Quantitative phenotyping of verbal and non-verbal cognitive impairment using diffusion-weighted MRI connectome: Preliminary study of the crowding effect in children with left hemispheric epilepsy.

The "crowding" effect (CE), wherein verbal functions are preserved presumably at the expense of nonverbal functions, which diminish following inter-hemispheric transfer of language functions, is recognized as a specific aspect of functional reorganization, offering an insight about neural plasticity in children with neural insult to the dominant hemisphere. CE is hypothesized as a marker for language preservation or improvement after left-hemispheric injury, yet it remains challenging to fully discern it in preoperative evaluation. We present a novel DWI connectome (DWIC) approach to predict the presence of CE in 24 drug-resistant epilepsy (DRE) patients with a left-hemispheric focus and 29 young healthy controls.

Distinguishing Laterality in Brain Injury in Rabbit Fetal Magnetic Resonance Imaging Using Novel Volume Rendering Techniques.

Introduction: Our laboratory has been exploring the MRI detection of fetal brain injury, which previously provided a prognostic biomarker for newborn hypertonia in an animal model of cerebral palsy (CP). The biomarker relies on distinct patterns of diffusion-weighted imaging-defined apparent diffusion coefficient (ADC) in fetal brains during uterine hypoxia-ischemia (H-I). Despite the challenges posed by small brains and tissue acquisition, our objective was to differentiate between left and right brain ADC changes.

Quantification of enlarged deep medullary vein volumes in Sturge-Weber syndrome.

Background: Enlarged deep medullary veins (EDMVs) in patients with Sturge-Weber syndrome (SWS) may channel venous blood from the surface to the deep vein system in brain regions affected by the leptomeningeal venous malformation. Thus, the quantification of EDMV volume may provide an objective imaging marker for this vascular compensatory process. The present study proposes a novel analytical method to quantify enlarged EDMV volumes in the affected hemisphere of patients with unilateral SWS.

Unsupervised abnormality detection in neonatal MRI brain scans using deep learning.

Analysis of 3D medical imaging data has been a large topic of focus in the area of Machine Learning/Artificial Intelligence, though little work has been done in algorithmic (particularly unsupervised) analysis of neonatal brain MRI's. A myriad of conditions can manifest at an early age, including neonatal encephalopathy (NE), which can result in lifelong physical consequences. As such, there is a dire need for better biomarkers of NE and other conditions.

Dynamic cortical and tractography atlases of proactive and reactive alpha and high-gamma activities.

Alpha waves-posterior dominant rhythms at 8-12 Hz reactive to eye opening and closure-are among the most fundamental EEG findings in clinical practice and research since Hans Berger first documented them in the early 20th century. Yet, the exact network dynamics of alpha waves in regard to eye movements remains unknown. High-gamma activity at 70-110 Hz is also reactive to eye movements and a summary measure of local cortical activation supporting sensorimotor or cognitive function.

Sevoflurane-induced high-frequency oscillations, effective connectivity and intraoperative classification of epileptic brain areas.

Objective: To determine how sevoflurane anesthesia modulates intraoperative epilepsy biomarkers on electrocorticography, including high-frequency oscillation (HFO) effective connectivity (EC), and to investigate their relation to epileptogenicity and anatomical white matter.

Methods: We studied eight pediatric drug-resistant focal epilepsy patients who achieved seizure control after invasive monitoring and resective surgery. We visualized spatial distributions of the electrocorticography biomarkers at an oxygen baseline, three time-points while sevoflurane was increasing, and at a plateau of 2 minimum alveolar concentration (MAC) sevoflurane.

Deep Venous Remodeling in Unilateral Sturge-Weber Syndrome: Robust Hemispheric Differences and Clinical Correlates.

Background: Enlarged deep medullary veins (EDMVs) in patients with Sturge-Weber syndrome (SWS) may provide compensatory venous drainage for brain regions affected by the leptomeningeal venous malformation (LVM). We evaluated the prevalence, extent, hemispheric differences, and clinical correlates of EDMVs in SWS.

