5.4 Results
5.4.1 Experiment 1
This experiment is subdivided in two separate experiments: one investigating the de-tection of the stimulus (dede-tection experiment), the other the human performance in discriminating the walking direction of the stimulus (discrimination experiment).
detection experiment
Neri et al. (1998) showed that the threshold for detecting a biological motion stimulus in noise increases linearly as a function of number of dots per stimulus frame. They also showed that this linear relationship holds for detecting a simple translatory dot pattern. Since in both stimuli only local motion signals increase in the same way, Neri et al. conclude that local motion signals contribute to the perception in translatory motion as well as in biological motion. On the other hand, Beintema and Lappe (2002) concluded from their experiments that the additional local motion signals only contribute to segregate the stimulus from the background.
To test both hypotheses, we conducted two experiments in which we presented both a target and a distractor simultaneously. Both tasks had in common that the global forms of target and distractor differ, but that they had equal density:
EXP1: Distractor variable
In the first experiment, target and distractor were variable but always equal in terms of their local motion signals, that is, the dots’ lifetime. Since the differences to EXP2 are to be found in the distractor characteristics, we denote this task as ’Distractor variable’.
EXP2: Distractor constant
In the second experiment, the lifetime of the target’s dots was still variable, whereas we set the lifetime of the distractor’s dots to a constant lifetime of 1 frame. Therefore, we denote this task as ’Distractor constant’.
If local motion signals are an essential part of perceiving biological motion as several studies imply (e.g. Cutting, 1988; Neri et al., 1998; Giese and Poggio, 2003) the detection of the target should be widely unaffected by the kind of distractor. Targets including local motion signals should be more easily detectable. On the other hand, if
the perception is a global process of form perception and local motion signals are used for segregation as proposed by other studies (e.g. Bertenthal and Pinto, 1994; Schenk and Zihl, 1997; Beintema and Lappe, 2002) than stimuli including local motion signals should be more easily perceived if they differ from the distractor and from the noise in terms of local motion contingent (Fig. 5.1).
Target lifetime
Noise lifetime 2
2 2
2 1 1
1 1
% correct
No. of noisedots
a) b)
Fig. 5.1: Hypothetical results for EXP1: Distractor variable, if it is important that stimulus and noise differ in terms of local motion as predicted by Beintema and Lappe (2002) a) or if it is important that the stimulus contains local motion signals as stated by Neri et al. (1998) b).
Fig. 5.2 presents the data of EXP1: Distractor variable (target and distractor include always the same amount of local motion signals and the same amount of dots per frame, only the spatial configuration of the dots varies). Statistical analysis revealed a significant influence of the number of noise dots (two-way ANOVA with repeated measures, F(4,12) = 21.33, p <0.01) but not of condition (F(3,9) = 2.19, p=.16). If we assume that conditions reveal differences only for high number of noise dots, still no significant differences could be observed. Even the condition containing local motion does not increase performance.
Fig. 5.3 shows the results when we compared conditions of EXP 1 and EXP 2.
Here, we only compared conditions in which the distractor had a lifetime of 1, lifetime of target and noise was variable. Statistical analysis revealed a significant influence of the number of noise dots (two-way ANOVA with repeated measures, F(3,9) = 16.78, p < 0.01) but not of condition (F(3,9) = 0.63, p = .62). If we assume that conditions reveal differences only for high number of noise dots, still no significant differences could be observed. Even the condition containing local motion does not increase performance.
Fig. 5.4 shows the results when we compared conditions of EXP 1 and EXP 2.
Here, we only compared conditions in which the distractor had a lifetime of 2, lifetime of target and noise was variable. Statistical analysis revealed a significant influence of the number of noise dots (F(3,9) = 17.80, p < 0.01) but not of condition (two-way ANOVA with repeated measures,F(3,9) = 2.41, p=.13). If we assume that conditions reveal differences only for high number of noise dots, a significant influence of condition could be observed for high number (>1000) of noise dots (F(3,9) = 4.33, p < 0.05) but no influence of noise dots (F(1,3) = 2.73, p = 0.20). Scheff´e’s Post-hoc test on the factor condition revealed that the subjects’ performance in the condition ’target:
lifetime 2, noise lifetime 1, distractor lifetime 1’ was significantly higher than in the condition ’target: lifetime 2, noise lifetime 1, distractor lifetime 2’.
EXP1: Distractor variable
detection experiment
200 600 1000 1400
0.5 0.6 0.7 0.8 0.9 1
200 600 1000 1400
0.5 0.6 0.7 0.8 0.9 1
200 600 1000 1400
0.5 0.6 0.7 0.8 0.9 1
No. of noisedots
% correct
% correctNo. of noisedots
Target lifetime
Noise lifetime
1
1 2
2 1
1 2 2
JL SK
KAR KAT
Mean
Distractor lifetime
1 1 2 2
Fig. 5.2: Results of EXP1: Distractor variable in the detection task. Target and distractor have always the same lifetime. Results are presented as the fraction of correct answers as function of noise dots for 4 subjects and the mean over all subjects.
Comparison of EXP1: Distractor variable and EXP2: Distractor constant
detection experiment for a target dot lifetime of 1 frame
Fig. 5.3: Comparison of the results of EXP1 and EXP2 in the detection task. Target and distractor have always the same lifetime of 1 frame. Results are presented as the fraction of correct answers as function of noise dots for 4 subjects and the mean over all subjects. Solid lines and dashed lines represent data with same conditions but from different experiments and are theoretically expected to be identical for same colors. Therefore, this task serves as a control.
