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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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Alternative to paired t-test for non independent data

I'm working on a research project where I predict fMRI activity using two separate sets of predictors, X1 and X2. In order to do this, I am fitting a linear regression from each predictor to each ...
Ebrahim Feghhi's user avatar
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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 ...
Bilal Bahadır Akbulut's user avatar
3 votes
1 answer
124 views

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), ...
John Smith's user avatar
2 votes
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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 ...
Toghrul's user avatar
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1 answer
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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 ...
Wei Ting Chua's user avatar
2 votes
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42 views

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. ...
Landak's user avatar
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5 votes
1 answer
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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 ...
Katie's user avatar
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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 ...
baptbapt's user avatar
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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. ...
Prams's user avatar
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852 views

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 ...
LCheng's user avatar
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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. ...
Adrian Mak's user avatar
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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 ...
TLL's user avatar
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269 views

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)...
messislore's user avatar
2 votes
1 answer
337 views

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 ...
redsoxfan4's user avatar
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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, ...
Yeti's user avatar
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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 ...
Abdullah Alshammaa's user avatar
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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 ...
user7468395's user avatar
1 vote
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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 ...
Walter Mandelbroth's user avatar
1 vote
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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 ...
Guest_user's user avatar
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1 answer
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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 ...
Devaa's user avatar
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2 votes
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521 views

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 ...
Uzaku's user avatar
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1 answer
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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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3 votes
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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 ...
Samira's user avatar
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101 views

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 ...
alle_meije's user avatar
2 votes
1 answer
1k views

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 ...
jessyjemy's user avatar
66 votes
1 answer
8k views

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 ...
R Greg Stacey's user avatar
4 votes
1 answer
1k views

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. ...
Laura Palacio's user avatar
3 votes
1 answer
834 views

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 ...
chainhomelow's user avatar
3 votes
0 answers
654 views

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 ...
erensezener's user avatar
11 votes
1 answer
1k views

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 ...
chainhomelow's user avatar
3 votes
1 answer
239 views

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 ...
user84405's user avatar
2 votes
3 answers
5k views

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 ...
chainhomelow's user avatar
5 votes
3 answers
2k views

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 ...
user avatar
1 vote
0 answers
43 views

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 ...
machinery's user avatar
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1 vote
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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), ...
Mathmath's user avatar
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0 votes
1 answer
139 views

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 ...
Hugo Botha's user avatar
21 votes
2 answers
21k views

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 ...
statHacker's user avatar
12 votes
3 answers
11k views

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 (...
Fahd's user avatar
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3 votes
0 answers
651 views

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 ...
4 votes
1 answer
2k views

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/...
José Alemán Bañón's user avatar
7 votes
2 answers
512 views

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 ...
zarat's user avatar
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4 votes
2 answers
1k views

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'...
Thomas's user avatar
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3 votes
1 answer
6k views

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 ...
Mien's user avatar
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