- Yves Matanga added an answer:6What are the main challenges in brain fMRI analysis?When we analyze the fMRI signal how do we combine it with MRI. What are the big challenges? Is it noise, big data, what is the interdisciplinary between neuroscience and machine learning?
I believe Martín Martínez Villar mentioned a very important information regarding hemodynamic response (fmRI) which I read about concerning how they correlate with brain activity.
May be you can do extra reading on it as well.
- Lasse Bang added an answer:5How to properly weight contrasts in SPM?
Hi all,Say you are modelling a task using a first-level model in SPM. The task consists of three conditions: congruent, incongruent, and control. When setting up the contrasts for this model, how would one properly weight the conditions for the following contrast: [congruent + incongruent] > control? Would this be 0.5 0.5 -1? On a related note, would the contrast [congruent + incongruent] > baseline be 0.5 0.5 0, or 1 1 0? I am confused as I've read that positive (and negative) contrasts should sum to 1, but I've seen people use contrasts such as 1 1 0 0 etc. for certain contrasts, which obviously do not sum to 1. Any input appreciated!
Thank you Niv for raising this point!
I omitted some details in the original post for simplification, as my question was a general one regarding contrast weights. Actually I am interested in between-group differences in my study (i.e. patients vs. controls). I am mainly interested in investigating between-group differences on the Incongruent > Congruent contrast.
Prior studies using a similar task paradigm have also compared groups on the [Incongruent + Congruent] > baseline, so I thought that I would do the same (to be able to compare my results with these studies). But you do raise an important point regarding the use of such contrasts; i.e. one would be unable to know if any significant between-group effects was mainly due to incongruent or congruent trials. I guess this could be clarified by extracting % signal change or raw beta weights from any sig clusters.Following
- Vladimir A. Kulchitsky added an answer:7Does anyone know of good research linking (right) angular gyrus activity with theory of mind tasks?
I am looking for neuroimaging or neurostimulation research on the right angular gyrus, especially in regards to theory of mind tasks.
Thank you, glad that it is necessary for the proposed work.Following
- Robert Turner added an answer:3Are there Publicly available MRI databases with T1, T2, T1 fat suppressed, and T2 fat suppressed with 1 mm resolution?
I have looked at datasets such as the Human Connectome Project and ADNI, which have T1 and T2 weighted MRI images but I would also like to have fat suppressed images. I am looking for resolution of at least 1.5 mm and similar distances between slices. Anyone know of a database with these specifications?
You might find the following paper useful: Tardif CL, Schäfer A, Trampel R, Villringer A, Turner R, Bazin PL. Open Science CBS Neuroimaging Repository: Sharing ultra-high-field MR images of the brain. Neuroimage. 2015 Aug 25. pii: S1053-8119(15)00761-2. doi: 10.1016/j.neuroimage.2015.08.042. [Epub ahead of print]
This provides links to down-loadable very high quality high resolution (0.5 mm isotropic) quantitative images of the parameters T1 and T2* acquired at 7T. As a basis for human brain systems neuroscience, these are the best available anywhere.Following
- Gila Behzadi added an answer:5How to identify cortical layer boundaries in live brain slice?
I am struggling to find cortical layer boundaries in mouse brain slice under differential interference contrast microscope. I typically use 400 um thick brain slice for my electrophysiology recording. Under 40x lens I kind of can see that the upper layers have smaller soma size and the soma is dense and in layer 5 the soma is bigger and sparse compared to upper layers.
The best image I can find online is this one in somatosensory cortex (http://jn.physiology.org/content/92/4/2185), in which mouse barrels in layer 4 can be easily identified.
Could anyone give me some links of good examples for identifying cortical boundaries in live brain slice?
Thank you in advance!
According to Paxinos & Watson atlas:
Barrel cortex: 2.3 mm posterior to Bregma,Lat 4 mm, V 1.5-1.8 from cortical surface (layer 4)
Motor cortex: 1.7-2 mm rostral to Bregma, Lat 1.5-1.8 mm, V 1.7 from cortical surface (layer 5)Following
- Sergiu Groppa added an answer:3What do negative t values in fMRI results indicate? What clinical significance might this info provide?
