- Mahsa Abadian asked a question:Can anyone help with a problem with extracting hippocampal volume using VBM and WFU-pickatlas?
Sorry I am new to VBM and I want to compare hippocampous volume by using two different method (manual tracing and atlas-based method ) .I have two kind of samples patient with MTLE and normal ones. I used a script “ get_totals.m” by Ged Ridgway and WFU-pickatlas but the results were odd and very small. There is also an article “ Age-related changes in regional brain volume evaluated by atlas-based method “ Wataru Gonoi 2010 springer , that used nearly the same method using WFU-pickatlas and SPM5.
I checked SPM mail archive there were same titles but unfortunately I got confused there were no clear answers and now I am not sure whether this method is correct and reliable .
I would be very appreciated if anyone could help me.
- Mohamed Najimi added an answer:Does anybody introduce some publications about Male vs. Female brain's structure differents?
I'm beginning a research subject as name of "The Study of Male vs. Female Brain's Functions in Various Behaviors by Neuroimaging Techniques" and I decided keep on it to higher level of my current study. For first step, I want to know about Male vs. Female brain's structure differents. So can anybody help me by introducing publications related to it?
Please see attached files and reference
- Neurosci Biobehav Rev. Feb 2014; 39(100): 34–50. doi:10.1016/j.neubiorev.2013.12.004
- Marc Tessera added an answer:What are the advantages and what are the problems of the hypothesis about “retinoid system”?Is the hypothesis about “retinoid system” (by Professor Arnold Trehub), as described in “Consciousness and Cognition” 16 (2007) 310–330 and in the other works of Professor Trehub, a plausible hypothesis? What are its advantages and what are its problems?
Professor Trehub describes it in the following words:
“Activation of the brainʼs putative retinoid system has been proposed as the
neuronal substrate for our basic sense of being centered within a volumetric
surround –- our minimal phenomenal consciousness (Trehub 2007). Here, the
assumed properties of the self-locus within the retinoid model are shown to
explain recent experimental findings relating to the out-of-body-experience. In
addition, selective excursion of the heuristic self-locus is able to explain many
important functions of consciousness, including the effective internal
representation of a 3D space on the basis of 2D perspective depictions. Our
sense of self-agency is shown to be a natural product of the role of the heuristic self-locus in the retinoid mechanism.” (Abstract, from: Where am I? Redux.)
For the publications of Professor Trehub see:
The question has been already discussed on the folowing thread:
Thank you for your answer. It is true that you cited Ionta et al 2011 paper in your paper ″Where Am I? Redux″. Actually you cited it in the following paragraph: ″Where in the brain might the retinoid system be located? A reasonable answer is that its complex neuronal structures are connected but are distributed over several anatomical regions of the brain. Presently, our neuroscientific tools are not sufficiently powerful to answer this question with greater precision. While we may make some informed conjectures on the basis of current knowledge (e.g., Blanke et al, 2004; Ionta et al, 2011; Strehler, 1991)″.
Well, as you know, Ionta et al specifically relate autoscopic phenomena like out-of-body experiences (OBEs) to neurological lesions of the temporo-parietal junction. In your paper you write that, according to the OBEs, ″So if our sense of self-location is not necessarily anchored within the envelope of our physical body, where in the world is it anchored? The answer is that it is anchored at the origin of the egocentric space of our own natural virtual world. This virtual world exists in parts of the human cognitive brain and is constituted by the neuronal structure and dynamics of the putative retinoid system″.
According to Heydrich and Blanke (see attached their 2013 paper ″Distinct illusory own-body perceptions caused by damage to posterior insula and extra striate cortex") ″during an out-of-body experience, the patient has the subjective feeling of being awake and experiences the ‘self’ or centre of awareness, as being located outside the physical body, at a somewhat elevated level (abnormal self-location)″ and they ″suggested that out-of-body experiences occur owing to disturbed multisensory integration of bodily signals in personal (somatosensory, visual and proprioceptive) and extrapersonal space (visual and vestibular) (Blanke et al., 2004; Ionta et al., 2011)″. Actually they hypothesize that a disturbed multisensory integration of bodily signals due to specific neurological lesions leads to the conscious experience of two different bodies: the physical body and the autoscopic body (i.e., an illusory body). Their notion of an autoscopic body seems quite different from your notion of an ″egocentric space of our own natural virtual world″ which "exists in parts of the human cognitive brain″ and is ″constituted by the neuronal structure and dynamics of the putative retinoid system″.
