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A New Approach to Spatial Covariance Modeling of Functional Brain Imaging Data: Ordinal Trend Analysis

ch629{at}columbia.edu, Cognitive Neuroscience Division, Taub Institute, and Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, NY 10032, U.S.A.

John W. Krakauer

jwk18{at}columbia.edu, Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, NY 10032, U.S.A.

Claude Ghez

cpg1{at}columbia.edu, Department of Neurology, College of Physicians and Surgeons, and Center for Neurobiology and Behavior, Columbia University, New York, NY 10032, U.S.A.

Harold A. Sackeim

has1{at}columbia.edu, Departments of Neurology, Psychiatry, and Radiology, College of Physicians and Surgeons, Columbia University, New York, NY 10032, and Department of Biological Psychiatry, New York State Psychiatric Institute, New York, NY 10032, U.S.A.

David Eidelberg

david1{at}nshs.edu, Center for Neurosciences, Institute for Medical Research, North Shore–Long Island Jewish Health System, Manhasset, NY 11030, and Department of Neurology, School of Medicine, New York University, New York, NY 10016, U.S.A.

Yaakov Stern

ys11{at}columbia.edu, Cognitive Neuroscience Division, Taub Institute, and Departments of Neurology and Psychiatry, College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA; and Department of Biological Psychiatry, New York State Psychiatric Institute, New York, NY 10032, U.S.A.

James R. Moeller

jrm8{at}columbia.edu, Cognitive Neuroscience Division, Taub Institute, and Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA
Department of Biological Psychiatry, New York State Psychiatric Institute, New York, NY 10032, U.S.A.

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, particularly in identifying group differences in regional functional connectivity, including differences as diverse as those associated with states of awareness and normal aging. However, we address the need for a within-group model that identifies patterns of regional functional connectivity that exhibit sustained activity across graduated changes in task parameters. For example, predictions of sustained connectivity are commonplace in studies 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 expression 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 functional connectivity based solely on experimental design variables. In particular, 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 information 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 methods applied. Second, we describe applications of OrT to an event-related fMRI study of verbal working memory and H₂¹⁵O-PET study of visuomotor 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.

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