My thinking is that when we usually use fMRI to assess BOLD signal activation in response to a task to check for which regions are activated, positive BOLD signal indicates flow of blood oxygen to a particular brain region. We then proceed with the t test to compare means of activation in control and in rest and establish a threshold (say 3.40) that considers voxels greater than that active.
I have data with some small negative t values (0 to -3.40) and a few negative t-values less than -3.40 (ex: -4.00). What would such a -4.00 t-value indicate? Does it indicate decreased BOLD decrease to a particular region from control to a task? Or does it have some other significance?Following
- Muhammad Yousefnezhad added an answer:4What is different between AFNI and SPM?
I want to know what is different between AFNI and SPM? Would you please tell me the pros and cons of each of them? And describe the applications of them?
I want to say thank you in advance for your kind support.
Thanks very much for your full description.Following
- Manuel Dujovny added an answer:4Does anybody know any software which can convert pictures from MHA format to NIFTI or DCM format?
Does anybody know any software which can convert pictures from MHA format to NIFTI or DCM format?
check out this link below, it might be a help
- Andreas Haslbeck added an answer:3Any advice on dealing with eye tracking logging asynchrony?
Has anyone had problems of synchrony between an eye-tracking system and the stimulus delivery software sending log messages to the eye-tracking system logs? And if so, what the possible sources of the problem could be, how to avoid the problem, and how to deal with it?
We have an MR-compatible eye tracker from MR Technologies hooked onto Arrington Research's ViewPoint EyeTracker software on one PC. On a different but connected PC, Neurobehavioral Systems Presentation software controls stimulus delivery. I have Presentation communicate to the eye tracking software's logs when my video stimulus starts and ends because I was told it was more reliable to manually start the eye tracking system rather than trying to control it through commands triggered from Presentation. As far as I understand, the eye-tracking system logs a line of data every 33ms even when there's tracking loss. I expect that I should have the same number of eye-tracking data lines between my video log markers -- so if my videos are 33 fps, I assume I should have the same number of eye data points as frames for a given video -- is that correct?
However, the eye-tracking data corresponding to a video is on the order of up to 3 seconds (1-80 data points) longer than the video. For example, for a random video and according to the Presentation log files for some random 2 subjects:
video X: 102 frames (25fps) = 4.1 sec length of video (according to Presentation log files and video)
sub1: 182 lines eye data @ 30fps = 6 sec of data marked as recorded during the length of video
sub2: 166 lines eye data @ 30fps = 5.5 sec
I am very hesitant to assume that the "video start" log marker I had Presentation send to the eye-tracker system log files really corresponds to when the video started (and then take only as much eye data as video length, ignoring the "video end" log marker -- or could this be a safe assumption?
Thanks in advance for any help and explanations!
To add some comments to David’s answer:
- Some laptops (connected to eye-trackers) deliver different recording rates depending on their power supply: quite stable and high rate when connected to a regular power supply, but reduce their performance for very short intervals when using the battery – even when manufacturers say that this won’t happen.
- The same might be an issue concerning Ethernet communication.
- Sometimes there are background programs running und consuming the CPU’s performance (every time other programs consume too much performance, recording programs skip single frames)
- Sometimes programs do not immediately start when you start them.Following
- Md. Asadur Rahman added an answer:26Better than EEG?Does anyone know of any low-cost methods for non-invasively monitoring brain function, but with yielding more information, more robustly than EEG?
I think we should not compare EEG and fNIR. As far I know we do not study fNIR a lot. Human society has to wait some more years to understand fNIR completely.Following
- Dirk Ulbricht added an answer:8Is there any research into how often short term memory is the first sign of Alzheimers?
I have just started researching about brain imaging techniques for early Alzheimer's Disease - something I know little about at present. It is often stated that short term memory is the first area that is affected for the patient. However, is there any research into how often this is actually the case, and how often it isn't? I haven't come across any so far in the literature I read. It is just often stated that it is the first sign, but I want something more substantive than that.
Short term memory from an imaging point of view, can be assessed by monitoring changes to the hippocampus. I am therefore investigating the existing techniques, and also seeing whether or not they can be improved on in anyway using my experience of imaging for other neurological conditions.
