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

Author:

Habeck Christian1,Krakauer John W.2,Ghez Claude3,Sackeim Harold A.4,Eidelberg David5,Stern Yaakov6,Moeller James R.7

Affiliation:

1. Cognitive Neuroscience Division, Taub Institute, and Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, NY 10032, U.S.A.

2. Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, NY 10032, U.S.A.

3. Department of Neurology, College of Physicians and Surgeons, and Center for Neurobiology and Behavior, Columbia University, New York, NY 10032, U.S.A.

4. 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.

5. 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.

6. 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.

7. Cognitive Neuroscience Division, Taub Institute, and Department of Neurology, 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.

Abstract

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.

Publisher

MIT Press - Journals

Subject

Cognitive Neuroscience,Arts and Humanities (miscellaneous)

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