Literature DB >> 25982222

Multimodal connectivity mapping of the human left anterior and posterior lateral prefrontal cortex.

Andrew T Reid1, Danilo Bzdok2,3,4, Robert Langner2,3, Peter T Fox5,6, Angela R Laird7, Katrin Amunts2,8, Simon B Eickhoff2,3, Claudia R Eickhoff2,9.   

Abstract

Working memory is essential for many of our distinctly human abilities, including reasoning, problem solving, and planning. Research spanning many decades has helped to refine our understanding of this high-level function as comprising several hierarchically organized components, some which maintain information in the conscious mind, and others which manipulate and reorganize this information in useful ways. In the neocortex, these processes are likely implemented by a distributed frontoparietal network, with more posterior regions serving to maintain volatile information, and more anterior regions subserving the manipulation of this information. Recent meta-analytic findings have identified the anterior lateral prefrontal cortex, in particular, as being generally engaged by working memory tasks, while the posterior lateral prefrontal cortex was more strongly associated with the cognitive load required by these tasks. These findings suggest specific roles for these regions in the cognitive control processes underlying working memory. To further characterize these regions, we applied three distinct seed-based methods for determining cortical connectivity. Specifically, we employed meta-analytic connectivity mapping across task-based fMRI experiments, resting-state BOLD correlations, and VBM-based structural covariance. We found a frontoparietal pattern of convergence which strongly resembled the working memory networks identified in previous research. A contrast between anterior and posterior parts of the lateral prefrontal cortex revealed distinct connectivity patterns consistent with the idea of a hierarchical organization of frontoparietal networks. Moreover, we found a distributed network that was anticorrelated with the anterior seed region, which included most of the default mode network and a subcomponent related to social and emotional processing. These findings fit well with the internal attention model of working memory, in which representation of information is processed according to an anteroposterior gradient of abstract-to-concrete representations.

Entities:  

Keywords:  Anterior lateral prefrontal cortex; Functional connectivity; Meta-analytic connectivity modeling; Posterior lateral prefrontal cortex; Structural covariance; Working memory

Mesh:

Year:  2015        PMID: 25982222      PMCID: PMC4791192          DOI: 10.1007/s00429-015-1060-5

Source DB:  PubMed          Journal:  Brain Struct Funct        ISSN: 1863-2653            Impact factor:   3.270


  103 in total

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Authors:  Peter E Turkeltaub; Guinevere F Eden; Karen M Jones; Thomas A Zeffiro
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2.  Observer-independent cytoarchitectonic mapping of the human superior parietal cortex.

Authors:  Filip Scheperjans; Klaudia Hermann; Simon B Eickhoff; Katrin Amunts; Axel Schleicher; Karl Zilles
Journal:  Cereb Cortex       Date:  2007-07-21       Impact factor: 5.357

3.  Threshold-free cluster enhancement: addressing problems of smoothing, threshold dependence and localisation in cluster inference.

Authors:  Stephen M Smith; Thomas E Nichols
Journal:  Neuroimage       Date:  2008-04-11       Impact factor: 6.556

4.  Minds at rest? Social cognition as the default mode of cognizing and its putative relationship to the "default system" of the brain.

Authors:  Leo Schilbach; Simon B Eickhoff; Anna Rotarska-Jagiela; Gereon R Fink; Kai Vogeley
Journal:  Conscious Cogn       Date:  2008-04-22

5.  Dissociating working memory from task difficulty in human prefrontal cortex.

Authors:  D M Barch; T S Braver; L E Nystrom; S D Forman; D C Noll; J D Cohen
Journal:  Neuropsychologia       Date:  1997-10       Impact factor: 3.139

Review 6.  Structural networks in Alzheimer's disease.

Authors:  Andrew T Reid; Alan C Evans
Journal:  Eur Neuropsychopharmacol       Date:  2013-01-05       Impact factor: 4.600

Review 7.  Top-down modulation: bridging selective attention and working memory.

Authors:  Adam Gazzaley; Anna C Nobre
Journal:  Trends Cogn Sci       Date:  2011-12-28       Impact factor: 20.229

8.  Minimizing within-experiment and within-group effects in Activation Likelihood Estimation meta-analyses.

Authors:  Peter E Turkeltaub; Simon B Eickhoff; Angela R Laird; Mick Fox; Martin Wiener; Peter Fox
Journal:  Hum Brain Mapp       Date:  2011-02-08       Impact factor: 5.038

9.  Investigating the functional heterogeneity of the default mode network using coordinate-based meta-analytic modeling.