In addition to the out-of-body experiences Heydrich and Blanke describe two other main forms of autoscopic phenomena:
- Autoscopic hallucinations;
Heydrich and Blanke ″note that most of the lesions in the patients with autoscopic hallucinations were within the occipital cortex″ and this would be the explanation why such ″damage to the occipital cortex did not interfere with self-location, self-identification or the first-person perspective″.
By contrast they ″argue that—although changes in self-location and the first-person perspective in heautoscopy are less prominent than those during out-of-body experiences—their more variable and dynamic character (and association with abnormal emotional–interoceptive signals) may be related to the sensation of bi-location that is present in heautoscopy, but absent in out-of-body experiences, the latter being characterized by a clear psychological separation between the autoscopic and the physical body″.
Actually they ″argue that heautoscopy is caused by damage to the left posterior insular cortex, leading to a disintegration of exteroceptive bodily signals (somatosensory, visual) with emotional and/or visceral corporeal signals. Such disintegration results in abnormal self-identification and heightened emotional affinity that patients with heautoscopy experience for the autoscopic body″.
Within the paradigm of your putative retinoid system how do you explain the two other main forms of autoscopic phenomena: autoscopic hallucinations and heautoscopy?Following
- Cynthia O'Rourke added an answer:Has anyone seen CLARITY tissue clearing with no electrophoresis?I just posted this in the CLARITY resource center forum, but posting it here too. We found this hydrogel perfused/embedded right hemisphere of a rat cortex to be nearly completely clear after sitting in clearing solution in 37 degree incubator for ~5 weeks completely unattended. Next to zero tissue damage and it looks by far better than any brain that we have run through our ETC chamber. Has anyone else seen this?
Please keep us updated, Gregory! We're trying the passive approach here, and I'm sure the researcher in charge of the project would love to know if the tubes need as much baby-sitting as they're giving them.Following
- Bruno Quendera added an answer:What are the currently available best systems for color calibration in the MR environment?Most systems are not MR compatible.
It's possible to measure the color conditions in bore if magnetic field is turned down (it a risky procedure rarely made in maintenance and with an high possibility of quench) in the same conditions as during experiments but without damaging the spectrophotometer.Following
- Cainositas Cainosito added an answer:What is the meaning of "synaptic puncta"?Could you tell me what does the "Synaptic puncta" mean?
Is it a synonym for synaptic surface?Following
- Wojciech Stefan Maksymowicz added an answer:Does anyone have experience with fMRI on Siemens Spectra (3T) or Siemens Aera (1.5T)?
It maybe looks like a strange question, because none of these scanners is probably your system of choice for neuroimaging research, but I would appreciate any sharing of experience.
Dear Ekaterina. In our department we use Siemens 3T MRI for fMRI. Please contact with my asistant dr Lukas Grabarczyk e-mail: firstname.lastname@example.org
- Michael H Lev added an answer:What are the best methods to compare the similarity of two medical images?When searching for a method to compare two medical images, e.g. to determine how similar they are or how much and where they differ, I came across several proposals. A simple subtraction image + width of histogram or entropy, crosscorrelation or joint histograms to name some of them. Nevertheless, I wonder if there is something like a standard method? And if not, it might be worth to discuss what could be a sensible approach.
Fully agree with Paul Hilario's answer, and would like to expand on this. Looking at the technical quality of the images only is insufficient for comparing the similarity of two different medical imaging modalities. Rather, the bottom line is, what is the CLINICAL QUESTION that you are trying to answer with the images, and HOW ACCURATE does that answer need to be for clinical management?
Clearly every different imaging modality will have different technical metrics that can quantify image noise, spatial resolution, contrast resolution, and - perhaps most useful for cross-sectional modalities such as CT and MRI - "noise power spectra".
Regardless of these metrics, however, what matters clinically is, what is the sensitivity and specificity for the detection of the known, "reference standard" pathologies that these imaging tests are being used to detect and delineate? An ROC curve analysis can be used to statistically compare the "area-under-curve" (AUC, proportional to accuracy) of the different imaging modalities, yielding a p-value. Correlation analyses can also help show the similarity between different imaging tests.
MOST IMPORTANTLY, however, although ROC curve and correlation analyses are very useful for showing the similarity (or, at least, "non-inferiority") of different imaging modalities for the detection and delineation of common pathologies in large POPULATIONS of patients for clinical trial purposes, it is the VARIABILITY of the measurements that is critical for making decisions regarding treatment/management of a given, INDIVIDUAL PATIENT. For this consideration, it is a BLAND-ALTMAN ANALYSIS that is ESSENTIAL.
