A5012106334- Functional Brain Connectivity Studies
- Epilepsy research and treatment
- EEG and Brain-Computer Interfaces
- Neurobiology of Language and Bilingualism
- Advanced MRI Techniques and Applications
- Advanced Neuroimaging Techniques and Applications
- Distributed and Parallel Computing Systems
- Hemispheric Asymmetry in Neuroscience
- Vagus Nerve Stimulation Research
- Medical Image Segmentation Techniques
- Neurological disorders and treatments
- Neural dynamics and brain function
- Optical Imaging and Spectroscopy Techniques
- Caching and Content Delivery
- Medical Imaging Techniques and Applications
- Advanced Neural Network Applications
- User Authentication and Security Systems
- Computer Graphics and Visualization Techniques
- Distributed systems and fault tolerance
- Visual perception and processing mechanisms
- Diet and metabolism studies
- Advanced Data Storage Technologies
- Context-Aware Activity Recognition Systems
- Age of Information Optimization
- Parallel Computing and Optimization Techniques
Nemours Children's Health System
2021
Miami Children's Hospital
2011-2019
Clinical Pharmacology of Miami
2019
Florida International University
2006-2018
University of Miami
2009-2010
Objective Vagus nerve stimulation (VNS) is a common treatment for medically intractable epilepsy, but response rates are highly variable, with no preoperative means of identifying good candidates. This study aimed to predict VNS using structural and functional connectomic profiling. Methods Fifty‐six children, comprising discovery (n = 38) validation 18) cohorts, were recruited from 3 separate institutions. Diffusion tensor imaging was used identify group differences in white matter...
Although chronic vagus nerve stimulation (VNS) is an established treatment for medically-intractable childhood epilepsy, there considerable heterogeneity in seizure response and little data are available to pre-operatively identify patients who may benefit from treatment. Since the therapeutic effect of VNS be mediated by afferent projections thalamus, we tested hypothesis that intrinsic thalamocortical connectivity associated with following children epilepsy. Twenty-one (ages 5-21 years)...
To study the neural networks reorganization in pediatric epilepsy, a consortium of imaging centers was established to collect functional data. Common paradigms and similar acquisition parameters were used. We studied 122 children (64 control 58 LRE patients) across five sites using EPI BOLD fMRI an auditory description decision task. After normalization MNI atlas, activation maps generated by FSL separated into three sub-groups distance method principal component analysis (PCA)-based...
This study describes a new 3-D liver segmentation method in support of the selective internal radiation treatment as for tumors. is based on coupling modified k-means with special localized contouring algorithm. In process, five separate regions are identified computerized tomography image frames. The merit proposed lays its potential to provide fast and accurate rendering well delineating tumor region(s), all minimal user interaction. Leveraging multicore platforms shown speed up processing...
Abstract Treatment-resistant epilepsy is a common and debilitating neurological condition, for which neurosurgical cure possible. Despite undergoing nearly identical ablation procedures however, individuals with treatment-resistant frequently exhibit heterogeneous outcomes. We hypothesized that treatment response may be related to the brain regions MR-guided laser volumes are functionally connected. To test this, we mapped resting-state functional connectivity of surgical ablations either...
Magnetic Resonance-guided Laser Interstitial Thermal Therapy (MRgLITT) is an emerging minimally-invasive alternative to resective surgery for medically-intractable epilepsy. The precise lesioning effect produced by MRgLITT supplies opportunities glean insights into epileptogenic regions and their interactions with functional brain networks. In this exploratory analysis, we sought characterize associations between ablation zones large-scale networks that portended seizure outcome using...
Atypical functional magnetic resonance imaging (fMRI) language patterns may be identified by visual inspection or region of interest (ROI)-based laterality indices (LI) but are constrained a priori assumptions. We compared data-driven novel application principal component analysis (PCA) to conventional methods. studied 122 fMRI data sets from control and localization-related epilepsy patients provided five children's hospitals. Each subject performed an auditory description decision task....
This article describes a pattern classification algorithm for pediatric epilepsy using fMRI language‐related activation maps. 122 datasets from control group (64) and localization related patients (58) provided by five children's hospitals were used. Each subject performed an auditory description decision task. Using the artificial data as training data, incremental Principal Component Analysis was used in order to generate feature space while overcoming memory requirements of large...