Methods: Fifty children (median age: 4.

Multi-Scale Deep Learning of Clinically Acquired Multi-Modal MRI Improves the Localization of Seizure Onset Zone in Children With Drug-Resistant Epilepsy.

The present study investigates the effectiveness of a deep learning neural network for non-invasively localizing the seizure onset zone (SOZ) using multi-modal MRI data that are clinically acquired from children with drug-resistant epilepsy. A cortical parcellation was applied to localize the SOZ in cortical nodes of the epileptogenic hemisphere. At each node, the laminar surface analysis was followed to sample 1) the relative intensity of gray matter and white matter in multi-modal MRI and 2) the neighboring white matter connectivity using diffusion tractography edge strengths.

Developmental organization of neural dynamics supporting auditory perception.

Purpose: A prominent view of language acquisition involves learning to ignore irrelevant auditory signals through functional reorganization, enabling more efficient processing of relevant information. Yet, few studies have characterized the neural spatiotemporal dynamics supporting rapid detection and subsequent disregard of irrelevant auditory information, in the developing brain. To address this unknown, the present study modeled the developmental acquisition of cost-efficient neural dynamics for auditory processing, using intracranial electrocorticographic responses measured in individuals receiving standard-of-care treatment for drug-resistant, focal epilepsy.

Diffusion tractography predicts propagated high-frequency activity during epileptic spasms.

Objective: To determine the structural networks that constrain propagation of ictal oscillations during epileptic spasm events, and compare the observed propagation patterns across patients with successful or unsuccessful surgical outcomes.

Methods: Subdural electrode recordings of 18 young patients (age 1-11 years) were analyzed during epileptic spasm events to determine ictal networks and quantify the amplitude and onset time of ictal oscillations across the cortical surface. Corresponding structural networks were generated with diffusion magnetic resonance imaging (MRI) tractography by seeding the cortical region associated with the earliest average oscillation onset time, and white matter pathways connecting active electrode regions within the ictal network were isolated.

Temporally and functionally distinct large-scale brain network dynamics supporting task switching.

Objective: Our daily activities require frequent switches among competing responses at the millisecond time scale. We determined the spatiotemporal characteristics and functional significance of rapid, large-scale brain network dynamics during task switching.

Methods: This cross-sectional study investigated patients with drug-resistant focal epilepsy who played a Lumosity cognitive flexibility training game during intracranial electroencephalography (iEEG) recording.

Effect of Pelvic Floor Muscle Training Using Pressure Biofeedback on Pelvic Floor Muscle Contraction and Trunk Muscle Activity in Sitting in Healthy Women.

Pelvic floor muscle training (PFMT) has been recommended as the first choice as one of the effective methods for preventing and improving urinary incontinence (UI). We aimed to determine whether pressure biofeedback unit training (PBUT) improves short term and retention performance of pelvic floor muscle contraction. The muscle activities of the external oblique (EO), transversus/internal oblique (TrA/IO), multifidus (MF) and the bladder base displacement were measured in the verbal feedback group (n = 10) and PBU group (n = 10) three times (baseline, post-training, and at the 1-week follow-up).

Naming-related spectral responses predict neuropsychological outcome after epilepsy surgery.

This prospective study determined the use of intracranially recorded spectral responses during naming tasks in predicting neuropsychological performance following epilepsy surgery. We recruited 65 patients with drug-resistant focal epilepsy who underwent preoperative neuropsychological assessment and intracranial EEG recording. The Clinical Evaluation of Language Fundamentals evaluated the baseline and postoperative language function.

Dissociable oscillatory theta signatures of memory formation in the developing brain.

