#OHBM2018 from Home

Learning from a conference at distance with Twitter

I'm a regular at OHBM, but I was in the USA and Canada in May, and I'm going to France in July, so this month of June I stayed home, missing my all-time favourite conference.

Twitter

At least I have Twitter @CyrilRPernetand many of my friends and colleagues use it too so I can benefit from them attending and telling the world what they found interesting.

Cool talks/posters and papers I had (more or less) time to check because I wasn't there

so what was hot on my twitter handle?

rs-fMRI and connectomics

Thomas Yeo started before the educational posting about an improved parcellation scheme for rs-fMRI: Spatial Topography of Individual-Specific Cortical Networks Predicts Human Cognition, Personality, and Emotion that comes with the code on GitHub.

Michael Breakspear was self-promoting a paper from the dynamic functional connectivity workshop: using structural connectome to simulate dynamic electrophysiology - super cool gif
https://twitter.com/i/status/1007405560440868864 see the preprint: Meta stable brain waves

Daniel Margulies keynote on rs-fmri gradients had a lot of attention too, here are two papers of interest: Situating the default-mode network along a principal gradient of macroscale cortical organization & Large-Scale Gradients in Human Cortical Organization

Martijn van den Heuvel keynote on connectomics also inspired many - I found his last paper really inspiring: Multiscale examination of cytoarchitectonic similarity and human brain connectivity

Tools, tools and tools

J. Lopez received the NeuroImage paper of the year for 'Reconstructing anatomy from electro-physiological data'

Andrew Doyle (sorry Pamela*) released a full tutorial on deep learning for the educational that is simply  amazing: https://brainhack101.github.io/IntroDL/

Got to mention the poster from Matteo Visconti on getting your Data into BIDS straight of the scanner 

Elizabeth Dupre got some interest in the hack room with muti-echo denoising and her tedana tool - thx to Ross Markelo for pointing out to 'the' right paper: Separating slow BOLD from non-BOLD baseline drifts using multi-echo fMRI

Out of this world

I've been checking up on the paper behind the Talairach lecture from K Friston: The Markov blankets of life: autonomy, active inference and the free energy principle

Special mention

Alex Bowring, Camille Maumet, Thomas Nichols paper on 'Exploring the Impact of Analysis Software on Task fMRI Results' got plenty of hits






* my mistake thought it was Pamela Douglas (speaker one) who made this one ...  updated on the 23rd