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X Demographics
Mendeley readers
Attention Score in Context
| Title |
New Protocol for Quantitative Analysis of Brain Cortex Electroencephalographic Activity in Patients With Psychiatric Disorders
|
|---|---|
| Published in |
Frontiers in Neuroinformatics, May 2018
|
| DOI | 10.3389/fninf.2018.00027 |
| Pubmed ID | |
| Authors |
Grzegorz M. Wojcik, Jolanta Masiak, Andrzej Kawiak, Piotr Schneider, Lukasz Kwasniewicz, Nikodem Polak, Anna Gajos-Balinska |
| Abstract |
The interview is still the main and most important tool in psychiatrist's work. The neuroimaging methods such as CT or MRI are widely used in other fields of medicine, for instance neurology. However, psychiatry lacks effective quantitative methods to support of diagnosis. A novel neuroinformatic approach to help clinical patients by means of electroencephalographic technology in order to build foundations for finding neurophysiological biomarkers of psychiatric disorders is proposed. A cohort of 30 right-handed patients (21 males, 9 females) with psychiatric disorders (mainly with panic and anxiety disorder, Asperger syndrome as well as with phobic anxiety disorders, schizophrenia, bipolar affective disorder, obsessive-compulsive disorder, nonorganic hypersomnia, and moderate depressive episode) were examined using the dense array EEG amplifier in the P300 experiment. The results were compared with the control group of 30 healthy, right-handed male volunteers. The quantitative analysis of cortical activity was conducted using the sLORETA source localization algorithm. The most active Brodmann Areas were pointed out and a new quantitative observable of electrical charge flowing through the selected Brodmann Area is proposed. The precise methodology and research protocol for collecting EEG data as well as the roadmap of future investigations in this area are presented. The essential result of this study is the idea proven by the initial results of our experiments that it is possible to determine quantitatively biomarkers of particular psychiatric disorders in order to support the process of diagnosis and hopefully choose most appropriate medical treatment later. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 81 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 14 | 17% |
| Student > Master | 10 | 12% |
| Student > Bachelor | 7 | 9% |
| Student > Doctoral Student | 6 | 7% |
| Researcher | 5 | 6% |
| Other | 12 | 15% |
| Unknown | 27 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 15 | 19% |
| Medicine and Dentistry | 9 | 11% |
| Neuroscience | 5 | 6% |
| Engineering | 4 | 5% |
| Computer Science | 4 | 5% |
| Other | 14 | 17% |
| Unknown | 30 | 37% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 June 2018.
All research outputs
#18,606,163
of 23,047,237 outputs
Outputs from Frontiers in Neuroinformatics
#628
of 754 outputs
Outputs of similar age
#255,355
of 330,315 outputs
Outputs of similar age from Frontiers in Neuroinformatics
#21
of 23 outputs
Altmetric has tracked 23,047,237 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 754 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one is in the 9th percentile – i.e., 9% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 330,315 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.