Understanding complex human brain functions is critically informed by studying such functions during development. Here, we addressed a major gap in models of human memory by leveraging rare direct electrophysiological recordings from children and adolescents. Specifically, memory relies on interactions between the medial temporal lobe (MTL) and prefrontal cortex (PFC), and the maturation of these interactions is posited to play a key role in supporting memory development.

Six-dimensional dynamic tractography atlas of language connectivity in the developing brain.

During a verbal conversation, our brain moves through a series of complex linguistic processing stages: sound decoding, semantic comprehension, retrieval of semantically coherent words, and overt production of speech outputs. Each process is thought to be supported by a network consisting of local and long-range connections bridging between major cortical areas. Both temporal and extratemporal lobe regions have functional compartments responsible for distinct language domains, including the perception and production of phonological and semantic components.

Dynamic tractography-based localization of spike sources and animation of spike propagations.

Objective: This study was undertaken to build and validate a novel dynamic tractography-based model for localizing interictal spike sources and visualizing monosynaptic spike propagations through the white matter.

Methods: This cross-sectional study investigated 1900 spike events recorded in 19 patients with drug-resistant temporal lobe epilepsy (TLE) who underwent extraoperative intracranial electroencephalography (iEEG) and resective surgery. Twelve patients had mesial TLE (mTLE) without a magnetic resonance imaging-visible mass lesion.

Neonatal encephalopathy prediction of poor outcome with diffusion-weighted imaging connectome and fixel-based analysis.

Background: Better biomarkers of eventual outcome are needed for neonatal encephalopathy. To identify the most potent neonatal imaging marker associated with 2-year outcomes, we retrospectively performed diffusion-weighted imaging connectome (DWIC) and fixel-based analysis (FBA) on magnetic resonance imaging (MRI) obtained in the first 4 weeks of life in term neonatal encephalopathy newborns.

Methods: Diffusion tractography was available in 15 out of 24 babies with MRI, five each with normal, abnormal motor outcome, or death.

Deep reasoning neural network analysis to predict language deficits from psychometry-driven DWI connectome of young children with persistent language concerns.

This study investigated whether current state-of-the-art deep reasoning network analysis on psychometry-driven diffusion tractography connectome can accurately predict expressive and receptive language scores in a cohort of young children with persistent language concerns (n = 31, age: 4.25 ± 2.38 years).

Prediction of baseline expressive and receptive language function in children with focal epilepsy using diffusion tractography-based deep learning network.

Purpose: Focal epilepsy is a risk factor for language impairment in children. We investigated whether the current state-of-the-art deep learning network on diffusion tractography connectome can accurately predict expressive and receptive language scores of children with epilepsy.

Methods: We studied 37 children with a diagnosis of drug-resistant focal epilepsy (age: 11.

Four-dimensional tractography animates propagations of neural activation via distinct interhemispheric pathways.

Objective: To visualize and validate the dynamics of interhemispheric neural propagations induced by single-pulse electrical stimulation (SPES).

Methods: This methodological study included three patients with drug-resistant focal epilepsy who underwent measurement of cortico-cortical spectral responses (CCSRs) during bilateral stereo-electroencephalography recording. We delivered SPES to 83 electrode pairs and analyzed CCSRs recorded at 268 nonepileptic electrode sites.

Deep Relational Reasoning for the Prediction of Language Impairment and Postoperative Seizure Outcome Using Preoperative DWI Connectome Data of Children With Focal Epilepsy.

Prolonged seizures in children with focal epilepsy (FE) may impair language functions and often reoccur after surgical intervention. This study is aimed at developing a novel deep relational reasoning network to investigate whether conventional diffusion-weighted imaging connectome analysis can be improved when predicting expressive and receptive scores of preoperative language impairments and classifying postoperative seizure outcomes (seizure freedom or recurrence) in individual FE children. To deeply reason the dependencies of axonal connections that are sparsely distributed in the whole brain, this study proposes the "dilated CNN + RN", a dilated convolutional neural network (CNN) combined with a relation network (RN).