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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Discriminating unipolar and bipolar depression by means of fMRI and pattern classification: a pilot study
|
|---|---|
| Published in |
European Archives of Psychiatry and Clinical Neuroscience, May 2012
|
| DOI | 10.1007/s00406-012-0329-4 |
| Pubmed ID | |
| Authors |
Dominik Grotegerd, Thomas Suslow, Jochen Bauer, Patricia Ohrmann, Volker Arolt, Anja Stuhrmann, Walter Heindel, Harald Kugel, Udo Dannlowski |
| Abstract |
Bipolar disorders rank among the most debilitating psychiatric diseases. Bipolar depression is often misdiagnosed as unipolar depression, leading to suboptimal therapy and poor outcomes. Discriminating unipolar and bipolar depression at earlier stages of illness could therefore help to facilitate efficient and specific treatment. In the present study, the neurobiological underpinnings of emotion processing were investigated in a sample of unipolar and bipolar depressed patients matched for age, gender, and depression severity by means of fMRI. A pattern-classification approach was employed to discriminate the two samples. The pattern classification yielded up to 90 % accuracy rates discriminating the two groups. According to the feature weights of the multivariate maps, medial prefrontal and orbitofrontal regions contributed to classifications specific to unipolar depression, whereas stronger feature weights in dorsolateral prefrontal areas contribute to classifications as bipolar. Strong feature weights were observed in the amygdala for the negative faces condition, which were specific to unipolar depression, whereas higher amygdala features weights during the positive faces condition were observed, specific to bipolar subjects. Standard univariate fMRI analysis supports an interpretation, where this might be related to a higher responsiveness, by yielding a significant emotion × group interaction within the bilateral amygdala. We conclude that pattern-classification techniques could be a promising tool to classify acutely depressed subjects as unipolar or bipolar. However, since the present approach deals with small sample sizes, it should be considered as a proof-of-concept study. Hence, results have to be confirmed in larger samples preferably of unmedicated subjects. |
X Demographics
The data shown below were collected from the profiles of 11 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 5 | 45% |
| United States | 1 | 9% |
| Unknown | 5 | 45% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 10 | 91% |
| Practitioners (doctors, other healthcare professionals) | 1 | 9% |
Mendeley readers
The data shown below were compiled from readership statistics for 174 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | <1% |
| Malaysia | 1 | <1% |
| Netherlands | 1 | <1% |
| Canada | 1 | <1% |
| Iran, Islamic Republic of | 1 | <1% |
| Greece | 1 | <1% |
| United States | 1 | <1% |
| Unknown | 167 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 33 | 19% |
| Student > Ph. D. Student | 30 | 17% |
| Student > Doctoral Student | 18 | 10% |
| Student > Master | 16 | 9% |
| Student > Postgraduate | 14 | 8% |
| Other | 29 | 17% |
| Unknown | 34 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 50 | 29% |
| Medicine and Dentistry | 28 | 16% |
| Neuroscience | 13 | 7% |
| Agricultural and Biological Sciences | 9 | 5% |
| Engineering | 8 | 5% |
| Other | 15 | 9% |
| Unknown | 51 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 14. 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 14 May 2021.
All research outputs
#2,430,133
of 24,338,161 outputs
Outputs from European Archives of Psychiatry and Clinical Neuroscience
#132
of 1,563 outputs
Outputs of similar age
#15,232
of 168,091 outputs
Outputs of similar age from European Archives of Psychiatry and Clinical Neuroscience
#2
of 15 outputs
Altmetric has tracked 24,338,161 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,563 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.1. This one has done particularly well, scoring higher than 91% of its peers.
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 168,091 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.