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It is well established that the formation of memories for life's experiences-episodic memory-is influenced by how we attend to those experiences, yet the neural mechanisms by which attention shapes episodic encoding are still unclear. We investigated how top-down and bottom-up attention contribute to memory encoding of visual objects in humans by m...
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... that stimulus-driven reorienting of attention triggers recruitment of the dorsal attention network (Corbetta et al., 2002; Giessing et al., 2006; Corbetta et al., 2008; Shulman et al., 2009). That is, effects revealed by this contrast may reflect the consequences of a stimulus-driven salience calculation (mediated in part by TPJ), which in turn serves to drive shifts in the locus of visuospatial attention (partially mediated by an FEF-IPS/SPL network) (e.g., Burrows & Moore, 2009; Shulman et al., 2009). It is notable that these ‘validity effects’ appear to overlap with the CSI-varying cue-related effects in medial—but not lateral—IPS (Fig. 2, yellow). This apparent dissociation would extend recent evidence suggesting that lateral and medial IPS functionally differ (Nelson et al., 2010), with mIPS differentially tracking demands on top-down attention (e.g., Hutchinson et al. 2009; Sestieri et al., 2010; Uncapher et al., 2010). Here, mIPS was engaged during the components of the Posner task that are thought to recruit top-down attention (most directly evidenced by the parametrically modulated cue-related contrast, and indirectly evidenced by the validity contrast, for reasons described in the previous paragraph). Interestingly, this mIPS/SPL region appears to anatomically overlap with that revealed in a recent meta-analysis of the top-down attention literature (compare the present mIPS/SPL top-down effects in Fig. 2, yellow+green, to the top-down attention ALE map in Fig. 1 of Uncapher et al., 2010). Importantly, the apparent selectivity of the present top-down effects to mIPS/SPL, not including lateral IPS, was confirmed by a disjunction analysis (i.e., identification of regions that exhibit significant effects in one contrast but not in the other). To identify regions that exhibited validity effects but not CSI-varying cue-related activity, we masked the validity contrast (p < .001) with the parametrically modulated cue-related contrast (thresholded at a lenient level, p < .10, to create a stringent mask). Importantly, left lateral IPS survived this disjunction analysis, indicating that it exhibited validity effects but no evidence of cue- related activity. We also performed the reverse disjunction analysis, masking the cue-related contrast (p < .001) with the validity contrast (thresholded at a lenient level, p < .10). This procedure did not reveal a disjunction in left mIPS/SPL (nor in FEF), suggesting that medial (and not lateral) parietal subregions are engaged during both the cue-related and validity contrasts (again, this finding is compatible with the view that top-down attention mechanisms can be triggered by stimulus-driven salience that drives the reorienting of attention). Together, these findings support the hypothesis that lateral and medial IPS functionally differ, with mIPS/SPL differentially tracking demands on top-down attention. Neural correlates of episodic encoding— Prior studies identifying the neural correlates of encoding have contrasted study items that were subsequently remembered vs. forgotten (e.g., Brewer et al., 1998; Wagner et al., 1998; Henson et al., 1999; for reviews, see Wagner et al., 1999; Paller & Wagner, 2002; Spaniol et al., 2009). Accordingly, we first analyzed stimulus-related activity on trials most analogous to prior subsequent memory experiments, namely trials on which the object appeared in an expected location (validly cued trials), and was later remembered with high confidence (HCH) vs. later forgotten (M). Consistent with the literature on MTL and PPC encoding effects (for respective reviews, see Davachi, 2006; Uncapher & Wagner, 2009), this contrast revealed positive subsequent memory effects (HCH > M) in multiple regions, including bilateral hippocampus and right posterior IPS (Fig. 3; Table 4). Also evident were bilateral clusters that encompassed fusiform and lateral occipital (LO) cortex (Fig. 3); these ventral temporal-occipital foci appear to include the lateral occipital complex (LOC), which is implicated in visual object representation (e.g., Malach et al., 1995; Grill-Spector, Kourtzi, Kanwisher, 2001; Grill- Spector and Malach, 2004). In support of this interpretation, an analysis of common objects vs. greebles identified a large swath of activity overlapping these fusiform and LO subsequent memory effects (available from the corresponding author upon ...