Authors:  Angela R Laird; Simon B Eickhoff; Karl Li; Donald A Robin; David C Glahn; Peter T Fox
Journal:  J Neurosci       Date:  2009-11-18       Impact factor: 6.167

10.  The BrainMap strategy for standardization, sharing, and meta-analysis of neuroimaging data.

Authors:  Angela R Laird; Simon B Eickhoff; P Mickle Fox; Angela M Uecker; Kimberly L Ray; Juan J Saenz; D Reese McKay; Danilo Bzdok; Robert W Laird; Jennifer L Robinson; Jessica A Turner; Peter E Turkeltaub; Jack L Lancaster; Peter T Fox
Journal:  BMC Res Notes       Date:  2011-09-09
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  13 in total

1.  Beyond consensus: Embracing heterogeneity in curated neuroimaging meta-analysis.

Authors:  Gia H Ngo; Simon B Eickhoff; Minh Nguyen; Gunes Sevinc; Peter T Fox; R Nathan Spreng; B T Thomas Yeo
Journal:  Neuroimage       Date:  2019-06-20       Impact factor: 6.556

2.  Multimodal Parcellations and Extensive Behavioral Profiling Tackling the Hippocampus Gradient.

Authors:  Anna Plachti; Simon B Eickhoff; Felix Hoffstaedter; Kaustubh R Patil; Angela R Laird; Peter T Fox; Katrin Amunts; Sarah Genon
Journal:  Cereb Cortex       Date:  2019-12-17       Impact factor: 5.357

3.  Resting-state test-retest reliability of a priori defined canonical networks over different preprocessing steps.

Authors:  Deepthi P Varikuti; Felix Hoffstaedter; Sarah Genon; Holger Schwender; Andrew T Reid; Simon B Eickhoff
Journal:  Brain Struct Funct       Date:  2016-08-22       Impact factor: 3.270

4.  Multimodal connectivity-based parcellation reveals a shell-core dichotomy of the human nucleus accumbens.

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Journal:  Hum Brain Mapp       Date:  2017-05-26       Impact factor: 5.038

5.  Multimodal connectivity of motor learning-related dorsal premotor cortex.

Authors:  Robert M Hardwick; Elise Lesage; Claudia R Eickhoff; Mareike Clos; Peter Fox; Simon B Eickhoff
Journal:  Neuroimage       Date:  2015-08-15       Impact factor: 6.556

6.  Hippocampus co-atrophy pattern in dementia deviates from covariance patterns across the lifespan.

Authors:  Anna Plachti; Shahrzad Kharabian; Simon B Eickhoff; Somayeh Maleki Balajoo; Felix Hoffstaedter; Deepthi P Varikuti; Christiane Jockwitz; Svenja Caspers; Katrin Amunts; Sarah Genon
Journal:  Brain       Date:  2020-09-01       Impact factor: 13.501

7.  Building an EEG-fMRI Multi-Modal Brain Graph: A Concurrent EEG-fMRI Study.

Authors:  Qingbao Yu; Lei Wu; David A Bridwell; Erik B Erhardt; Yuhui Du; Hao He; Jiayu Chen; Peng Liu; Jing Sui; Godfrey Pearlson; Vince D Calhoun
Journal:  Front Hum Neurosci       Date:  2016-09-28       Impact factor: 3.169

8.  Investigating the Neural Correlates of Emotion-Cognition Interaction Using an Affective Stroop Task.

Authors:  Nora M Raschle; Lynn V Fehlbaum; Willeke M Menks; Felix Euler; Philipp Sterzer; Christina Stadler
Journal:  Front Psychol       Date:  2017-09-01

9.  Multi-Modal Imaging of Neural Correlates of Motor Speed Performance in the Trail Making Test.

Authors:  Julia A Camilleri; Andrew T Reid; Veronika I Müller; Christian Grefkes; Katrin Amunts; Simon B Eickhoff
Journal:  Front Neurol       Date:  2015-10-27       Impact factor: 4.003

10.  Psychological intervention with working memory training increases basal ganglia volume: A VBM study of inpatient treatment for methamphetamine use.

Authors:  S J Brooks; K H Burch; S A Maiorana; E Cocolas; H B Schioth; E K Nilsson; K Kamaloodien; D J Stein
Journal:  Neuroimage Clin       Date:  2016-08-24       Impact factor: 4.881

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