For example, let's say that you have a potentially toxic chemotherapy drug for brain tumors, that is only helpful if the lesion volume is >100 ml, but that will cause unacceptably dangerous side effects for lesions <100 ml. In this case, the CLINICAL QUESTION that you are trying to answer is, "is the brain tumor > or < 100 ml?", and a reasonable "REQUIRED ACCURACY" is +/-10-15 ml, so that you don't harm patients unnecessarily but also don't deny potentially life-saving treatment unnecessarily.
Let's assume in this made-up example that T2-weighted MRI - owing to it's very high spatial and contrast resolution, with very low image noise - is the operational "reference standard", and that the two tests that we are comparing to MRI are CT and US. Now, it's entirely possible that both CT and ultrasound (US) are "non-inferior" to MRI for answering the > vs < 100 ml clinical question, based on both ROC and correlation analyses showing terrific AUC's and "R-sqr" correlation coefficients of >0.85.
Despite great AUC and correlation coefficient values AVERAGED OVER HUNDREDS OF PATIENTS, however, if the US images are "noisier" than the CT images, then for ANY GIVEN INDIVIDUAL PATIENT, CT might be useful and US may not be. Specifically, let's say that, on BLAND-ALTMAN analysis, compared to the MRI reference standard, the maximal variability in the CT measurements is +/-10-15 ml, but the maximal variability in the US measurements is +/- 20-25 ml. In this case, even though the US has a great overall linear correlation with the MRI measurements, and is sufficiently accurate on a population basis, it is UNACCEPTABLY NOISY to risk making a treatment decision for a given individual patient.
Summary/conclusion: Bland-Altman analyses of measurement variability relative to an accepted reference standard are essential for deciding if a clinical imaging modality is appropriate for making treatment / management decisions for individual patients.
- Jamie Lars Hanson added an answer:Are there many published papers using PPI (Psycho-Physiological Interaction) that more fully graph the main effect and interaction terms?Most PPI papers often report statistics of an interaction (but that seem challenging to interpret since the main effects of that brain regions aren't necessarily discussed/graphed).
Thank you for the thoughtful response! And for the paper suggestions! Since asking the question, I also found a few papers that graphed the interaction (but it still seems as though the preponderance of publications do not include such graphics, sadly).
I will check out those papers! Thanks again!Following
- Mark Charles DeLano added an answer:If you could buy any 3T human MRI right now, what would you get? Why would you choose that system?Ingenia, Achieva, Skyra, Verio, Discovery, which one is best for fMRI, for DTI, for MRS? How about a Trio with the new Tim 4G electronics? Or maybe you want a Fonar...
Though my previous post some time ago favored GE, after serious consideration I went with the Prisma. Parallel transmit reduces B1 issues, better gradients reduce distortions on EPI and should give better echo spacing on everything, better coils facilitate better acceleration factors, and better software/multi-band and zoom it for our DTI/DSI and fMRI work tipped the scales. The scanner is impressively quiet. We go live clinically soon--ran into a snag with a flood in the room of the new building it is going into. The 64 channel head coil is 40 head/24 neck elements and there are 12 anterior and 12 posterior elements. Haven't had the opportunity to use it and will repost after a bit of experience.Following
- Vigneswaran Veeramuthu added an answer:Negative correlation between fractional anisotropy and neuropsychological performance scores at admission for patients with mild TBI - any thoughts?
Literatures are generally equivocal about negative correlation found in diffusion tensor imaging (DTI) of mTBI patients, especially when the inverse correlations are found at the initial admission DTI and neuropsychological testing. Some associate the negative correlation with cytotoxic edema (thus the increased FA vs poorer neurocognitive performance). How do you justify both positive correlation and negative correlation with poorer cognitive performance at admission?
Thank you so much for your suggestions Dorian Pustina. I will definitely take your suggestion into account. Truly appreciate your kind gesture in lending your expertise in this area.Following
- Silvia Alemany added an answer:Does anybody know about any study relating olfactory cortex volume or function and childhood maltreatment?Croy and colleagues (2010; see attached) mentioned "Due to the reported volume
reduction and functional peculiarities in parts of the central
olfactory processing system in patients with child maltreatment and PTSD we
expected an altered activation, as detected by fMRI, in these areas
in response to olfactory stimuli"; however I have not yet found any neuroimaging study specificcally linking olfactory cortex to exposure to early stress.
