Faculty Bibliography
Searched for:
Department/Unit:Neurology
Total Results:
24282
JAAPA : official journal of the American Academy of Physician Assistants. 2020:33(12):26-28.DOI: 10.1097/01.JAA.0000721660.97428.0c
An unusual artery causing an unusual stroke [Case Report]
Bilateral thalamic infarctions are uncommon and often lead to more severe and long-lasting symptoms than unilateral thalamic infarctions. This article describes a patient with bilateral thalamic infarction caused by occlusion in the artery of Percheron, an anatomic variant thought to be present in 4% to 12% of the population.
PMID: 33234892
ISSN: 1547-1896
CID: 5883472
Amyotrophic lateral sclerosis & frontotemporal degeneration. 2020:21(sup1):1-2.DOI: 10.1080/21678421.2020.1840795
Preface: promoting research in PLS: current knowledge and future challenges [Editorial]
PMID: 33602018
ISSN: 2167-9223
CID: 5874172
Amyotrophic lateral sclerosis care and research in the United States during the COVID-19 pandemic: Challenges and opportunities
Coronavirus disease 2019 has created unprecedented challenges for amyotrophic lateral sclerosis (ALS) clinical care and research in the United States. Traditional evaluations for making an ALS diagnosis, measuring progression, and planning interventions rely on in-person visits that may now be unsafe or impossible. Evidence- and experience-based treatment options, such as multidisciplinary team care, feeding tubes, wheelchairs, home health, and hospice, have become more difficult to obtain and in some places are unavailable. In addition, the pandemic has impacted ALS clinical trials by impairing the ability to obtain measurements for trial eligibility, to monitor safety and efficacy outcomes, and to dispense study drug, as these also often rely on in-person visits. We review opportunities for overcoming some of these challenges through telemedicine and novel measurements. These can reoptimize ALS care and research in the current setting and during future events that may limit travel and face-to-face interactions.
PMCID:7283687
PMID: 32445195
ISSN: 1097-4598
CID: 5873462
Amyotrophic lateral sclerosis: update on clinical management
PURPOSE OF REVIEW:The current review will provide recent updates in the clinical management of amyotrophic lateral sclerosis (ALS). RECENT FINDINGS:Although there is no cure for ALS, there are new treatments, growing knowledge of genetics, development of clinical staging systems, and the recent coronavirus disease 2019 pandemic that have recently impacted the clinical management of ALS. Increased understanding of genetics has helped provide insights into pathophysiology, the staging systems and clinical measures help to provide tools for monitoring disease clinically, and the recent coronavirus disease 2019 pandemic has provided opportunities to develop telemedicine and remote monitoring of disease thereby increasing accessibility to care and reducing burden of travel to centers for people living with the disease and their caregivers. SUMMARY:ALS is a progressive neurodegenerative disease that causes degeneration of the motor neurons which leads to paralysis and respiratory failure. Despite the lack of a cure, multidisciplinary care, proactive respiratory management, nutritional care and management of symptoms as well as pharmacological interventions that can improve quality of life and survival.
PMID: 32868602
ISSN: 1473-6551
CID: 5873482
Amyotrophic lateral sclerosis & frontotemporal degeneration. 2020:21(7-8):509-518.DOI: 10.1080/21678421.2020.1771734
Real-world evidence of riluzole effectiveness in treating amyotrophic lateral sclerosis
To compare the effect of riluzole on median survival in population studies of patients with amyotrophic lateral sclerosis (ALS) with that observed in clinical trials. Methods: Two independent PubMed searches were conducted, to identify population studies that reported median survival for ALS patients who were either treated with riluzole or remained riluzole-free. Results: We identified 14 studies that met the inclusion criteria of reporting median survival and an additional study that reported mean survival of both riluzole and riluzole-free patients. Analysis of the 15 studies found that a majority reported increased survival of riluzole vs. riluzole-free patients. In 8 studies, the median survival for patients treated with riluzole was 6-19 months longer compared with patients not treated with riluzole (p < 0.05). Three additional studies reported a clinically meaningful treatment effect (range 3-5.9 months) but did not meet statistical significance. The remaining 4 studies did not show a meaningful treatment effect between riluzole and riluzole-free groups (<3 months), and differences among the groups were not significant. Also, 5 of the studies used multivariate regression analysis to investigate the level of association between treatment with riluzole and survival; these analyses supported the positive effect of riluzole on survival. Conclusions: A majority of population studies that compared riluzole vs. riluzole-free ALS patients found significant differences in median survival between the two groups, ranging from 6 to 19 months. This is substantially longer than the 2- to 3-month survival benefit observed in the pivotal clinical trials of riluzole.
