Generating controlled image sets in cognitive neuroscience research.

Full Abstract

The investigation of perceptual and cognitive functions with non-invasive brain imaging methods critically depends on the careful selection of stimuli for use in experiments. For example, it must be verified that any observed effects follow from the parameter of interest (e.g. semantic category) rather than other low-level physical features (e.g. luminance, or spectral properties). Otherwise, interpretation of results is confounded. Often, researchers circumvent this issue by including additional control conditions or tasks, both of which are flawed and also prolong experiments. Here, we present some new approaches for controlling classes of stimuli intended for use in cognitive neuroscience, however these methods can be readily extrapolated to other applications and stimulus modalities. Our approach is comprised of two levels. The first level aims at equalizing individual stimuli in terms of their mean luminance. Each data point in the stimulus is adjusted to a standardized value based on a standard value across the stimulus battery. The second level analyzes two populations of stimuli along their spectral properties (i.e. spatial frequency) using a dissimilarity metric that equals the root mean square of the distance between two populations of objects as a function of spatial frequency along x- and y-dimensions of the image. Randomized permutations are used to obtain a minimal value between the populations to minimize, in a completely data-driven manner, the spectral differences between image sets. While another paper in this issue applies these methods in the case of acoustic stimuli (Aeschlimann et al., Brain Topogr 2008), we illustrate this approach here in detail for complex visual stimuli.

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Author information

Author/s: Knebel, Jean-François (JF); Toepel, Ulrike (U); Hudry, Julie (J); le Coutre, Johannes (J); Murray, Micah M (MM);

Affiliation: The Functional Electrical Neuroimaging Laboratory, Neuropsychology and Neurorehabilitation Service, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland. jean-francois.knebel(-atsign-)chuv.ch

Journal and publication information

Publication Type: Journal Article; Research Support, Non-U.S. Gov't

Journal: Brain topography (Brain Topogr), published in United States. (Language: eng)

Reference: 2008-Jun; vol 20 (issue 4) : pp 284-9

Dates: Created 2008/04/04; Completed 2008/07/30;

PMID: 18338244, status: MEDLINE (last retrieval date: 11/6/2008)

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MeSH headings (categories)

This article was linked to the MESH Headings shown below.

Brain - physiology
Brain Mapping
Cognition - physiology
Cognitive Science
Food
Humans

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