Short-term memory is one way to say things, others would be working memory, etc. I am not aware of any good epidemiological work addressing this issue in AD. But some informations may be found in the vast literature on mild cognitive impairment, where AD seems to result mostly from amnestic MCI. The trouble is that there are most likely other symptoms such as apathy, anxiety, which may precede MCI or AD, which resembles the non-motor-signs of Parkinson's. In Neuropathology, the first area to be affected is Area 28 (entorhinal cortex). This has been described by Heiko Braak end of the 80s, and recently updated to pre symptomatic AD in a review published in Brain.Following
- Nik Murphy added an answer:7How can I follow up interactions in EEG analysis: mixed opinion on the need for correcting multiple comparisons?
My question is about whether there is an established procedure for investigating interactions in EEG analysis.
Some papers seem to correct for multiple comparisons and others do not, so I am wondering if there is an agreed perspective as to when correction is needed. To use a relatively simple example, if I have a 3 way interaction between Factor 1 (three levels), Hemisphere (Left, Right) and Region (Anterior, Central, Posterior), I would investigate this by doing a single-comparison between the levels of Factor 1 in each combination of the Hemisphere*Region interaction.
But I have seen different approaches used to achieve this: One approach would be to take a subset of each site (i.e., Left-Anterior, Right-Central etc.) and do a one-way anova to investigate the effect of Factor 1 at each of these sites, then run (uncorrected) contrasts to investigate which levels of Factor 1 differ. The argument here is that the uncorrected follow-ups are licensed by effects/interactions in the preceding interactions.
Alternatively, a much stricter approach is to run corrected t-tests (e.g., Bonferroni) at every possible combination of Factor1*Region*Hemisphere (which by most methods in R/SPSS includes correcting for comparisons I am not interested in (e.g., Level 1-Anterior-Left vs. Level3-Posterior-Right and thus produces very strict p-values). So I am interested in what EEG experts would do and precisely when (and to which single comparisons) they would apply a correction procedure – if any?
It may seem like a simple question, but it is one for which there seems to be very mixed approaches across the many papers I have read.
Interesting. Correction for multiple comparisons is always a good idea with repeated measures contrasts.
I'm a bit confused when you mention p600 and LAN. Are you comparing these in the same anova, and if so why? But I won't delve into this without knowing fully how your comparisons are set up.
if you already know where your effect is localised to (e.g you have a strict region that shows the P600) , and above you say parietal kind of sites, then remember the physiology of EEG here. These electrodes will all likely pick up the same activity, so you could feasibly take the regional average. You'll boost your power massively by reducing the number of levels in the anova. Additionally, if you're hypothesis is to see effects on the left then maybe you could exclude the right hemisphere for now?
Or, as above you could be more exploratory and use fieldtip or the massunivariate toolbox to perform non-parametric clusterbased permutations. However, beware that this might pick up on elements of the signal that are more difficult to explain (not necessarily the peaks).
Alternatively, you could reduce things down even further. Try running ICA on the datasets and then clustering the components. This might reduce down the dataset to a level that could be compared in a much simpler model (e.g 1 component, 2 conditions).
I might have gotten a bit carried away here (or missed the point), but I agree with all of above posts - keep it simple. My input would be don't go chasing significance, and be conservative with your tests. Also, remember to compute appropriate effect sizes and confidence intervals, as these will tell you much more about your effects/interactions than a p value will - regardless of how many corrections, and levels, you have in your model.
If you're really stuck then try running all possible models and see what changes between them. You might surprise yourself.Following
- Julieta Campi added an answer:10Has anyone ever imaged calcium in brain slices (cortex or hippocampus) while perfusing glutamate?
I am trying to image Calcium with a two-photon microscope in slices from mice injected with a virus to express GCaMP6. The expression is good and I can see activity when I electrically stimulate the slice. When I perfuse Glutamate (100 uM in acsf), I see no activity at all. Does anyone know what could be the problem? I was expecting to see a lot of activity!
Thanks in advance.
Thank you so much to all of you. In the end I tried puffing a much more concentrated Glutamate solution (1 mM) and I saw a lot of activity. Luckily, that was enough for my control. Thank you very much for taking the time to try to help me. It is really appreciated.
- Ali Hasan added an answer:6How can I get free MRI brain dataset?
