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Introduction. Development occurs in the real world, in noisy, distracting, and occasionally chaotic environments. Within these environments, the infant’s biggest challenge is to separate the signal from the noise, to understand what is a relevant cue, and to learn what is a distraction. Prior research has shown that infants do well in situations where attention orienting is supported by redundant multisensory cues (Bahrick & Lickliter, 2000; Lewkowicz, 2000; Richardson & Kirkham, 2004; Wu & Kirkham, 2010). But, what these studies have failed to show is how this works outside of the lab, in real-world contexts, where attention-grabbing cues are not time-locked or controlled. The majority of research to date has been non-ecological, not engaging with the richness of the environment. And in fact, a series of studies from our lab, investigating the effects of multisensory cues on learning has shown that in less controlled situations, the answer is far from simple, with task performances shifting with age, cue modality, learning goals, and individual differences (Broadbent et al., 2018; 2019; Kirkham et al., 2019)
Methods and Results. So, in a real-world context, what is influencing the infant’s attention? In a multi-task experiment (N=49), we looked at the impact of noise on attention, specifically focussing on home environments. In one task, we presented 10-month-olds with a visuospatial statistical learning paradigm (Tummeltshammer & Kirkham, 2013), in one of three conditions: Silent, Acute Noise or Chronic Noise. Infants were shown different shapes that moved around the screen, according to specified statistics. In the Acute condition, a cell phone alert sounded concurrently with eight randomly selected events per sequence; in the Chronic condition, a background track of non-verbal ‘home noise’ played (ringtones, TV sounds, vacuum cleaner). The Silent condition had no sounds playing during the task. Results showed that infants in the Chronic condition are showing a trend to perform worse than those in the Acute condition (p=.095), taking longer to orient to the predicted target locations, suggesting that an occasional irrelevant (yet salient) event could re-orient attention to the task. Participants were further split into quieter and noisier homes based on a median split of in-home recorded sound levels (58.42 dB). Infants from quieter homes followed the same trend as described above, while infants from noisier homes showed no change in performance across noise conditions. Higher average sound levels recorded from the home predicted better auditory sensory processing ability on the sensory processing (SP2) questionnaire (r2=.141, p=.002). Higher sound choppiness (i.e., decibel fluctuations) in the home environment significantly correlated with more time spent awake at night as recorded in a Sleep Diary (p=.016).
Conclusions. Taken together, these results demonstrate that real-world environments are closely linked to attentional deployment, as well as to other factors that are known to influence attentional ability. In this talk, we will examine these findings and position them within the broader literature of attentional development, placing emphasis on the interaction between attention and environment, and discussing the role of individual differences.