Christian Habeck

Dr. Christian Habeck

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Research Focus & Metrics

Academic Career Length

22Years (2005-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 May 2008 in NeuroImage
Verified
Journal Article
Closed access
CHChristian Habeck
Christian Habeck
NFNorman L. Foster
Norman L. Foster
RPRobert Perneczky
Robert Perneczky
AKAlexander Kurz
Alexander Kurz
PAPanagiotis Alexopoulos
Panagiotis Alexopoulos
YSYaakov Stern
Yaakov Stern

1 September 2018 in NeuroImage
Verified
Journal Article
Closed access
YSYaakov Stern
Yaakov Stern
YGYunglin Gazes
Yunglin Gazes
QRQolomreza Razlighi
Qolomreza Razlighi
JSJason Steffener
Jason Steffener
CHChristian Habeck
Christian Habeck

24 July 2010 in Cell Biochemistry and Biophysics
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Journal Article
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TIThe Alzheimer’s Disease Neuroimaging Initiative
The Alzheimer’s Disease Neuroimaging Initiative
CHChristian Habeck
Christian Habeck
YSYaakov Stern
Yaakov Stern

1 July 2005 in Neural Computation
Verified
Journal Article
Closed access
CHChristian Habeck
Christian Habeck
JKJohn W. Krakauer
John W. Krakauer
CGClaude Ghez
Claude Ghez
HSHarold A. Sackeim
Harold A. Sackeim
DEDavid Eidelberg
David Eidelberg
JMJames R. Moeller
James R. Moeller
In neuroimaging studies of human cognitive abilities, brain activation patterns that include regions that are strongly interactive in response to experimental task demands are of particular interest. Among the existing network analyses, partial least squares (PLS; McIntosh, 1999; McIntosh, Bookstein, Haxby, & Grady, 1996) has been highly successful, particu-larly in identifying group differences in regional functional connectivity, including differences as diverse as those associated with states of aware-ness and normal aging. However, we address the need for a within-group model that identifies patterns of regional functional connectivity that ex-hibit sustained activity across graduated changes in task parameters. For example, predictions of sustained connectivity are commonplace in stud-ies of cognition that involve a series of tasks over which task difficulty increases (Baddeley, 2003). We designed ordinal trend analysis (OrT) to identify activation patterns that increase monotonically in their expres-sion as the experimental task parameter increases, while the correlative relationships between brain regions remain constant. Of specific interest are patterns that express positive ordinal trends on a subject-by-subject basis. A unique feature of OrT is that it recovers information about func-tional connectivity based solely on experimental design variables. In par-ticular, there is no requirement by OrT to provide either a quantitative model of the uncertain relationship between functional brain circuitry and subject variables (e.g., task performance and IQ) or partial informa-tion about the regions that are functionally connected. In this letter, we provide a step-by-step recipe of the computations performed in the new OrT analysis, including a description of the inferential statistical meth-ods applied. Second, we describe applications of OrT to an event-related fMRI study of verbal working memory and H2 15 O-PET study of visuo-motor learning. In sum, OrT has potential applications to not only studies of young adults and their cognitive abilities, but also studies of normal aging and neurological and psychiatric disease.

1 May 2005 in Cognitive Brain Research
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Journal Article
Closed access
CHChristian Habeck
Christian Habeck
BRBrian C. Rakitin
Brian C. Rakitin
JMJames Moeller
James Moeller
NSNikolaos Scarmeas
Nikolaos Scarmeas
EZEric Zarahn
Eric Zarahn
YSYaakov Stern
Yaakov Stern

1 December 2014 in NeuroImage
Verified
Journal Article
Closed access
YSYaakov Stern
Yaakov Stern
CHChristian Habeck
Christian Habeck
JSJason Steffener
Jason Steffener
DBDaniel Barulli
Daniel Barulli
YGYunglin Gazes
Yunglin Gazes
TSTimothy Salthouse
Timothy Salthouse