Publications by authors named "Makris N"

Article Synopsis
  • The retinogeniculate visual pathway (RGVP) transmits visual data from the retina to the brain, making its identification crucial for understanding vision-related conditions.
  • DeepRGVP, a new deep learning framework, allows efficient and precise mapping of the RGVP from diffusion MRI data, overcoming the challenges of manual tract selection.
  • Experiments demonstrate DeepRGVP's superior accuracy in identifying the RGVP compared to existing methods, even in patients with lesions, highlighting the promise of deep learning in improving visual pathway analysis.
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We have successfully demonstrated the integration of a commercial O-band Quantum Key Distribution (QKD) system over a testbed that replicates a carrier-grade Fiber-to-the-Home (FTTH) optical access network consisting of components and systems installed in real-life FTTH operational deployments. The experiment demonstrated a QKD transmission over a 1:16 user Gigabit Optical Passive Network (GPON) configuration featuring a total of 9 Optical Network Terminals (ONTs) at the premises of the Telecom Operator COSMOTE that followed the operator's standard FTTH divided in two splitting stages. The architecture we implemented was a downstream access network with the quantum transmitter located at the operator's Central Office (CO) and the quantum receiver located on the end user's side.

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  • The study introduces Fiber Microstructure Quantile (FMQ) Regression, a new statistical method designed to analyze the relationship between brain white matter fiber bundles and factors like cognitive scores.
  • FMQ Regression uses quantile regression to examine different regions of white matter based on fractional anisotropy (FA), considering sex differences in brain-behavior associations.
  • The analysis, carried out on data from the Human Connectome Project, shows that FMQ Regression is more effective than traditional methods in identifying significant links between brain structure and cognitive performance, highlighting unique effects for males and females.
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Sensing limitations have impeded knowledge about how individual predator-prey interactions build to organized multi-species group behaviour across an ecosystem. Population densities of overlapping interacting oceanic fish predator and prey species, however, can be instantaneously distinguished and quantified from roughly the elemental individual to spatial scales spanning thousands of square kilometres by wide-area multispectral underwater-acoustic sensing, as shown here. This enables fundamental mechanisms behind large-scale ordered predator-prey interactions to be investigated.

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The superficial white matter (SWM) consists of numerous short-range association fibers connecting adjacent and nearby gyri and plays an important role in brain function, development, aging, and various neurological disorders. Diffusion MRI (dMRI) tractography is an advanced imaging technique that enables in vivo mapping of the SWM. However, detailed imaging of the small, highly-curved fibers of the SWM is a challenge for current clinical and research dMRI acquisitions.

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Hypothesis: This study investigates the impact of different diffusion magnetic imaging (dMRI) acquisition settings and mathematical fiber models on tractography performance for depicting cranial nerve (CN) VII in healthy young adults.

Background: The aim of this study is to optimize visualization of CN VII for preoperative assessment in surgeries near the nerve in the cerebellopontine angle, reducing surgery-associated complications. The study analyzes 100 CN VII in dMRI images from the Human Connectome Project, using three separate sets with different b values ( b = 1,000 s/mm 2 , b =2,000 s/mm 2 , b =3,000 s/mm 2 ) and four different tractography methods, resulting in 1,200 tractographies analyzed.

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Telomere length (TL) is an important cellular marker of biological aging impacting the brain and heart. However, how it is related to the brain (e.g.

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Parcellation of human cerebellar pathways is essential for advancing our understanding of the human brain. Existing diffusion magnetic resonance imaging tractography parcellation methods have been successful in defining major cerebellar fibre tracts, while relying solely on fibre tract structure. However, each fibre tract may relay information related to multiple cognitive and motor functions of the cerebellum.

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The study of brain differences across Eastern and Western populations provides vital insights for understanding potential cultural and genetic influences on cognition and mental health. Diffusion MRI (dMRI) tractography is an important tool in assessing white matter (WM) connectivity and brain tissue microstructure across different populations. However, a comprehensive investigation into WM fiber tracts between Eastern and Western populations is challenged due to the lack of a cross-population WM atlas and the large site-specific variability of dMRI data.

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Neuroimaging-based prediction of neurocognitive measures is valuable for studying how the brain's structure relates to cognitive function. However, the accuracy of prediction using popular linear regression models is relatively low. We propose a novel deep regression method, namely , that allows full supervision for contrastive learning in regression tasks using diffusion MRI tractography.

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Autopsy followed by histopathological examination is foundational in clinical and forensic medicine for discovering and understanding pathological changes in disease, their underlying processes, and cause of death. Imaging technology has become increasingly important for advancing clinical research and practice, given its noninvasive, in vivo and ex vivo applicability. Medical and forensic autopsy can benefit greatly from advances in imaging technology that lead toward minimally invasive, whole-brain virtual autopsy.

