Meta-Analysis of the Functional Neuroanatomy of Single-Word Reading: Method and Validation

By Peter E. Turkeltaub, Guinevere F. Eden, Karen M. Jones, Thomas A. Zeffiro. NeuroImage, 2002

1,602 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Developmental and Educational Psychology

View Paper: https://www.semanticscholar.org/paper/b0f0cf8a0c3f11f7c27ba6136ef9c9b33c76de4a

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In Cognitive Neuroscience

In Developmental and Educational Psychology

Citations in the corpus

From brain maps to cognitive ontologies: informatics and the search for mental structure (2015, methodology): “Drawing on such databases and tools, researchers have conducted hundreds of fMRI metaanalyses on topics ranging from single-word reading (Turkeltaub et al. 2002) to rectal distension in irritable bowel syndrome (Tillisch et al. 2011).”
Neuroimaging studies of shifting attention: a meta-analysis (2004, methodology): “, 2002), and our technique is similar to that employed by several other groups (Chein et al., 2002; Turkeltaub et al., 2002).”
The anatomy of first-episode and chronic schizophrenia: an anatomical likelihood estimation meta-analysis. (2008, methodology): “The likelihood of anatomical differences between groups was estimated on the basis of the equally weighted coordinates reported by the primary studies (12).”
Meta-analysis of Go/No-go tasks demonstrating that fMRI activation associated with response inhibition is task-dependent. (2008, methodology): “One method of meta-analysis called activation likelihood estimate (ALE) ( Turkeltaub, Eden, Jones, & Zeffiro, 2002 ), allows for statistically verifiable concurrence across functional neuroimaging studies.”
A meta-analysis of neurofunctional imaging studies of emotion and cognition in major depression (2012, positive): “, 2011), we integrated neuroimaging results using the Activation Likelihood Estimate (ALE) method (Turkeltaub et al., 2002), which provides a kernel-based approach for meta-analyses of neuroimaging data in BrainMap (Laird et al.”
Involvement of the inferior frontal junction in cognitive control: Meta‐analyses of switching and Stroop studies (2005, methodology): “In the context of effect-location meta-analytic approaches, models have been developed to compare empirical distributions of activation peaks to random distributions to identify above-chance activation clusters [Chein et al., 2002; Turkeltaub et al., 2002; Wager et al., 2003].”
Meta-analysis of gray matter anomalies in schizophrenia: application of anatomic likelihood estimation and network analysis. (2008, neutral): “The practice of reporting brain locations as coordinates in stereotactic space is common in the functional neuroimaging literature (14), improving the generalizability of individual experiments and fueling the development of novel meta-analytic procedures (15).”
A meta-analytic review of multisensory imagery identifies the neural correlates of modality-specific and modality-general imagery (2012, methodology): “Techniques such as Activation Likelihood Estimation (ALE) (Chein et al., 2002; Turkeltaub et al., 2002) and Multilevel Kernel Density Analysis (MKDA) (Wager et al.”
N‐back working memory paradigm: A meta‐analysis of normative functional neuroimaging studies (2005, methodology): “It was notable that maximum ALE scores and volumes of activation foci were generally reduced compared to the size and salience of activated loci identified by meta-analysis of the larger set of coordinates drawn from all n-back studies (Table II).”
Functional atlas of emotional faces processing: a voxel-based meta-analysis of 105 functional magnetic resonance imaging studies. (2009, neutral): “neutral) and 5) reported data in standard stereotactic coordinates (either Talairach or Montreal Neurological Institute [MNI] space).(37,38) The 2 researchers assessed the inclusion criteria by consensus.”
Behavior, Sensitivity, and power of activation likelihood estimation characterized by massive empirical simulation (2016, neutral): “Empirically, it has repeatedly been noted that significant effects may be largely driven by even a single experiment if the total number of experiments is relatively low (Bzdok et al., 2011; Raemaekers et al., 2007; Turkeltaub et al., 2012; Wager et al., 2007).”