An integrated brain–behavior model for working memory

Moser, Dominik A.; Doucet, Gaëlle E.; Ing, Alex; Dima, Danai; Schumann, Günter; Bilder, Robert M.; Frangou, Sophia

doi:10.1038/mp.2017.247

Cited by 44 publications

(44 citation statements)

References 49 publications

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“…Of salience to the treatment context, these disparate patterns of developmental timing may help explain why developing adolescent cognitive skills like working memory, which is supported by dlPFC (Moser et al., ; Nee et al., ; Wager and Smith, ), along with abstract thinking and reasoning, which rely upon the most rostral portions of dlPFC (Dumontheil, ), emerge a bit later in the developing cognitive skill cascade.…”

Section: The Nature Of the Adolescent Brain: Characteristic Features mentioning

confidence: 99%

Hunting for What Works: Adolescents in Addiction Treatment

Silvers

Squeglia

Thomsen³

et al. 2019

Alcoholism Clin & Exp Res

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Although adolescents are developmentally distinct from adults, they often receive addiction treatment based on adult models. This is problematic because adolescents face significantly different conditions in addiction treatment, including distinct basic biological and neurodevelopmental stages, unique sociodevelopmental concerns, distinctive addiction trajectories, and, in turn, disparate treatment goals and outcomes. In sum, it can be difficult for even savvy clinicians to know how to approach addiction treatment with this important age group. In an effort to help clinicians and researchers consider substance use via a neurodevelopmental lens, we approached this review with 4 goals: (i) characterize the prevalence, and related health and safety implications of substance use within this age group; (ii) identify the nature of the adolescent brain, including characteristic features of this phase of neurodevelopment relevant to adolescent substance use treatment; (iii) provide an overview of current adolescent addiction interventions and avenues to improve clinical treatment and clinical research efforts for adolescents; and (iv) examine the intersection between the nature of the developing brain and adolescent substance use, and utilize that information to inform alternative routes and directions for substance use treatment in this critical age group. This review concludes by offering a novel neurodevelopmental model and framework to examine substance use interventions, along with a series of recommendations to optimize adolescent substance use treatment and clinical research.

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Section: The Nature Of the Adolescent Brain: Characteristic Features mentioning

confidence: 99%

Hunting for What Works: Adolescents in Addiction Treatment

Silvers

Squeglia

Thomsen³

et al. 2019

Alcoholism Clin & Exp Res

View full text Add to dashboard Cite

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“…Indeed, one of the key components of WM processing is the capacity of actively maintaining information no longer available and to manipulate this information for usage over short delays (Moser et al, 2018). This requires the integration of neuronal circuits on large scale, including regions in dorsolateral prefrontal cortex, parietal cortex, and dorsal anterior cingulate cortex (Liang et al, 2016).…”

Section: Discussionmentioning

confidence: 99%

Brain Network Modularity During a Sustained Working-Memory Task

et al. 2020

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Spontaneous oscillations of the blood oxygenation level-dependent (BOLD) signal are spatially synchronized within specific brain networks and are thought to reflect synchronized brain activity. Networks are modulated by the performance of a task, even if the exact features and degree of such modulations are still elusive. The presence of networks showing anticorrelated fluctuations lend initially to suppose that a competitive relationship between the default mode network (DMN) and task positive networks (TPNs) supports the efficiency of brain processing. However, more recent results indicate that cooperative and competitive dynamics between networks coexist during task performance. In this study, we used graph analysis to assess the functional relevance of the topological reorganization of brain networks ensuing the execution of a steady state working-memory (WM) task. Our results indicate that the performance of an auditory WM task is associated with a switching between different topological configurations of several regions of specific networks, including frontoparietal, ventral attention, and dorsal attention areas, suggesting segregation of ventral attention regions in the presence of increased overall integration. However, the correct execution of the task requires integration between components belonging to all the involved networks.

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“…We implemented sCCA [33] in MatlabR2018b using an in-house script in accordance with our previously published work [34,35,46] to test the association between the linguistic, clinical, and neuroimaging data (details in Supplementary Material, Section 1.4). We considered four datasets; a nonimaging dataset comprising the clinical variables (Supplementary Table S2), a nonimaging dataset comprising the linguistic variables ( Supplementary Table S3), a functional dataset comprising the functional network connectivity variables ( Supplementary Table S4), and a structural dataset comprising the morphometric variables (Supplementary Table S5).…”

Section: Sparse Canonical Correlation Analysesmentioning

confidence: 99%

“…Specifically, we employ sparse canonical correlation analysis (sCCA) [33] to identify linked patterns of covariation between multiple linguistic features and brain morphology and functional connectivity. sCCA is an extension of traditional CCA, is more appropriate for smaller samples, it is less susceptible to overfitting and has been extensively used to describe brain-cognition associations by us [34,35] and others [36][37][38]. Our initial hypotheses are that (a) amount of speech and measures of syntactic complexity will show significant covariation with symptoms; (b) both syntactic and semantic features will covary with brain structural and functional measures of the language network and its functional integration with cognitive control networks; and (c) brain-language covariation patterns would be altered by CHR status.…”

Section: Introductionmentioning

confidence: 99%

Linking language features to clinical symptoms and multimodal imaging in individuals at clinical high risk for psychosis

et al. 2020

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Background. Abnormalities in the semantic and syntactic organization of speech have been reported in individuals at clinical high-risk (CHR) for psychosis. The current study seeks to examine whether such abnormalities are associated with changes in brain structure and functional connectivity in CHR individuals. Methods. Automated natural language processing analysis was applied to speech samples obtained from 46 CHR and 22 healthy individuals. Brain structural and resting-state functional imaging data were also acquired from all participants. Sparse canonical correlation analysis (sCCA) was used to ascertain patterns of covariation between linguistic features, clinical symptoms, and measures of brain morphometry and functional connectivity related to the language network. Results. In CHR individuals, we found a significant mode of covariation between linguistic and clinical features (r = 0.73; p = 0.003), with negative symptoms and bizarre thinking covarying mostly with measures of syntactic complexity. In the entire sample, separate sCCAs identified a single mode of covariation linking linguistic features with brain morphometry (r = 0.65; p = 0.05) and resting-state network connectivity (r = 0.63; p = 0.01). In both models, semantic and syntactic features covaried with brain structural and functional connectivity measures of the language network. However, the contribution of diagnosis to both models was negligible. Conclusions. Syntactic complexity appeared sensitive to prodromal symptoms in CHR individuals while the patterns of brain-language covariation seemed preserved. Further studies in larger samples are required to establish the reproducibility of these findings.

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An integrated brain–behavior model for working memory

Cited by 44 publications

References 49 publications

Hunting for What Works: Adolescents in Addiction Treatment

Hunting for What Works: Adolescents in Addiction Treatment

Brain Network Modularity During a Sustained Working-Memory Task

Linking language features to clinical symptoms and multimodal imaging in individuals at clinical high risk for psychosis

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