| Chapter title |
Alpha Wavelet Power as a Biomarker of Antidepressant Treatment Response in Bipolar Depression
|
|---|---|
| Chapter number | 180 |
| Book title |
Influenza and Respiratory Care
|
| Published in |
Advances in experimental medicine and biology, March 2017
|
| DOI | 10.1007/5584_2016_180 |
| Pubmed ID | |
| Book ISBNs |
978-3-31-951711-7, 978-3-31-951712-4
|
| Authors |
Jernajczyk, Wojciech, Gosek, Paweł, Latka, Miroslaw, Kozlowska, Klaudia, Święcicki, Łukasz, West, Bruce J., Wojciech Jernajczyk, Paweł Gosek, Miroslaw Latka, Klaudia Kozlowska, Łukasz Święcicki, Bruce J. West |
| Abstract |
There is mounting evidence of a link between the properties of electroencephalograms (EEGs) of depressive patients and the outcome of pharmacotherapy. The goal of this study was to develop an EEG biomarker of antidepressant treatment response which would require only a single EEG measurement. We recorded resting 21-channel EEG in 17 in-patients suffering from bipolar depression in eyes-closed and eyes-open conditions. The EEG measurement was performed at the end of a short washout period which followed previous unsuccessful pharmacotherapy. We calculated the normalized wavelet power of alpha rhythm using two referential montages and an average reference montage. The difference in the normalized alpha wavelet power between 10 responders and 7 non-responders was most strongly pronounced in link mastoid montage in the eyes-closed condition. In particular, in the occipital (O1, O2, Oz) channels the wavelet power of responders was up to 84 % higher than that of non-responders. Using a novel classification algorithm we were able to correctly predict the outcome of treatment with 90 % sensitivity and 100 % specificity. The proposed biomarker requires only a single EEG measurement and consequently is intrinsically different from biomarkers which exploit the changes in prefrontal EEG induced by pharmacotherapy over a given time. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 32 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 16% |
| Student > Bachelor | 2 | 6% |
| Student > Postgraduate | 2 | 6% |
| Professor > Associate Professor | 2 | 6% |
| Student > Master | 2 | 6% |
| Other | 3 | 9% |
| Unknown | 16 | 50% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 6 | 19% |
| Physics and Astronomy | 2 | 6% |
| Biochemistry, Genetics and Molecular Biology | 1 | 3% |
| Psychology | 1 | 3% |
| Social Sciences | 1 | 3% |
| Other | 3 | 9% |
| Unknown | 18 | 56% |