Selective attention involves the ability to attend to relevant information while ignoring irrelevant information. In early research on this topic, a critical question was whether attention occurs before (early selection) or after (late selection) the information is processed for meaning. One of the tasks used to answer this question is the dichotic listening task. In this task, participants listen to different passages of text presented in each ear through headphones. Researchers found that when questioned about the message in the unattended or ignored ear, participants detected changes in perceptual characteristics (e.g., pitch, volume) but did not notice other meaning-based changes. This result suggests the existence of a perceptual filter that selects information based on features such as volume or pitch. This filter serves to limit the amount of information entering short-term memory (i.e., the “bottleneck” in processing). However, other evidence suggests that unattended information also passes through the filter, though at an attenuated level, whereas still other results suggest that attention occurs much later, after all information has been processed for meaning. One current model of selective attention proposes that attention can occur early or late, depending on the perceptual and memory demands imposed by the task.
Selective attention is also investigated employing tasks using reaction time, measured in milliseconds, as the variable of interest. In the Stroop task, participants name the color of the ink in which a word is printed. Individuals are slower to respond in an incongruent condition (e.g., the word red printed in green ink) compared to a congruent condition (e.g., the word red printed in red ink), because the relatively automatic word-naming response must be inhibited in the incongruent condition. This interference is more pronounced with increased age, even in relatively healthy older adults. In visual search tasks, participants identify a target item among irrelevant distractor items. Under difficult conditions, when distractors are physically similar to the target, search becomes less efficient, particularly for older adults. However, under conditions in which the target is a unique item and tends to “pop out” from the distractors, search performance is comparable for younger and older adults. Using these tasks with brain-imaging techniques has allowed researchers to identify a frontoparietal network of brain regions involved in selective attention. Healthy older adults show increased activations, compared to younger adults, in this frontoparietal network, combined with decreased activations in visual cortical regions. The increased activation may serve as a compensatory mechanism for age-related declines in visual processing.
Other causes of individual differences in selective attention include attention deficit hyperactivity disorder (ADHD), which has typically been associated with global deficits in attention. However, recent research using visual search tasks suggests no differential impairment in selective attention between ADHD children and matched control children, although ADHD-related deficits have been observed in other components of attention, such as the ability to switch between two different tasks. Although there is little evidence of sex differences in selective attention, a few studies using the dichotic listening and visual search tasks have found moderate differences in selective attention favoring women.
SEE ALSO Attention-Deficit/Hyperactivity Disorder; Neuroscience
Lavie, Nilli, Aleksandra Hirst, Jan W. de Fockert, and Essi Viding. 2004. Load Theory of Selective Attention and Cognitive Control. Journal of Experimental Psychology: General 133 (3): 339–354.
Wolfe, Jeremy M. 2003. Moving Towards Solutions to Some Enduring Controversies in Visual Search. Trends in Cognitive Science 7 (2): 70–76.
David J. Madden