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Dynamic shifts in brain network activation during supracapacity working memory task performance.

ABSTRACT: Despite significant advances in understanding how brain networks support working memory (WM) and cognitive control, relatively little is known about how these networks respond when cognitive capabilities are overtaxed. We used a fine-grained manipulation of memory load within a single trial to exceed WM capacity during functional magnetic resonance imaging to investigate how these networks respond to support task performance when WM capacity is exceeded. Analyzing correct trials only, we observed a nonmonotonic (inverted-U) response to WM load throughout the classic WM network (including bilateral dorsolateral prefrontal cortex, posterior parietal cortex, and presupplementary motor areas) that peaked later in individuals with greater WM capacity. We also observed a relative increase in activity in medial anterior prefrontal cortex, posterior cingulate/precuneus, and lateral temporal and parietal regions at the highest WM loads, and a set of predominantly subcortical and prefrontal regions whose activation was greatest at the lowest WM loads. At the individual subject level, the inverted-U pattern was associated with poorer performance while expression of the early and late activating patterns was predictive of better performance. In addition, greater activation in bilateral fusiform gyrus and right occipital lobe at the highest WM loads predicted better performance. These results demonstrate dynamic and behaviorally relevant changes in the level of activation of multiple brain networks in response to increasing WM load that are not well accounted for by present models of how the brain subserves the cognitive ability to hold and manipulate information on-line.

SUBMITTER: Van Snellenberg JX

PROVIDER: S-EPMC4722876 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Episodic memory is essential for forming and retaining personal experiences, representing a fundamental aspect of human cognition. Traditional studies of episodic memory have typically used static analysis methods, viewing the brain as an unchanging entity and overlooking its dynamic properties over time. In this study, we utilized dynamic functional connectivity analysis on fMRI data from healthy adults performing an episodic memory task. We quantified integration and recruitment metrics and examined their correlation with memory performance using Pearson correlation. During encoding, integration across the entire brain, especially within the frontoparietal subnetwork, was significantly correlated with memory performance. During retrieval, recruitment becomes significantly associated with memory performance in visual subnetwork, somatomotor subnetwork, and ventral attention subnetwork. At the nodal level, a significant negative correlation was observed between memory scores and integration of the anterior cingulate gyrus, precentral gyrus, and inferior frontal gyrus within the frontoparietal network during encoding task. During retrieval task, a significant negative correlation was found between memory scores and recruitment in the left progranular cortex and right transverse gyral ventral, whereas positive correlations were seen in the right posterior inferior temporal, left middle temporal, right frontal operculum, and left operculum nodes. Moreover, the dynamic reconfiguration of the functional network was predictive of predict memory performance, as demonstrated by a significant correlation between actual and predicted memory scores. These findings advance our understanding network mechanisms underlying memory processes and developing intervention approaches for memory-related disorders as they shed light on critical factors involved in cognitive processes and provide a deeper understanding of the underlying mechanisms driving cognitive function.

Project description:OBJECTIVE:Working memory (WM) deficits are consistently reported in schizophrenia and are related to poor functional outcomes. Functional magnetic resonance imaging studies of adult-onset schizophrenia have reported decreased functional activations and connectivity in the WM network, but no prior functional magnetic resonance imaging study has examined WM in childhood-onset schizophrenia (COS). The aim of this study was to examine the neural correlates of WM in COS. METHOD:Adult patients with COS (n = 32, 21.3 ± 1.1 years), nonpsychotic siblings of patients with COS (n = 30, 19.4 ± 0.8 years), and healthy controls (n = 39, 20.0 ± 0.7 years) completed 1- and 2-back WM tasks during 3-T functional magnetic resonance imaging. Functional activation and connectivity analyses were conducted. A separate group of 23 younger patients with COS (17.9 ± 7.4 years) could not perform the tasks after twice completing a standard training and are not included in this report. RESULTS:Patients with COS who were included scored significantly lower than controls on all tasks (p < .001). Patients with COS showed significantly lower activations in the dorsolateral prefrontal cortices, posterior parietal cortices, cerebellum, and caudate and decreased frontoparietal and corticostriatal functional connectivity compared with controls (p < .05, corrected). Siblings had functional activations and connectivity intermediate between those of patients and controls in a similar set of regions (p < .05, corrected). In patients, functional connectivity strength in the left frontoparietal network correlated positively with accuracy scores during the 1-back task (p = .0023, corrected). CONCLUSION:Decreased functional activation and connectivity in the WM network in COS supports pathophysiologic continuity with adult-onset schizophrenia. The low participation rate and accuracy of the patients highlights the disease severity of COS. Hypo-activations and hypo-connectivity were shared by siblings of patients with COS, suggesting COS as a potential endophenotype. CLINICAL TRIAL REGISTRATION INFORMATION:Evaluating Genetic Risk Factors for Childhood-Onset Schizophrenia; http://ClinicalTrials.gov;NCT00001198.

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Dynamic shifts in brain network activation during supracapacity working memory task performance.

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