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Intracortical bipolar stimulation allows selective activation of neuronal populations in the cortex #BCI

Intracortical bipolar stimulation allows selective activation of neuronal populations in the cortex
Background Intracortical electrical stimulation has emerged as a promising approach for sensory restoration, such as a cortical visual prosthesis, yet its effectiveness is limited by current spread and electrode density constraints. Objective To determine whether intracortical bipolar current steering—via modulation of the return electrode position—can enhance neural activation selectivity compared to traditional monopolar stimulation, with the aim of improving spatial precision in sensory…

The pure condition for incidence geometries
Daniel Irving Bernstein, Signe Lundqvist
https://arxiv.org/abs/2507.02661 https://arxiv.o…

The pure condition for incidence geometries
The space of \emph{parallel redrawings} of an incidence geometry $(P,H,I)$ with an assigned set of normals is the set of points and hyperplanes in $\mathbb{R}^d$ satisfying the incidences given by $(P,H,I)$, such that the hyperplanes have the assigned normals. In 1989, Whiteley characterized the incidence geometries that have d-dimensional realizations with generic hyperplane normals such that all points and hyperplanes are distinct. However, some incidence geometries can be realized as point…

Forecasting Nigerian Equity Stock Returns Using Long Short-Term Memory Technique
Adebola K. Ojo, Ifechukwude Jude Okafor
https://arxiv.org/abs/2507.01964 h…

Forecasting Nigerian Equity Stock Returns Using Long Short-Term Memory Technique
Investors and stock market analysts face major challenges in predicting stock returns and making wise investment decisions. The predictability of equity stock returns can boost investor confidence, but it remains a difficult task. To address this issue, a study was conducted using a Long Short-term Memory (LSTM) model to predict future stock market movements. The study used a historical dataset from the Nigerian Stock Exchange (NSE), which was cleaned and normalized to design the LSTM model. Th…

Comparing Bitcoin and Ethereum tail behavior via Q-Q analysis of cryptocurrency returns
A. H. Nzokem
https://arxiv.org/abs/2507.01983 https://

Comparing Bitcoin and Ethereum tail behavior via Q-Q analysis of cryptocurrency returns
The cryptocurrency market presents both significant investment opportunities and higher risks relative to traditional financial assets. This study examines the tail behavior of daily returns for two leading cryptocurrencies, Bitcoin and Ethereum, using seven-parameter estimates from prior research, which applied the Generalized Tempered Stable (GTS) distribution. Quantile-quantile (Q-Q) plots against the Normal distribution reveal that both assets exhibit heavy-tailed return distributions. Howe…

Behavioral Probability Weighting and Portfolio Optimization under Semi-Heavy Tails
Ayush Jha, Abootaleb Shirvani, Ali M. Jaffri, Svetlozar T. Rachev, Frank J. Fabozzi
https://arxiv.org/abs/2507.04208

Behavioral Probability Weighting and Portfolio Optimization under Semi-Heavy Tails
This paper develops a unified framework that integrates behavioral distortions into rational portfolio optimization by extracting implied probability weighting functions (PWFs) from optimal portfolios modeled under Gaussian and Normal-Inverse-Gaussian (NIG) return distributions. Using DJIA constituents, we construct mean-CVaR99 frontiers, alongwith Sharpe- and CVaR-maximizing portfolios, and estimate PWFs that capture nonlinear beliefs consistent with fear and greed. We show that increasing tai…