Neural electrodes for brain‐computer interface system: From rigid to soft
D Yang, G Tian, J Chen, Y Liu, E Fatima, J Qiu… - …, 2025 - Wiley Online Library
Brain‐computer interface (BCI) is an advanced technology that establishes a direct
connection between the brain and external devices, enabling high‐speed and real‐time …
connection between the brain and external devices, enabling high‐speed and real‐time …
Data efficiency, dimensionality reduction, and the generalized symmetric information bottleneck
KM Martini, I Nemenman - Neural Computation, 2024 - direct.mit.edu
The symmetric information bottleneck (SIB), an extension of the more familiar information
bottleneck, is a dimensionality-reduction technique that simultaneously compresses two …
bottleneck, is a dimensionality-reduction technique that simultaneously compresses two …
Principled, practical, flexible, fast: a new approach to phylogenetic factor analysis
Biological phenotypes are products of complex evolutionary processes in which selective
forces influence multiple biological trait measurements in unknown ways. Phylogenetic …
forces influence multiple biological trait measurements in unknown ways. Phylogenetic …
Massive parallelization boosts big Bayesian multidimensional scaling
Big Bayes is the computationally intensive co-application of big data and large, expressive
Bayesian models for the analysis of complex phenomena in scientific inference and …
Bayesian models for the analysis of complex phenomena in scientific inference and …
Low-dimensional encoding of decisions in parietal cortex reflects long-term training history
KW Latimer, DJ Freedman - Nature Communications, 2023 - nature.com
Neurons in parietal cortex exhibit task-related activity during decision-making tasks.
However, it remains unclear how long-term training to perform different tasks over months or …
However, it remains unclear how long-term training to perform different tasks over months or …
Geodesic Lagrangian Monte Carlo over the space of positive definite matrices: with application to Bayesian spectral density estimation
ABSTRACT We present geodesic Lagrangian Monte Carlo, an extension of Hamiltonian
Monte Carlo for sampling from posterior distributions defined on general Riemannian …
Monte Carlo for sampling from posterior distributions defined on general Riemannian …
Automatic bad channel detection in implantable brain-computer interfaces using multimodal features based on local field potentials and spike signals
M Li, Y Liang, L Yang, H Wang, Z Yang, K Zhao… - Computers in biology …, 2020 - Elsevier
Abstract “Bad channels” in implantable multi-channel recordings bring troubles into the
precise quantitative description and analysis of neural signals, especially in the current “big …
precise quantitative description and analysis of neural signals, especially in the current “big …
Modeling dynamic functional connectivity with latent factor Gaussian processes
Dynamic functional connectivity, as measured by the time-varying covariance of
neurological signals, is believed to play an important role in many aspects of cognition …
neurological signals, is believed to play an important role in many aspects of cognition …
Flexible Bayesian dynamic modeling of correlation and covariance matrices
Modeling correlation (and covariance) matrices can be challenging due to the positive-
definiteness constraint and potential high-dimensionality. Our approach is to decompose the …
definiteness constraint and potential high-dimensionality. Our approach is to decompose the …
Simultaneous Dimensionality Reduction for Extracting Useful Representations of Large Empirical Multimodal Datasets
E Abdelaleem - arXiv preprint arXiv:2410.19867, 2024 - arxiv.org
The quest for simplification in physics drives the exploration of concise mathematical
representations for complex systems. This Dissertation focuses on the concept of …
representations for complex systems. This Dissertation focuses on the concept of …