Complementary information for "Magnocellular bias in exogenous attention to biologically salient stimuli as revealed by manipulating their luminosity and color "(Journal of Cognitive Neuroscience, 2017)

1- Physical characteristics of distractors

1.1. Figure against ground surface

To compute this surface, figures were converted to absolute black (0, 0, 0 in the RGB scale) and grounds to absolute white (255, 255, 255). Then, luminosity was computed for both figures. If figure surface is maximal (i.e., black completely hides white), luminosity is 0; if figure surface is minimal (surface=0), there is not any black pixel hiding the white ground so luminosity is 255.

Resulting surface was 55.2 for both the spider and the wheel.

1.2. Spatial Frequency (SF)

We followed the procedure described in [Delplanque, S., N’diaye, K., Scherer, K., & Grandjean, D. (2007). Spatial frequencies or emotional effects? A systematic measure of spatial frequencies for IAPS pictures by a discrete wavelet analysis. Journal of Neuroscience Methods, 165, 144–150] to compute SFs.

In order to provide a maximal value in the power spectral density range (minimum power spectral density is 0, but there is not an a priori maximal as in the case of figure surface) for each analyzed SF band (high, intermediate and low), so the relative distance between spider and wheel within the maximal range can be computed, an additional stimuli was introduced: a high-pass filtered spider.

Resulting spider minus wheel differences were 3.65% (high SF band), 18.83% (intermediate SF band) and 0.60% (low SF band) of maximal interval.

Click here for detailed information on SF

1.3. Luminance / color

1.3.1. "Par" stimuli (isoluminant, heterochromatic)

In order to equalize luminance of the red figures and the green ground in Par stimuli, green was set to [0, 128, 0] and red to [255, 0, 0] in the RGB scale (were 0, 0, 0 means absolute black and 255, 255, 255 means absolute white). This yielded an equalized luminosity for figure and ground: 76 in a 0 to 255 scale as measured through Photoshop CS3 (sRGB IEC61966-2.1 profile). As a consequence, the whole figure + ground square (212x212 pixel size, 7.5º x 7.5º visual angle), had also 76 as luminance level.

Additionally, and as an alternative method to test isoluminance, figure+ground squares were converted to grayscale in order to confirm whether both figure and ground resulted as equally gray (i.e, whether the figure + ground squares were converted to an homogeneous gray square). To that aim, the color to grayscale conversion algorythm proposed by Grundland and Dodgson (2005) [R*0.30, G*0.59, B*0.11] was employed. This algorythm has been reported as the most accurate in subjective terms by a wide sample of subjects (n=119) when compared to six other methods (Ĉadík, 2008).

Finally, luminance emitted by the green and red colors selected as explained above was measured through a TES-137 luminance meter. To that aim, each of both colors was presented filling the whole screen in the same computer monitor employed during the experiment, and with identical gamma, color balance, brightness and contrast settings. The input extreme of the luminance meter´s cylindrical probe was placed in contact with the central part of the screen. The probe was positioned perpendicular to the screen plane. Due to slight variations in luminance readings from one test to another, ten measurements were taken for each color. Average readings for both the red and the green color were 26.922 and 26.901cd/m2, respectively (0.02% variation with respect the total luminance rank). Click here to see average measurements and other luminance recording details.

1.3.2. "Mag" stimuli (heteroluminant, isochromatic)

In order to achieve the same figure + ground square luminosity as Par stimuli, which was 76 as explained, the gray background was set to [97, 97, 97] and the figure to [0, 0, 0]. Luminance meter recordings (taken as explained in the previous section, see the link for details) confirmed Parvo-Magno luminance closeness (4.27% variation).

1.3.3. References

  • Ĉadík, M. (2008). Perceptual evaluation of Color‐to‐Grayscale image conversions. Computer Graphics Forum, 27 (7) pp. 1745-1754. PDF.
  • Grundland M., Dodgson N. A.: The Decolorize Algorithm for Contrast Enhancing, Color to Grayscale Conversion. Tech. Rep. UCAM-CL-TR-649, University of Cambridge, 2005. PDF

1.4. Distractor downloading

Please refer to this paper if you employ these stimuli in your research. Actual luminances may diverge from those reported above as a function of the computer monitor (and its settings) where the stimuli are displayed, so these figures should be adjusted in chromatic terms to guarantee correct luminance values.

[SpiderMag] [SpiderPar] [WheelMag] [WheelPar]



2- Scale of fears

This scale is not standardized nor published, but it has often been employed at our laboratory. It consists of a brief questionnaire in which critical items to the study's scope (spiders in this case) are presented among other, irrelevant items, so it is not obvious for participants (prior to the recording session) which stimuli will be presented / the study is interested on.

Click here to view the scale of fears



3- Supplement to Figure 2

Figure legend. Spatial factors in which TF2 (P1p) and TF1 (P2a/N2p) were decomposed, both those showing significant effects of the experimental treatment, which appear in the original Figure 2 (and are marked here with an asterisk) and those not showing significant effects.

Click here to view Supplement to Figure 2