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Visual Categorization and Object Shape: ROI Analysis of fMRI Data

MPS-Authors
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Graf,  M
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Dahl,  C
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

/persons/resource/persons83839

Bülthoff,  HH
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Citation

Erb, M., Graf, M., Dahl, C., Grodd, W., & Bülthoff, H. (2004). Visual Categorization and Object Shape: ROI Analysis of fMRI Data. Poster presented at 10th Annual Meeting of the Organization for Human Brain Mapping (HBM 2004), Budapest, Hungary.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-D927-6
Abstract
Introduction:
Visual categorization is a fundamental capability of the visual system. Deforming shape (morphing)
transformations are well suited to describe the shape variability of members of common basic level categories
(see Figure 1). We investigated the cortical processes underlying basic level categorization, using region of
interest (ROI) analyses.
Material and Methods:
Objects from 25 common basic level categories were generated by morphing between two members of the same
category. Eleven subjects participated in three tasks, starting with the categorization task. Subjects had to decide
as fast as possible whether two sequentially presented objects belonged to the same basic level category. The
transformational distance between category members was varied (event-related design). In a second task, the
updating task, the same observers perceived intact morphing sequences, scrambled morphing sequences, and
static presentations of different morph exemplars (block design). In a third task [1] we presented intact objects,
scrambled objects, or periods of simple fixation. Subjects were required to perform a one-back-task (shape task,
block design).
fMRI data were acquired on a 3T scanner (Siemens Trio), measuring 24 slices of 64x64 voxels every two seconds
(resolution of 3x3x5 mm3 ), covering the whole brain.
Based on the shape processing tasks (red in Figure 2), we calculated ROIs. While the contrast ’intact objects -
scrambled objects’ revealed the usual LOC region (Figure 2c), a large network of ventral, dorsal and frontal
regions was activated when also the fixation period was included (contrast ’intact - scrambled - fixation’) (Figure
2a,b,d). We used these ventral, dorsal and frontal regions as templates for ROI analysis.
Within these ROIs, averaged time courses were calculated using the tools of Kalina Christoff
(http://www-psych.stanford.edu/~kalina/SPM99/Tools/roi.html).
Results:
In the categorization task the contrast long vs. short morph distance revealed an increasing BOLD signal in LOC
(lateral occipital complex), in the superior parietal cortex (BA 7), and in the frontal cortex (BA 44) (Figure 2
yellow). ROI analyses showed highly similar pattern of results for ventral and dorsal regions (Figure 3). In the
updating task we found dorsal activation for the contrast between intact - (scrambled + static) conditions. This
activation spot was close to the dorsal activation in the categorization task, but was not identical (Figure 2b
green). Nevertheless, an ROI analysis on the categorization data, based on the dorsal activation in the updating
task as a ROI, showed similar results as the previous analyses.
Discussion:
The results confirm that basic level categorization is not limited to the ventral pathway, but rather relies on a
network of ventral, dorsal and frontal areas. ROI analyses showed that the activation within this network is
systematically dependent on the amount of shape transformation. Similar patterns of activation were found in the
ventral and dorsal stream, suggesting that both visual streams are involved in visual categorization.