@article{poil_age_2014,
	title = {Age dependent electroencephalographic changes in attention-deficit/hyperactivity disorder ({ADHD}).},
	volume = {125},
	issn = {1872-8952},
	url = {http://www.sciencedirect.com/science/article/pii/S1388245714000509},
	doi = {10.1016/j.clinph.2013.12.118},
	abstract = {OBJECTIVE: Objective biomarkers for attention-deficit/hyperactivity disorder (ADHD) could improve diagnostics or treatment monitoring of this psychiatric disorder. The resting electroencephalogram (EEG) provides non-invasive spectral markers of brain function and development. Their accuracy as ADHD markers is increasingly questioned but may improve with pattern classification.

METHODS: This study provides an integrated analysis of ADHD and developmental effects in children and adults using regression analysis and support vector machine classification of spectral resting (eyes-closed) EEG biomarkers in order to clarify their diagnostic value.

RESULTS: ADHD effects on EEG strongly depend on age and frequency. We observed typical non-linear developmental decreases in delta and theta power for both ADHD and control groups. However, for ADHD adults we found a slowing in alpha frequency combined with a higher power in alpha-1 (8-10Hz) and beta (13-30Hz). Support vector machine classification of ADHD adults versus controls yielded a notable cross validated sensitivity of 67\% and specificity of 83\% using power and central frequency from all frequency bands. ADHD children were not classified convincingly with these markers.

CONCLUSIONS: Resting state electrophysiology is altered in ADHD, and these electrophysiological impairments persist into adulthood.

SIGNIFICANCE: Spectral biomarkers may have both diagnostic and prognostic value.},
	number = {8},
	urldate = {2015-03-26},
	journal = {Clinical neurophysiology},
	author = {Poil, S-S and Bollmann, S and Ghisleni, C and O'Gorman, R L and Klaver, P and Ball, J and Eich-Höchli, D and Brandeis, D and Michels, L},
	month = aug,
	year = {2014},
	pmid = {24582383},
	keywords = {Adolescent, Adult, Aged, Aging, Aging: physiology, Attention, Attention Deficit Disorder with Hyperactivity, Attention Deficit Disorder with Hyperactivity: dia, Attention Deficit Disorder with Hyperactivity: phy, Child, Electroencephalography, Female, Humans, Male, Middle Aged, Prognosis, Regression Analysis, Rest, Rest: physiology, Sensitivity and Specificity, Support Vector Machines, Young Adult},
	pages = {1626--38},
}