Comparison of EXP1: Distractor variable and EXP2: Distractor constant
detection experiment for a target dot lifetime of 2 frames
Fig. 5.4: Comparison of the results of EXP1 and EXP2 in the detection task. Target and distractor are identical in the case of solid lines (lifetime of 2) but differ in the case of dashed lines (distractor: lifetime 1, target: lifetime 2). Results are presented as the fraction of correct answers as function of noise dots for 4 subjects and the mean over all subjects. ∗ indicates significant differences between the two conditions for number of noise dots >1000.
discrimination experiment
After detecting the stimulus we asked subjects to discriminate the walking direction of the walker. Fig. 5.5 presents the data ofEXP1: Distractor variable(target and distrac-tor include always the same amount of local motion signals and the same amount of dots per frame, only the spatial configuration of the dots varies). Statistical analysis revealed a significant influence of the number of noise dots (two-way ANOVA with repeated mea-sures,, F(4,12) = 17.42, p <0.01) but not of condition (F(3,9) = 0.63, p=.61). If we assume that conditions reveal differences only for high number of noise dots, still no significant differences could be observed. Even the condition containing local motion does not increase performance.
Fig. 5.6 shows the results when we compared conditions of EXP 1 and EXP 2.
Here, we only compared conditions in which the distractor had a lifetime of 1, lifetime of target and noise was variable. Statistical analysis revealed a significant influence of the number of noise dots (two-way ANOVA with repeated measures, F(3,9) = 16.59, p < 0.01) but not of condition (F(3,9) = 0.91, p = .47). If we assume that conditions reveal differences only for high number of noise dots, still no significant differences could be observed. Even the condition containing local motion does not increase performance.
Fig. 5.7 shows the results when we compared conditions ofEXP 1andEXP 2. Here, we only compared conditions in which the distractor had a lifetime of 2, lifetime of target and noise was variable. Statistical analysis revealed a significant influence of the number of noise dots (two-way ANOVA with repeated measures, F(3,9) = 19.56, p <
0.01) but not of condition (F(3,9) = 0.37, p=.78). If we assume that conditions reveal differences only for high number of noise dots (similar to th detection task above), still no significant influence of condition could be observed for high number (>1000) of noise dots (F(3,9) = 1.37, p= 0.31) and no influence of noise dots (F(1,3) = 41, p= 0.57).
In contrast to the detection experiment subjects did not benefit from additional local motion signals in the discrimination experiment, when we compared EXP1 and EXP2 for a lifetime of 2 frames in the target dots (Fig. 5.7). No significant advantage for any condition could be observed in any experiment.
EXP1: Distractor variable
discrimination experiment
200 600 1000 1400
0.5 0.6 0.7 0.8 0.9 1
200 600 1000 1400
0.5 0.6 0.7 0.8 0.9 1
200 600 1000 1400
0.5 0.6 0.7 0.8 0.9 1
No. of noisedots
% correct
% correctNo. of noisedots
Target lifetime
Noise lifetime
1
1 2
2 1
1 2 2
JL SK
KAR KAT
Mean
Distractor lifetime
1 1 2 2
Fig. 5.5: Results of EXP1: Distractor variablein the discrimination experiment. Target and distractor have always the same lifetime. Results are presented as the fraction of correct answers as function of noise dots for 4 subjects and the mean over all subjects.
Comparison of EXP1: Distractor variable and EXP2: Distractor constant
discrimination experiment for a target dot lifetime of 1 frame
200 600 1000 1400
0.5 0.6 0.7 0.8 0.9 1
200 600 1000 1400
0.5 0.6 0.7 0.8 0.9 1
200 600 1000 1400
0.5 0.6 0.7 0.8 0.9 1
No. of noisedots
% correct
% correctNo. of noisedots
Target lifetime
Noise lifetime
1
1 2
2 1
1 1 1
JL SK
KAR KAT
Mean
Distractor lifetime
1 1 1 1
Fig. 5.6: Comparison of the results of EXP1 and EXP2 in the discrimination experiment.
Target and distractor have always the same lifetime of 1. Results are presented as the fraction of correct answers as function of noise dots for 4 subjects and the mean over all subjects. Solid lines and dashed lines represent data with same conditions but from different experiments and are theoretically expected to be identical for same colors. Therefore, this task serves as a control.
Comparison of EXP1: Distractor variable and EXP2: Distractor constant
discrimination experiment for a target dot lifetime of 2 frames
200 600 1000 1400
0.5 0.6 0.7 0.8 0.9 1
200 600 1000 1400
0.5 0.6 0.7 0.8 0.9 1
200 600 1000 1400
0.5 0.6 0.7 0.8 0.9 1
No. of noisedots
% correct
% correctNo. of noisedots
Target lifetime
Noise lifetime
1
1 2
2 2
2 2 2
JL SK
KAR KAT
Mean
Distractor lifetime
2 2 1 1
Fig. 5.7: Comparison of the results of EXP1 and EXP2 in the discrimination task. Target and distractor are identical in the case of solid lines (lifetime of 2) but differ in the case of dashed lines (distractor: lifetime 1, target: lifetime 2) . Results are presented as the fraction of correct answers as function of noise dots for 4 subjects and the mean over all subjects.