The interplay of spatial attentional biases and mental codes in VSTM: Developmentally informed hypotheses.

Shimi, Andria; Scerif, Gaia

doi:10.1037/a0039057

Cited by 16 publications

(22 citation statements)

References 106 publications

(169 reference statements)

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“…In this paradigm, visual search for targets embedded in repeated scenes is more efficient compared with visual search for a novel target not associated with a contextual memory trace. Furthermore, attention orienting is most effective for memoranda for which familiar representations are available in long-term memory, both in children and in adults 98 .…”

Section: Visual Attention Development and Memorymentioning

confidence: 99%

The attentive brain: insights from developmental cognitive neuroscience

2015

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Visual attention functions as a filter to select environmental information for learning and memory, making it the first step in the eventual cascade of thought and action systems. Here, we review studies of typical and atypical visual attention development and explain how they offer insights into the mechanisms of adult visual attention. We detail interactions between visual processing and visual attention, as well as the contribution of visual attention to memory. Finally, we discuss genetic mechanisms underlying attention disorders and how attention may be modified by training.

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Section: Visual Attention Development and Memorymentioning

confidence: 99%

The attentive brain: insights from developmental cognitive neuroscience

2015

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“…Recent work has also started to explore the extent to which children are able to direct their attention towards aspects of a task environment that are particularly goal-relevant (e.g. Cowan, Fristoe, Elliott, Brunner, & Saults, 2006;Cowan, Morey, AuBuchon, Zwilling, & Gilchrist, 2010;Shimi & Scerif, 2015;Shimi, Nobre, Astle, & Scerif, 2014). For example, Shimi et al (2014) presented 7 year-olds, 11 year-olds and young adults with simultaneous four-object arrays, followed by a single recognition probe, while manipulating the timing (before versus after encoding) and location (central versus peripheral) of visual cues orienting participants to a particular item in the array.…”

Section: Introductionmentioning

confidence: 99%

The limits of visual working memory in children: Exploring prioritization and recency effects with sequential presentation.

Berry¹,

Waterman²,

Baddeley³

et al. 2018

Developmental Psychology

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Recent research has demonstrated that, when instructed to prioritize a serial position in visual working memory, adults are able to boost performance for this selected item, at a cost to nonprioritized items (e.g. Hu et al., 2014). While executive control appears to play an important role in this ability, the increased likelihood of recalling the most recently presented item (i.e. the recency effect) is relatively automatic, possibly driven by perceptual mechanisms. In three experiments 7 to 10-year-old's ability to prioritize items in working memory was investigated using a sequential visual task (total N = 208). The relationship between individual differences in working memory and performance on the experimental task was also explored. Participants were unable to prioritize the first (Experiments 1 & 2) or final (Experiment 3) item in a 3-item sequence, while large recency effects for the final item were consistently observed across all experiments. The absence of a priority boost across three experiments indicates that children may not have the necessary executive resources to prioritize an item within a visual sequence, when directed to do so. In contrast, the consistent recency boosts for the final item indicate that children show automatic memory benefits for the most recently encountered stimulus. Finally, for the baseline condition in which children were instructed to remember all three items equally, additional working memory measures predicted performance at the first and second but not the third serial position, further supporting the proposed automaticity of the recency effect in visual working memory.

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“…VWM increases dramatically with age (Gathercole, 1999 ; Cowan et al, 2005 ) with accompanied maturational changes in the brain (Kwon et al, 2002 ; Klingberg et al, 2002 ; Luna et al, 2004 ; Crone and Ridderinkhof, 2011 ; Jolles et al, 2011 ; Barriga-Paulino et al, 2014 ). Driven by the advances in the adult cognitive neuroscience literature and given that selective attention also undergoes dramatic improvement during childhood (Plude et al, 1994 ; Scerif, 2010 ; Johnson, 2011 ; Stevens and Bavelier, 2012 ), recent developmental research has also started examining the influence of visual attention mechanisms on the developing VWM system (Olesen et al, 2007 ; Cowan et al, 2010 ; Ross-Sheehy et al, 2011 ; Sander et al, 2011 ; Wendelken et al, 2011 ; Astle et al, 2012 , 2014 ; Markant and Amso, 2013 ; Shimi et al, 2014a , b ; Shimi and Scerif, 2015 ), rather than focusing solely on increases in VWM storage. Extending the adult findings to the developmental domain, in a recent study, Shimi et al ( 2014a ) demonstrated that age-related differences in the temporal dynamics of attentional orienting mechanisms before or after encoding items in VWM contributed to differences in VWM performance between children and adults.…”

Section: Introductionmentioning

confidence: 99%

ERP markers of target selection discriminate children with high vs. low working memory capacity

Shimi

Nobre

Scerif

2015

Front. Syst. Neurosci.

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Selective attention enables enhancing a subset out of multiple competing items to maximize the capacity of our limited visual working memory (VWM) system. Multiple behavioral and electrophysiological studies have revealed the cognitive and neural mechanisms supporting adults’ selective attention of visual percepts for encoding in VWM. However, research on children is more limited. What are the neural mechanisms involved in children’s selection of incoming percepts in service of VWM? Do these differ from the ones subserving adults’ selection? Ten-year-olds and adults used a spatial arrow cue to select a colored item for later recognition from an array of four colored items. The temporal dynamics of selection were investigated through EEG signals locked to the onset of the memory array. Both children and adults elicited significantly more negative activity over posterior scalp locations contralateral to the item to-be-selected for encoding (N2pc). However, this activity was elicited later and for longer in children compared to adults. Furthermore, although children as a group did not elicit a significant N2pc during the time-window in which N2pc was elicited in adults, the magnitude of N2pc during the “adult time-window” related to their behavioral performance during the later recognition phase of the task. This in turn highlights how children’s neural activity subserving attention during encoding relates to better subsequent VWM performance. Significant differences were observed when children were divided into groups of high vs. low VWM capacity as a function of cueing benefit. Children with large cue benefits in VWM capacity elicited an adult-like contralateral negativity following attentional selection of the to-be-encoded item, whereas children with low VWM capacity did not. These results corroborate the close coupling between selective attention and VWM from childhood and elucidate further the attentional mechanisms constraining VWM performance in children.

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The interplay of spatial attentional biases and mental codes in VSTM: Developmentally informed hypotheses.

Cited by 16 publications

References 106 publications

The attentive brain: insights from developmental cognitive neuroscience

The attentive brain: insights from developmental cognitive neuroscience

The limits of visual working memory in children: Exploring prioritization and recency effects with sequential presentation.

ERP markers of target selection discriminate children with high vs. low working memory capacity

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