Language task-based fMRI analysis using machine learning and deep learning.

Introduction: Task-based language fMRI is a non-invasive method of identifying brain regions subserving language that is used to plan neurosurgical resections which potentially encroach on eloquent regions. The use of unstructured fMRI paradigms, such as naturalistic fMRI, to map language is of increasing interest. Their analysis necessitates the use of alternative methods such as machine learning (ML) and deep learning (DL) because task regressors may be difficult to define in these paradigms.

Modular GAN: positron emission tomography image reconstruction using two generative adversarial networks.

Introduction: The reconstruction of PET images involves converting sinograms, which represent the measured counts of radioactive emissions using detector rings encircling the patient, into meaningful images. However, the quality of PET data acquisition is impacted by physical factors, photon count statistics and detector characteristics, which affect the signal-to-noise ratio, resolution and quantitative accuracy of the resulting images. To address these influences, correction methods have been developed to mitigate each of these issues separately.

Image synthesis of interictal SPECT from MRI and PET using machine learning.

Background: Cross-modality image estimation can be performed using generative adversarial networks (GANs). To date, SPECT image estimation from another medical imaging modality using this technique has not been considered. We evaluate the estimation of SPECT from MRI and PET, and additionally assess the necessity for cross-modality image registration for GAN training.

Introducing the Concept of Sanctuary Sites in Ischemic Stroke.

Background: The topography of arterial territories has been defined using digital maps of supratentorial infarcts. Regions with a high probability of infarction (Pi) exist in the deep compartment due to a paucity of collaterals. However, less attention has been given to regions with a low Pi.

ParaPET: non-invasive deep learning method for direct parametric brain PET reconstruction using histoimages.

Background: The indirect method for generating parametric images in positron emission tomography (PET) involves the acquisition and reconstruction of dynamic images and temporal modelling of tissue activity given a measured arterial input function. This approach is not robust, as noise in each dynamic image leads to a degradation in parameter estimation. Direct methods incorporate into the image reconstruction step both the kinetic and noise models, leading to improved parametric images.

A short F-FDG imaging window triple injection neuroimaging protocol for parametric mapping in PET.

Background: In parametric PET, kinetic parameters are extracted from dynamic PET images. It is not commonly used in clinical practice because of long scan times and the requirement for an arterial input function (AIF). To address these limitations, we designed an F-fluorodeoxyglucose (F-FDG) triple injection dynamic PET protocol for brain imaging with a standard field of view PET scanner using a 24-min imaging window and an input function modeled using measurements from a region of interest placed over the left ventricle.

A custom MR-compatible dataglove for fMRI of the human motor cortex at 7T.

We present a custom-built MR-compatible data glove to capture hand motion during concurrent fMRI experiments at 7 Tesla. Thermal and phantom tests showed our data glove can be used safely and without degradation of image quality. Subject-specific Blood Oxygen Level Dependent (BOLD) signal models, for use in fMRI analysis, were constructed based on recorded kinematic measurements.

Complement Component 5 (C5) Deficiency Improves Cognitive Outcome After Traumatic Brain Injury and Enhances Treatment Effects of Complement Inhibitors C1-Inh and CR2-Crry in a Mouse Model.

A potent effector of innate immunity, the complement system contributes significantly to the pathophysiology of traumatic brain injury (TBI). This study investigated the role of the complement cascade in neurobehavioral outcomes and neuropathology after TBI. Agents acting at different levels of the complement system, including 1) C1 esterase inhibitor (C1-Inh), 2) CR2-Crry, an inhibitor of all pathways acting at C3, and 3) the selective C5aR1 antagonist, PMX205, were administered at 1 h post-TBI.

Phase II randomised placebo-controlled trial of sodium selenate as a disease-modifying treatment in chronic drug-resistant temporal lobe epilepsy: the SeLECT study protocol.

Introduction: Epilepsy is one of the most common neurological conditions worldwide. Despite many antiseizure medications (ASMs) being available, up to one-third of patients do not achieve seizure control. Preclinical studies have shown treatment with sodium selenate to have a disease-modifying effect in a rat model of chronic temporal lobe epilepsy (TLE).

Improved dynamic distortion correction for fMRI using single-echo EPI and a readout-reversed first image (REFILL).

The boundaries between tissues with different magnetic susceptibilities generate inhomogeneities in the main magnetic field which change over time due to motion, respiration and system instabilities. The dynamically changing field can be measured from the phase of the fMRI data and corrected. However, methods for doing so need multi-echo data, time-consuming reference scans and/or involve error-prone processing steps, such as phase unwrapping, which are difficult to implement robustly on the MRI host.

Effects of C1-INH Treatment on Neurobehavioral Sequelae and Late Seizures After Traumatic Brain Injury in a Mouse Model of Controlled Cortical Impact.

C1 human-derived C1 esterase inhibitor (C1-INH) is a U.S. Food and Drig Administration-approved drug with anti-inflammatory actions.

Measures of Subjective Memory for People with Epilepsy: A Systematic Review of Measurement Properties.

People with epilepsy frequently express concern about the burden of memory problems in their everyday lives. Self-report memory questionnaires may provide valuable insight into individuals' perceptions of their everyday memory performance and changes over time. Yet, despite their potential utility, the measurement properties of self-report memory questionnaires have not been evaluated in epilepsy.

Spikes with and without concurrent high-frequency oscillations: Topographic relationship and neural correlates using EEG-fMRI.

