| Literature DB >> 28076362 |
Daniel S Messinger1,2,3,4, Whitney I Mattson1, James Torrence Todd5, Devon N Gangi1, Nicholas D Myers6, Lorraine E Bahrick5.
Abstract
Although looking time is used to assess infant perceptual and cognitive processing, little is known about the temporal structure of infant looking. To shed light on this temporal structure, 127 three-month-olds were assessed in an infant-controlled habituation procedure and presented with a pre-recorded display of a woman addressing the infant using infant-directed speech. Previous individual look durations positively predicted subsequent look durations over a six look window, suggesting a temporal dependency between successive infant looks. The previous look duration continued to predict the subsequent look duration after accounting for habituation-linked declines in look duration, and when looks were separated by an inter-trial interval in which no stimulus was displayed. Individual differences in temporal dependency, the strength of associations between consecutive look durations, are distinct from individual differences in mean infant look duration. Nevertheless, infants with stronger temporal dependency had briefer mean look durations, a potential index of stimulus processing. Temporal dependency was evident not only between individual infant looks but between the durations of successive habituation trials (total looking within a trial). Finally, temporal dependency was evident in associations between the last look at the habituation stimulus and the first look at a novel test stimulus. Thus temporal dependency was evident across multiple timescales (individual looks and trials comprised of multiple individual looks) and persisted across conditions including brief periods of no stimulus presentation and changes from a familiar to novel stimulus. Associations between consecutive look durations over multiple timescales and stimuli suggest a temporal structure of infant attention that has been largely ignored in previous work on infant looking.Entities:
Mesh:
Year: 2017 PMID: 28076362 PMCID: PMC5226676 DOI: 10.1371/journal.pone.0169458
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Fig 1An illustration of the temporal dependency hypothesis.
Individual looks occur within trials of the habituation protocol. Individual look durations positively predict subsequent look durations. Previous trial durations predict subsequent trial durations.
Sample demographics.
| Presentation Type | N | Mean Age in Days (SD) | Male | Non-Hispanic Caucasian | Hispanic | African-American/Asian/Other |
|---|---|---|---|---|---|---|
| Audiovisual | 88 | 103.34 (14.96) | 41 | 4 | 81 | 3 |
| Visual Only | 39 | 91.90 (5.11) | 17 | 5 | 33 | 1 |
| Combined | 127 | 99.83 (13.80) | 58 | 9 | 114 | 4 |
Habituation trials and individual looks.
| Presentation Type | N | Mean Look Duration (SD) | Mean Number of Looks (SD) | Mean Number of Looks per Trial (SD) | Mean Trial Duration (SD) | Mean Number of Trials (SD) |
|---|---|---|---|---|---|---|
| Audiovisual | 88 | 9.46 (12.34) | 27.72 (14.31) | 2.62 (2.34) | 24.75 (21.55) | 10.59 (3.07) |
| Visual Only | 39 | 8.78 (11.30) | 28.00 (12.70) | 2.67 (1.99) | 23.41 (20.70) | 10.56 (3.08) |
| Combined | 127 | 9.25 (12.03) | 27.80 (13.79) | 2.63 (2.24) | 24.36 (21.29) | 10.58 (3.06) |
Durations are in seconds. The mean number of trials includes the habituation trials and two post-habituation trials.
The audiovisual and the visual only conditions did not in the number of trials per infant, t(125) = .05, p = .96, the number of individual infant looks to the stimulus, t(125) = -0.17, p = .87, or their mean duration, t(125) = 0.58, p = .56.
Model predicting look duration with five previous looks (lags).
| Fixed Effects | Random Effects | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Model Parameters | ||||||||||
| Intercept | 0.75 | 0.01 | 53.78 | 126 | < .001 | 0.02 | 0.14 | 588.31 | 122 | < .001 |
| Lag 1 Duration | 0.10 | 0.02 | 4.64 | 126 | < .001 | 0.02 | 0.13 | 150.55 | 122 | .040 |
| Lag 2 Duration | 0.05 | 0.02 | 2.69 | 126 | .009 | 0.01 | 0.07 | 121.66 | 122 | > .50 |
| Lag 3 Duration | 0.05 | 0.02 | 2.24 | 126 | .027 | 0.01 | 0.11 | 138.93 | 122 | .140 |
| Lag 4 Duration | 0.05 | 0.02 | 2.24 | 126 | .027 | 0.01 | 0.12 | 130.11 | 122 | .291 |
| Lag 5 Duration | 0.09 | 0.02 | 5.20 | 126 | < .001 | 0.01 | 0.05 | 101.32 | 122 | > .50 |
The model describes the unique effects of the durations of previous five looks on the duration of the nth in a series of looks. Lag 1 refers to the immediately previous look, Lag 2 to the look previous to that, and so on until Lag 5. The model’s equation and unstructured (full) covariance matrix are reported in S2 Table.
