Images tagged with "meta-analysis"

Found 80 images.

ID Name Collection(s) Description
65629 Meta-analysis result from 13 VBM studies: Thresholded Z map to match figure 2. Postive values are reduction in gray matter volume Meta-Analysis of 89 Structural MRI Studies in Posttraumatic Stress Disorder and Comparison With Major Depressive Disorder The following inclusion criteria were applied to the database of 113 studies: 1) gray matter VBM study comparing adult patients with PTSD to either non-traumatised-controls or traumatised-controls; 2) results presented in Talairach or MNI coordinates; 3) studies were only included if a whole brain analysis was performed rather than a small volume correction to ensure no bias in the regions reported. Thirteen studies met inclusion criteria and are listed in Table S1. We emailed all study authors who used SPM (Statistical Parametric Mapping) to process their data for a ‘T-map’ image comparing PTSD gray matter volume to the control group. ‘T-maps’ are three dimensional maps comprising statistical data of volume differences in thousands of voxels in the brain and provide far more detailed information than significant coordinates reported in studies. However, SDM allows both T-maps and coordinates to be combined in a single meta-analysis and the methodology reported in detail by Radua et al.8 We received 6 T-maps from 6 independent studies and these were included in the meta-analyses. In addition to the main meta-analysis comparing PTSD to all controls, three additional VBM analyses were conducted: 1) comparing the PTSD group with non-traumatised-controls only 2) comparing the PTSD group with traumatised-controls only, 3) comparing PTSD group with all controls and widening the criteria to include paediatric studies. T-maps and coordinates signifying gray matter volume changes from where we were unable to obtain T-maps were extracted from relevant studies and analysed using Seed-based d Mapping (SDM version 5.14, http://www.sdmproject.com). For studies where coordinate data was used, these were convolved with a Gaussian kernel (FWHM=20mm) in order to optimally compensate the sensitivity and specificity of the analysis. As is standard in SDM analyses, the number of randomizations were set to 100 and a threshold was set at p<0.005 as well as a cluster-level threshold of 10 voxels in order to increase sensitivity and correctly control false-positive rate.8 A jackknife sensitivity analysis was performed in order to assess the robustness of the results which was achieved by excluding one study in each of the analyses.
65111 Thresholded ALE contrast analysis: visuospatial selective Meta-analytic evidence for a core problem solving network across multiple representational domains Visuospatial problem solving ALE contrast map: [Visuospatial – Mathematical] ∩ [Visuospatial – Verbal]. Voxel-wise thresholding at P < 0.01 (FDR-corrected) using 250 mm3 minimum cluster volumes and 10,000 permutations.
65630 Meta-analysis result from 13 VBM studies: Hedges g effect size, gray matter volume (contrast is PTSD<Control so positive values are a reduction in gray matter volume) Meta-Analysis of 89 Structural MRI Studies in Posttraumatic Stress Disorder and Comparison With Major Depressive Disorder The following inclusion criteria were applied to the database of 113 studies: 1) gray matter VBM study comparing adult patients with PTSD to either non-traumatised-controls or traumatised-controls; 2) results presented in Talairach or MNI coordinates; 3) studies were only included if a whole brain analysis was performed rather than a small volume correction to ensure no bias in the regions reported. Thirteen studies met inclusion criteria and are listed in Table S1. We emailed all study authors who used SPM (Statistical Parametric Mapping) to process their data for a ‘T-map’ image comparing PTSD gray matter volume to the control group. ‘T-maps’ are three dimensional maps comprising statistical data of volume differences in thousands of voxels in the brain and provide far more detailed information than significant coordinates reported in studies. However, SDM allows both T-maps and coordinates to be combined in a single meta-analysis and the methodology reported in detail by Radua et al. We received 6 T-maps from 6 independent studies and these were included in the meta-analyses. In addition to the main meta-analysis comparing PTSD to all controls, three additional VBM analyses were conducted: 1) comparing the PTSD group with non-traumatised-controls only 2) comparing the PTSD group with traumatised-controls only, 3) comparing PTSD group with all controls and widening the criteria to include paediatric studies. T-maps and coordinates signifying gray matter volume changes from where we were unable to obtain T-maps were extracted from relevant studies and analysed using Seed-based d Mapping (SDM version 5.14, http://www.sdmproject.com). For studies where coordinate data was used, these were convolved with a Gaussian kernel (FWHM=20mm) in order to optimally compensate the sensitivity and specificity of the analysis. As is standard in SDM analyses, the number of randomizations were set to 100 and a threshold was set at p<0.005 as well as a cluster-level threshold of 10 voxels in order to increase sensitivity and correctly control false-positive rate.8 A jackknife sensitivity analysis was performed in order to assess the robustness of the results which was achieved by excluding one study in each of the analyses.