This paper develops a client-side context-aware search application which is built on the infrastructure. A architecture designed to collect mobile user's context information, derive current context, distribute user among applications, and support applications. The acquisition centralized at server ensure reusability of information devices, while reasoning remains level. Algorithms are proposed consider profiles. By promoting feedback dynamics system, prior selection now saved for further...
The brain activation associated with the Spinning Dancer Illusion, a cognitive visual illusion, is not entirely known. Inferences from other study modalities point to involvement of dorso-parieto-occipital areas in spontaneous switchings perception bistable non-kinetic illusions. fMRI mature technique used investigate responses mental changes. Resting-state novel that may help ascertain effects changes top-down regulation perception. purpose this report describe subjective illusory kinetic...
In this study, a novel application of Principal Component Analysis (PCA) is proposed to detect language activation map patterns. These patterns were obtained by processing functional Magnetic Resonance Imaging (fMRI) studies on both control and localization related epilepsy (LRE) patients as they performed an auditory word definition task. Most group statistical analyses fMRI datasets look for ldquocommonalityrdquo under the assumption homogeneity sample. However, inter-subject variance may...
In this work, we will test the hypothesis that connectivity of language areas in normal children is asymmetric between hemispheres. Intrahemispheric region interest (ROI)-to-ROI was assessed 40 right-handed children. Asymmetries were (1) hemispheres (global connectivity); (2) Brodmann (BAs) pairs (pairwise and (3) two homotopic BA (Global connectivity). Sixteen BAs selected: 6, 7, 9, 19, 21, 22, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47. T scores for each pair ascertained using MATLAB toolbox...
This paper describes a novel multimedia tool to facilitate visual assessment of Functional Magnetic Resonance Imaging (fMRI) activation patterns by human experts. A great effort is placed radiologists and neurologists present consistent methodology provide for brain map images. Since each radiologist has his own way perform the analysis on images findings, rating large heterogeneous group hard task. Although this focused assessing fMRI related language network paradigms, can be extended...
This study describes the performance results on testing MatLab applications using parallel computing and distributed toolboxes under different platforms with hardware operating systems. Each trial was executed keeping fixed changing system to obtain unbiased results. To standardize benchmarking test, Fast Fourier Transform (FFT), discrete cosine transform (DCT), edge detection matrix multiplication algorithms were executed. The show that leveraging of multicore can speed up considerably...
Purpose: We present for the first time utilization of an average resting-state points (rs-Mean) to localize epilepsy focus in a group pediatric patients with medical refractory epilepsy. Materials and Methods: Twenty nine had drug-resistant epilepsy, 22 subject controls underwent rs-fMRI. Comparison among means was performed. Regions Interest (ROI) derived from nuclear medicine studies (GS) focal hyperintensities yielded by rs-Mean were converted into ellipsoids. Euclidian Distance (ED)...
This research presents a novel application of Lateralization Index (LI) in support decision making process for the classification subjects based on their brain activation patterns using functional Magnetic Resonance Imaging (fMRI) datasets. The considers subject grouping additional spatial information provided by LI behavior each individual when calculated specific Broca's and Wernicke's language areas. presented results were obtained applying concept to assess pattern both control...
Background: fMRI of mental phenomena is quite difficult to perform because lack patient’s cooperation or the symptoms are stable. In some exceptional cases, however, and DTI capable provide insights on anatomy organic hallucinations. Methods: this report we describe a 14-year-old boy with left fronto-dorsal tumor who experienced chronic complex brief, frequent repetitive visual auditory His clinical picture included multiple severe social mood problems. During presurgical mapping patient...
This paper presents a theoretical elaboration aimed to explain the correlation found between new rs-fMRI modality and electrophysiology nuclear medicine neuroimaging, performed localize epileptogenic brain areas. We present in detail clinical history, electrophysiological neuroimaging results of one child with intractable epilepsy, who was submitted for Phase-1 work-up as candidate epilepsy surgery. The patient underwent thorough workup including video-telemetry, ictal interictal imaging,...