The Relationship between fMRI adaptation and category selectivity

This project investigates the link between adaptation and areas of the cortex linked to face recognition and limb recognition using an event related design.

Background

fMRI Adaptation is a phenomena that takes place in higher order cortical areas in which the BOLD response signal decreases in response to repeated identical visual stimuli. Adaptation has been shown to occur in higher order visual areas but not early visual areas such as V1 [1]. This study investigates the relationship between object selectivity and fMRI adapation. More specifically, it will examine face selective areas as well as body part selective areas with regards to adaptation. Furthermore, it will look at the differences between adaptation within the ROIs of those two specific categories as well as the similarities in adaptation across various anatomical brain areas.

Methods

Pre-processed data was used from the lab of Kalanit Grill-Spector from the parts of an experiment outlined below [2].

Subjects

The data from the right hemisphere of one subject, a male in his late 20s, was analyzed.

MR acquisition

The subject participated in two experiments, an event related design followed by a block design localizer scan. The first, event related design, consisted of 8 runs of 156 trials lasting for 2 seconds each. Each trial consisted of the presentation of an image of either a face, limb, car, or house for 1000ms followed by a 1000ms blank. Within each run, only two of the images were repeated six times, the rest not repeated at all. None of the images were repeated across scans.

The second experiment was a block design used to identify category selective areas within the ventral stream. Blocks were 12 seconds long with a 750ms stimulus presentation period followed by a 250 ms blank period. Each run consisted of 32 blocks, 4 blocks for each category (faces, limbs, flowers, cars, guitars, houses, and scrambled) as well as four blank blocks.

12 slices were acquired at a resolution of 1.5 x 1.5 x 3mm per voxel and a TR of 1000 ms.

MR Analysis

As mentioned above, the data I analyzed was pre-processed. That high resolution MR data was was then analyzed using mrVista software tools.

ROIs

Using the localizer data from the second experiment, I created ROIs specific for areas selective for faces and areas selective for limbs. I chose the 4 different face selective areas seen in figure 1.

FIGURE 1

                    ROIs are named as follows: Face Selective 1- Blue
                                               Face Selective 2- Red
                                               Face Selective 3- Cyan
                                               Face Selective 4- Yellow

Using the localizer data for limb selective regions from the same experiment I selected 3 limb selective ROIs (See figure 2). I chose these 3 ROIs in order to obtain data from one ROI in 3 differing anatomical regions.

FIGURE 2

                    ROIs are named as follows: Limb Selective 1- Blue
                                               Limb Selective 2- Green
                                               Limb Selective 3- Magenta

These ROIs were then uploaded onto their respective adaptation maps obtained from the first experiment. Face Selective adaptation map(figure 3) and Limb selective adaptation map (figure 4).

                     FIGURE 3                                               FIGURE 4

The time course for each ROI was then extracted from the adaptation data in order to compare the adaptation between categories, ROIs, and anatomical regions.