TY - JOUR
T1 - Independence is elusive
T2 - Set size effects on encoding precision in visual search
AU - Mazyar, Helga
AU - van den Berg, Ronald
AU - Seilheimer, Robert L.
AU - Ma, Wei Ji
PY - 2013
Y1 - 2013
N2 - Looking for a target in a visual scene becomes more difficult as the number of stimuli increases. In a signal detection theory view, this is due to the cumulative effect of noise in the encoding of the distractors, and potentially on top of that, to an increase of the noise (i.e., a decrease of precision) per stimulus with set size, reflecting divided attention. It has long been argued that human visual search behavior can be accounted for by the first factor alone. While such an account seems to be adequate for search tasks in which all distractors have the same, known feature value (i.e., are maximally predictable), we recently found a clear effect of set size on encoding precision when distractors are drawn from a uniform distribution (i.e., when they are maximally unpredictable). Here we interpolate between these two extreme cases to examine which of both conclusions holds more generally as distractor statistics are varied. In one experiment, we vary the level of distractor heterogeneity; in another we dissociate distractor homogeneity from predictability. In all conditions in both experiments, we found a strong decrease of precision with increasing set size, suggesting that precision being independent of set size is the exception rather than the rule.
AB - Looking for a target in a visual scene becomes more difficult as the number of stimuli increases. In a signal detection theory view, this is due to the cumulative effect of noise in the encoding of the distractors, and potentially on top of that, to an increase of the noise (i.e., a decrease of precision) per stimulus with set size, reflecting divided attention. It has long been argued that human visual search behavior can be accounted for by the first factor alone. While such an account seems to be adequate for search tasks in which all distractors have the same, known feature value (i.e., are maximally predictable), we recently found a clear effect of set size on encoding precision when distractors are drawn from a uniform distribution (i.e., when they are maximally unpredictable). Here we interpolate between these two extreme cases to examine which of both conclusions holds more generally as distractor statistics are varied. In one experiment, we vary the level of distractor heterogeneity; in another we dissociate distractor homogeneity from predictability. In all conditions in both experiments, we found a strong decrease of precision with increasing set size, suggesting that precision being independent of set size is the exception rather than the rule.
KW - Bayesian inference
KW - Capacity limitations
KW - Precision
KW - Visual attention
KW - Visual search
UR - http://www.scopus.com/inward/record.url?scp=84878369662&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84878369662&partnerID=8YFLogxK
U2 - 10.1167/13.5.8
DO - 10.1167/13.5.8
M3 - Article
C2 - 23576114
AN - SCOPUS:84878369662
SN - 1534-7362
VL - 13
JO - Journal of vision
JF - Journal of vision
IS - 5
M1 - 8
ER -