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(1 - 5 of 5)
- Title
- DEVELOPING NON-LINEAR AND ADAPTIVE NEURONAL SYNCHRONY AND CONNECTIVITY ANALYSIS TO PERSONALIZE CLOSED-LOOP DBS THERAPY FOR TREATING EPILEPSY
- Creator
- Farahmand, Sina
- Date
- 2019
- Description
-
Epilepsy disease afflicts more than seventy million people worldwide. In approximately one third of the cases, antiepileptic medications fail...
Show moreEpilepsy disease afflicts more than seventy million people worldwide. In approximately one third of the cases, antiepileptic medications fail to control seizures. Over the last few decades, electrical stimulation of the brain has been evaluated as a potential alternative to treat surgically and medically refractory epilepsy patients. Despite some successes, most of the devices using this protocol operate based on pre-determined stimulation parameters (e.g. frequency and location of stimulation) that have little or no relationship to the individuals’ underlying brain dynamics, which we hypothesize may explain their low clinical efficacy in preventing or terminating seizures.In this study, a non-linear adaptive neuronal synchrony and connectivity analysis was developed in order to extract stimulation parameters from endogenous, multi-site brain dynamics of epilepsy patients. A non-linear analytical methodology was proposed to assess phase-synchrony dynamics in epilepsy patients as seizures evolve. This study revealed a desynchronization around seizure onset. However, the synchrony level started to increase gradually towards seizure end and reached its maximum at seizure termination. This results reveal that hyper-synchronization of the epileptic network may be a critical self-regulatory mechanism by which the brain terminates seizures. In the other phase of this study, a non-linear adaptive phase-connectivity analysis was developed in order to extract frequency and locations of stimulation that match the synchronized network dynamics at seizure termination. Matching these parameters to the endogenous brain dynamics of epilepsy patients as seizure naturally terminates may not only terminate seizures prior to their development, but it may also lead to a personalized deep brain stimulation (DBS) therapy with higher clinical efficacy.
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- Title
- Pre-implant Brain Activation Modeling to Drive Placement of Depth Leads in White Matter for Direct Neurostimulation Therapy in Epilepsy
- Creator
- Cendejas Zaragoza, Leopoldo
- Date
- 2019
- Description
-
A critical step towards applying direct brain stimulation therapy in focal onset epilepsy is to effectively interface with epileptogenic...
Show moreA critical step towards applying direct brain stimulation therapy in focal onset epilepsy is to effectively interface with epileptogenic neural circuits using a limited set of active contacts. This takes special relevance when interacting with networks that exhibit two or more foci. A strategy to influence the maximum extent of the epileptogenic circuit is to stimulate white matter pathways to enhance propagation to distant epileptic tissue.A significant number of elements must be considered in the clinical response to stimulation delivered directly to neuronal populations. These variables include: stimulation parameter settings, number and interdependence of anatomical targets, electrode number, electrode location and orientation, geometry or shape of the electrode contacts, contact polarity, biophysical properties of stimulated medium, andtrajectory of axonal bundles adjacent to the stimulation site.This document addresses the development of a computational model which takes into consideration all the mentioned variables to predict activation of distant sites via white matter pathways. A method to calculate the extracellular potential field, induced by the application of time-dependent stimulation waveforms, is discussed. Such a method considers both the anisotropic conductivity nature of neural tissue and the electrochemical phenomena of the electrode-tissue interface. The response of white matter fibers is then evaluated by solving a compartmental cable model based in the Hodgkin and Huxley membrane description.The model was integrated into a pre-surgical workflow and was used prospectively to guide stereotactic implantation of depth leads to apply direct neurostimulation therapy in four patients with refractory focal onset epilepsy.
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- Title
- SPECIFICITY OF DEFICITS IN EXECUTIVE FUNCTIONING IN YOUTH WITH NONVERBAL LEARNING DISABILITY, ATTENTION DEFICIT HYPERACTIVITY DISORDER AND READING DISORDER
- Creator
- McCue, Kimberly Ann
- Date
- 2021
- Description
-
Nonverbal Learning Disability (NLD) has been the focus of four decades of neuropsychological research. However, it has yet to be included as a...
