1,720,964 research outputs found
Feature selection technique for time-series fMRI data of schizophrenia patients
No full textRelated Research Article: Mean deviation based identification of activated voxels from time-series fMRI data of schizophrenia patients, F1000Research.
Cite the article as "Chatterjee I. Mean deviation based identification of activated voxels from time-series fMRI data of schizophrenia patients. F1000Research 2018, 7:1615 (doi: 10.12688/f1000research.16405.1)"
Cite the software as " CHATTERJEE, INDRANATH. (2018, September 29). Feature selection technique for time-series fMRI data of schizophrenia patients (Version v1.0.0). Zenodo. http://doi.org/10.5281/zenodo.1438539 "
By: Indranath Chattterjee
Department of Computer Science, University of Delhi, Delhi-110007,
E-mail: [email protected]
Run the code in the following order:
Step 1. Run the 'script_dataload.m' locating the proper directory containing all the runs of the preprocessed time-series fMRI data.
Step 2. Run the 'intersection_union_script.m'
Step 3. If want to classify with SVM, run 'classification_SVM.m', and if with ELM then run 'classification_ELM.m'
The MAT-file named 'Contrast_AudOdd_Dev_Std_15T_2D.mat' contains the data for 34 healthy subjects (first 34) and 34 schizophrenia patients (next 34). These are the contrast maps obtained from GLM analysis of time-series fMRI data for 4 runs of Auditory-oddball task. Each row contains the 153594 voxels covering the whole brain for each subject. The 4 runs of each subject's data are averaged.
This program will fetch the time-series fMRI data of each of the 4 runs of the Auditory-oddball (AUD) task for each of the 34 healthy subjects and 34 schizophrenia patients.
This program will try to find the changes in the activation pattern within a particular voxel along its time-series with the help of mean-deviation based analysis.
Using the simple set operations, the index of the relevant brain voxels will be obtained.
This index file can be fed as input to the classifier as a feature set during building the classification model.
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GICA supported region-based feature selection technique for fMRI data.
No full textG-ICA supported region-based feature selection technique for fMRI data.
By: Indranath Chattterjee
Department of computer science, University of Delhi, Delhi-110007,
E-mail: [email protected]
Run the code in the following order:
1. Run GICA on 3 runs of SIRP task fMRI data
2. Taking mean of all the runs for each subject for each component.
3. Now we have 13 components for each of the subjects.
4. Select 116 brain regions from AAL atlas.
5. For each component,
a. Mapped the connected brain regions identified by ICA with the marked regions in the atlas.
b. From each component, take those regions of the AAL atlas map which is also present in that particular component.
c. For each region, we measured five statistical features (say a1 to a5) on the basis of voxel values of that particular region for all the subjects individually.
d. Find the FDR score for each of the five measures for each region for all the subjects.
e. Sort and arrange the FDR scores in descending order. Higher the FDR score, more important the particular measure is.
f. All the statistical measures for every region are arranged in descending order of FDR score. (5 measure*116 region = 580 features)
g. Runs the scheme in LOOCV leaving one subject for testing.
i. Iteratively add each of the features (a1 to a5) for all one by one according to descending FDR score. (Sequential forward selection)
ii. Training set and test set are built with the selected feature subset.
iii. Feature subsets are selected, if it results the high accuracy in classification task. This way the best set of features can be obtained.
iv. Check to see which region has more contribution in selection of feature subset, i.e. the more number of statistical features in a particular region.
v. Count and save those regions.
vi. Repeat the same for all 68 subjects, as LOOCV runs.
h. Check the average classification accuracy for each component and note the identified brain regions after all rounds of LOOCV classification.
6. Now check and note the brain regions occurring most often in each of the components and also check the frequency of its occurrence during 68 times LOOCV classification.
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Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
No full text“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
No full textWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Anomaly detection from time-series fMRI data of schizophrenia patients.
No full textThis is the abstract of the project was performed at the OHBM Brainhack 2018, National University of Singapore (NUS), Singapore during June 14-16, 2018
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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