Inertia in value-driven attention.
Ontology highlight
ABSTRACT:
SUBMITTER: Liao MR
PROVIDER: S-EPMC7670862 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:When an otherwise inconspicuous stimulus is learned to predict a reward, this stimulus will automatically capture visual attention. This learned attentional bias is not specific to the precise object previously associated with reward, but can be observed for different stimuli that share a defining feature with the reward cue. Under certain circumstances, value-driven attentional biases can even transfer to new contexts in which the reward cues were not previously experienced, and can also be evident for different exemplars of a stimulus category, suggesting some degree of tolerance in the scope of the underlying bias. Whether a match to a reward-predictive feature is necessary to support value-driven attention, or whether similar-looking features also receive some degree of elevated priority following associative reward learning, remains an open question. Here, I examine the impact of learned associations between reward and red- and green-colored stimuli on the processing of other colors. The findings show that even though other colors experienced during training were non-predictive with respect to reward, the speed with which targets possessing these colors were identified in a subsequent test phase was affected by their similarity to the high-value color. Thus, value-driven attentional biases for stimulus features are imprecise, as would be predicted by a sensory gain model of value-driven attention.
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Project description:Importance:Enhanced selective attention toward nonsocial objects and impaired attention to social stimuli constitute key clinical features of autism spectrum disorder (ASD). Yet, the mechanisms associated with atypical selective attention in ASD are poorly understood, which limits the development of more effective interventions. In typically developing individuals, selective attention to social and nonsocial stimuli is associated with the informational value of the stimuli, which is typically learned over the course of repeated interactions with the stimuli. Objective:To examine value learning (VL) of social and nonsocial stimuli and its association with selective attention in preschoolers with and without ASD. Design, Setting, and Participants:This case-control study compared children with ASD vs children with developmental delay (DD) and children with typical development (TD) recruited between March 3, 2017, and June 13, 2018, at a university-based research laboratory. Participants were preschoolers with ASD, DD, or TD. Main Outcomes and Measures:Procedure consisted of an eye-tracking gaze-contingent VL task involving social (faces) and nonsocial (fractals) stimuli and consisting of baseline, training, and choice test phases. Outcome measures were preferential attention to stimuli reinforced (high value) vs not reinforced (low value) during training. The hypotheses were stated before data collection. Results:Included were 115 preschoolers with ASD (n?=?48; mean [SD] age, 38.30 [15.55] months; 37 [77%] boys), DD (n?=?31; mean [SD] age, 45.73 [19.49] months; 19 [61%] boys), or TD (n?=?36; mean [SD] age, 36.53 [12.39] months; 22 [61%] boys). The groups did not differ in sex distribution; participants with ASD or TD had similar chronological age; and participants with ASD or DD had similar verbal IQ and nonverbal IQ. After training, the ASD group showed preference for the high-value nonsocial stimuli (mean proportion, 0.61 [95% CI, 0.56-0.65]; P?<?.001) but not for the high-value social stimuli (mean proportion, 0.51 [95% CI, 0.46-0.56]; P?=?.58). In contrast, the DD and TD groups demonstrated preference for the high-value social stimuli (DD mean proportion, 0.59 [95% CI, 0.54-0.64]; P?=?.001 and TD mean proportion, 0.57 [95% CI, 0.53-0.61]; P?=?.002) but not for the high-value nonsocial stimuli (DD mean proportion, 0.52 [95% CI, 0.44-0.59]; P?=?.64 and TD mean proportion, 0.50 [95% CI, 0.44-0.57]; P?=?.91). Controlling for age and nonverbal IQ, autism severity was positively correlated with enhanced learning in the nonsocial domain (r?=?0.22; P?=?.03) and with poorer learning in the social domain (r?=?-0.26; P?=?.01). Conclusions and Relevance:Increased attention to objects in preschoolers with ASD may be associated with enhanced VL in the nonsocial domain. When paired with poor VL in the social domain, enhanced value-driven attention to objects may play a formative role in the emergence of autism symptoms by altering attentional priorities and thus learning opportunities in affected children.
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Project description:Sleep inertia is affected by circadian phase, with worse performance upon awakening from sleep during the biological night than biological day. Visual search/selective visual attention performance is known to be sensitive to sleep inertia and circadian phase. Individual differences exist in the circadian timing of habitual wake time, which may contribute to individual differences in sleep inertia. Because later chronotypes awaken at an earlier circadian phase, we hypothesized that later chronotypes would have worse visual search performance during sleep inertia than earlier chronotypes if awakened at habitual wake time. We analysed performance from 18 healthy participants [five females (22.1 ± 3.7 years; mean ± SD)] at ~1, 10, 20, 30, 40 and 60 min following electroencephalogram-verified awakening from an 8 h in-laboratory sleep opportunity. Cognitive throughput and reaction times of correct responses were impaired by sleep inertia and took ~10-30 min to improve after awakening. Regardless whether chronotype was defined by dim light melatonin onset or mid-sleep clock hour on free days, derived from the Munich ChronoType Questionnaire, the duration of sleep inertia for cognitive throughput and reaction times was longer for later chronotypes (n = 7) compared with earlier chronotypes (n = 7). Specifically, performance for earlier chronotypes showed significant improvement within ~10-20 min after awakening, whereas performance for later chronotypes took ~30 min or longer to show significant improvement (P < 0.05). Findings have implications for decision making immediately upon awakening from sleep, and are consistent with circadian theory suggesting that sleep inertia contributes to longer-lasting impairments in morning performance in later chronotypes.
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