Errors and other considerations in brain imaging

[Hutan]

A couple of recent posts, in
Increase in prefrontal cortical volume following cognitive behavioural therapy in patients with CFS, 2008, de Lange et al
(that one made a big deal of a 0.7% change in grey matter volume in people with ME/CFS, supposedly achieved by CBT)
Hypothalamus volumes in adolescent [ME/CFS]: Impact of self-reported fatigue and illness duration, 2023, Byrne et al.
(that didn't really find much at all)
made me wonder what the accuracy of brain size measurements might be, and if they can change quickly.

I found this paper, that seemed to suggest that grey matter volumes can change quickly:
Estimated gray matter volume rapidly changes after a short motor task 2022

Rapid changes in GMV estimates while executing tasks may however confound between- and within-subject differences. ... Estimated GMV was decreased in motor regions during FTT compared with rest.
These sensitive and behavior-related GMV changes pose serious questions to reproducibility across studies, and morphological investigations during skill learning can also open new avenues on how to study rapid brain plasticity.

They concluded
"Larger GMV while resting (as compared with Finger Tapping Task) indicates that engaging in a task prior to anatomical imaging may induce morphological changes."

I'm not sure that these changes would add up to much at the whole grey matter volume level, but for sure they could change things for particular bits of the brain. So, rushing to get to the MRI, or having to do a cognitive task just before imaging might also possibly affect volume estimates.

 

[Hutan]

Variability in the analysis of a single neuroimaging dataset by many teams, 2019, Botvinik-Nezer et al
This paper highlights the issues with analytic flexibility in fMRI.

And a couple more about fMRI.

A Machine Learning Approach to the Differentiation of Functional Magnetic Resonance Imaging Data of Chronic Fatigue Syndrome (CFS) From a Sedentary Control
A study of people with CFS and healthy controls found 29 regions of interest on Day 1 and 28 regions on Day 2 after a physical and cognitive challenge. However, only 10 of the regions of interest were common to both days, demonstrating how important it is to manage activity prior to fMRI.

Time of day is associated with paradoxical reductions in global signal fluctuation and functional connectivity
fMRI also varies during the day; it has been suggested that variation in time of day could potentially account for between-study variation in results and failed replications.

 

[SNT Gatchaman]

Also note the opposite finding in one LC study: Larger gray matter volumes in neuropsychiatric long-COVID syndrome (2022)

To our best knowledge, this is the first study reporting regionally increased gray matter in long-COVID patients with neuropsychiatric symptoms such as fatigue, depression and cognitive deficits and a mean time since disease onset of 8 months (range 2–16 months).

The longitudinal landmark study by Douaud et al. reported decreased cortical thickness in orbitofrontal and parahippocampal gyrus in participants previously infected with SARS-CoV-2 compared to their pre-infection status. This seemingly conflicting finding might result from several methodical differences between both studies. First of all, measures of cortical thickness and cortical volume, although often intercorrelated, deliver different information about changes in local cortical gray matter.

The presence of larger rather than smaller GMV in long-COVID patients when compared to controls, might indicate compensatory or recovery effects. This is in line with the findings by Lu et al. (2020).

Apart from compensatory processes, an alternative explanation for larger GMV in patients with COVID-19 could be ongoing inflammatory activity that results in endothelial activation, microvascular dysfunction, and vasogenic increase of tissue water. This hypothesis is worth testing, since there is some evidence of systemically increased inflammatory markers in long-COVID patients. Those markers were associated with long-term symptoms of depression and anxiety. Also, reduced levels of IL-6 predicted improvement of depressive symptoms. In immunometabolic major depression, which is clinically similar to neuropsychiatric long-COVID, dysregulation of both the innate and adaptive immune system was reported. There is a measurable increase of pro-inflammatory markers both on a systemic as well as CNS level.

 

[Hutan]

Interpreting BOLD: towards a dialogue between cognitive and cellular neuroscience

some background on BOLD signals in fMRI - although a 2016 paper

In short then, variability in neurovascular coupling mechan-isms meansthat the BOLD signal evoked bya given net increasein neuronal activity not only could vary in magnitude acrossdifferent experimental conditions, ages, brain areas and brainstates, but also could reflect different balances of circuit activity.How all these factors interact to generate the BOLD signal fromchanges in underlying neuronal activity has only been wellcharacterized during primary sensory processing, mostly inanaesthetized animals. Much further work is required to under-stand exactly how the neurovascular coupling relationshipvaries across the brain and therefore what exactly BOLD caninform us about underlying patterns of neuronal activity

Our lack ofknowledge of how neurovascular coupling is altered in dis-ease and pathology impacts our ability to accuratelyinterpret BOLD data.