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... that stimulus-driven reorienting of attention triggers recruitment of the dorsal attention network (Corbetta et al., 2002; Giessing et al., 2006; Corbetta et al., 2008; Shulman et al., 2009). That is, effects revealed by this contrast may reflect the consequences of a stimulus-driven salience calculation (mediated in part by TPJ), which in turn serves to drive shifts in the locus of visuospatial attention (partially mediated by an FEF-IPS/SPL network) (e.g., Burrows & Moore, 2009; Shulman et al., 2009). It is notable that these ‘validity effects’ appear to overlap with the CSI-varying cue-related effects in medial—but not lateral—IPS (Fig. 2, yellow). This apparent dissociation would extend recent evidence suggesting that lateral and medial IPS functionally differ (Nelson et al., 2010), with mIPS differentially tracking demands on top-down attention (e.g., Hutchinson et al. 2009; Sestieri et al., 2010; Uncapher et al., 2010). Here, mIPS was engaged during the components of the Posner task that are thought to recruit top-down attention (most directly evidenced by the parametrically modulated cue-related contrast, and indirectly evidenced by the validity contrast, for reasons described in the previous paragraph). Interestingly, this mIPS/SPL region appears to anatomically overlap with that revealed in a recent meta-analysis of the top-down attention literature (compare the present mIPS/SPL top-down effects in Fig. 2, yellow+green, to the top-down attention ALE map in Fig. 1 of Uncapher et al., 2010). Importantly, the apparent selectivity of the present top-down effects to mIPS/SPL, not including lateral IPS, was confirmed by a disjunction analysis (i.e., identification of regions that exhibit significant effects in one contrast but not in the other). To identify regions that exhibited validity effects but not CSI-varying cue-related activity, we masked the validity contrast (p < .001) with the parametrically modulated cue-related contrast (thresholded at a lenient level, p < .10, to create a stringent mask). Importantly, left lateral IPS survived this disjunction analysis, indicating that it exhibited validity effects but no evidence of cue- related activity. We also performed the reverse disjunction analysis, masking the cue-related contrast (p < .001) with the validity contrast (thresholded at a lenient level, p < .10). This procedure did not reveal a disjunction in left mIPS/SPL (nor in FEF), suggesting that medial (and not lateral) parietal subregions are engaged during both the cue-related and validity contrasts (again, this finding is compatible with the view that top-down attention mechanisms can be triggered by stimulus-driven salience that drives the reorienting of attention). Together, these findings support the hypothesis that lateral and medial IPS functionally differ, with mIPS/SPL differentially tracking demands on top-down attention. Neural correlates of episodic encoding— Prior studies identifying the neural correlates of encoding have contrasted study items that were subsequently remembered vs. forgotten (e.g., Brewer et al., 1998; Wagner et al., 1998; Henson et al., 1999; for reviews, see Wagner et al., 1999; Paller & Wagner, 2002; Spaniol et al., 2009). Accordingly, we first analyzed stimulus-related activity on trials most analogous to prior subsequent memory experiments, namely trials on which the object appeared in an expected location (validly cued trials), and was later remembered with high confidence (HCH) vs. later forgotten (M). Consistent with the literature on MTL and PPC encoding effects (for respective reviews, see Davachi, 2006; Uncapher & Wagner, 2009), this contrast revealed positive subsequent memory effects (HCH > M) in multiple regions, including bilateral hippocampus and right posterior IPS (Fig. 3; Table 4). Also evident were bilateral clusters that encompassed fusiform and lateral occipital (LO) cortex (Fig. 3); these ventral temporal-occipital foci appear to include the lateral occipital complex (LOC), which is implicated in visual object representation (e.g., Malach et al., 1995; Grill-Spector, Kourtzi, Kanwisher, 2001; Grill- Spector and Malach, 2004). In support of this interpretation, an analysis of common objects vs. greebles identified a large swath of activity overlapping these fusiform and LO subsequent memory effects (available from the corresponding author upon ...
