| Title |
A new method of the description of the information flow in the brain structures
|
|---|---|
| Published in |
Biological Cybernetics, July 1991
|
| DOI | 10.1007/bf00198091 |
| Pubmed ID | |
| Authors |
M. J. Kaminski, K. J. Blinowska |
| Abstract |
The paper describes the method of determining direction and frequency content of the brain activity flow. The method was formulated in the framework of the AR model. The transfer function matrix was found for multichannel EEG process. Elements of this matrix, properly normalized, appeared to be good estimators of the propagation direction and spectral properties of the investigated signals. Simulation experiments have shown that the estimator proposed by us unequivocally reveals the direction of the signal flow and is able to distinguish between direct and indirect transfer of information. The method was applied to the signals recorded in the brain structures of the experimental animals and also to the human normal and epileptic EEG. The sensitivity of the method and its usefulness in the neurological and clinical applications was demonstrated. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 428 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 11 | 3% |
| Germany | 7 | 2% |
| Italy | 2 | <1% |
| Spain | 2 | <1% |
| Canada | 2 | <1% |
| United Kingdom | 2 | <1% |
| France | 1 | <1% |
| Finland | 1 | <1% |
| Netherlands | 1 | <1% |
| Other | 4 | <1% |
| Unknown | 395 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 137 | 32% |
| Researcher | 81 | 19% |
| Student > Master | 55 | 13% |
| Student > Bachelor | 27 | 6% |
| Professor > Associate Professor | 20 | 5% |
| Other | 59 | 14% |
| Unknown | 49 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 112 | 26% |
| Neuroscience | 65 | 15% |
| Computer Science | 43 | 10% |
| Agricultural and Biological Sciences | 35 | 8% |
| Medicine and Dentistry | 32 | 7% |
| Other | 48 | 11% |
| Unknown | 93 | 22% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 05 July 2023.
All research outputs
#3,525,716
of 25,998,826 outputs
Outputs from Biological Cybernetics
#48
of 686 outputs
Outputs of similar age
#985
of 16,482 outputs
Outputs of similar age from Biological Cybernetics
#1
of 8 outputs
Altmetric has tracked 25,998,826 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 686 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done particularly well, scoring higher than 92% of its peers.
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We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them