| Title |
Long-Range Temporal Correlations Reflect Treatment Response in the Electroencephalogram of Patients with Infantile Spasms
|
|---|---|
| Published in |
Brain Topography, September 2017
|
| DOI | 10.1007/s10548-017-0588-5 |
| Pubmed ID | |
| Authors |
Rachel J. Smith, Amanda Sugijoto, Neggy Rismanchi, Shaun A. Hussain, Daniel W. Shrey, Beth A. Lopour |
| Abstract |
Infantile spasms syndrome is an epileptic encephalopathy in which prompt diagnosis and treatment initiation are critical to therapeutic response. Diagnosis of the disease heavily depends on the identification of characteristic electroencephalographic (EEG) patterns, including hypsarrhythmia. However, visual assessment of the presence and characteristics of hypsarrhythmia is challenging because multiple variants of the pattern exist, leading to poor inter-rater reliability. We investigated whether a quantitative measurement of the control of neural synchrony in the EEGs of infantile spasms patients could be used to reliably distinguish the presence of hypsarrhythmia and indicate successful treatment outcomes. We used autocorrelation and Detrended Fluctuation Analysis (DFA) to measure the strength of long-range temporal correlations in 21 infantile spasms patients before and after treatment and 21 control subjects. The strength of long-range temporal correlations was significantly lower in patients with hypsarrhythmia than control patients, indicating decreased control of neural synchrony. There was no difference between patients without hypsarrhythmia and control patients. Further, the presence of hypsarrhythmia could be classified based on the DFA exponent and intercept with 92% accuracy using a support vector machine. Successful treatment was marked by a larger increase in the DFA exponent compared to those in which spasms persisted. These results suggest that the strength of long-range temporal correlations is a marker of pathological cortical activity that correlates with treatment response. Combined with current clinical measures, this quantitative tool has the potential to aid objective identification of hypsarrhythmia and assessment of treatment efficacy to inform clinical decision-making. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 46 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 8 | 17% |
| Researcher | 8 | 17% |
| Student > Bachelor | 5 | 11% |
| Student > Master | 4 | 9% |
| Student > Doctoral Student | 2 | 4% |
| Other | 6 | 13% |
| Unknown | 13 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 11 | 24% |
| Medicine and Dentistry | 6 | 13% |
| Engineering | 5 | 11% |
| Computer Science | 2 | 4% |
| Chemical Engineering | 1 | 2% |
| Other | 3 | 7% |
| Unknown | 18 | 39% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 27 November 2017.
All research outputs
#15,332,207
of 23,577,761 outputs
Outputs from Brain Topography
#290
of 491 outputs
Outputs of similar age
#189,144
of 317,373 outputs
Outputs of similar age from Brain Topography
#5
of 9 outputs
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