Thank you very much for your responses! :)
- Danilo Maziero added an answer:Does anyone have experience with ICA using BV?I scanned 20 subjects during 6 min resting state. now, I would like to apply ICA (using BV). I know that in FSL one can calculate the optimal number of components (for each subjects). Can BV do the same? I tried to use 30 components to all subjects, however looking at the "networks", I think I should use different number of components to each subjects.Well, I have been working with ICA in BV for a while, basically in epilepsy patients data, always doing individual analysis. In epilepsy patients data I had found from 25 to 200 components (a lot of noise, motion and also RSN split in different components).
You are right, even for health subjects we can have a large range of components to be found (from 20 to 60).
There are some strategies for estimating the "ideal" number of ICs to be found, one of them is the RAICAR (Ranking and Averaging Independent Component Analysis by Reproducibility).
Particularly, I have always applied the PCA from FSL and them used that number in BV (It sounds not usual to apply FSL at the beginning and then BV, but I have always preferred to see my results in BV, once we have the license).
I hope this is helpful
- Erik A. Martens added an answer:Has anyone tried the new CLARITY technique out of the Deisseroth lab in Stanford?We are about to get the necessary materials to do CLARITY with rat brains, and wonder if anyone else here has given it a shot. I figured this might be a good place to share any pitfalls we might come across, etc. I don't anticipate any problems at the moment, as the protocol is very clear and detailed. Very excited to be trying CLARITY out.
Here is a link to the CLARITY protocol: http://clarityresourcecenter.org/
Chung, K., J. Wallace, S.-Y. Kim, S. Kalyanasundaram, A. S. Andalman, T. J. Davidson, J. J. Mirzabekov, K. A. Zalocusky, J. Mattis, A. K. Denisin, S. Pak, H. Bernstein, C. Ramakrishnan, L. Grosenick, V. Gradinaru, and K. Deisseroth. 2013. Structural and molecular interrogation of intact biological systems. Nature advance online publication (April). http://www.nature.com/nature/journal/vaop/ncurrent/full/nature12107.htmlMost clarification methods such as Clarity, seeDB, Scale, are preceeded by an incubation period in 4% PFA of the sample before it is clarified. The length of incubation is typically 12h - can longer incubation times impact the clarification so it fails?Following
- Valia Rodriguez added an answer:Can anyone advise me in search of software for EEG sources?I'm doing source analysis. Does anyone know a software for source analysis like FD VARETA?Look in here http://www.uzh.ch/keyinst/loreta.htmFollowing
- Umeo Ito added an answer:Is there an international need for manual structural volume analysis in MRI studies?In my research I have analysed structural volumes in MRI scans by manual tracing measures and correlated against automated measures, with particular interest in subcortical grey matter structures. As I am still a student it is interesting to gauge the overall need for the skill in the international community, either as a diagnostic tool or as an inter-rater reliability measure.For neurosurgical use, the manual segmentation is too time consuming prior to emergency operation. Practically, estimation of the size of lesions seeing the three horizontal, coronal and sagittal view is sufficient. For animal experiment, planimetry of HE stained sections of constant thickness enlarged on the papers by CP scanner is more practical.Following
- Asaid Khateb added an answer:Can someone suggest a good, short duration fMRI activation task?I am looking for a good fMRI task which shows strong activation, but is approximately 6 minutes or less in duration. This task is to be used with older people. A memory paradigm would be preferable, but suggestions for attentional tasks would also be helpful.The semantic categorization task we developed in Geneva for pre surgical purposes is a good, short (4 minutes duration) and reliable, easy to perform by old people. It had been used in more than 100 patients including epilepsy, aphasia , tumors etc..
1. Seghier M, Lazeyras F, Momjian S, Annoni J-M, de Tribolet N, Khateb A. Language representation in a patient with a dominant right hemisphere: fMRI evidence for an intrahemispheric reorganisation. NeuroReport 2001;12:2785-2790.
2. Khateb A, Martory MD, Annoni JM, Lazeyras F, de Tribolet N, Pegna AJ, Mayer E, Michel CM, Seghier ML. Transient crossed aphasia evidenced by functional brain imagery. Neuroreport 2004;15:785-790.
