Lucas C. Parra

Correlated Components Analysis - Extracting Reliable Dimensions in Multivariate Data

How does one find dimensions in multivariate data that are reliably expressed across repetitions? For example, in a brain imaging study one may want to identify combinations of neural signals that...

EEG in the classroom: Synchronised neural recordings during video presentation

We performed simultaneous recordings of electroencephalography (EEG) from multiple students in a classroom, and measured the inter-subject correlation (ISC) of activity evoked by a common video...

Origins of power-law degree distribution in the heterogeneity of human activity in social networks

The probability distribution of number of ties of an individual in a social network follows a scale-free power-law. However, how this distribution arises has not been conclusively demonstrated in...

Capturing contextual dependencies in medical imagery using hierarchical multi-scale models

Spatial projections of neural arrays: A short guide to classic and new signal analysis techniques

Maximum Likelihood Blind Source Separation: A Context-Sensitive Generalization of ICA

Unmixing Hyperspectral Data

Adaptive Template Matching with Shift-Invariant Semi-NMF

Hierarchical Image Probability (H1P) Models

Higher-Order Statistical Properties Arising from the Non-Stationarity of Natural Signals

Symplectic Nonlinear Component Analysis

Maximising Sensitivity in a Spiking Network

Second Order Bilinear Discriminant Analysis for single trial EEG analysis

Mammographic mass detection with a hierarchical image probability (HIP) model

Bayesian correlated component analysis for inference of joint EEG activation

Simultaneous and proportional control of 2D wrist movements with myoelectric signals

On the role of electric field orientation in optimal design of transcranial current stimulation

Amplification of small electric fields by neurons; implications for spike timing