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... attention seeds show connectivity that differs according to encoding success or failure. A , Regions whose connectivity with L mIPS/SPL (green sphere, peak mIPS/SPL coordinates of the top-down attention contrast illustrated in Fig 2) was stronger during preparatory periods of trials resulting in objects being remembered vs. forgotten (‘positive subsequent connectivity effects’; warm colors). Regions showing the opposite effect, or stronger connectivity with L mIPS/SPL during preparatory periods leading to forgotten vs. remembered objects (‘negative subsequent connectivity effects’) are displayed in cool colors [Note the small cluster in dorsal AnG (coordinates 39, -57, 33) is in fact spatially contiguous with the large ventral AnG cluster that has been surface-rendered dorsally (see Table 6 for details)]. Scatter plot illustrates that individual differences in the strength of the positive subsequent connectivity effect in LO/Fus during encoding correlates with across-subject differences in later memory performance, such that the stronger the mIPS/SPL—LO/Fus connectivity, the superior the later memory performance. B , Regions whose connectivity with L or R TPJ (red spheres, peak TPJ coordinates from the bottom-up attention contrast illustrated in Fig 2) was stronger during the presentation of objects that were later remembered vs. forgotten, and vice versa (positive and negative subsequent connectivity effects). Coloring scheme same as used in A ...
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... attention seeds show connectivity that differs according to encoding success or failure. A , Regions whose connectivity with L mIPS/SPL (green sphere, peak mIPS/SPL coordinates of the top-down attention contrast illustrated in Fig 2) was stronger during preparatory periods of trials resulting in objects being remembered vs. forgotten (‘positive subsequent connectivity effects’; warm colors). Regions showing the opposite effect, or stronger connectivity with L mIPS/SPL during preparatory periods leading to forgotten vs. remembered objects (‘negative subsequent connectivity effects’) are displayed in cool colors [Note the small cluster in dorsal AnG (coordinates 39, -57, 33) is in fact spatially contiguous with the large ventral AnG cluster that has been surface-rendered dorsally (see Table 6 for details)]. Scatter plot illustrates that individual differences in the strength of the positive subsequent connectivity effect in LO/Fus during encoding correlates with across-subject differences in later memory performance, such that the stronger the mIPS/SPL—LO/Fus connectivity, the superior the later memory performance. B , Regions whose connectivity with L or R TPJ (red spheres, peak TPJ coordinates from the bottom-up attention contrast illustrated in Fig 2) was stronger during the presentation of objects that were later remembered vs. forgotten, and vice versa (positive and negative subsequent connectivity effects). Coloring scheme same as used in A ...