4. Seghier ML, Lazeyras F, Pegna AJ, Annoni JM, Zimine I, Mayer E, Michel CM, Khateb A. Variability of fMRI activation during a phonological and semantic language task in healthy subjects. Hum Brain Mapp 2004;23:140-155.
5. Seghier ML, Lazeyras F, Pegna AJ, Annoni JM, Khateb A. Group analysis and the subject factor in functional magnetic resonance imaging: Analysis of fifty right-handed healthy subjects in a semantic language task. Hum Brain Mapp 2008;29:461-477.Following
- Brian A Gordon added an answer:Does anyone have an opinion about the use of nuisance covariate regression in fMRI local connectivity measures?Nuisance covariate regression (head motion, CSF and WM signal, global signal) in local connectivity measures (like Regional Homogeneity (ReHo), Amplitude of Low Frequency Fluctuations (ALFF and fALFF), Degree Centrality and Voxel-Mirrored Homotopic Connectivity (VMHC)) is still a matter of debate. What is your opinion? Is nuisance regression more effective before or after bandpass filtering?There is some merit in throwing out volumes with high motion rather than simply regressing out motion covariates. There have been a number of papers on this topic lately. Here are just a couple.
As far as regressing the global signal, most lab tends towards removing it. This article is worth a read on that topic.
- Matthew B Wall added an answer:Can the suprachiasmatic nucleus be a 'seed region' in a resting state fMRI investigation?We are designing a neuroimaging study to test hypothesised circadian moderation of reward function in humans. Seems like our hypothesis is best tested using resting state methods, ideally with the hypothalamic suprachiasmatic nucleus as a 'seed region' to investigate correlations with brain reward centres (particularly ventral striatum).
I understand that small, deep brain centres are difficult to image.No problem, and best of luck with the project, it sounds really interesting.
- Mohamed Alji asked a question:What is the form and the meaning of blobby-shaped brain tumor?I am confronted with the word "blobby-shaped" brain tumor. Is it the opposite of simple-shaped brain tumor? Does it mean the tumor is an aggressive one? Or that the tumor has sharp boundaries?
Can someone provide a picture of a typical blobby-shaped brain tumor?
- Humera Tariq added an answer:Does anyone have any suggestions for brain MR image segmentation?I used T1 weighted brain MR images with 3mm slice thickness, 3% noise, and 40% intensity non-uniformity for segmentation into white matter, gray matter and CSF. Can I use Brain Web Discrete or fuzzy anatomical model as a gold standard? Why or why not? What is the best choice to compare different segmentation algorithms otherwise?Alan many thanks for the reference. I am almost doing the same but using region based segmentation techniques. I think i can use your Discrete reference data to compare my algorithm segmentation result for gm and wm comparison?? I further need clarification on two points:
1) The starting and end axial slices seems entirely different do we loop through all slices in processing or consider only middle slices say z = 20 to z =30???
2) MRI data is stored in 3 dimensions. Then loop through only in one direction i.e Z gives us our desired gm and wm count /fraction. There is no need to do it for two other dimensions. Am I right???Following
- Nicholas Fallon added an answer:Which MNI coordinates belong to the anterior insula?I'm currently working on my thesis using sLORETA. My region of interest is the anterior insula but unfortunately I'm unable to find a summary of all MNI coordinates that belong to it. Any help is much appreciated.Hi Daniel, perhaps you would find the following articles which discuss parcellation of the insula cortex useful:
Functional connectivity of the insula in the resting brain
Franco Caudaa, Federico D'Agataa, Katiuscia Saccoa,Sergio Ducaa, Giuliano miniania, Alessandro Vercellid
NeuroImage, Volume 55, Issue 1, 1 March 2011, Pages 8–23
or this subsequent meta-analysis:
Meta-analytic clustering of the insular cortex: characterizing the meta-analytic connectivity of the insula when involved in active tasks.
Cauda F, Costa T, Torta DM, Sacco K, D'Agata F, Duca S, Geminiani G, Fox PT, Vercelli A.
Neuroimage. 2012 Aug 1;62(1):343-55. doi: 10.1016/j.neuroimage.2012.04.012. Epub 2012 Apr 14.