{"_id":"3tRs8YhjaYMJH4ycz","bibbaseid":"poil-bollmann-ghisleni-ogorman-klaver-ball-eichhchli-brandeis-etal-agedependentelectroencephalographicchangesinattentiondeficithyperactivitydisorderadhd-2014","author_short":["Poil, S.","Bollmann, S","Ghisleni, C","O'Gorman, R L","Klaver, P","Ball, J","Eich-Höchli, D","Brandeis, D","Michels, L"],"bibdata":{"bibtype":"article","type":"article","title":"Age dependent electroencephalographic changes in attention-deficit/hyperactivity disorder (ADHD).","volume":"125","issn":"1872-8952","url":"http://www.sciencedirect.com/science/article/pii/S1388245714000509","doi":"10.1016/j.clinph.2013.12.118","abstract":"OBJECTIVE: Objective biomarkers for attention-deficit/hyperactivity disorder (ADHD) could improve diagnostics or treatment monitoring of this psychiatric disorder. The resting electroencephalogram (EEG) provides non-invasive spectral markers of brain function and development. Their accuracy as ADHD markers is increasingly questioned but may improve with pattern classification. METHODS: This study provides an integrated analysis of ADHD and developmental effects in children and adults using regression analysis and support vector machine classification of spectral resting (eyes-closed) EEG biomarkers in order to clarify their diagnostic value. RESULTS: ADHD effects on EEG strongly depend on age and frequency. We observed typical non-linear developmental decreases in delta and theta power for both ADHD and control groups. However, for ADHD adults we found a slowing in alpha frequency combined with a higher power in alpha-1 (8-10Hz) and beta (13-30Hz). Support vector machine classification of ADHD adults versus controls yielded a notable cross validated sensitivity of 67% and specificity of 83% using power and central frequency from all frequency bands. ADHD children were not classified convincingly with these markers. CONCLUSIONS: Resting state electrophysiology is altered in ADHD, and these electrophysiological impairments persist into adulthood. SIGNIFICANCE: Spectral biomarkers may have both diagnostic and prognostic value.","number":"8","urldate":"2015-03-26","journal":"Clinical neurophysiology","author":[{"propositions":[],"lastnames":["Poil"],"firstnames":["S-S"],"suffixes":[]},{"propositions":[],"lastnames":["Bollmann"],"firstnames":["S"],"suffixes":[]},{"propositions":[],"lastnames":["Ghisleni"],"firstnames":["C"],"suffixes":[]},{"propositions":[],"lastnames":["O'Gorman"],"firstnames":["R","L"],"suffixes":[]},{"propositions":[],"lastnames":["Klaver"],"firstnames":["P"],"suffixes":[]},{"propositions":[],"lastnames":["Ball"],"firstnames":["J"],"suffixes":[]},{"propositions":[],"lastnames":["Eich-Höchli"],"firstnames":["D"],"suffixes":[]},{"propositions":[],"lastnames":["Brandeis"],"firstnames":["D"],"suffixes":[]},{"propositions":[],"lastnames":["Michels"],"firstnames":["L"],"suffixes":[]}],"month":"August","year":"2014","pmid":"24582383","keywords":"Adolescent, Adult, Aged, Aging, Aging: physiology, Attention, Attention Deficit Disorder with Hyperactivity, Attention Deficit Disorder with Hyperactivity: dia, Attention Deficit Disorder with Hyperactivity: phy, Child, Electroencephalography, Female, Humans, Male, Middle Aged, Prognosis, Regression Analysis, Rest, Rest: physiology, Sensitivity and Specificity, Support Vector Machines, Young Adult","pages":"1626–38","bibtex":"@article{poil_age_2014,\n\ttitle = {Age dependent electroencephalographic changes in attention-deficit/hyperactivity disorder ({ADHD}).},\n\tvolume = {125},\n\tissn = {1872-8952},\n\turl = {http://www.sciencedirect.com/science/article/pii/S1388245714000509},\n\tdoi = {10.1016/j.clinph.2013.12.118},\n\tabstract = {OBJECTIVE: Objective biomarkers for attention-deficit/hyperactivity disorder (ADHD) could improve diagnostics or treatment monitoring of this psychiatric disorder. The resting electroencephalogram (EEG) provides non-invasive spectral markers of brain function and development. Their accuracy as ADHD markers is increasingly questioned but may improve with pattern classification.\n\nMETHODS: This study provides an integrated analysis of ADHD and developmental effects in children and adults using regression analysis and support vector machine classification of spectral resting (eyes-closed) EEG biomarkers in order to clarify their diagnostic value.\n\nRESULTS: ADHD effects on EEG strongly depend on age and frequency. We observed typical non-linear developmental decreases in delta and theta power for both ADHD and control groups. However, for ADHD adults we found a slowing in alpha frequency combined with a higher power in alpha-1 (8-10Hz) and beta (13-30Hz). Support vector machine classification of ADHD adults versus controls yielded a notable cross validated sensitivity of 67\\% and specificity of 83\\% using power and central frequency from all frequency bands. ADHD children were not classified convincingly with these markers.\n\nCONCLUSIONS: Resting state electrophysiology is altered in ADHD, and these electrophysiological impairments persist into adulthood.\n\nSIGNIFICANCE: Spectral biomarkers may have both diagnostic and prognostic value.},\n\tnumber = {8},\n\turldate = {2015-03-26},\n\tjournal = {Clinical neurophysiology},\n\tauthor = {Poil, S-S and Bollmann, S and Ghisleni, C and O'Gorman, R L and Klaver, P and Ball, J and Eich-Höchli, D and Brandeis, D and Michels, L},\n\tmonth = aug,\n\tyear = {2014},\n\tpmid = {24582383},\n\tkeywords = {Adolescent, Adult, Aged, Aging, Aging: physiology, Attention, Attention Deficit Disorder with Hyperactivity, Attention Deficit Disorder with Hyperactivity: dia, Attention Deficit Disorder with Hyperactivity: phy, Child, Electroencephalography, Female, Humans, Male, Middle Aged, Prognosis, Regression Analysis, Rest, Rest: physiology, Sensitivity and Specificity, Support Vector Machines, Young Adult},\n\tpages = {1626--38},\n}\n\n","author_short":["Poil, S.","Bollmann, S","Ghisleni, C","O'Gorman, R L","Klaver, P","Ball, J","Eich-Höchli, D","Brandeis, D","Michels, L"],"key":"poil_age_2014","id":"poil_age_2014","bibbaseid":"poil-bollmann-ghisleni-ogorman-klaver-ball-eichhchli-brandeis-etal-agedependentelectroencephalographicchangesinattentiondeficithyperactivitydisorderadhd-2014","role":"author","urls":{"Paper":"http://www.sciencedirect.com/science/article/pii/S1388245714000509"},"keyword":["Adolescent","Adult","Aged","Aging","Aging: physiology","Attention","Attention Deficit Disorder with Hyperactivity","Attention Deficit Disorder with Hyperactivity: dia","Attention Deficit Disorder with Hyperactivity: phy","Child","Electroencephalography","Female","Humans","Male","Middle Aged","Prognosis","Regression Analysis","Rest","Rest: physiology","Sensitivity and Specificity","Support Vector Machines","Young Adult"],"metadata":{"authorlinks":{}},"html":""},"bibtype":"article","biburl":"https://bibbase.org/zotero/asrommel","dataSources":["J8fbWsdsy3xAaB3pX"],"keywords":["adolescent","adult","aged","aging","aging: physiology","attention","attention deficit disorder with hyperactivity","attention deficit disorder with hyperactivity: dia","attention deficit disorder with hyperactivity: phy","child","electroencephalography","female","humans","male","middle aged","prognosis","regression analysis","rest","rest: physiology","sensitivity and specificity","support vector machines","young adult"],"search_terms":["age","dependent","electroencephalographic","changes","attention","deficit","hyperactivity","disorder","adhd","poil","bollmann","ghisleni","o'gorman","klaver","ball","eich-höchli","brandeis","michels"],"title":"Age dependent electroencephalographic changes in attention-deficit/hyperactivity disorder (ADHD).","year":2014}