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... be introduced, however, if subsequent memory analyses were expanded to include all recognized items (rather than restricted to HCHs), as source memory was better for all hits in the valid vs. invalid conditions (t 17 = 1.9, p<.04). This finding of biased source memory for all hits, but unbiased source memory for high confident hits, reinforces the restriction of subsequent memory analyses to high confident hits. Finally, study task RTs conditionalized as a function of later memory performance revealed that study RTs did not differ as a function of subsequent memory (Table 1; valid HCH vs. M: t 17 < 1; invalid HCH vs. M: t 17 < 1). This finding rules out the possibility that the neural subsequent memory effects were simply a consequence of the amount of time spent initially processing study items (i.e., differential ‘duty cycles’). The present experiment was designed to directly assess the degree to which top-down and bottom-up attention mechanisms contribute to the formation of event memories. Our analysis strategy first considered the factors of attention and encoding separately, and then examined the relationship between them by (a) investigating regional overlap between attention and encoding effects, and (b) investigating connectivity effects. Neural correlates of top-down and bottom-up attention— We first examined whether our attention paradigm gave rise to patterns of activity similar to those observed in prior Posner cueing studies (which primarily used detection tasks with repeated simple shapes, whereas our paradigm included a discrimination task and trial-unique meaningful objects). Based on prior studies, top-down attention effects were predicted to (a) be elicited by the arrow cues to shift attention, and (b) vary in duration according to the interval over which attention was maintained (the variable CSI) (see Experimental procedures). Supporting these predictions, a parametric modulation analysis revealed that cue-related activity (cue > fixation) varied positively according to CSI in the frontal eye fields (FEF), the left medial intraparietal sulcus (mIPS), extending into superior parietal lobule (SPL) (Fig. 2; Table 3). These findings are consistent with an extensive literature suggesting that these fronto-parietal regions form a ‘dorsal attention network’ (e.g., Corbetta et al., 1993; Nobre et al., 1997; Kastner et al., 1999; Hopfinger et al., 2000; Sylvester et al., 2007; reviewed in Corbetta et al., 2008). Confirming the outcome of the parametric modulation analysis, analysis of non-modulated cue effects (i.e., the canonical cue-related HRF) revealed the same set of regions (bilateral FEF and left mIPS/SPL). Notably, this contrast also identified an additional set of regions in visual cortex (bilateral visual cortex, centered on [12 − 99 6] and [ − 18 − 93 6], Z = 4.17), consistent with the idea that the non-modulated effects reflect a combination of low-level visual and high-level attention-related processes. Finally, to determine which non-modulated effects exhibited a sustained response, we inclusively masked the non-modulated effects (p < .001) with the dispersion derivative contrast (p < .05). The outcome of this procedure revealed 34 voxels in mIPS/SPL (centered on [ − 24 − 57 54], Z = 3.66) that showed a more sustained response than the canonical cue-related HRF, further confirming the findings from the parametric modulation analysis. To identify neural correlates of bottom-up attention, objects appearing in unexpected locations were contrasted with those appearing in expected locations (i.e., invalidly > validly cued objects). Multiple regions were more active when the object was invalidly cued, including bilateral temporoparietal junction (TPJ) (Fig. 2; Table 3). This pattern is consistent with the proposal that TPJ is a key component of a ‘ventral attention network’ that mediates stimulus-driven reorienting of attention (Corbetta et al., 2008). Additional regions revealed in this contrast included FEF and IPS (Fig. 2; Table 3), a finding consistent with ...
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... be introduced, however, if subsequent memory analyses were expanded to include all recognized items (rather than restricted to HCHs), as source memory was better for all hits in the valid vs. invalid conditions (t 17 = 1.9, p<.04). This finding of biased source memory for all hits, but unbiased source memory for high confident hits, reinforces the restriction of subsequent memory analyses to high confident hits. Finally, study task RTs conditionalized as a function of later memory performance revealed that study RTs did not differ as a function of subsequent memory (Table 1; valid HCH vs. M: t 17 < 1; invalid HCH vs. M: t 17 < 1). This finding rules out the possibility that the neural subsequent memory effects were simply a consequence of the amount of time spent initially processing study items (i.e., differential ‘duty cycles’). The