Best of luckFollowing
- Wei Wang asked a question:Does anyone have experience in the analyze of dSTORM super-resolution imaging with Ripley's K function?For my project, I performed dSTORM super-resolution microscope imaging for my interesting protein in axonal growth cone with F-actin and tubulin. I saw some literature using Ripley's K function analysis to analyze whether the two clusters relationship follow a particular model. I am wondering if anyone has worked on this or has created a formatted routine in matlab to test this directly?Following
- Janak Gaire added an answer:What is the mechanism for Fluoro-Jade staining and what does it bind to?Fluoro-Jade staining is used for staining degenerating neurons. What stages of dying neurons does it bind to?Thanks Roxana and Lakshmi for sharing the papers.Following
- Kenneth Sung Lai Yuen added an answer:What 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?Yes, fMRI analyse time series data. The conventional approach is to apply general linear modelling to all voxel time series and check which voxel(s) have a significant correlation with the contrast-of-interest. This approach is univariate in nature, i.e. the analysis is performed on voxel-by-voxel basis.
However, there is a new trend to consider signals from multiple voxels as a pattern and feed them into machine learning algorithms. Using machine learning algorithms on fMRI BOLD or EEG/EMG signals is a very new and active field in the imaging community. People had successfully made classification for clinical diagnosis, predict active brain states using activation paradigm (brain decoding), and even develop brain-machine interface with real-time fMRI.
Just a few seminal papers you probably would interested in:
Soon, C.S., Brass, M., Heinze, H.J.& Haynes, J.D. (2008). Unconscious determinants of free decisions in the human brain. Nature Neuroscience 11, 543-5.
Reconstructing Visual Experiences From Brain Activity Evoked by Natural Movies
Shinji Nishimoto, An T. Vu, Thomas Naselaris, Yuval Benjamini, Bin Yu & Jack L. Gallant (Current Biology 2011)Following
- Stefan Bauer added an answer:Is anyone interested in MRI Brain Tumor Segmentation Tool?Anybody interested in a simple tool for automated brain tumor segmentation from multimodal MRI images, please check out our BraTumIA (Brain Tumor Image Analysis) software. It can be downloaded from http://www.istb.unibe.ch/content/research/medical_image_analysis/software/index_eng.htmlsorry, unfortunately I have no time at the moment for supporting different OSFollowing
- Thomas Schmidt added an answer:Overwriting the neural processing of subliminally presented stimuli with the processing of the following mask?We think about the optimal presentation time of the mask and wonder whether the neural processing might be overwritten with the processing of the mask when we choose a long presentation time. Has someone got experience with that or is aware of any publications? ThanksThe overwriting idea is too simple. Once a stimulus signal is in the system, it can go down multiple paths, and a subsequent mask signal will not catch up with it. This is probably the mechanism behind masked priming and the reason why primed motor activation can be independent of masking (Vorberg et al., 2003). But overwriting is still possible in the sense that the mask can replace the original stimulus in visual awareness, e.g., by interrupting recursive processing (see TMS studies of V1 stimulation). In addition, the mask is a new bottom-up signal that starts being processed in its own right. However, the popular old idea that the mask can "stop" processing of the masked stimulus is certainly wrong, because by the time the mask arrives at V1 the original signal can already be processed elsewhere.Following
- André Barreto Vianna added an answer:Does neuroinflammation and neurodegeneration induced by continuous infusion (intracerebroventricular) of LPS occur in all CNS neurons?Does neuroinflammation and neurodegeneration induced by continuous infusion (intracerebroventricular) of LPS occur in all CNS neurons or only in specific regions? The literature is rich in research about the hippocampus, but not on other regions. I have special interest in the hypothalamus.Dear Frank,
Thank you for the article, it is great.
I'm interested to know how neurons in the hypothalamus will react with and without administration of drugs with anti-inflammatory potential. But for this, I need to know how the hypothalamus will react to this model of inflammation (continuous infusion of LPS).
Soon as I have some answer, I'll tell you more!
- Michele Sessolo asked a question:How to load astrocytes in vivo without bulk loading?Anyone know how to load astrocytes in vivo with SR101 without using bulk loading?Following
- Lieven Gevaert added an answer:How are neuron activities strongly involved in using medical image analysis in order to detect and also to treat Lung Cancer in HIV+ patients?Strong correlations of lung cancer in most HIV+ patients have been attracting my intention to research more in reference to medical image analysis currently, instead of spiritual computing in the past.
My current question is, if we talk about breathing and immunity toward lung cancer and HIV+ treatment, how are strong relationships of neuron activities strongly involved in using medical image analysis in order to detect and also to treat Lung Cancer in HIV+ patients?malignant lymphoma and Kaposi sarcoma are significant complications of human immunodeficiency virus (HIV) infection