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Hall, D.

Publications and source records attributed to Hall, D..

38 records · Page 3Linked to original sources
bioRxiv2019

Neuropathological validation of the MDS-PSP criteria with PSP and other frontotemporal lobar degeneration

BackgroundProgressive supranuclear palsy (PSP) is clinically heterogeneous. Clinical diagnostic criteria were revised in 2017, to increase sensitivity and operationalize the diagnosis of PSP Richardsons syndrome (PSP-RS) and \"variant\" syndromes (vPSP).\n\nObjectivesTo determine the (1) sensitivity and specificity of the 1996 NINDS-SPSP and 2017 MDS-PSP criteria; (2) false positive rates in frontotemporal dementia with frontotemporal lobar degeneration (FTLD); and (3) clinical evolution of variant PSP syndromes (vPSP).\n\nMethodsRetrospective multicenter review of 108 neuropathologically-confirmed PSP patients and 81 patients with other forms of FTLD: 38 behavioral variant frontotemporal dementia (bvFTD), 14 non-fluent/agrammatic variant primary progressive aphasia (nfvPPA), and 29 corticobasal degeneration (CBD), Sensitivity and specificity of the MDS-PSP criteria were compared to the NINDS-SPSP criteria at baseline. In a subset of cases, the timing and frequency of clinical features were compared across groups over six years.\n\nResultsSensitivity for recognition of probable and possible PSP pathology was higher by MDS-PSP criteria (72.2-100%) than NINDS-SPSP criteria (48.1-61.1%). Specificity was higher by NINDS-SPSP criteria (97.5-100%) than MDS-PSP criteria (53.1-95.1%). False positives by MDS-PSP criteria were few for bvFTD (10.5-18.4%) but common for CBD and nfvPPA (fulfilling \"suggestive of PSP). Most vPSP cases developed PSP-RS-like features within six years, including falls and supranuclear gaze palsy, distinguishing frontal presentations of PSP from bvFTD, and speech/language presentations of PSP from nfvPPA.\n\nConclusionsThe 2017 MDS-PSP criteria successfully identify PSP, including variant phenotypes. This independent validation of the revised clinical diagnostic criteria strengthens the case for novel therapeutic strategies against PSP to include variant presentations.

neuroscience↗
bioRxiv2018

meaRtools: an R package for the Comprehensive Analysis of Neuronal Networks Recorded on Multi-Electrode Arrays

Here we present an open-source R package meaRtools that provides a platform for analyzing neuronal networks recorded on Microelectrode Arrays (MEAs). Cultured neuronal networks monitored with MEAs are now being widely used to characterize in vitro models of neurological disorders and to evaluate pharmaceutical compounds. meaRtools provides core algorithms for MEA spike train analysis, feature extraction, statistical analysis and plotting of multiple MEA recordings with multiple genotypes and treatments. meaRtools functionality covers novel solutions for spike train analysis, including algorithms to assess electrode cross-correlation using the spike train tiling coefficient (STTC), mutual information, synchronized bursts and entropy within cultured wells. Also integrated is a solution to account for bursts variability originating from mixed-cell neuronal cultures. The package provides a statistical platform built specifically for MEA data that can combine multiple MEA recordings and compare extracted features between different genetic models or treatments. We demonstrate the utilization of meaRtools to successfully identify epilepsy-like phenotypes in neuronal networks from Celf4 knockout mice. The package is freely available under the GPL license (GPL>=3) and is updated frequently on the CRAN web-server repository. The package, along with full documentation can be downloaded from: https://cran.r-project.org/web/packages/meaRtools/.\n\nAuthor summaryCultured neuronal networks are widely used to study and characterize neuronal network activity. Among the many uses of neuronal cultures are the capabilities to evaluate neurotoxicity and the effects of pharmacological compounds on cellular physiology. Multi-well microelectrode arrays (MEAs) can collect high-throughput data from multiple neuronal cultures simultaneously, and thereby make possible hypotheses-driven inquiries into neurobiology and neuropharmacology. The analysis of MEA-derived information presents many computational challenges. High frequency data recorded simultaneously from hundreds of electrodes can be difficult to handle. The need to compare network activity across various drug treatments or genotypes recorded on the same plate from experiments lasting several weeks presents another challenge. These challenges inspired us to develop meaRtools; an MEA data analysis package that contains new methods to characterize network activity patterns, which are illustrated here using examples from a genetic mouse model of epilepsy. Among the highlights of meaRtools are novel algorithms designed to characterize neuronal activity dynamics and network properties such as bursting and synchronization, options to combine multiple recordings and use a robust statistical framework to draw appropriate statistical inferences, and finally data visualizations and plots. In summary, meaRtools provides a platform for the analyses of singular and longitudinal MEA experiments.

neuroscience↗