present experiment was designed to directly assess the degree to which top-down and bottom-up attention mechanisms contribute to the formation of event memories. Our analysis strategy first considered the factors of attention and encoding separately, and then examined the relationship between them by (a) investigating regional overlap between attention and encoding effects, and (b) investigating connectivity effects. Neural correlates of top-down and bottom-up attention— We first examined whether our attention paradigm gave rise to patterns of activity similar to those observed in prior Posner cueing studies (which primarily used detection tasks with repeated simple shapes, whereas our paradigm included a discrimination task and trial-unique meaningful objects). Based on prior studies, top-down attention effects were predicted to (a) be elicited by the arrow cues to shift attention, and (b) vary in duration according to the interval over which attention was maintained (the variable CSI) (see Experimental procedures). Supporting these predictions, a parametric modulation analysis revealed that cue-related activity (cue > fixation) varied positively according to CSI in the frontal eye fields (FEF), the left medial intraparietal sulcus (mIPS), extending into superior parietal lobule (SPL) (Fig. 2; Table 3). These findings are consistent with an extensive literature suggesting that these fronto-parietal regions form a ‘dorsal attention network’ (e.g., Corbetta et al., 1993; Nobre et al., 1997; Kastner et al., 1999; Hopfinger et al., 2000; Sylvester et al., 2007; reviewed in Corbetta et al., 2008). Confirming the outcome of the parametric modulation analysis, analysis of non-modulated cue effects (i.e., the canonical cue-related HRF) revealed the same set of regions (bilateral FEF and left mIPS/SPL). Notably, this contrast also identified an additional set of regions in visual cortex (bilateral visual cortex, centered on [12 − 99 6] and [ − 18 − 93 6], Z = 4.17), consistent with the idea that the non-modulated effects reflect a combination of low-level visual and high-level attention-related processes. Finally, to determine which non-modulated effects exhibited a sustained response, we inclusively masked the non-modulated effects (p < .001) with the dispersion derivative contrast (p < .05). The outcome of this procedure revealed 34 voxels in mIPS/SPL (centered on [ − 24 − 57 54], Z = 3.66) that showed a more sustained response than the canonical cue-related HRF, further confirming the findings from the parametric modulation analysis. To identify neural correlates of bottom-up attention, objects appearing in unexpected locations were contrasted with those appearing in expected locations (i.e., invalidly > validly cued objects). Multiple regions were more active when the object was invalidly cued, including bilateral temporoparietal junction (TPJ) (Fig. 2; Table 3). This pattern is consistent with the proposal that TPJ is a key component of a ‘ventral attention network’ that mediates stimulus-driven reorienting of attention (Corbetta et al., 2008). Additional regions revealed in this contrast included FEF and IPS (Fig. 2; Table 3), a finding consistent with ...
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... be introduced, however, if subsequent memory analyses were expanded to include all recognized items (rather than restricted to HCHs), as source memory was better for all hits in the valid vs. invalid conditions (t 17 = 1.9, p<.04). This finding of biased source memory for all hits, but unbiased source memory for high confident hits, reinforces the restriction of subsequent memory analyses to high confident hits. Finally, study task RTs conditionalized as a function of later memory performance revealed that study RTs did not differ as a function of subsequent memory (Table 1; valid HCH vs. M: t 17 < 1; invalid HCH vs. M: t 17 < 1). This finding rules out the possibility that the neural subsequent memory effects were simply a consequence of the amount of time spent initially processing study items (i.e., differential ‘duty cycles’). The present experiment was designed to directly assess the degree to which top-down and bottom-up attention mechanisms contribute to the formation of event memories. Our analysis strategy first considered the factors of attention and encoding separately, and then examined the relationship between them by (a) investigating regional overlap between attention and encoding effects, and (b) investigating connectivity effects. Neural correlates of top-down and bottom-up attention— We first examined whether our attention paradigm gave rise to patterns of activity similar to those observed in prior Posner cueing studies (which primarily used detection tasks with repeated simple shapes, whereas our paradigm included a discrimination task and trial-unique meaningful objects). Based on prior studies, top-down attention effects were predicted to (a) be elicited by the arrow cues to shift attention, and (b) vary