Questions tagged [neuroimaging]
Various techniques to create a visual representation of the activity of nervous systems, such as fMRI, EEG, MEG, PET, etc.
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How can I merge data from two different raters for the same dataset?
We're analyzing patient MRI sections of the brain for tumour volume. We do this manually, frame by frame, drawing the borders of the tumour. To ensure more accurate results, we have used two different ...
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Relationship between beta and t-value in Shen (2018)
As far as I know [source],
$$t_{\widehat{\beta}} = \frac{\widehat{\beta}}{\widehat{SE_{\beta}}}.$$
It means the sign of the t-value should be the same as the sign of beta.
In Table S1 of Shen (2018), ...
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Predicting nested categorical variables from a set of continuous predictors
My dataset contains multiple continuous predictors (responses from n neurons) from which I would like to predict two categorical variables (A and B), where B is nested under A. A can take 8 different ...
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Averaging brain subregion correlation coefficients into a single measure
I've got a 257x257 correlation matrix of functional connectivity (fMRI) data. It is a symmetric matrix where each value is the Pearsons correlation of the brain area in the row with the brain area in ...
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Nested Fixed Effects
I have been reading up on nesting in Linear Mixed Effects modelling, and typically nesting is for random effects. However, if I want to estimate the effects of language and type of word for each ...
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Nested Linear Mixed Effects Model for Region-of-Interest to Region-of-Interest (ROI-to-ROI) Analysis
I am trying to examine the effects of language (English/Mother Tongue) on functional connectivity between different regions of interest (ROI). Hence, I employed a nested Linear Mixed Effects Model ...
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Fitting a well-specified 1D function of time to 3D spatial and spatially correlated data
I have acquired experimental data that can be considered to be a scalar field in physical three-dimensional space, $(x,y,z)$ that I have observed over time, measured on an equally spaced regular grid. ...
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How to statistically combine regression coefficients derived from subsamples of data
I wrote a version of this question yesterday, and I think in my effort to be brief, I wasn't clear. So I'm trying again.
I have questions about a cross validation for ensuring the independence of data ...
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Clustering and T-test (number of neurons in two groups of mice)
I will present my problem to you.
I have a database of brain slides of 40 mice. There are two groups of mice, mice 1 and mice 2, and each of the groups is made up of 20 mice.
On each slide of the ...
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Machine learning (CNN) - What questions can I answer while violating assumption of independence?
Introduction to the experiment and data type:
Suppose that I have 20 or so participants exposed to visual stimuli in several trials in two different conditions: Simple, and Complex, of 3 flavors each. ...
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One Multi-Label Classifier or Two Single-Label Classifier?
I have a dataset that each feature in a data could have two separate labels depending on separate definitions. According to definition 1, each feature could have one of two labels (A, B). According to ...
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Design of contrast for GLM in voxel-wise analysis
I'm attempting voxel-wise analysis of biomedical imaging (DWI-MRI) using FSLs GLM GUI (https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/GLM) but got confused when designing more complex experimental designs. ...
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Machine learning using neuroimaging data
Suppose I have collected the hemodynamic responses of participants when they were performing cognitive tasks (e.g. n-back) using a 16-channel functional near-infrared spectroscopy device. I would like ...
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Linear mixed model / cross-lagged panel model for longitudinal relationship between imaging metric and symptoms on continuous scale?
Background
I'm working with longitudinal volumetric brain data and psychiatric symptoms, measured simultaneously at two time points during childhood (let's call them brain1, brain2, symptom1, symptom2)...
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Paired or unpaired non-parametric 2 sample test?
I've got a relative simple question. I'm doing an imaging study with a phantom. I've run the same phantom through the MRI scanner 5 times, each time running the same scan twice and only varying one ...
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Best meta-analytic approach with Mean, SD, Sample size for regional values of MRI measure
I'm interested in evaluting the evidence in the literature I've collected for spatial/anatomical variation in an MRI measure. The data consists of mean values, standard deviations and sample sizes, ...
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What is an appropriate repeated-measures approach for statistically comparing results from two different methods?
I have a diffusion MRI dataset, with values of white matter tract volume and fractional anisotropy that were derived using tract masks generated from two different tractography software packages. I ...
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How to find difference between data recorded for 1431 variables for X subjects, across 3 time points?
I am doing research using magnetoencephalography (MEG). I'm performing coherence analysis which, briefly, is a measure of neuronal synchronicity and functional connectivity.
For each subject scanned ...
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For EEG analysis, why is it more efficient to use the raw data than images of the data?
Data Science publications for EEG analysis like EEGNet: A Compact Convolutional Network for EEG-based Brain-Computer Interfaces use the raw EEG data (see: github vlawhern/arl-eegmodels ) rather than ...
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How can I evaluate with R the interaction between a within-subject effect and a continuous variable at the subject level?
Scenario: 62 subjects did a selection task composed of 128 items, that can be divided into four conditions, because each item has a cue and a target (also other options but thats not of interest in ...
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Developing novel association measure with t-SNE
I am an MSc. student in computing and I am currently writing my thesis on radiogenomics (imaging genomics) for brain cancer research. I NEED YOUR HELP.
My supervisor and I are thinking about ...
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Correction for multiple comparisons with multiple region of interest analyses
I'm having an issue with deciding how to correct for multiple comparisons with my structural MRI region of interest analyses. I have two groups, Group A and Group B, and am looking at cortical ...
