
by Sofia Gusakova, Liudmila Smirnova, Oleg Borodin, Elena Epimakhova, Alexander Seregin and Vasily Yarnykh
Bioengineering 2026, 13(1), 78; https://doi.org/10.3390/bioengineering13010078 - 11 Jan 2026
Cited by 1 | Viewed by 693
Abstract
Recurrent depressive disorder (RDD) and bipolar disorder (BD) are the most common affective disorders worldwide. However, the pathogenesis of these disorders remains far from understood. Macromolecular proton fraction (MPF) mapping is a sensitive and specific quantitative MRI method for the assessment of brain [...] Read more.
Recurrent depressive disorder (RDD) and bipolar disorder (BD) are the most common affective disorders worldwide. However, the pathogenesis of these disorders remains far from understood. Macromolecular proton fraction (MPF) mapping is a sensitive and specific quantitative MRI method for the assessment of brain tissue myelination, but its clinical value for affective disorders remains unknown. This cross-sectional study employed fast MPF mapping on a 1.5 T MRI scanner using the single-point synthetic reference method to investigate myelin abnormalities in white matter of RDD and BD patients. ANOVA revealed a significant main effect of the group (RDD vs. BD vs. two age-matched control groups; F (3.76) = 7.42, p < 0.001, η2 = 0.227). MPF values were significantly reduced in RDD versus BD patients (p < 0.001). BD showed elevated MPF compared to controls (p = 0.01). MPF levels showed significant weak-to-moderate correlations with clinical scales of affective disorders. These findings demonstrate divergent cerebral myelination patterns—hypomyelination in RDD versus an increased myelin content in BD. In conclusion, MPF mapping demonstrated a promise as a marker of myelin content changes in affective disorder. Full article
(This article belongs to the Special Issue Neuroimaging Techniques and Applications in Neuroscience)
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16 pages, 7333 KB  
Article
Dynamic Cerebral Perfusion Electrical Impedance Tomography: A Neuroimaging Technique for Bedside Cerebral Perfusion Monitoring During Mannitol Dehydration
by Weice Wang, Lihua Hou, Canhua Xu, Mingxu Zhu, Yitong Guo, Rong Zhao, Weixun Duan, Yu Wang, Zhenxiao Jin and Xuetao Shi
Bioengineering 2025, 12(11), 1187; https://doi.org/10.3390/bioengineering12111187 - 31 Oct 2025
Viewed by 1137
Abstract
Mannitol dehydration is routinely used to prevent and treat cerebral damage after total aortic arch replacement (TAAR), but existing neuroimaging technologies cannot achieve bedside real-time quantitative assessment of its impact on cerebral perfusion in different patients. This study applied dynamic cerebral perfusion electrical [...] Read more.
Mannitol dehydration is routinely used to prevent and treat cerebral damage after total aortic arch replacement (TAAR), but existing neuroimaging technologies cannot achieve bedside real-time quantitative assessment of its impact on cerebral perfusion in different patients. This study applied dynamic cerebral perfusion electrical impedance tomography (DCP-EIT), a non-invasive neuroimaging technique, for bedside cerebral perfusion monitoring in TAAR patients during dehydration. Seventeen patients with normal neurological function and nineteen with neurological dysfunction (ND) were enrolled. The variation patterns and differences in perfusion impedance, images, and the relative ratios (RY) of mean perfusion velocity (MV), height of systolic wave (Hs), inflow volume velocity (IV), and angle between the ascending branch and baseline (Aab) were analyzed. Results showed DCP-EIT could visualize cerebral perfusion changes, with detected poorly perfused regions showing good consistency with ischemic areas identified by computed tomography (CT). RY of normal patients fluctuated around 0.97–1.04, with no significant difference from baseline. RY of ND patients peaked at 14–20 min after dehydration and remained higher than baseline even at 100 min (p < 0.001). DCP-EIT holds potential to optimize individualized cerebral protection strategies for other cerebral damage scenarios and neurocritical care. Full article
(This article belongs to the Special Issue Neuroimaging Techniques and Applications in Neuroscience)
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