in duration according to the interval over which attention was maintained (the variable CSI) (see Experimental procedures). Supporting these predictions, a parametric modulation analysis revealed that cue-related activity (cue > fixation) varied positively according to CSI in the frontal eye fields (FEF), the left medial intraparietal sulcus (mIPS), extending into superior parietal lobule (SPL) (Fig. 2; Table 3). These findings are consistent with an extensive literature suggesting that these fronto-parietal regions form a ‘dorsal attention network’ (e.g., Corbetta et al., 1993; Nobre et al., 1997; Kastner et al., 1999; Hopfinger et al., 2000; Sylvester et al., 2007; reviewed in Corbetta et al., 2008). Confirming the outcome of the parametric modulation analysis, analysis of non-modulated cue effects (i.e., the canonical cue-related HRF) revealed the same set of regions (bilateral FEF and left mIPS/SPL). Notably, this contrast also identified an additional set of regions in visual cortex (bilateral visual cortex, centered on [12 − 99 6] and [ − 18 − 93 6], Z = 4.17), consistent with the idea that the non-modulated effects reflect a combination of low-level visual and high-level attention-related processes. Finally, to determine which non-modulated effects exhibited a sustained response, we inclusively masked the non-modulated effects (p < .001) with the dispersion derivative contrast (p < .05). The outcome of this procedure revealed 34 voxels in mIPS/SPL (centered on [ − 24 − 57 54], Z = 3.66) that showed a more sustained response than the canonical cue-related HRF, further confirming the findings from the parametric modulation analysis. To identify neural correlates of bottom-up attention, objects appearing in unexpected locations were contrasted with those appearing in expected locations (i.e., invalidly > validly cued objects). Multiple regions were more active when the object was invalidly cued, including bilateral temporoparietal junction (TPJ) (Fig. 2; Table 3). This pattern is consistent with the proposal that TPJ is a key component of a ‘ventral attention network’ that mediates stimulus-driven reorienting of attention (Corbetta et al., 2008). Additional regions revealed in this contrast included FEF and IPS (Fig. 2; Table 3), a finding consistent with ...
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Citations
... In research with young adults, there is substantial evidence to support that attentional control is important for memory (e.g., Aly & Turk-Browne, 2016a, 2016bNoonan et al., 2016;Uncapher et al., 2011;Uncapher & Rugg, 2005). There has been less exploration of how attention and memory interact in children, however there is some literature to suggest that attentional processes affect children's memory performance as well (Kee & Nakayama, 1980;Shing et al., 2008). ...
... The present focus on factors driving age-related declines in neural selectivity revealed that topdown attention during encoding (a) predicts subsequent memory (28,30,65,92), (b) modulates neural selectivity (17,22,26), (c) does not vary with plasma or CSF biomarkers of preclinical AD, and (d) partially accounts for age-independent and age-related variability in memory through its impact on neural selectivity. Controlling for age, CU older adults with greater memory-related neural activity in the DAN demonstrated higher neural selectivity during subsequently remembered events, with the DAN SME being the top predictor of variance in neural selectivity. ...
Human aging affects the ability to remember new experiences, in part, because of altered neural function during memory formation. One potential contributor to age-related memory decline is diminished neural selectivity -- i.e., a decline in the differential response of cortical regions to preferred vs. non-preferred stimuli during event perception -- yet the factors driving variability in neural selectivity with age remain unclear. We examined the impact of top-down attention and preclinical Alzheimer's disease (AD) pathology on neural selectivity during memory encoding in 156 cognitively unimpaired older participants who underwent fMRI while performing a word-face and word-scene associative memory task. Neural selectivity in face- and place-selective cortical regions was greater during events that were later remembered compared to forgotten. Critically, neural selectivity during learning positively scaled with memory-related variability in top-down attention, whereas selectivity negatively related to early AD pathology, evidenced by elevated plasma pTau181. Path analysis revealed that neural selectivity at encoding mediated the effects of age, top-down attention, and pTau181 on associative memory. Collectively, these data reveal multiple pathways that contribute to memory differences among older adults -- AD-independent reductions in top-down attention and AD-related pathology alter the precision of cortical representations of events during experience, with consequences for remembering.
