2nd level modelling in fMRI analysis with a clinically depressed sample - Comparisons between classical and Bayesian methods
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1
Swinburne University, BPsyC, Australia
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2
Monash Alfred Psychiatric Research Centre, Australia
The use of the Frequentist statistics in fMRI analysis has been the mainstay of the field for the last 25 years. Several other methods have been developed as alternatives, including those based on Bayesian statistics. Bayesian analysis methods have the benefit of allowing interrelation of data through effect size and confidence thresholds, can be more robust to outlier data and may negate the need for stringent multiple comparison correction. When examining functional differences in those with a mental illness , this can lead to detection of more subtle activation that may be of importance. Depression is a disorder that despite a common theme of symptoms is also characterised by functional heterogeneities between individuals, making inferences using Frequentist methods sometimes difficult.
Utilising both Frequentist and Bayesian 2nd level analysis methods offered by SPM8 , we examined differences in activation between a healthy control sample and those with major depressive disorder during a novel emotional processing n-back task. Activation using classical methods showed small differences in more posterior visual regions however this was only detectable with liberal thresholding (p = .001 uncorrected, k = 0). In contrast Bayesian analysis (y = 0, 95% confidence) uncovered widespread differences (including overlap with those areas found with the Frequentist method) in multiple regions implicated with the disorder.
This suggests that using Bayesian methods in fMRI analysis with a clinical population could be extremely useful in detecting responses that may otherwise go unnoticed or under-represented in more traditional methods, however determination of effect size importance is paramount.
Keywords:
Depression,
fMRI,
working memory,
Bayesian,
Frequentist
Conference:
XII International Conference on Cognitive Neuroscience (ICON-XII), Brisbane, Queensland, Australia, 27 Jul - 31 Jul, 2014.
Presentation Type:
Poster
Topic:
Methods Development
Citation:
Goodin
P,
Ciorciari
J,
Rossell
S,
Hughes
M and
Nibbs
R
(2015). 2nd level modelling in fMRI analysis with a clinically depressed sample - Comparisons between classical and Bayesian methods.
Conference Abstract:
XII International Conference on Cognitive Neuroscience (ICON-XII).
doi: 10.3389/conf.fnhum.2015.217.00203
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Received:
19 Feb 2015;
Published Online:
24 Apr 2015.
*
Correspondence:
Mr. Peter Goodin, Swinburne University, BPsyC, Hawthorn, Australia, peter@hitiq.com