Showing papers on "Working memory published in 2026"
TL;DR: This study examines the interplay between two verbal working memory systems, one specific and one general-purpose, using the Maxispan instructions to control their joint use. Results show improved recall with Maxispan instructions, but also reveal the general system's capacity is reduced when the specific system is overloaded.
Abstract: • Two systems (a specific and a general) maintain verbal items in working memory. • The Maxispan instructions control their joint use for a single series of items. • Maxispan instructions improve immediate recall and memory spans. • When the specific system is overloaded, the general system takes over. • Hence, this overload reduces the capacity of the general system. Most models of working memory (WM) include two systems for maintaining verbal information: one specific using verbal rehearsal and the other, general-purpose, relying on attention. These systems have been studied independently, but little is known about their interplay. The present study aimed at examining their interaction, especially when the verbal specific system is overloaded. Our hypothesis was that, in such a case, the attention-based system takes over, hence depleting attentional resources for maintenance. Though previously mentioned, this hypothesis has never been formally tested. We took advantage of a new methodology based on the Maxispan instructions, which controls the involvement of each system in immediate serial recall tasks. In the Maxispan instructions, participants cumulatively rehearse orally a defined number of the earlier items until recall, while also memorizing the subsequent items. Their performance was compared to that obtained in the regular instructions condition (i.e., no specific instructions). The articulatory demand of the verbal specific system was also manipulated by presenting either monosyllabic or trisyllabic words or pseudowords. Across five experiments, results supported our hypotheses. Maxispan (vs. regular) instructions led to improved recall performance for both rehearsed and non-rehearsed items. Importantly, rehearsing more syllables in the Maxispan instructions impaired maintenance of the later non-rehearsed items, bringing their recall close to the level of the regular instructions condition. These findings shed light on the interplay between the two systems of verbal maintenance, constraining WM models. Moreover, some peculiarities in words recall questioned the role of semantics in WM.
TL;DR: This study investigates the relationship between attentional capture and working memory (WM) resource allocation, finding that WM representation precision does not affect attentional capture effects, suggesting that attention bias in WM representation is a key factor in attentional capture.
Abstract: Attention can be automatically captured by the distractor that matches the representation of working memory (WM) in search tasks, impairing visual search efficiency and resulting in attentional capture effects. The resource hypothesis of visual search predicts that resource allocation affects attentional capture. However, previous studies have shown partly opposing results inconsistent with this prediction. The purpose of this study is to assess the connection between attentional capture and WM resource allocation. Two experiments were conducted to combine the attentional capture paradigm with continuous delayed-estimation tasks. In Experiment 1, we manipulated the number of memory items between one and two and measured the WM representation precision as well as the magnitude of attentional capture. In Experiment 2, we manipulated resource allocation using a retro-cue task with the presentation of two memory items. In Experiment 1, the results show that when remembering one item, a single-item representation had higher precision compared to the scenario for remembering two items, and it also involved a greater allocation of WM resources. However, there was no significant difference in the magnitude of attentional capture effects between the two conditions. In Experiment 2, the results show that memory precision was higher when the cue pointed to the item compared to when it did not, but there was no significant difference in the magnitude of attentional capture effects between the cued-match and non-cued-match conditions. The findings show that the size of attentional capture effects based on WM is unaffected by the distribution of WM resources. Attentional capture effects may reflect the attention bias of WM representation that occurs in preparation stage of memory-based attentional guidance.
TL;DR: Childhood trauma, particularly physical neglect, is linked to impaired working memory performance in schizophrenia, but not through altered frontoparietal connectivity; instead, suppression of default mode network activity by the left dorsolateral prefrontal cortex predicts better working memory in patients.
Abstract: Introduction: Schizophrenia is associated with aberrations in resting-state and task-based functional connectivity, particularly in the frontoparietal network, which is critical for higher-order cognitive functions such as working memory [1]. Evidence, primarily from resting-state fMRI studies, suggests that childhood trauma exposure may induce changes in brain function in clinical and non-clinical populations [2]. Behavioural findings further indicate that childhood trauma, particularly physical neglect, is linked to cognitive impairments [3]. It remains unclear how childhood trauma affects frontoparietal connectivity during active working memory processes, and whether such alterations contribute to working memory deficits in schizophrenia. We hypothesized that physical neglect would be associated with poorer working memory performance, and that this would be partially mediated by frontoparietal connectivity in a diagnosis-independent manner.