PMID: 32573277
ISSN: 2167-9223
CID: 5873472
A reinforcement-learning model of active avoidance behavior: Differences between Sprague Dawley and Wistar-Kyoto rats
Avoidance behavior is a typically adaptive response performed by an organism to avert harmful situations. Individuals differ remarkably in their tendency to acquire and perform new avoidance behaviors, as seen in anxiety disorders where avoidance becomes pervasive and inappropriate. In rodent models of avoidance, the inbred Wistar-Kyoto (WKY) rat demonstrates increased learning and expression of avoidance compared to the outbred Sprague Dawley (SD) rat. However, underlying mechanisms that contribute to these differences are unclear. Computational modeling techniques can help identify factors that may not be easily decipherable from behavioral data alone. Here, we utilize a reinforcement learning (RL) model approach to better understand strain differences in avoidance behavior. An actor-critic model, with separate learning rates for action selection (in the actor) and state evaluation (in the critic), was applied to individual data of avoidance acquisition from a large cohort of WKY and SD rats. Latent parameters were extracted, such as learning rate and subjective reinforcement value of foot shock, that were then compared across groups. The RL model was able to accurately represent WKY and SD avoidance behavior, demonstrating that the model could simulate individual performance. The model determined that the perceived negative value of foot shock was significantly higher in WKY than SD rats, whereas learning rate in the actor was lower in WKY than SD rats. These findings demonstrate the utility of computational modeling in identifying underlying processes that could promote strain differences in behavioral performance.
PMCID:7423762
PMID: 32585299
ISSN: 1872-7549
CID: 5865622
Dataset of active avoidance in Wistar-Kyoto and Sprague Dawley rats: Experimental data and reinforcement learning model code and output
Data were collected from 40 Wistar-Kyoto (WKY) and 40 Sprague Dawley (SD) rats during an active escape-avoidance experiment. Footshock could be avoided by pressing a lever during a danger period prior to onset of shock. If avoidance did not occur, a series of footshocks was administered, and the rat could press a lever to escape (terminate shocks). For each animal, data were simplified to the presence or absence of lever press and stimuli in each 12-second time frame. Using the pre-processed dataset, a reinforcement learning (RL) model, based on an actor-critic architecture, was utilized to estimate several different model parameters that best characterized each rat's behaviour during the experiment. Once individual model parameters were determined for all 80 rats, behavioural recovery simulations were run using the RL model with each animal's "best-fit" parameters; the simulated behaviour generated avoidance data (percent of trials avoided during a given experimental session) that could be compared across simulated rats, as is customarily done with empirical data. The datasets representing both the experimental data and the model-generated data can be interpreted in various ways to gain further insight into rat behaviour during avoidance and escape learning. Furthermore, the estimated parameters for each individual rat can be compared across groups. Thus, possible between-strain differences in model parameters can be detected, which might provide insights into strain differences in learning. The software implementing the RL model can also be applied to or serve as a template for other experiments involving acquisition learning. Reference for Co-Submission: K.M. Spiegler, J. Palmieri, K.C.H. Pang, C.E. Myers, A reinforcement-learning model of active avoidance behavior: Differences between Sprague-Dawley and Wistar-Kyoto rats. Behav. Brain Res. (2020 Jun 22[epub ahead of print]) doi: 10.1016/j.bbr.2020.112784.
PMCID:7451822
PMID: 32904157
ISSN: 2352-3409
CID: 5865632
Challenges and Opportunities with Causal Discovery Algorithms: Application to Alzheimer's Pathophysiology
Causal Structure Discovery (CSD) is the problem of identifying causal relationships from large quantities of data through computational methods. With the limited ability of traditional association-based computational methods to discover causal relationships, CSD methodologies are gaining popularity. The goal of the study was to systematically examine whether (i) CSD methods can discover the known causal relationships from observational clinical data and (ii) to offer guidance to accurately discover known causal relationships. We used Alzheimer's disease (AD), a complex progressive disease, as a model because the well-established evidence provides a "gold-standard" causal graph for evaluation. We evaluated two CSD methods, Fast Causal Inference (FCI) and Fast Greedy Equivalence Search (FGES) in their ability to discover this structure from data collected by the Alzheimer's Disease Neuroimaging Initiative (ADNI). We used structural equation models (which is not designed for CSD) as control. We applied these methods under three scenarios defined by increasing amounts of background knowledge provided to the methods. The methods were evaluated by comparing the resulting causal relationships with the "gold standard" graph that was constructed from literature. Dedicated CSD methods managed to discover graphs that nearly coincided with the gold standard. For best results, CSD algorithms should be used with longitudinal data providing as much prior knowledge as possible.
PMCID:7031278
PMID: 32076020
ISSN: 2045-2322
CID: 5864672
The genetic architecture of the human cerebral cortex
The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder.
PMID: 32193296
ISSN: 1095-9203
CID: 5864682
White matter atrophy in cerebral amyloid angiopathy
OBJECTIVE:We postulated that cerebral amyloid angiopathy (CAA) is associated with white matter atrophy (WMA) and that WMA can be related to cognitive changes in CAA. METHODS:White matter volume expressed as percent of intracranial volume (pWMV) of prospectively enrolled patients without dementia diagnosed with probable CAA was compared to age-matched healthy controls (HC) and patients with Alzheimer disease (AD). Cognitive scores were also sought to understand the potential effects of WMA on cognitive function. RESULTS:= 0.003, respectively). All associations remained independent in multivariable analyses. Within the CAA cohort, higher pWMV independently correlated with better scores of executive function. CONCLUSIONS:Patients with CAA show WMA when compared to age-matched HC and patients with AD. WMA independently correlates with the number of lobar microbleeds, a marker of CAA severity. Consistent spatial patterns of WMA especially in posterior regions might be related to CAA. The association between WMA and measures of executive function suggests that WMA might represent an important mediator of CAA-related neurologic dysfunction.
PMCID:7455340
PMID: 32611644
ISSN: 1526-632x
CID: 5864692