I am wondering about how to get Free dataset of MRI brain scans and there are many sites provide dataset but in muv format. could tell me what is this format I have not find the appropriate software for this format
Many thanks for your comments
- Ion C. Andronache added an answer:3How can I calculate the amount of synaptic contacts (fluorescence images, 2 channels, z-stacks)?
Hello, I need to quantify the amount of possible synaptic contacts between neurons in 2 different channels. I've been reconstructing the 3D images with Fiji/ImageJ (simple neurite tracer plug-in) but I couldn't find a way to quantify the contacts (other than manually).
Do you have any suggestions?
Thank you in advance
You can use SynapCountJ. I send you plugin and user guide, too. Unrar archive and put folder in plugin's folder from ImageJ. At me works.
- Sébastien Scannella added an answer:1Who knows a way to plot conjunction map results of sLORETA ?
I'd like to plot two different sLORETA files (t-values maps) on a same template as two overlays to highlight the conjunction areas like in MRIcron with t-maps from SPM.
I spent a lot of time unsucessfuly trying to find a way to convert sLORETA files into a neuroimaging format that MRIcron would be able to load as an overlay.
Thanks a lot for your help.
Finally found a way to do it, in sLORETA software...
In the slice viewer, one can simply save the results in .nifti format (many options) and use it as an overlay in Mricon on any template. The normalization is perfect!Following
- Hamidreza Farhidzadeh asked a question:OpenIs there anyway to make mask by DICOM-RT file for a sequence of slices?
Hi, I want to make mask by using dicomRT file for a sequence of MRIs. Is the any way to do that?
- Monika Pawłowska added an answer:11What is the best technique for clearing the brain while preserving endogenously expressed GFP?
I have looked at CLARITY, SeeDB, 3DISCO, in the literature and they almost always require immunolabeling. Which technique preserves GFP (or YFP) the best, without additional immuno?
Thank you for quick answers! Perhaps we should try RIMS too. Another person in my lab does immunostaining of slices after CUBIC, but we aim at thicker samples that are probably too thick for immuno.
Mario: we've used glycerol already, but not the way you describe it, thanks for the link!Following
- Jean-Pierre Thibaut added an answer:1Does anyone have data on both features and exemplars of a concept combination and its constituents?
Does anyone happen to have (or know of) data on both features and exemplars for a particular concept combination and also for its two constituents? (e.g. feature and exemplar data on PET, feature and exemplar data on FISH, and feature and exemplar data on PET FISH?) There is lots of partial data but we are looking for a complete data set of this kind.
Many thanks in advance.
James Hampton (City university of London) has done a lot on the conceptual combination issue.
Or Geert Storms in Leuven Belgium. I think that Geert has some norms on this. It sounds familiar.Following
- Christos Papantoniou added an answer:4Is there a way to in vivo visualize the formation of a memory?
I was wondering if there was a way to "see" the activation of all the neurons needed to form a new memory in vivo. For example, to begin from the hippocampus and end to the cortical areas in which the memory would be stored.
Thanks a lot Kees!Following
- Matthias Preusser added an answer:3Neuroimaging immunotherapy responses: what are your ideas on utilizing imaging techniques to track GBM response to immunotherapy?
I am interested in developing methods that would be clinically relevant for imaging responses to immunotherapy for GBM. Any thoughts?
We have a paragraph on this topic in a recent review: http://rdcu.be/dEITFollowing
- Meghan O'Sullivan added an answer:3Can anyone please explain why I might be finding FWE significant and not FDR in a ROI analysis?
I am currently analyzing SPM results from a sample of 175. However, when investigating between group associations, I noticed that one of my results were significant for FWE-corrections, and not for FDR-corrections during ROI analysis. As I understand it, FDR corrections are more liberal, while FWE corrections are generally more conservative, so I cannot make sense of this finding- any ideas?
I am referring to peak-level inferences. And for the ROI analysis, an explicit mask was applied at batch-level... so yes, in a way this is a correction, but in order to report significance, I understand that I need to report the p-value using either FWE or FDR correction (selected from the output of whole brain analysis).
I hope this makes sense. Many thanksFollowing
- Rakesh Pandey added an answer:9Can anyone provide details of SynAmps 2 EEG amplifier with Curry Scan 7 Neuroimaging Suite?