Objective: Epilepsy surgery is the best therapeutic option for patients with drug-resistant focal epilepsy. During presurgical investigation, interictal spikes can provide important information on eligibility, lateralisation and localisation of the surgical target. However, their relationship to epileptogenic tissue is variable.

From CNNs to GANs for cross-modality medical image estimation.

Cross-modality image estimation involves the generation of images of one medical imaging modality from that of another modality. Convolutional neural networks (CNNs) have been shown to be useful in image-to-image intensity projections, in addition to identifying, characterising and extracting image patterns. Generative adversarial networks (GANs) use CNNs as generators and estimated images are classified as true or false based on an additional discriminator network.

Towards automated in vivo parcellation of the human cerebral cortex using supervised classification of magnetic resonance fingerprinting residuals.

Background: Accurate parcellation of the cerebral cortex in an individual is a guide to its underlying organization. The most promising in vivo quantitative magnetic resonance (MR)-based microstructural cortical mapping methods are yet to achieve a level of parcellation accuracy comparable to quantitative histology.

Methods: We scanned 6 participants using a 3D echo-planar imaging MR fingerprinting (EPI-MRF) sequence on a 7T Siemens scanner.

Neural activation during emotional interference corresponds to emotion dysregulation in stressed teachers.

Teacher stress and burnout has been associated with low job satisfaction, reduced emotional wellbeing, and poor student learning outcomes. Prolonged stress is associated with emotion dysregulation and has thus become a focus of stress interventions. This study examines emotional interference effects in a group of teachers suffering from high stress and to explore how individual differences in cognitive control, emotion dysregulation, and emotion recognition related to patterns of neural activation.

Social Cognition in Temporal and Frontal Lobe Epilepsy: Systematic Review, Meta-analysis, and Clinical Recommendations.

Objective: Despite the importance of social cognitive functions to mental health and social adjustment, examination of these functions is absent in routine assessment of epilepsy patients. Thus, this review aims to provide a comprehensive overview of the literature on four major aspects of social cognition among temporal and frontal lobe epilepsy, which is a critical step toward designing new interventions.

Method: Papers from 1990 to 2021 were reviewed and examined for inclusion in this study.

Neural correlates of affective empathy in aging: A multimodal imaging and multivariate approach.

Empathy is one such social-cognitive capacity that undergoes age-related change. C urrently, however, not well understood is the structural and functional neurocircuitry underlying age-related differences in empathy. This study aimed to delineate brain structural and functional networks that subserve affective empathic response in younger and older adults using a modified version of the Multifaceted Empathy Task to both positive and negative emotions.

A CNN Based Software Gradiometer for Electromagnetic Background Noise Reduction in Low Field MRI Applications.

The shielding of electromagnetic noise is critical in obtaining magnetic resonance imaging measurements in the ultra-low magnetic field regime where the intrinsic signal-to-noise ratio is very small. The traditional approach of using an enclosure for electromagnetic shielding is expensive and hinders system portability. We describe here the use of a CNN-based software gradiometer to suppress the effect of electromagnetic ambient background noise sources that inductively couple into the signal detection coils.

Generalisation of continuous time random walk to anomalous diffusion MRI models with an age-related evaluation of human corpus callosum.

Diffusion MRI measures of the human brain provide key insight into microstructural variations across individuals and into the impact of central nervous system diseases and disorders. One approach to extract information from diffusion signals has been to use biologically relevant analytical models to link millimetre scale diffusion MRI measures with microscale influences. The other approach has been to represent diffusion as an anomalous transport process and infer microstructural information from the different anomalous diffusion equation parameters.

Magnetic resonance fingerprinting residual signals can disassociate human grey matter regions.

The importance of accurate structural discrimination of the human grey matter regions has motivated the development of observer-independent reproducible methods that account for inter-individual architectonic variations. We introduce a non-invasive statistical residual analysis framework, employing unique tissue-specific magnetic resonance fingerprinting (MRF) signals after adjusting for the effect of T and T MR relaxometry parameters (here termed MRF residuals). A 7 T Siemens MR scanner was used to acquire MRF signals, quantitative transmit magnetic field (B) maps and T-weighted anatomical images of eleven cortical areas (5L, 5M, 5Ci, 7A, 7P, 7PC, hIP3, BA2, BA4a, BA4p and BA6) from six female participants.

Anatomy of the lumbar interspinous ligament: findings relevant to epidural insertion using loss of resistance.

Background And Objectives: The 'loss of resistance' technique is used to determine entry into the epidural space, often by a midline needle in the interspinous ligament before the ligamentum flavum. Anatomical explanations for loss of resistance without entry into the epidural space are lacking. This investigation aimed to improve morphometric characterization of the lumbar interspinous ligament by observation and measurement at dissection and from MRI.

The aryl hydrocarbon receptor: A diagnostic and therapeutic target in glioma.

Glioblastoma multiforme (GBM) is a deadly disease; 5-year survival rates have shown little improvement over the past 30 years. In vivo positron emission tomography (PET) imaging is an important method of identifying potential diagnostic and therapeutic molecular targets non-invasively. The aryl hydrocarbon receptor (AhR) is a transcription factor that regulates multiple genes involved in immune response modulation and tumorigenesis.

Usefulness and yield of routine electroencephalogram: a retrospective study.

Background: The electroencephalogram (EEG) is a common diagnostic tool used to investigate patients for various indications including seizure disorders.

Aims: To investigate factors that predict the presence of epileptiform abnormalities on EEG and review the common indications for ordering an EEG.

Methods: We retrospectively reviewed all routine adult EEG performed in a hospital over a 6-month period.