In everyday life, people categorize objects so
easily that they do not realize how complex this task is. Objects from
the same category are very different from one another. Even the same
object never projects the exact same image to the retina, because of
changes in the surrounding illumination, the particular viewpoint from
which the person is looking at the object, how close the person is to
the object, etc. Furthermore, we are capable of extracting different
forms of categorical information from the same objects, depending on
environmental demands (e.g., from a single face we can extract
information about age, gender, race, etc.).
multidimensional signal detection theory to study independent object
Visual processing in the brain results in a re-description of the
sensory input in terms of a number of “high-level” object properties.
Much effort has been dedicated to understanding which object properties
are represented “independently” or “invariantly” from other properties,
and which properties are represented in a more “holistic” manner. The
best current framework for the study of different forms of perceptual
independence is general recognition theory (GRT). Unlike other
approaches, GRT offers precise formal definitions to concepts such as
“holistic,” “independent,” and “invariant” processing. Furthermore, GRT
is an extension to signal detection theory and inherits from it the
ability to dissociate perceptual from decisional factors in the study
of perceptual independence.
Our work has extended GRT in two directions. First, we developed GRT
Individual Differences (GRT-wIND), a model that
problems with traditional GRT models and allows the study of individual
differences in perceptual decision making. Among other applications, we
have used GRT-wIND to study independent processing of face dimensions,
such as identity and emotional expression.
Second, we have developed GRT tests of separability (a form of
perceptual independence) that are applicable to neurobiological data.
We have applied these tests to the analysis of fMRI and EEG data, with
the goal of understanding how separable are the representations of face
dimensions in different brain areas.
We are currently using these new GRT tools to study how new
separable object dimensions are learned.
Independence of face
dimensions in health and disease
Faces are some of the most important objects encountered by people in
their everyday lives, and several psychological disorders (e.g.,
depression) involve abnormal processing of face categories (in
particular, emotional expression). More specifically, previous research
shown that emotional expression interferes with processing of other
face dimensions (e.g., gender) to a greater degree in people with
depressive symptoms than in people without such symptoms. We are
currently studying this effect using tools from multidimensional
signal detection theory to determine the independence of face