Show moreNonverbal Learning Disability (NLD) has been the focus of four decades of neuropsychological research. However, it has yet to be included as a diagnostic category in the Diagnostic and Statistical Manual of Mental Disorders (i.e., currently in its fifth edition, DSM-5, American Psychiatric Association, 2013). Many of the characteristics associated with Nonverbal Learning Disorder (NLD) are similar to those found in other more established disorders such as Attention-Deficit/Hyperactivity Disorder (ADHD), Specific Learning Disorders (SLD), and Autism Spectrum Disorder (ASD). Recent research in neuropsychology and other fields has contributed to a greater understanding of the cognitive profiles of NLD, ADHD, and Reading Disorder (RD). However, the neurological underpinnings of deficits in executive functioning specific to NLD versus ADHD and RD have yet to be fully elucidated. Ongoing research has failed to distinguish NLD from other childhood disorders, including ADHD, based on specific structural or functional neurological deficits. The current study examined the specificity of deficits in executive functioning in youth with nonverbal learning disability, attention deficit hyperactivity disorder and reading disorder. In addition, the study examined the degree to which the Rey Complex Figure Test subscales and Processing Speed Index (PSI) and Working Memory Index (WMI) scores (WISC-IV or WISC-III) could discriminate between the NLD group from ADHD and RD groups. Data for the present study were collected from a population served by the Pediatric Neuropsychological Service at The University of Chicago Medicine. Children who had been referred for neuropsychological assessment and whose comprehensive battery included a WISC measure (WISC-III or WISC-IV) and RCFT measurements were included. All data were archival, i.e., gleaned from the Service database; data from 202 participants was retrieved, including youth who underwent neuropsychological evaluation between 2003 and 2016. The present study hypothesized differences between NLD, ADHD, and RD diagnostic groups on visuo-spatial planning/organization, visuo-spatial working memory, long-term visuo-spatial recall, visuo-spatial recognition, verbal working memory, and processing speed. In summary, of the six executive function domains examined, two domains showed significant underperformance for the NLD group, two domains showed a non-significant trend of underperformance for the NLD group and two domains did not show significant differences between diagnostic groups.
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- Title
- Retrospective Quantitative T1 Imaging to Examine Characteristics of Multiple Sclerosis Lesions
- Creator
- Young, Griffin James
- Date
- 2024
- Description
-
Quantitative MRI plays an essential role in assessing tissue abnormality and diseaseprogression in multiple sclerosis (MS). Specifically, T1...
Show moreQuantitative MRI plays an essential role in assessing tissue abnormality and diseaseprogression in multiple sclerosis (MS). Specifically, T1 relaxometry is gaining popularity as elevated T1 values have been shown to correlate with increased inflammation, demyelination, and gliosis. The predominant issue is that relaxometry requires parametric mapping through advanced imaging techniques not commonly included in standard clinical protocols. This leaves an information gap in large clinical datasets from which quantitative mapping could have been performed. We introduce T1-REQUIRE, a retrospective T1 mapping method that approximates T1 values from a single T1-weighted MR image. This method has already been shown to be accurate within 10% of a clinically available reference standard in healthy controls but will be further validated in MS cohorts. We also further aim to determine T1-REQUIRE’s statistical significance as a unique biomarker for the assessment of MS lesions as they relate to clinical disability and disease burden. A 14-subject comparison between T1-REQUIRE maps derived from 3D T1 weighted turbo field echoes (3D T1w TFE) and an inversion-recovery fast field echo (IRFFE) revealed a whole-brain voxel-wise Pearson’s correlation of r = 0.89 (p < 0.001) and mean bias of 3.99%. In MS white matter lesions, r = 0.81, R2 = 0.65 (p < 0.001, N = 159), bias = 10.07%, and in normal appearing white matter (NAWM), r = 0.82, R 2 = 0.67 (p < 0.001), bias = 9.48%. Mean lesional T1-REQUIRE and MTR correlated significantly (r = -0.68, p < 0.001, N = 587) similar to previously published literature. Median lesional MTR correlated significantly with EDSS (rho = -0.34, p = 0.037), and lesional T1-REQUIRE exhibited xiii significant correlations with global brain tissue atrophy as measured by brain parenchymal fraction (BPF) (r = -0.41, p = 0.010, N = 38). Multivariate linear regressions between T1- REQUIRE NAWM provided meaningful statistical relationships with EDSS (β = 0.03, p = 0.027, N = 38), as well as did mean MTR values in the Thalamus (β = -0.27, p = 0.037, N = 38). A new spoiled gradient echo variation of T1-REQUIRE was assessed as a proof of concept in a small 5-subject MS cohort compared with IR-FFE T1 maps, with a whole brain voxel-wise correlation of r = 0.88, R2 = 0.77 (p < 0.001), and Bias = 0.19%. Lesional T1 comparisons reached a correlation of r = 0.75, R2 = 0.56 (p < 0.001, N = 42), and Bias = 10.81%. The significance of these findings means that there is the potential to provide supplementary quantitative information in clinical datasets where quantitative protocols were not implemented. Large MS data repositories previously only containing structural T1 weighted images now may be used in big data relaxometric studies with the potential to lead to new findings in newly uncovered datasets. Furthermore, T1-REQUIRE has the potential for immediate use in clinics where standard T1 mapping sequences aren’t able to be readily implemented.
