A coordinate-based meta-analysis of the n-back working memory paradigm using activation likelihood estimation

Wang, Hui; He, Weijiang; Wu, Jingting; Zhang, Junjun; Jin, Zhenlan; Li, Ling

doi:10.1016/j.bandc.2019.01.002

Cited by 93 publications

(69 citation statements)

References 74 publications

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“…Patterns of activation with increasing working memory load in each group were remarkably consistent following our within-group meta-analyses. Prototypical regions – including the bilateral IPL, bilateral MFG, bilateral anterior insula, and SFG – extending ventrally into the anterior cingulate cortex – were seen within each group and are consistent with prior meta-analytic studies examining working memory load in non-patient populations (22, 23). The lack of grossly discernable differences is not entirely unexpected given that impairments in behavior often result in subtle, rather than large scale, changes in functional activity.…”

Section: Discussionsupporting

confidence: 84%

“…We first collapsed data across all healthy participants that were included in any of the undermentioned contrasts. Healthy participants activated an array of regions typically associated with prior examinations of working memory during the n-back paradigm (22, 23). These regions included bilateral inferior parietal lobule (IPL) extending to precuneus, bilateral insula, bilateral declive of the cerebellum, bilateral mid frontal gyrus (MFG), left precentral gyrus extending into the anterior cingulate, right superior frontal gyrus (SFG), left ventral anterior nucleus of the thalamus extending to the mediodorsal nucleus, and bilateral tuber of the cerebellum (Figure 1, first row; Table 3).…”

Section: Resultsmentioning

confidence: 99%

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Common default mode network dysfunction across psychopathologies: A neuroimaging meta-analysis of the n-back working memory paradigm

Farruggia

Laird

Mattfeld

2020

Preprint

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41The National Institute of Mental Health's (NIMH) Research Domain Criteria (RDoC) classifies 42 disorders based on shared aspects of behavioral and neurobiological dysfunction. One common 43 behavioral deficit observed in various psychopathologies, namely ADHD, addiction, bipolar 44 disorder, depression, and schizophrenia, is a deficit in working memory performance. However, 45 it is not known to what extent, if any, these disorders share common neurobiological 46abnormalities that contribute to decrements in performance. The goal of the present study was to 47 for DSM-diagnosed individuals compared to healthy controls. Foci from ADHD, addiction, 56 bipolar disorder, schizophrenia, and major depression studies contributed to the formation of this 57 cluster. These results provide evidence that default-mode intrusion may constitute a shared seed 58 of dysregulation across multiple psychopathologies, ultimately resulting in poorer working 59 memory performance. (WORD COUNT: 224) 60Keywords: n-back task, meta-analysis, working memory, psychopathology, ADHD, 61 addiction, depression, bipolar disorder, schizophrenia 62 63 64 neuroimaging studies, namely low statistical power, high false positive rates, and potential for 88 software errors (15). 89The goal of the present study was to examine the convergence and/or divergence of 90 functional neuroimaging findings as it relates to working memory-related load across 91 psychopathologies, namely, ADHD, schizophrenia, addiction, depression, and bipolar disorder. 92We chose to examine working memory-related load across various permutations of the n-back 93 task, which has been extensively validated as a probe for our psychological construct of interest 94 (16). First, we aggregated all peer-reviewed publications meeting our search criteria. All papers 95 had to include contrasts with patients having a DSM diagnosis of interest. Exceptions were made 96 for the 'Addiction' contrast to include illicit substance use more broadly, due to the lack of a 97 pervasive application of DSM criteria in this case. Imaging analyses furthermore had to include a 98 minimum n-back contrast of 2-back > rest. That is, a 2-back (or 3-back) > rest contrast was 99 acceptable for our purposes, but not 1-back > rest, 1-back > 0-back, or 3-back with no baseline. 100Second, we extracted coordinates from all articles reporting within-group contrasts as well as 101 between-group contrasts (e.g., controls > bipolar disorder). Third, we ran each contrast in the 102 GingerALE software to create thresholded ALE images. We examined convergence within 103 psychopathologies to characterize the working memory-related activation patterns specific to 104 each disease. We then examined convergence between psychopathologies to identify regions that 105 showed either shared or unique contributions to the neurobiological differences related to 106 working memory performance. 107

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Section: Discussionsupporting

confidence: 84%

Section: Resultsmentioning

confidence: 99%

Common default mode network dysfunction across psychopathologies: A neuroimaging meta-analysis of the n-back working memory paradigm

Farruggia

Laird

Mattfeld

2020

Preprint

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“…To identify candidate studies, the PubMed database was searched on July 7, 2018, with the search strings: “fMRI AND ‘working memory’ AND (encoding OR maintenance OR retrieval OR Sternberg OR ‘delayed match to sample’ OR ‘delayed simple matching’)”. In addition, the reference sections from relevant meta‐analysis studies (e.g., Rottschy et al, ; Wager & Smith, ; Wang et al, ) were screened to identify studies not identified by the online database search. Search results were filtered to include only studies that met the following inclusion/exclusion criteria: Only studies that tested healthy subjects with no sign of mental or neurological illness were included. Only studies that involved the presentation of stimuli through a visual modality were included. Only studies that reported whole‐brain data and peak activation foci in standard stereotaxic coordinates (i.e., Talairach or Montreal Neurological Institute [MNI]) were included. Only studies that reported activation effects of all three phases were included (see section 1 for the rationale for this criterion). A few studies employed a design that involved the presentation of external stimuli during a maintenance phase, such as distractors.…”

