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Stimulus onset quenches neural variability: a widespread cortical phenomenon
Neural responses are typically characterized by computing the mean firing rate, but response variability can exist across trials. Many studies have examined the effect of a stimulus on the mean…
Influence of heart rate on the BOLD signal: The cardiac response function
Gaussian-process factor analysis for low-dimensional single-trial analysis of neural population activity
A novel method for extracting neural trajectories-Gaussian-process factor analysis (GPFA) is presented-which unifies the smoothing and dimensionality-reduction operations in a common probabilistic framework and shows how such methods can be a powerful tool for relating the spiking activity across a neural population to the subject's behavior on a single-trial basis.
A High-Performance Neural Prosthesis Enabled by Control Algorithm Design
A new control algorithm is presented, the recalibrated feedback intention–trained Kalman filter (ReFIT-KF) that incorporates assumptions about the nature of closed-loop neural prosthetic control and demonstrates repeatable high performance for years after implantation in two monkeys, thereby increasing the clinical viability of neural prostheses.
Dimensionality reduction for large-scale neural recordings
This review examines three important motivations for population studies: single-trial hypotheses requiring statistical power, hypotheses of population response structure and exploratory analyses of large data sets, and practical advice about selecting methods and interpreting their outputs.
Linear dimensionality reduction: survey, insights, and generalizations
This survey and generic solver suggest that linear dimensionality reduction can move toward becoming a blackbox, objective-agnostic numerical technology.
Bayesian Optimization with Inequality Constraints
- Jacob R. Gardner, Matt J. Kusner, Z. Xu, Kilian Q. Weinberger, J. Cunningham
- Computer ScienceInternational Conference on Machine Learning
- 21 June 2014
This work presents constrained Bayesian optimization, which places a prior distribution on both the objective and the constraint functions, and evaluates this method on simulated and real data, demonstrating that constrainedBayesian optimization can quickly find optimal and feasible points, even when small feasible regions cause standard methods to fail.
Cortical Preparatory Activity: Representation of Movement or First Cog in a Dynamical Machine?
BLACK BOX VARIATIONAL INFERENCE FOR STATE SPACE MODELS
- Evan Archer, Il Memming Park, Lars Buesing, J. Cunningham, L. Paninski
- Computer Science
- 23 November 2015
A structured Gaussian variational approximate posterior is proposed that carries the same intuition as the standard Kalman filter-smoother but permits us to use the same inference approach to approximate the posterior of much more general, nonlinear latent variable generative models.
Long-term stability of neural prosthetic control signals from silicon cortical arrays in rhesus macaque motor cortex
It is suggested that action potential amplitude declines more slowly than previously supposed, and performance can be maintained over the course of multiple years when decoding from threshold-crossing events rather than isolated action potentials.