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- Title
- Retrospective Quantitative T1 Imaging to Examine Characteristics of Multiple Sclerosis Lesions
- Creator
- Young, Griffin James
- Date
- 2024
- Description
-
Quantitative MRI plays an essential role in assessing tissue abnormality and diseaseprogression in multiple sclerosis (MS). Specifically, T1...
Show moreQuantitative MRI plays an essential role in assessing tissue abnormality and diseaseprogression in multiple sclerosis (MS). Specifically, T1 relaxometry is gaining popularity as elevated T1 values have been shown to correlate with increased inflammation, demyelination, and gliosis. The predominant issue is that relaxometry requires parametric mapping through advanced imaging techniques not commonly included in standard clinical protocols. This leaves an information gap in large clinical datasets from which quantitative mapping could have been performed. We introduce T1-REQUIRE, a retrospective T1 mapping method that approximates T1 values from a single T1-weighted MR image. This method has already been shown to be accurate within 10% of a clinically available reference standard in healthy controls but will be further validated in MS cohorts. We also further aim to determine T1-REQUIRE’s statistical significance as a unique biomarker for the assessment of MS lesions as they relate to clinical disability and disease burden. A 14-subject comparison between T1-REQUIRE maps derived from 3D T1 weighted turbo field echoes (3D T1w TFE) and an inversion-recovery fast field echo (IRFFE) revealed a whole-brain voxel-wise Pearson’s correlation of r = 0.89 (p < 0.001) and mean bias of 3.99%. In MS white matter lesions, r = 0.81, R2 = 0.65 (p < 0.001, N = 159), bias = 10.07%, and in normal appearing white matter (NAWM), r = 0.82, R 2 = 0.67 (p < 0.001), bias = 9.48%. Mean lesional T1-REQUIRE and MTR correlated significantly (r = -0.68, p < 0.001, N = 587) similar to previously published literature. Median lesional MTR correlated significantly with EDSS (rho = -0.34, p = 0.037), and lesional T1-REQUIRE exhibited xiii significant correlations with global brain tissue atrophy as measured by brain parenchymal fraction (BPF) (r = -0.41, p = 0.010, N = 38). Multivariate linear regressions between T1- REQUIRE NAWM provided meaningful statistical relationships with EDSS (β = 0.03, p = 0.027, N = 38), as well as did mean MTR values in the Thalamus (β = -0.27, p = 0.037, N = 38). A new spoiled gradient echo variation of T1-REQUIRE was assessed as a proof of concept in a small 5-subject MS cohort compared with IR-FFE T1 maps, with a whole brain voxel-wise correlation of r = 0.88, R2 = 0.77 (p < 0.001), and Bias = 0.19%. Lesional T1 comparisons reached a correlation of r = 0.75, R2 = 0.56 (p < 0.001, N = 42), and Bias = 10.81%. The significance of these findings means that there is the potential to provide supplementary quantitative information in clinical datasets where quantitative protocols were not implemented. Large MS data repositories previously only containing structural T1 weighted images now may be used in big data relaxometric studies with the potential to lead to new findings in newly uncovered datasets. Furthermore, T1-REQUIRE has the potential for immediate use in clinics where standard T1 mapping sequences aren’t able to be readily implemented.
Show less