A simulation study on the effects of neuronal ensemble properties on decoding algorithms for intracortical brain-machine interfaces

Background: Intracortical brain-machine interfaces (BMIs) harness movement information by sensing neuronal activities using chronic microelectrode implants to restore lost functions to patients with paralysis. However, neuronal signals often vary over time, even within a day, forcing one to rebuild a BMI every time they operate it. The term "rebuild" means overall procedures for operating a BMI, such as decoder selection, decoder training, and decoder testing. It gives rise to a practical issue of what decoder should be built for a given neuronal ensemble. This study aims to address it by exploring how decoders' performance varies with the neuronal properties. To extensively explore a range of neuronal properties, we conduct a simulation study. Methods: Focusing on movement direction, we examine several basic neuronal properties, including the signal-to-noise ratio of neurons, the proportion of well-tuned neurons, the uniformity of their preferred directions (PDs), and the non-stationarity of PDs. We investigate the performance of three popular BMI decoders: Kalman filter, optimal linear estimator, and population vector algorithm. Results: Our simulation results showed that decoding performance of all the decoders was affected more by the proportion of well-tuned neurons that their uniformity. Conclusions: Our study suggests a simulated scenario of how to choose a decoder for intracortical BMIs in various neuronal conditions

InVERT molding for scalable control of tissue microarchitecture

Complex tissues contain multiple cell types that are hierarchically organized within morphologically and functionally distinct compartments. Construction of engineered tissues with optimized tissue architecture has been limited by tissue fabrication techniques, which do not enable versatile microscale organization of multiple cell types in tissues of size adequate for physiological studies and tissue therapies. Here we present an ‘Intaglio-Void/Embed-Relief Topographic molding’ method for microscale organization of many cell types, including induced pluripotent stem cell-derived progeny, within a variety of synthetic and natural extracellular matrices and across tissues of sizes appropriate for in vitro, pre-clinical, and clinical studies. We demonstrate that compartmental placement of non-parenchymal cells relative to primary or induced pluripotent stem cell-derived hepatocytes, compartment microstructure, and cellular composition modulate hepatic functions. Configurations found to sustain physiological function in vitro also result in survival and function in mice for at least 4 weeks, demonstrating the importance of architectural optimization before implantation.National Institutes of Health (U.S.) (EB008396)National Institutes of Health (U.S.) (DK56966)National Cancer Institute (U.S.) (Cancer Center Support Core Grant P30-CA14051)National Institutes of Health (U.S.). Ruth L. Kirschstein National Research Service Award (1F32DK091007)National Institutes of Health (U.S.). Ruth L. Kirschstein National Research Service Award (1F32DK095529)National Science Foundation (U.S.). Graduate Research Fellowship Program (1122374

Weather conditions and daily television use in the Netherlands, 1996–2005

This study examines the impact of daily atmospheric weather conditions on daily television use in the Netherlands for the period 1996–2005. The effects of the weather parameters are considered in the context of mood and mood management theory. It is proposed that inclement and uncomfortable weather conditions are associated with lower human mood, and that watching entertainment and avoiding informational programs may serve to repair such mood. We consequently hypothesize that people spend more time watching television if inclement and uncomfortable weather conditions (low temperatures, little sunshine, much precipitation, high wind velocity, less daylight) coincide with more airtime for entertainment programs, but that they view less if the same weather conditions coincide with more airtime devoted to information fare. We put this interaction thesis to a test using a time series analysis of daily television viewing data of the Dutch audience obtained from telemeters (T = 3,653), merged with meteorological weather station statistics and program broadcast figures, whilst controlling for a wide array of recurrent and one-time societal events. The results provide substantial support for the proposed interaction of program airtime and the weather parameters temperature and sunshine on aggregate television viewing time. Implications of the findings are discussed

Whole transcriptome organisation in the dehydrated supraoptic nucleus

The supraoptic nucleus (SON) is part of the central osmotic circuitry that synthesises the hormone vasopressin (Avp) and transports it to terminals in the posterior lobe of the pituitary. Following osmotic stress such as dehydration, this tissue undergoes morphological, electrical and transcriptional changes to facilitate the appropriate regulation and release of Avp into the circulation where it conserves water at the level of the kidney. Here, the organisation of the whole transcriptome following dehydration is modelled to fit Zipf's law, a natural power law that holds true for all natural languages, that states if the frequency of word usage is plotted against its rank, then the log linear regression of this is -1. We have applied this model to our previously published euhydrated and dehydrated SON data to observe this trend and how it changes following dehydration. In accordance with other studies, our whole transcriptome data fit well with this model in the euhydrated SON microarrays, but interestingly, fit better in the dehydrated arrays. This trend was observed in a subset of differentially regulated genes and also following network reconstruction using a third-party database that mines public data. We make use of language as a metaphor that helps us philosophise about the role of the whole transcriptome in providing a suitable environment for the delivery of Avp following a survival threat like dehydration

Monetary models of exchange rates and sweep programs

Numerous studies find that monetary models of exchange rates cannot beat a random walk model. Such a finding, however, is not surprising given that such models are built upon money demand functions and traditional money demand functions appear to have broken down in many developed countries. In this article, we investigate whether using a more stable underlying money demand function results in improvements in forecasts of monetary models of exchange rates. More specifically, we use a sweep-adjusted measure of US monetary aggregate M1 which has been shown to have a more stable money demand function than the official M1 measure. The results suggest that the monetary models of exchange rates contain information about future movements of exchange rates, but the success of such models depends on the stability of money demand functions and the specifications of the models.

Investment sensitivity to interest rates in an uncertain context: is a positive relationship possible?

NPV, Interest rates models, GMM , GARCH model, Threshold model, E22, E43, G31,