Integrating brainstem and cortical functional architectures.

The brainstem is a fundamental component of the central nervous system, yet it is typically excluded from in vivo human brain mapping efforts, precluding a complete understanding of how the brainstem influences cortical function. In this study, we used high-resolution 7-Tesla functional magnetic resonance imaging to derive a functional connectome encompassing cortex and 58 brainstem nuclei spanning the midbrain, pons and medulla. We identified a compact set of integrative hubs in the brainstem with widespread connectivity with cerebral cortex.

Speech motor impairment in ALS is associated with multiregional cortical thinning beyond primary motor cortex.

Introduction: Cortical thinning is well-documented in individuals with amyotrophic lateral sclerosis (ALS), yet its association with speech deterioration remains understudied. This study characterizes anatomical changes in the brain within the context of speech impairment patterns in individuals with ALS, providing insight into the disease's multiregional spread and biology.

Methods: To evaluate patterns of cortical thickness in speakers with ALS with and without functional speech changes compared to healthy controls (HCs) using whole-brain and region of interest (ROI) analyses.

Physics-guided self-supervised learning: Demonstration for generalized RF pulse design.

Purpose: To introduce a new method for generalized RF pulse design using physics-guided self-supervised learning (GPS), which uses the Bloch equations as the guiding physics model.

Theory And Methods: The GPS framework consists of a neural network module and a physics module, where the physics module is a Bloch simulator for MRI applications. For RF pulse design, the neural network module maps an input target profile to an RF pulse, which is subsequently loaded into the physics module.

BOOSTING SKULL-STRIPPING PERFORMANCE FOR PEDIATRIC BRAIN IMAGES.

Skull-stripping is the removal of background and non-brain anatomical features from brain images. While many skull-stripping tools exist, few target pediatric populations. With the emergence of multi-institutional pediatric data acquisition efforts to broaden the understanding of perinatal brain development, it is essential to develop robust and well-tested tools ready for the relevant data processing.

Dose-dependent effects of transcranial photobiomodulation on brain temperature in patients with major depressive disorder: a spectroscopy study.

This study aimed to evaluate the dose-dependent brain temperature effects of transcranial photobiomodulation (t-PBM). Thirty adult subjects with major depressive disorder were randomized to three t-PBM sessions with different doses (low: 50 mW/cm, medium: 300 mW/cm, high: 850 mW/cm) and a sham treatment. The low and medium doses were administered in continuous wave mode, while the high dose was administered in pulsed wave mode.

Using heart rate variability to predict neurological outcomes in preterm infants: a scoping review.

Infants born preterm are at higher risk of neurological complications, including intraventricular haemorrhage and white matter injury. After discharge, these infants may experience adverse neurodevelopmental outcomes and exhibit lower educational attainment. Early detection of brain injury and accurate prediction of neurodevelopmental impairment would allow early intervention and support.

PET imaging assist investigation of HDAC6 expression change in MDD and evaluating antidepressant efficacy of a newly developed HDAC6 inhibitor.

The histone deacetylase 6 (HDAC6) is closely related to the pathogenesis of depression in epigenetic regulation. However, it remains unclear how HDAC6 expression changes in depression pathophysiology and whether it is a target for antidepressant treatment. Herein, we investigate the expression change of HDAC6 in major depressive disorder (MDD) and evaluate the efficacy of a novel HDAC6 inhibitor, PB200, using positron emission tomography (PET) imaging.

Assessing generalizability of an AI-based visual test for cervical cancer screening.

A number of challenges hinder artificial intelligence (AI) models from effective clinical translation. Foremost among these challenges is the lack of generalizability, which is defined as the ability of a model to perform well on datasets that have different characteristics from the training data. We recently investigated the development of an AI pipeline on digital images of the cervix, utilizing a multi-heterogeneous dataset of 9,462 women (17,013 images) and a multi-stage model selection and optimization approach, to generate a diagnostic classifier able to classify images of the cervix into "normal", "indeterminate" and "precancer/cancer" (denoted as "precancer+") categories.

Shared subcortical arousal systems across sensory modalities during transient modulation of attention.

Subcortical arousal systems are known to play a key role in controlling sustained changes in attention and conscious awareness. Recent studies indicate that these systems have a major influence on short-term dynamic modulation of visual attention, but their role across sensory modalities is not fully understood. In this study, we investigated shared subcortical arousal systems across sensory modalities during transient changes in attention using block and event-related fMRI paradigms.

Improved Dipole Source Localization from Simultaneous MEG-EEG Data by Combining a Global Optimization Algorithm with a Local Parameter Search: A Brain Phantom Study.

Dipole localization, a fundamental challenge in electromagnetic source imaging, inherently constitutes an optimization problem aimed at solving the inverse problem of electric current source estimation within the human brain. The accuracy of dipole localization algorithms is contingent upon the complexity of the forward model, often referred to as the head model, and the signal-to-noise ratio (SNR) of measurements. In scenarios characterized by low SNR, often corresponding to deep-seated sources, existing optimization techniques struggle to converge to global minima, thereby leading to the localization of dipoles at erroneous positions, far from their true locations.

Reduced physiology-induced temporal instability achieved with variable-flip-angle fast low-angle excitation echo-planar technique with multishot echo planar time-resolved imaging.

Purpose: Echo planar time-resolved imaging (EPTI) is a new imaging approach that addresses the limitations of EPI by providing high-resolution, distortion- and T/  blurring-free imaging for functional MRI (fMRI). However, as in all multishot sequences, intershot phase variations induced by physiological processes can introduce temporal instabilities to the reconstructed time-series data. This study aims to reduce these instabilities in multishot EPTI.

Quantitative MRI distinguishes different leukodystrophies and correlates with clinical measures.

Objectives: The leukodystrophy "vanishing white matter" (VWM) and "metachromatic leukodystrophy" (MLD) affect the brain's white matter, but have very different underlying pathology. We aim to determine whether quantitative MRI reflects known neuropathological differences and correlates with clinical scores in these leukodystrophies.

Methods: VWM and MLD patients and controls were prospectively included between 2020 and 2023.

Absolute Metabolite Quantification in Individuals with Glioma and Healthy Individuals Using Whole-Brain Three-dimensional MR Spectroscopic and Echo-planar Time-resolved Imaging.

Background: MR spectroscopic imaging (MRSI) can be used to quantify an extended brain metabolic profile but is confounded by changes in tissue water levels due to disease.

Purpose: To develop a fast absolute quantification method for metabolite concentrations combining whole-brain MRSI with echo-planar time-resolved imaging (EPTI) relaxometry in individuals with glioma and healthy individuals.

Materials And Methods: In this prospective study performed from August 2022 to August 2023, using internal water as concentration reference, the MRSI-EPTI quantification method was compared with the conventional method using population-average literature relaxation values.