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What type of analysis should i perform on my data
I have two groups of clinical subjects i.e healthy (25 subjects) and patient group (25 subjects) ,for each subject i have volumetric data for several regions of brain (15 regions ).
I would like to ...
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I have p >> n and no overfitting, why?
I try to classify a brainstate (binary problem) on fMRI-data using a SVM (scikit-learn, which wrapps libsvm).
Also I use clusters arround local maxima in group-level TMaps as mask for the subject ...
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Machine Learning application to neuroscientific data
I have the following question, and it is (for me) an open research question. I really don't have a feeling if it is a difficult question or a trivial one, getting a better feeling for approaches I ...
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Is Fisher's z transformation necessary when comparing the variances of correlation coefficients?
I am working on functional connectivity between brain regions, where functional connectivity is represented by the Pearson correlation coefficient between the time series (fMRI) of brain regions. I am ...
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when is linear svm with incremental / decremental learning a good idea?
The data that I want to classify are large 3D medical images (the input vectors are the pixels, order of 1M coefficients). It has been argued that a linear SVM is a good classifier for these data ...
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What's the meaning of the expansion coefficient of the AR model?
I am trying to understand the meaning of the phi parameter of the AR modeling. A bit of background: I am digging into statistical parametric mapping (SPM) and the prewhitening method, used to get rid ...
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40,000 neuroscience papers might be wrong
I saw this article in the Economist about a seemingly devastating paper [1] casting doubt on "something like 40,000 published [fMRI] studies." The error, they say, is because of "erroneous statistical ...
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What does the number of independent components produced by ICA depend on?
I'm a student working on my bachelor thesis performing
independent component analysis (ICA) on some fMRI data using MELODIC FSL.
I would like to ask some questions regarding the results of ICA. ...
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Removing nuisance PCA components from the fMRI data
So in attempting to replicate analysis pipeline from Tambini & Davachi, PNAS 2013, Persistence of hippocampal multivoxel patterns into
postencoding rest is related to memory I'm hoping to use PCA ...
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How to do dimensionality reduction on a huge data set?
I am working with fMRI data of ~1000 subject. Each subject has a feature vector of ~150 million dimension. So I can only keep the feature vectors of ~10 subjects in memory.
What are some algorithms ...
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A paper mentions a "Monte Carlo simulation to determine the number of principal components"; how does it work?
I'm doing a Matlab analysis on MRI data where I have performed PCA on a matrix sized 10304x236 where 10304 is the number of voxels (think of them as pixels) and 236 is the number of timepoints. The ...
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Comparing Functional Connectivity as measured by fMRI
This question has been giving me a headache for a while so I'll define the problem before asking the question.
fMRI is a measure of Blood Oxygenation Level Dependent signal. Higher the blood ...
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Can you perform an ANOVA on r-values (correlation values)?
I am doing neuroimaging research yielding what is essentially a correlational analysis wherein my output is a brain's-worth of r-values (so like 15000 voxels worth of r-values). In this particular ...
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What is Bartlett's theory?
This neuroimaging paper has been cited thousands of times. In it, a method is proposed for computing the correlations among several seed regions and all other brain voxels. Part of this method ...
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Map of activated brain regions for special feature extraction method
I have read the following paper: "Feature Extraction for fMRI-Based Human Brain Activity Recognition". The most useful point for me is the new method of extracting features from fMRI images. It ...
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Request for literature on applications of manifold-valued random variables in medical imaging
I'd appreciate some references/literature on the applications of manifold-valued random variables, i.e., random variables $X:\Omega\to M$, where M is a manifold (could be even infinite dimensional), ...
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Dealing with overlapping control/patient groups in SPM
Seeing as this question combines statistics, neuroimaging and programming I wasn't sure where to ask it, I apologize if it needs to be moved.
I have data from a study where subjects were asked to ...
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How to interpret PCA on time-series data?
I am trying to understand the use of PCA in a recent journal article titled "Mapping brain activity at scale with cluster computing" Freeman et al., 2014 (free pdf available on the lab website). They ...
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The best way for clustering an adjacency matrix
I've had a hard time interpreting resulting clusters of an adjacency matrix. I have 200 relatively big matrices representing subjects that contains partial correlations (z scores) of time series (...
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Recommendation for books/notes for linear mixed effect models for longitudinal data?
I'm a beginner in data analysis who needs to learn (say in a period of 2 to 3 weeks or so) the key ideas and techniques in the linear mixed effect models for longitudinal data. I'll apply them in ...
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5-way interaction
I am running a mixed factors ANOVA for a brain imaging study on language processing. The design includes four within-subject factors:
complexity: simple/complex;
agreement: correct/number violation/...
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Large number of correlations with MRI region of interest (ROI) variables: What adjustment should I perform?
In our group, we have measured grey matter volumes of about 20 regions of interest (ROI) and frequency of cannabis use. Now, we would like find out whether cannabis use is associated with grey matter ...
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Visualization of a nondirected graph with nodes in specific positions
I have a variety of brain regions and information about how they're connected. (Not FMRI in this case, but the diffusion information about the white matter tracts connecting gray matter regions.)
I'...
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What is a null conjunction analysis in an fMRI study?
I'm reading an article, The commonality of neural networks for verbal and visual short-term memory (Majerus et al., J Cogn Neurosci 2010 22(11): 2570), about brain imaging in which the results are ...
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