Section: Methodsmentioning

confidence: 99%

“…To identify candidate studies, the PubMed database was searched on July 7, 2018, with the search strings: "fMRI AND 'working memory' AND (encoding OR maintenance OR retrieval OR Sternberg OR 'delayed match to sample' OR 'delayed simple matching')". In addition, the reference sections from relevant meta-analysis studies (e.g., Rottschy et al, 2011;Wager & Smith, 2003;Wang et al, 2019) were screened to identify studies not identified by the online database search. Search results were filtered to include only studies that met the following inclusion/exclusion criteria:…”

Section: Data Collectionmentioning

confidence: 99%

“…Several studies performed quantitative meta-analyses of WMneuroimaging data to identify significant concordance across individual studies. These studies typically focused exclusively on "n-back" tasks (Owen, McMillan, Laird, & Bullmore, 2005;Wang et al, 2019;Yaple & Arsalidou, 2018), which do not permit the separation of the different temporal phases, or collapsed analyses across data regarding n-back and other delayed-response tasks (Hill, Laird, & Robinson, 2014;Rottschy et al, 2011;Wager & Smith, 2003). Although a recent study (Daniel, Katz, & Robinson, 2016) focused exclusively on a delayed-response paradigm, namely, delayed match to sample, it did not perform any specific analysis relevant to the separation of different phase effects.…”

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confidence: 99%

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Neural activity during working memory encoding, maintenance, and retrieval: A network‐based model and meta‐analysis

Kim

2019

Human Brain Mapping

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It remains unclear whether and to what extent working memory (WM) temporal subprocesses (i.e., encoding, maintenance, and retrieval) involve shared or distinct intrinsic networks. To address this issue, I constructed a model of intrinsic network contributions to different WM phases and then evaluated the validity of the model by performing a quantitative meta‐analysis of relevant functional neuroimaging data. The model suggests that the transition from the encoding to maintenance and to retrieval stages involves progressively decreasing involvement of the dorsal attention network (DAN), but progressively increasing involvement of the frontoparietal control network (FPCN). Separate meta‐analysis of each phase effect and direct comparisons between them yielded results that were largely consistent with the model. This evidence included between‐phase double dissociations that were consistent with the model, such as encoding > maintenance contrast showing some DAN, but no FPCN, regions, and maintenance > encoding contrast showing the reverse, that is, some FPCN, but no DAN, regions. Two closely juxtaposed regions that are members of the DAN and FPCN, such as inferior frontal junction versus caudal prefrontal cortex and superior versus inferior intraparietal sulcus, showed a high degree of functional differentiation. Although all regions identified in the present study were already identified in previous WM studies, this study uniquely enhances our understating of their roles by clarifying their network membership and specific associations with different WM phases.

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Hands off, brain off? A meta‐analysis of neuroimaging data during active and passive driving

Jordan,

Emanuelle

2023

Brain and Behavior

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BackgroundCar driving is more and more automated, to such an extent that driving without active steering control is becoming a reality. Although active driving requires the use of visual information to guide actions (i.e., steering the vehicle), passive driving only requires looking at the driving scene without any need to act (i.e., the human is passively driven).Materials & MethodsAfter a careful search of the scientific literature, 11 different studies, providing 17 contrasts, were used to run a comprehensive meta‐analysis contrasting active driving with passive driving.ResultsTwo brain regions were recruited more consistently for active driving compared to passive driving, the left precentral gyrus (BA3 and BA4) and the left postcentral gyrus (BA4 and BA3/40), whereas a set of brain regions was recruited more consistently in passive driving compared to active driving: the left middle frontal gyrus (BA6), the right anterior lobe and the left posterior lobe of the cerebellum, the right sub‐lobar thalamus, the right anterior prefrontal cortex (BA10), the right inferior occipital gyrus (BA17/18/19), the right inferior temporal gyrus (BA37), and the left cuneus (BA17).DiscussionFrom a theoretical perspective, these findings support the idea that the output requirement of the visual scanning process engaged for the same activity can trigger different cerebral pathways, associated with different cognitive processes. A dorsal stream dominance was found during active driving, whereas a ventral stream dominance was obtained during passive driving. From a practical perspective, and contrary to the dominant position in the Human Factors community, our findings support the idea that a transition from passive to active driving would remain challenging as passive and active driving engage distinct neural networks.

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A coordinate-based meta-analysis of the n-back working memory paradigm using activation likelihood estimation

Cited by 93 publications

References 74 publications

Common default mode network dysfunction across psychopathologies: A neuroimaging meta-analysis of the n-back working memory paradigm

Common default mode network dysfunction across psychopathologies: A neuroimaging meta-analysis of the n-back working memory paradigm

Neural activity during working memory encoding, maintenance, and retrieval: A network‐based model and meta‐analysis

Hands off, brain off? A meta‐analysis of neuroimaging data during active and passive driving

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