Estimating the prevalence of missing experiments in a neuroimaging meta‐analysis

Samartsidis, Pantelis; Montagna, Silvia; Laird, Angela R.; Fox, Peter T.; Johnson, Timothy D.; Nichols, Thomas E.

doi:10.1002/jrsm.1448

Cited by 34 publications

(17 citation statements)

References 37 publications

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“…It was applied for the estimation of the robustness against unpublished neuroimaging findings. A recent study using the data from BrainMap provides evidence for the existence of a file drawer effect, with the rate of missing contrasts estimated as at least 6 per 100 reported 50 …”

Section: Methodsmentioning

confidence: 99%

“…A recent study using the data from BrainMap provides evidence for the existence of a file drawer effect, with the rate of missing contrasts estimated as at least 6 per 100 reported. 50 Therefore, the convergence meta‐analysis was retested starting with an additional 6% noise to evaluate the robustness of the identified clusters. The surviving clusters were then retested, with a noise rate of up to 30%, as in the previous study.…”

Section: Methodsmentioning

confidence: 99%

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Neuroimaging alterations in dementia with Lewy bodies and neuroimaging differences between dementia with Lewy bodies and Alzheimer's disease: An activation likelihood estimation meta‐analysis

Tian

Yao

et al. 2021

CNS Neurosci Ther

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Aims The aim of this study was to identify brain regions with local, structural, and functional abnormalities in dementia with Lewy bodies (DLB) and uncover the differences between DLB and Alzheimer's disease (AD). The neural networks involved in the identified abnormal brain regions were further described. Methods PubMed, Web of Science, OVID, Science Direct, and Cochrane Library databases were used to identify neuroimaging studies that included DLB versus healthy controls (HCs) or DLB versus AD. The coordinate‐based meta‐analysis and functional meta‐analytic connectivity modeling were performed using the activation likelihood estimation algorithm. Results Eleven structural studies and fourteen functional studies were included in this quantitative meta‐analysis. DLB patients showed a dysfunction in the bilateral inferior parietal lobule and right lingual gyrus compared with HC patients. DLB patients showed a relative preservation of the medial temporal lobe and a tendency of lower metabolism in the right lingual gyrus compared with AD. The frontal‐parietal, salience, and visual networks were all abnormally co‐activated in DLB, but the default mode network remained normally co‐activated compared with AD. Conclusions The convergence of local brain regions and co‐activation neural networks might be potential specific imaging markers in the diagnosis of DLB. This might provide a pathway for the neural regulation in DLB patients, and it might contribute to the development of specific interventions for DLB and AD.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Neuroimaging alterations in dementia with Lewy bodies and neuroimaging differences between dementia with Lewy bodies and Alzheimer's disease: An activation likelihood estimation meta‐analysis

Tian

Yao

et al. 2021

CNS Neurosci Ther

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“…The number of foci and subjects of those experiments were such to match the distribution they had in the original data. Samartsidis and colleagues (Samartsidis et al, 2020) estimated that the fail-drawer effect of the BrainMap database amounts to the 6%. Thus, we decided to perform a series of Fail-Safe analyses adding the 6% and the 60% of random experiment to each dataset, so as to evaluate the robustness of our results.…”

Section: [Experiments Context Is Normal Mapping] and [Experiments Activmentioning

confidence: 99%

Default Mode Network spatial configuration varies across task domains

Mancuso

Liloia

et al. 2021

Preprint

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Recent developments in network neuroscience suggest reconsidering what we thought we knew about the Default Mode Network (DMN). Although this network has always been seen as unitary and associated with the resting state, a new deconstructive line of research is pointing out that the DMN could be divided into multiple subsystems supporting different functions. By now, it is well known that the DMN is not only deactivated by tasks, but also involved in affective, mnestic, and social paradigms, among others. Nonetheless, it is starting to become clear that the array of activities in which it is involved, might also be extended to more extrinsic functions. The present meta-analytic study is meant to push this boundary a bit further. The BrainMap database was searched for all experimental paradigms activating the DMN, and their activation maps were then computed. An additional map of task-induced deactivations was also created. A Multidimensional Scaling indicated that such maps could be arranged along an anatomo-psychological gradient, which goes from midline core activations, associated with the most internal functions, to the involvement of lateral cortices in more external tasks. Further investigations suggested that such extrinsic mode is especially related to reward, semantic, and emotional functions. However, an important finding was that the variability of task-induced DMN anatomic redistribution was hard to recapitulate, as none of the maps, or any linear combination of them, could represent the whole space of its dynamical reconfiguration. Altogether, our findings suggest that the DMN may be characterized by a richer functional diversity and a more spatial complexity than previously suggested.

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“…Secondly, papers with non-significant results are less likely to be published. This publishing bias is also known as the ‘file-drawer problem’ ( Rosenthal, 1979 ; Ioannidis et al, 2014 ; de Winter and Dodou, 2015 ; for evidence in fMRI studies, see Jennings and Van Horn, 2012 ; Acar et al, 2018 ; David et al, 2018 ; Samartsidis et al, 2020 ). Prejudice against the null hypothesis systematically biases our knowledge of true effects ( Greenwald, 1975 ).…”

Section: Introductionmentioning

confidence: 99%

Providing Evidence for the Null Hypothesis in Functional Magnetic Resonance Imaging Using Group-Level Bayesian Inference

Masharipov

Knyazeva

Nikolaev

et al. 2021

Front. Neuroinform.

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Classical null hypothesis significance testing is limited to the rejection of the point-null hypothesis; it does not allow the interpretation of non-significant results. This leads to a bias against the null hypothesis. Herein, we discuss statistical approaches to ‘null effect’ assessment focusing on the Bayesian parameter inference (BPI). Although Bayesian methods have been theoretically elaborated and implemented in common neuroimaging software packages, they are not widely used for ‘null effect’ assessment. BPI considers the posterior probability of finding the effect within or outside the region of practical equivalence to the null value. It can be used to find both ‘activated/deactivated’ and ‘not activated’ voxels or to indicate that the obtained data are not sufficient using a single decision rule. It also allows to evaluate the data as the sample size increases and decide to stop the experiment if the obtained data are sufficient to make a confident inference. To demonstrate the advantages of using BPI for fMRI data group analysis, we compare it with classical null hypothesis significance testing on empirical data. We also use simulated data to show how BPI performs under different effect sizes, noise levels, noise distributions and sample sizes. Finally, we consider the problem of defining the region of practical equivalence for BPI and discuss possible applications of BPI in fMRI studies. To facilitate ‘null effect’ assessment for fMRI practitioners, we provide Statistical Parametric Mapping 12 based toolbox for Bayesian inference.

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Estimating the prevalence of missing experiments in a neuroimaging meta‐analysis

Cited by 34 publications

References 37 publications

Neuroimaging alterations in dementia with Lewy bodies and neuroimaging differences between dementia with Lewy bodies and Alzheimer's disease: An activation likelihood estimation meta‐analysis

Neuroimaging alterations in dementia with Lewy bodies and neuroimaging differences between dementia with Lewy bodies and Alzheimer's disease: An activation likelihood estimation meta‐analysis

Default Mode Network spatial configuration varies across task domains

Providing Evidence for the Null Hypothesis in Functional Magnetic Resonance Imaging Using Group-Level Bayesian Inference

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