## Gabor-filter models for visual neuroscience

Let's use a state of the art machine learning library to build an old-fashioned Gabor wavelet pyramid model

## Regression to the mean strikes again

Simulating how voxel selection in fMRI caused regression to the mean in a recently-retracted paper

## The curse of low statistical power

How selection bias perpetuates low power in science

## Understanding noise ceiling metrics: 'RSA' compared to Spearman-Brown

How do you calculate a noise ceiling? What is the difference between the estimates calculated in RSA and those reported in the encoding model literature?

## Power, prevalence, and the positive predictive value

In which we study how statistical power and significance thresholding influences reproducibility by relating it to positive and negative predictive values.

## Pilab tutorial 3: importing fMRI data and ROIs, searchlight mapping

We demonstrate how to apply pilab linear discriminant contrast methods to a real fMRI dataset, including searchlight mapping over the full volume.

## Pilab tutorial 2: linear discriminant contrast

We estimate multivariate discriminability with linear discriminant contrast (also known as cross-validated Mahalanobis distance, crossnobis).

## Pilab tutorial 1: model fit and cross-validation

We simulate a basic fMRI dataset, and estimate cross-validated prediction performance for a convolved design.

## Journal club: Estimating the dimensionality of neuronal representations during cognitive tasks

It's a bit of a cliche that the best papers are the ones that raise more questions than they answer (in fact, many papers seem to answer hardly anything at all on close inspection and it doesn't mean they're great). But I think this might be one of those papers …

## Reproducible scientific python setup with (Ana) Conda

Getting a scientific python install up and running is still way too complicated. In this post I describe how I use a conda to keep a reproducible record of the packages I use.

In the past, I have usually hacked together my own developing environment through whatever tools were most …