Category: layer-fMRI field

OHBM 2022 Hackathon project: MOSAIC for VASO fMRI

Description

Vascular Space Occupancy is an fMRI method that is popular for high-resolution layer-fMRI. Currently, the most popular sequence is the one by Rüdiger Stirnberg from the DZNE in Bonn, which is actively being employed at more than 30 sites.

Current users of the DZNE VASO sequence. Interactive map

This sequence concomitantly acquires fMRI BOLD and blood volume signals. In the SIEMENS reconstruction pipeline, these signals are mixed together within the same time series, which challenges its user friendliness. Specifically:
The “raw” dicom2nii-converted time-series are not BIDS compatible (see https://github.com/bids-standard/bids-specification/issues/1001).
The order of odd and even BOLD and VASO image TRs is dependent on the nii-converter.
Workarounds with 3D distortion correction, results in interpolation artifacts.
Workarounds without MOSAIC decorators result in impracticable large data sizes.

The goal of this Hackathon is to extend the 3D-MOSAIC to solve these constraints. This functor is commonly used to sort images by echo-times, by RF-channels, by magnitude and phase in the SIEMENS reconstruction pipeline into sets of mosaics . However currently, this functor does not yet support the dimensionality of SETs. In this project we seek to include SETs into the capabilities of the functor.

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Which sequence is best for layer-fMRI? A graphic story in cynical metaphors.

There are many sequences that have been proposed to be suited for layer-fMRI. This list includes GE-BOLD (Menon 1999), SE-EPI (Goense 2006), CPMG (Scheffler 2021), ASL (Kashyap 2021), diffusion fMRI (Truong 2009), 3D-GRASE (Moerel 2018), calibrated BOLD aka CMRO2 mapping (Guidi 2020), VASO (Hua 2013), phase regression (Stanley 2021), onset-time imaging (Yu 2014), depth-dependent deconvolution (Markuerkiaga 2021), CVR-calibration (Guidi 2016), and many more.

In this blog post, I want to summarise the take-home message from the seemingly never ending  battle between researchers fighting about the best sequence for layer-fMRI. I seek to do so by means of cynical metaphors in graphical form. Because, why not. There are plenty more serious discussions already elsewhere1,2,3.

Continue reading “Which sequence is best for layer-fMRI? A graphic story in cynical metaphors.” →

Third Virtual Layer-fMRI ‘Dinner’: Cognitive Models and Cortical Layers.

On April 20th 2021, the third virtual layer-fMRI took place. 120 (unique) attendees joined and discussed the connection between layer-fMRI and cognitive models.

This meeting is held as a succession of the first two virtual dinner in May 2020, and Sept 2020:

In this third event, it will be discussed how the layer-fMRI methodologies might be able to inform Cognitive models. The three speakers are researchers that are working to examine cognitive processes whose study is aided by understanding the structure and function of cortical layers. These cognitive processes could include memory, attention, learning, dreaming, language or cortical predictions (plus many, many more!)

Floris de Lange will give an overview of work done by his group to capture laminar fMRI activity changes in the visual cortex for prediction, attention and bottom-up input. André Bastos will present results of laminar LFP recordings and how feed-forward gamma-band and feedback alpha/beta band modulations help to understand cognitive effects including attention, working memory, and prediction processing. Michelle Moerel will talk about how computational models can be combined with laminar fMRI to understand human auditory processing. 

Below you find the important links of the virtual event. Embedded videos of the talks, discussions, and a summary of the hot topics are going to be added on the day after the event.

Continue reading “Third Virtual Layer-fMRI ‘Dinner’: Cognitive Models and Cortical Layers.” →

Second Virtual Layer-fMRI ‘Dinner’: Laminae in the brain; fMRI vs. electrophysiology

On Sept 28th 2020, the second virtual layer-fMRI event is scheduled.

This meeting is held as a succession of the first virtual dinner in May 2020: https://layerfmri.com/virtualevent1/

In this second event, it will be discussed how the research field can bridge the gap between layer-dependent activity measures that are obtained with fMRI and electrophysiology, respectively. Kamil Ugurbil will present the perspective of high resolution for human neuroscience, Lucia Melloni will present the perspective of depth-dependent electrophysiological recordings in humans, and Seong-Gi Kim will talk about the combination of both worlds, layer-fMRI and layer-dependent electrophysiological recordings. 

Below you find the important links of the the virtual event. Embedded videos of the talks, discussions, and a summary of the hot topics are going to be added on the day after the event.

Continue reading “Second Virtual Layer-fMRI ‘Dinner’: Laminae in the brain; fMRI vs. electrophysiology” →

Meeting minutes of the virtual layer-fMRI event #1

On May 7th 2020, there was a virtual layerfMRI event to discuss current issues in the field.

This meeting was held as a replacement of an originally planned layer-fMRI dinner at ISMRM and happened in succession of an earlier in-person layerfMRI workshop in November 2019 (meeting minutes here).

Below you find the important links of the the virtual event, videos of the talks and discussions, and a summary of the hot topics that were discussed.

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Layer-fMRI VASO worldwide

This blog post gives an overview of the scientific network of researchers that are using the VASO (vascular space occupancy) for applications in layer-fMRI. I tried to give an overview of all layer-fMRI VASO papers published so far and provide a map of all layer-fMRI VASO labs around the globe. Continue reading “Layer-fMRI VASO worldwide” →

Layer-fMRI Jobs

 

This page lists all open layer-fMRI job opportunities.

Suggestions are welcome to layerfMRI@gmail.com

Tweet intro
Don’t we all feel like Daniel in his Tweet(screenshot taken with permission)

How many layers should I extract?

In this blog post, I want to share my thoughts on the number of layers that should be extracted from any given dataset. I will try to give an overview of how many layers are usually extracted in the field, I’ll describe my personal choices of layer numbers, and I will try to discuss the challenges of layer signal extraction along the way.

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layer-fMRI software repositories

There is a long list of software packages that are capable of performing high-resolution MRI analysis.

Some of them are used by multiple groups and some of them are customized for specific studies only.

In this post, I want to give an overview over the most important software packages, their advantages and disadvantages, and their popularity in the field.

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