Methods: Childhood trauma history, working memory performance, and task-based fMRI data were collected from 38 individuals with schizophrenia or schizoaffective disorder and 128 healthy controls. fMRI data were preprocessed and denoised using a modular preprocessing pipeline in the CONN toolbox [4]. Seed-to-voxel connectivity analyses were conducted using four predefined frontoparietal regions (right and left dorsolateral prefrontal cortices, right and left posterior parietal cortices) as seeds, and all other voxels brain-wide as targets. Connectivity patterns during the working memory task were contrasted across diagnostic groups to identify group differences in connectivity. Additionally, high versus low working memory load conditions were contrasted across the whole sample to isolate connectivity patterns associated with higher cognitive load. To examine the interactions between physical neglect, frontoparietal connectivity, and working memory performance, we conducted a moderated mediation analysis in RStudio using PROCESS Macro Model 59, with diagnosis as moderator.
Results: Patients showed widespread patterns of both hyper- and hypo-connectivity within the frontoparietal network compared to controls. Across all participants, physical neglect was associated with reduced working memory performance (r = -0.2595, p = 0.0019). However, this association was not mediated by frontoparietal connectivity. Under high working memory load, there was suppression of medial frontal cortex (MedFC) activity by the left dorsolateral prefrontal cortex (dlPFC) (T(1, 165) = -5.4, p < 0.001). Diagnosis moderated both the association between physical neglect and left dlPFC–MedFC connectivity (R2 change = 2.98%, p = 0.0223), and the association between connectivity and working memory performance (R2 change = 2.75%, p = 0.0112). Although the relationship between physical neglect and left dlPFC-MedFC connectivity was not significant in either group, greater suppression of MedFC by left dlPFC was associated with better working memory performance in patients only (effect = -10.8334, p = 0.0054).
Conclusion: Contrary to our hypothesis, frontoparietal connectivity did not mediate the relationship between physical neglect and impaired working memory performance. We provide evidence that suppression of the default mode network – namely, the MedFC – by the left dlPFC under high working memory load predicted better working memory performance in patients only. These findings support the view of schizophrenia as a disorder of functional dysconnectivity, and suggest that neural mechanisms supporting cognitive performance may differ by diagnosis. Understanding these mechanisms may inform future interventions targeting cognitive deficits in schizophrenia.
Methods: Childhood trauma history, working memory performance, and task-based fMRI data were collected from 38 individuals with schizophrenia or schizoaffective disorder and 128 healthy controls. fMRI data were preprocessed and denoised using a modular preprocessing pipeline in the CONN toolbox [4]. Seed-to-voxel connectivity analyses were conducted using four predefined frontoparietal regions (right and left dorsolateral prefrontal cortices, right and left posterior parietal cortices) as seeds, and all other voxels brain-wide as targets. Connectivity patterns during the working memory task were contrasted across diagnostic groups to identify group differences in connectivity. Additionally, high versus low working memory load conditions were contrasted across the whole sample to isolate connectivity patterns associated with higher cognitive load. To examine the interactions between physical neglect, frontoparietal connectivity, and working memory performance, we conducted a moderated mediation analysis in RStudio using PROCESS Macro Model 59, with diagnosis as moderator.
Results: Patients showed widespread patterns of both hyper- and hypo-connectivity within the frontoparietal network compared to controls. Across all participants, physical neglect was associated with reduced working memory performance (r = -0.2595, p = 0.0019). However, this association was not mediated by frontoparietal connectivity. Under high working memory load, there was suppression of medial frontal cortex (MedFC) activity by the left dorsolateral prefrontal cortex (dlPFC) (T(1, 165) = -5.4, p < 0.001). Diagnosis moderated both the association between physical neglect and left dlPFC–MedFC connectivity (R2 change = 2.98%, p = 0.0223), and the association between connectivity and working memory performance (R2 change = 2.75%, p = 0.0112). Although the relationship between physical neglect and left dlPFC-MedFC connectivity was not significant in either group, greater suppression of MedFC by left dlPFC was associated with better working memory performance in patients only (effect = -10.8334, p = 0.0054).
Conclusion: Contrary to our hypothesis, frontoparietal connectivity did not mediate the relationship between physical neglect and impaired working memory performance. We provide evidence that suppression of the default mode network – namely, the MedFC – by the left dlPFC under high working memory load predicted better working memory performance in patients only. These findings support the view of schizophrenia as a disorder of functional dysconnectivity, and suggest that neural mechanisms supporting cognitive performance may differ by diagnosis. Understanding these mechanisms may inform future interventions targeting cognitive deficits in schizophrenia.
TL;DR: This study examines how rumination and distraction affect working memory in individuals with depressive tendencies and trait anxiety, finding that self-relevant positive distractions may enhance executive functioning and aid in cognitive recovery.
Abstract: Self-relevant positive distractions may enhance executive functioning, particularly in individuals vulnerable to rumination such as those with depressive tendencies or trait anxiety. These results provide insight into low-intensity content-based strategies for cognitive recovery after negative thought engagement and have potential applications in preventive interventions for subclinical emotional dysregulation.