Fig 2Temporal dependency.
Individual look durations are predicted by previous individual look durations (A–C) and trial durations are predicted by the previous trial duration (D). Durations are displayed in seconds on a log 10 scale. A. The modeled effect of five previous look durations predicts the duration of the nth in a series of looks (see Table 3). B. The modeled effect of look count (habituation) and previous look duration predicts the duration of the nth in a series of looks (see Table 4). C. The modeled effect of look count (habituation) and the duration of the last look of a previous trial predicts the duration of the first look of the next trial (see Table 5). D. The modeled effect of trial count (habituation) and previous trial duration predict the duration of the nth in a series of trial durations (see Table 6).
Final model predicting individual look durations.
| Fixed Effects | Random Effects | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Intercept | 0.83 | 0.02 | 53.89 | 126 | < .001 | 0.02 | 0.16 | 866.46 | 126 | < .001 |
| Log10 Look Count | -0.51 | 0.03 | -14.94 | 126 | < .001 | 0.07 | 0.27 | 314.48 | 126 | < .001 |
| Lag 1 Duration | 0.05 | 0.02 | 2.50 | 126 | .014 | 0.01 | 0.08 | 150.48 | 126 | .068 |
| 2546.53 | 10 | 3409 | 100.66 | < .001 | 2566.53 | 2581.86 | ||||
Individual look duration is uniquely predicted by log10 look count (habituation) and lag 1 duration (temporal dependency). The χ describes a comparison to a model with no temporal dependency (Lag 1) effects (see text). The inclusion of Log10 Look Count as a predictor accounted for 27.0% more variance than a model with the intercept alone. The inclusion of Lag 1 Duration as a predictor accounted for 0.6% more variance than a model with Log10 Look Count. For the model’s equation and unstructured (full) covariance matrix see S1 Text.
Final model predicting the first individual look of a habituation trial.
| Fixed Effects | Random Effects | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Intercept | 0.98 | 0.02 | 58.14 | 126 | < .001 | 0.03 | 0.16 | 450.26 | 126 | < .001 |
| Log10 Look Count | -0.62 | 0.04 | -14.53 | 126 | < .001 | 0.07 | 0.27 | 178.42 | 126 | .002 |
| Lag 1 Duration | 0.07 | 0.03 | 2.55 | 126 | .012 | 0.03 | 0.17 | 162.01 | 126 | .017 |
| 595.16 | 10 | 1215 | 146.26 | < .001 | 615.16 | 626.01 | ||||
The duration of the first individual look of a trial is uniquely predicted by log10 look count (habituation) and lag 1 duration (temporal dependency). The model uses the last look of one trial to predict the first look of the next trial in the habituation protocol. The χ describes a comparison to a model with no temporal dependency (Lag 1) effects (see text). The inclusion of Log10 Look Count as a predictor accounted for 40.8% more variance than a model with the intercept alone. The inclusion of Lag 1 Duration as a predictor accounted for 10.7% more variance than a model with Log10 Look Count. For the model equation and unstructured (full) covariance matrix see S1 Text.
Final Model Predicting Trial Durations.
| Fixed Effects | Random Effects | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Intercept | 1.17 | 0.02 | 60.26 | 126 | < .001 | 0.04 | 0.19 | 574.63 | 126 | < .001 |
| Log10 Trial Count | -0.81 | 0.06 | -14.11 | 126 | < .001 | 0.07 | 0.27 | 136.43 | 126 | .248 |
| Lag 1 Duration | 0.18 | 0.03 | 5.39 | 126 | < .001 | 0.02 | 0.14 | 116.07 | 126 | > .50 |
| 903.47 | 10 | 1217 | 116.73 | < .001 | 923.47 | 934.32 | ||||
Trial looking duration is uniquely predicted by log10 trial count (temporal dependency) and lag 1, the previous trial duration (temporal dependency). The χ describes a comparison to a model with no temporal dependency (Lag 1) effects (see text). The inclusion of Log10 Trial Count as a predictor accounted for 38.6% more variance than a model with the intercept alone. The inclusion of Lag 1 Duration as a predictor accounted for 5.6% more variance than a model with Log10 Trial Count. For the model’s equation and unstructured (full) covariance matrix see S1 Text.
Fig 3Individual infants’ temporal dependency parameters were derived from the final multilevel model (Table 4).
A. Infants with shorter mean look length had higher levels of temporal dependency, r(125) = -.42, p <.001. B. Using a median split, short lookers exhibited stronger temporal dependency than long lookers, t(125) = 5.28, p <.001. Bars indicate standard errors of the mean.