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Introduction:
Children with specific language impairment (SLI) have difficulties in different speech and language domains. Electrophysiological studies have documented that auditory processing in children with SLI is atypical and probably caused by delayed and abnormal auditory maturation. During the resting state, or different auditory tasks, children with SLI show low or high beta spectral power, which could be a clinical correlate for investigating brain rhythms.
Methods:
The aim of this study was to examine the electrophysiological cortical activity of the beta rhythm while listening to words and nonwords in children with SLI in comparison to typical development (TD) children. The participants were 50 children with SLI, aged 4 and 5 years, and 50 age matched TD children. The children were divided into two subgroups according to age: (1) children 4 years of age; (2) children 5 years of age.
Results:
The older group differed from the younger group in beta auditory processing, with increased values of beta spectral power in the right frontal, temporal, and parietal regions. In addition, children with SLI have higher beta spectral power than TD children in the bilateral temporal regions.
Conclusion:
Complex beta auditory activation in TD and SLI children indicates the presence of early changes in functional brain connectivity.
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Associative memory improves during childhood, suggesting an age-related improvement in the binding mechanism responsible for linking information together. However, tasks designed to measure associative memory not only measure binding, but also place demands on attention. This makes it difficult to dissociate age-related improvements in memory from the development of attention. One way to reduce attentional demands is to test memory implicitly versus explicitly. In this study, children (8-, 10-, and 12-years-old) completed separate implicit and explicit associative memory tests. For the implicit task, children incidentally encoded pairs of objects by making an object categorization decision. At test, they completed the same task, but unbeknownst to the participants, the pairs were either intact, rearranged, or new. Next, children completed another incidental encoding phase, then an explicit test in which they indicated whether the pairs were intact, rearranged, or new. For the implicit test, all age groups had faster reaction times for intact than rearranged pairs (indicative of implicit associative memory). In the explicit test, memory performance (d’) improved with age. A separate measure of attention related to performance in both the explicit and implicit tasks. Together, these results support that attentional mechanisms are responsible for age-related improvements in associative memory.
... Imaging Neuroscience, Volume 2, 2024 studies comparing encoding under high and low attention conditions (e.g., full versus divided attention) supported this hypothesis. In these investigations, significant effects consistently emerged within diverse sensory-perceptual regions and the lateral PFC ( Kensinger et al., 2003;Uncapher & Rugg, 2005Uncapher et al., 2011), whereas they appeared more rarely within the hippocampus ( Uncapher & Rugg, 2008. The putative regional distinctions in attentional impact explain why the meta-analysis presented compelling evidence to support the attentional and semantic hypotheses while failing to substantiate the hippocampal hypothesis. ...
The subsequent memory paradigm is a fundamental tool in neuroimaging investigations of encoding processes. Although some studies have contrasted remembered trials with forgotten ones, others have focused on strongly remembered trials versus forgotten ones. This study employed a meta-analytic approach to juxtapose the effects observed in the two types of contrast. Three distinct perspectives on memory formation—semantic elaboration, attentional focus, and hippocampal processing—yield diverse hypotheses about the regions responsible for the formation of strong memories. The meta-analysis yielded evidence supporting the attentional and semantic hypotheses while failing to substantiate the hippocampal hypothesis. The discussion section integrates these varied perspectives into a coherent view, culminating in the proposal of a model called the Significance-driven and Attention-driven Memory (SAM). Several pivotal postulates underpin the SAM model. First, it establishes a link between fluctuations in the trial-to-trial encoding performance and continuous variations in sustained attention. Second, the model contends that attention exerts a potent influence on both perceptual and semantic processing, while its impact on hippocampal processing remains moderate. Lastly, the model accentuates the heightened role of the hippocampus in significance-driven encoding, as opposed to attention-driven encoding. From a specific perspective, the model’s value lies in promoting a holistic understanding of the current extensive meta-analytic results. In a more comprehensive context, the model introduces an integrated framework that synthesizes various encoding-related cognitive and neural processes into a cohesive and unified perspective.
