# Tag Archives: Data analysis

## Layer-wise decorrelation in deep-layered artificial neuronal networks

The most commonly used deep networks are purely feed-forward nets. The input is passed to layers 1, 2, 3, then at some point to the final layer (which can be 10, 100 or even 1000 layers away from the input). … Continue reading

## A convolutional network to deconvolve calcium traces, living in an embedding space of statistical properties

As mentioned before (here and here), the spikefinder competition was set up earlier this year to compare algorithms that infer spiking probabilities from calcium imaging data. Together with Stephan Gerhard, a PostDoc in our lab, I submitted an algorithm based on convolutional networks. Looking … Continue reading

## A short report from a Cold Spring Harbor lab course

One of the best things of being a PhD student is that one is supposed to learn new things. As part of this mission, I attended a two-week laboratory course in the Cold Spring Harbor Laboratories on ‘Advanced Techniques in … Continue reading

## Whole-cell patch clamp, part 3: Limitations of quantitative whole-cell voltage clamp

Before I first dived into experimental neuroscience, I imagined whole-cell voltage clamp recordings to be the holy grail of precision. Directly listening to the currents that take place inside of a living neuron! How beautiful and precise, compared to poor-resolution techniques like fMRI or … Continue reading

## Spike detection competition

The main drawback of functional calcium imaging is its slow dynamics. This is not only due to limited frame rates, but also due to calcium dynamics, which are a slow transient readout of fast spiking activity. A perfect algorithm would infer the … Continue reading

## Neuroscience on Youtube

Recently, I’ve been to the Basel ICON conference, where the recent Nobel laureate Eric Betzig gave an impressive talk on microscopy techniques (including lattice light sheet, SIM and expansion microscopy). Some days ago, I found a similar talk by Eric … Continue reading

## Beyond correlation analysis: incremental mutual information

Incremental Mutual Information: A New Method for Characterizing the Strength and Dynamics of Connections in Neuronal Circuits is a 2010 paper by A. Singh and N. Lesica in PLoS Computational Biology that describes a method which can be used as an … Continue reading