Esteemed RG members
For a collaborative research project I wish to use SynAmps 2 64 channel EEG amplifier as the same device is proposed to be used at UK site of the project. For this amplifier the Compumedics suggest Curry Scan 7 neuroimaging suite and for ERP Stim2. My queries are:
1. Is the said EEG system better of comparable to Biosemi Active-2 system?
2. If I prefer to use SynAmps (to have parity in the equipment with other collborators) then can I use some open source /free software for data acquisition and analysis or I will have to use their proposed software?
3. There are different licenses for Curry 7. Can EEG and ERP studies be performed by the "acquisition and processing" license?
4. What are the advantages of going for the license of "Basic, Advanced source and image analysis"?
5.. For ERP studies they suggest Stim2 (stimulus presentation software). Can I use SuperLab or DirectRT or e-prime for the same?
I am not well versed with EEG systems and EEG studies and thus a more detailed suggestion with helpful links will be of much help to me.
With best regards
Thanks Ross and Rodolfo for your clear and comprehensive answers to my queries and helpful suggestions. From your replies it is apparent that Synamps2 will be very useful and helpful for my studies.Following
- Juergen Ralf Schlaier added an answer:5Is it really necessary to run two complete acquisitions with opposing polarities of the phase-encode blips with FSL TOPUP?
Or is there any way to apply TOPUP with one complete acquisition (64 read-out directions) and only one anti-parallel B0 Volume to estimate the magnetic field and use "applytopup"?
I came as far as to create the two files (which look quite good in fslview):
But when I apply:
"applytopup --imain=blip_up,blip_down --inindex=1,2 --datatin=my_acq_param.txt --topup=my_topup_results --out=my_hifi_images"
the program tells me (understandably) that the two sets are mismatched and I get no results. Since I only have the 4D data set of the "blip_up" acquisition and one anti-parallel B0 volume, is there any way around that problem? If there is, how would I have to change the command line to obtain unwarped images of "blip_up" ?
Hi, it´s me again.
I have talked to our IT specialist,who would be really grateful if we could have parts of the script for your pipeline. That would make his and my life a lot easier. If it is more convenient for you to send it to me directly, this is my email account: email@example.com
Thank you again very muchFollowing
- Andy Yeung added an answer:3Why such a huge difference between different VBM8 methods and which one should be selected?
I have been using VBM8 in SPM12 for a few months now for volumetric analysis of the human Hippocampus, between two different groups. I'm completely aware that depending of the kind of modulation you apply to your data (affine vs non-linear) the different results you get. But in terms of correctness I didn't expect such a huge difference. Using the prior one (affine) and literately following the VBM8 manual I achieve very strange results being quite contradictory in comparison to the last named procedure. The major set-up difference between those two is the affine vs the non-linear selection and using the head size as covariate only for the affine method.
I have been thinking the possibility that this huge difference could be due to my contrast matrix being [-1 1 0 0 0] vs [-1 1 0 0] for the affine and non-linear method respectively. But it looks to be right for the two sample test as I have two groups and three covariates (age, head size (only for the affine) and HAMD.
I would appreciate if any of you could make this clear to me.
Thank you in advance!
Best regards; Cecilio.
As VBM8 Manual states: Affine+non-linear allows comparison of the absolute amount of tissue, while Non-linear only allows comparison of the absolute amount of tissue corrected for individual brain sizes. Do the two groups of subjects have significantly different average brain sizes? If so, the outcome measurement may differ 'hugely'.
- Basar Bilgic added an answer:2Is there any international network (just like DIAN) targeting asymptomatic progranulin and tau mutation carriers?
Neuroimaging including resting state fMRI.
Thank you for the answer.Following
- Zhiqiang Zhang added an answer:3Can anyone suggest how to set a maximum pixel cluster size as a threshold in REST toolbox for RS fMRI seed based analysis?
Resting state fMRI - detection DMN with seed in hippocampus:
I would like to set a maximum pixel cluster size as threshold to compare seed based analysis results of data sets made on different scanners and with different head coils. This is not possible with the REST toolbox. Any other suggestions? Thanks in advance.
Multiple correction for result representation?
AlphaSim correction can be done on toolkit of REST: Utility-->REST AlphaSIM, which is not dependent on what's the analysis you done. seed-based FC, ALFF, task-state activation or else.... why emphaaaaasize RS fMRI seed based analysis?Following