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Article Synopsis
  • The study explores a brain age prediction model for rhesus macaques using machine learning algorithms applied to neuroimaging data, aiming to determine their biological age and compare it to human brain aging.
  • Structural MRI data from 43 macaques were analyzed to create a comprehensive brain atlas, resulting in a model that predicts biological age with a correlation of 0.72 using 22 key features.
  • Key brain regions identified in the model, such as the Right Fronto-orbital Cortex and Right Frontal Pole, highlight similarities and differences in brain aging processes between non-human primates and humans.
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Enlarged lateral ventricle (LV) volume and decreased volume in the corpus callosum (CC) are hallmarks of schizophrenia (SZ). We previously showed an inverse correlation between LV and CC volumes in SZ, with global functioning decreasing with increased LV volume. This study investigates the relationship between LV volume, CC abnormalities, and the microRNA MIR137 and its regulated genes in SZ, because of MIR137's essential role in neurodevelopment.

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Current views on immunity support the idea that immunity extends beyond defense functions and is tightly intertwined with several other fields of biology such as virology, microbiology, physiology and ecology. It is also critical for our understanding of autoimmunity and cancer, two topics of great biological relevance and for critical public health considerations such as disease prevention and treatment. Central to this review, the immune system is known to interact intimately with the nervous system and has been recently hypothesized to be involved not only in autonomic and limbic bio-behaviors but also in cognitive function.

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Article Synopsis
  • Shape is crucial in computer graphics and brain imaging, helping to interpret the structure and function of the human brain's morphology.
  • Researchers analyze 3D white matter connections using diffusion magnetic resonance imaging (dMRI) and extract shape descriptors alongside traditional features.
  • The Shape-fused Fiber Cluster Transformer (SFFormer) model shows promise in predicting language performance based on brain shape, connectivity, and microstructure, indicating a strong link between the brain's structural connections and cognitive functions like language.
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Article Synopsis
  • TractGeoNet is a new system that uses advanced techniques from geometry and deep learning to analyze brain images and predict how well people do on language tests.
  • Unlike older methods, it looks at all details of brain fibers at once instead of averaging them, which helps make better predictions.
  • The system also highlights important areas of the brain that affect language skills, showing that certain brain regions, like the left arcuate fasciculus, are key to understanding language performance.
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Article Synopsis
  • The ABCD Study® has gathered brain development data from over 10,000 children at 21 locations, but inconsistencies in imaging methods posed challenges with diffusion MRI (dMRI) data.
  • To resolve these issues, a harmonized and processed dMRI dataset was created from 9,345 subjects, focusing on the baseline session and requiring around 50,000 CPU hours for processing.
  • The dataset, which includes extensive white matter imaging and is available through the NIMH Data Archive, provides a valuable resource for studying structural connectivity in adolescent brain development.
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On average, healthy older adults prefer positive over neutral or negative stimuli. This positivity bias is related to memory and attention processes and is linked to the function and structure of several interconnected brain areas. However, the relationship between the positivity bias and white matter integrity remains elusive.

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Article Synopsis
  • The retinogeniculate visual pathway (RGVP) transmits visual information from the retina to the brain, and understanding its anatomy is crucial for studying visual system diseases.
  • Diffusion MRI (dMRI) tractography is a technique for mapping the RGVP, but current methods for identifying it are slow and subjective, relying on manual expert input.
  • This paper introduces a deep learning framework called DeepRGVP, which uses advanced techniques to quickly and accurately identify the RGVP from dMRI data while maintaining effectiveness even in cases of brain lesions, demonstrating the promise of AI in medical imaging.
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Aims: Complete haematologic response to treatment for light chain cardiac amyloidosis (AL-CA) may lead to improvement of myocardial function and better outcomes. We sought to evaluate the effect of response to treatment for AL-CA on echocardiographic indices of myocardial deformation and work and their prognostic significance.

Methods And Results: Sixty-one patients treated for AL were enrolled and underwent echocardiographic assessment at baseline and at 1 year.

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The impact of COVID-19 and the associated lockdown measures on people's physical and mental wellbeing, as well as their daily lives and functioning, has been extensively studied. This study takes the approach of investigating the consequences of COVID-19 on a national scale, considering sociodemographic factors. The main objective is to make a contribution to ongoing research by specifically examining how age, gender, and marital status influence the overall impact of COVID-19 and wellbeing indicators during the second lockdown period that was implemented in response to the COVID-19 pandemic in the Greek population.

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In his seminal part IV, vol. 81, 1926 paper, Schrödinger has developed a clear understanding about the wave equation that produces the correct quadratic dispersion relation for matter-waves and he first presents a real-valued wave equation that is fourth-order in space and second-order in time. In the view of the mathematical difficulties associated with the eigenvalue analysis of a fourth-order, differential equation in association with the structure of the Hamilton-Jacobi equation, Schrödinger splits the fourth-order real operator into the product of two, second-order, conjugate complex operators and retains only one of the two complex operators to construct his iconic second-order, complex-valued wave equation.

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The temporal pole (TP) is considered one of the major paralimbic cortical regions, and is involved in a variety of functions such as sensory perception, emotion, semantic processing, and social cognition. Based on differences in cytoarchitecture, the TP can be further subdivided into smaller regions (dorsal, ventrolateral and ventromedial), each forming key nodes of distinct functional networks. However, the brain structural connectivity profile of TP subregions is not fully clarified.

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A key set of connections necessary for the most complex brain functions are the long association cortico-cortical fiber tracts. These pathways have been described by the Dejerines and others using post mortem histological or brain dissection techniques. Given methodological limitations, these fiber connections have not been delineated completely in humans.

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