... Previous research has implicated this region in successful encoding (Uncapher and Wagner 2009;Lee et al. 2017;Rugg and King 2018), especially for multisensory memories (Bonnici et al. 2016; Jablonowski and Rose 2022. The angular gyrus identifies cross-modal information perceived as behaviorally self-relevant (Cabeza et al. 2008;Singh-Curry and Husain 2009;Uncapher et al. 2011), and integrates it into a common egocentric framework to support re-experiencing during retrieval (Yazar et al. 2014;Bonnici et al. 2018;Bréchet et al. 2018;Humphreys et al. 2021). We add to this literature by showing that multisensory signals underpinning a stable sense of body ownership frames how the angular gyrus encodes an event. ...
How is the fundamental sense of one’s body, a basic aspect of selfhood, incorporated into memories for events? Disrupting bodily self-awareness during encoding impairs functioning of the left posterior hippocampus during retrieval, which implies weakened encoding. However, how changes in bodily self-awareness influence neural encoding is unknown. We investigated how the sense of body ownership, a core aspect of the bodily self, impacts encoding in the left posterior hippocampus and additional core memory regions including the angular gyrus. Furthermore, we assessed the degree to which memories are reinstated according to body ownership during encoding and vividness during retrieval as a measure of memory strength. We immersed participants in naturalistic scenes where events unfolded while we manipulated feelings of body ownership with a full-body-illusion during functional magnetic resonance imaging scanning. One week later, participants retrieved memories for the videos during functional magnetic resonance imaging scanning. A whole brain analysis revealed that patterns of activity in regions including the right hippocampus and angular gyrus distinguished between events encoded with strong versus weak body ownership. A planned region-of-interest analysis showed that patterns of activity in the left posterior hippocampus specifically could predict body ownership during memory encoding. Using the wider network of regions sensitive to body ownership during encoding and the left posterior hippocampus as separate regions-of-interest, we observed that patterns of activity present at encoding were reinstated more during the retrieval of events encoded with strong body ownership and high memory vividness. Our results demonstrate how the sense of physical self is bound within an event during encoding, which facilitates reactivation of a memory trace during retrieval.
... We also detected activations in the right cerebellum and the left primary motor cortex (BA4), reflecting the need for a motor response from the participants. We further found bilateral activation of the insula, the anterior IPS (Fig. 1a) and the dorso-posterior thalamus (Fig. 1b), which are implicated in error awareness and salience processing 17 , top-down regulation of attention 18 and target detection 19 , respectively. ...
... Based on this, we hypothesized that non-visual effects of light on the posterior thalamus/pulvinar could greatly modulate the activity of top-down attention-related areas, such as IPS 18 , resulting in improved alertness and attention to an ongoing auditory attentional task such as the oddball. Previous human fMRI studies identified the posterior thalamus/pulvinar as the area most consistently affected by light exposure during nonvisual cognitive tasks 7,10-12 . ...
Exposure to blue wavelength light stimulates alertness and performance by modulating a widespread set of task-dependent cortical and subcortical areas. How light affects the crosstalk between brain areas to trigger this stimulating effect is not established. Here we record the brain activity of 19 healthy young participants (24.05±2.63; 12 women) while they complete an auditory attentional task in darkness or under an active (blue-enriched) or a control (orange) light, in an ultra-high-field 7 Tesla MRI scanner. We test if light modulates the effective connectivity between an area of the posterior associative thalamus, encompassing the pulvinar, and the intraparietal sulcus (IPS), key areas in the regulation of attention. We find that only the blue-enriched light strengthens the connection from the posterior thalamus to the IPS. To the best of our knowledge, our results provide the first empirical data supporting that blue wavelength light affects ongoing non-visual cognitive activity by modulating task-dependent information flow from subcortical to cortical areas.