65133 Unthresholded ALE meta-analysis: mathematical problem solving Meta-analytic evidence for a core problem solving network across multiple representational domains Unthresholded ALE map of mathematical problem solving experiments.
65631 Meta-analysis result from 13 VBM studies: Unthresholded Z map, gray matter volume, (contrast is PTSD<Control so positive values are a reduction in gray matter volume Meta-Analysis of 89 Structural MRI Studies in Posttraumatic Stress Disorder and Comparison With Major Depressive Disorder The following inclusion criteria were applied to the database of 113 studies: 1) gray matter VBM study comparing adult patients with PTSD to either non-traumatised-controls or traumatised-controls; 2) results presented in Talairach or MNI coordinates; 3) studies were only included if a whole brain analysis was performed rather than a small volume correction to ensure no bias in the regions reported. Thirteen studies met inclusion criteria and are listed in Table S1. We emailed all study authors who used SPM (Statistical Parametric Mapping) to process their data for a ‘T-map’ image comparing PTSD gray matter volume to the control group. ‘T-maps’ are three dimensional maps comprising statistical data of volume differences in thousands of voxels in the brain and provide far more detailed information than significant coordinates reported in studies. However, SDM allows both T-maps and coordinates to be combined in a single meta-analysis and the methodology reported in detail by Radua et al. We received 6 T-maps from 6 independent studies and these were included in the meta-analyses. In addition to the main meta-analysis comparing PTSD to all controls, three additional VBM analyses were conducted: 1) comparing the PTSD group with non-traumatised-controls only 2) comparing the PTSD group with traumatised-controls only, 3) comparing PTSD group with all controls and widening the criteria to include paediatric studies. T-maps and coordinates signifying gray matter volume changes from where we were unable to obtain T-maps were extracted from relevant studies and analysed using Seed-based d Mapping (SDM version 5.14, http://www.sdmproject.com). For studies where coordinate data was used, these were convolved with a Gaussian kernel (FWHM=20mm) in order to optimally compensate the sensitivity and specificity of the analysis. As is standard in SDM analyses, the number of randomizations were set to 100 and a threshold was set at p<0.005 as well as a cluster-level threshold of 10 voxels in order to increase sensitivity and correctly control false-positive rate.8 A jackknife sensitivity analysis was performed in order to assess the robustness of the results which was achieved by excluding one study in each of the analyses.
65115 Thresholded ALE meta-analysis: verbal problem solving Meta-analytic evidence for a core problem solving network across multiple representational domains Cluster-level FWE-corrected (alpha=0.05, CDT=0.001) ALE map of verbal problem solving experiments.
24849 Figure 1 Brain structure anomalies in autism spectrum disorder-a meta-analysis of VBM studies using anatomic likelihood estimation Significant clusters of convergence obtained by ALE-based analysis indicating locations in the lateral occipital lobe, the pericentral region, the medial temporal lobe, the basal ganglia and proximate to the right parietal operculum. Both foci indicating gray and white matter changes were included in this model. Since disturbances in brain growth trajectories were discussed as a key pathophysiological feature in ASD, we integrated both foci reporting increases and decreases of gray matter (GM) or white matter (WM) in our analysis. Thus, the depicted clusters indicate brain regions consistently altered in ASD patients.
59098 Figure 1 Neural networks related to dysfunctional face processing in autism spectrum disorder A single cluster indicating convergent evidence for hypoac- tivation in ASD patients compared to healthy controls during face processing was located in the left lateral temporal lobe, in particular the fusiform gyrus (-43, -61, -10, k = 172) [p < 0.05 (cluster-level FWE corrected for multiple comparisons, cluster-forming threshold p < 0.001 at voxel level)]. There were no clusters indicating increased activation in ASD patients compared to healthy controls
59099 Left Cluster 1 Co-activation based parcellation of the human frontal pole Cluster 1 binary mask of left hemisphere 3 cluster solution shown in Fig 2
59100 Left Cluster 2 Co-activation based parcellation of the human frontal pole Cluster 2 binary mask of left hemisphere 3 cluster solution shown in Fig 2
59101 Left Cluster 3 Co-activation based parcellation of the human frontal pole Cluster 3 binary mask of left hemisphere 3 cluster solution shown in Fig 2
59102 Right Cluster 1 Co-activation based parcellation of the human frontal pole Cluster 1 binary mask of right hemisphere 3 cluster solution shown in Fig 2
59103 Right Cluster 2 Co-activation based parcellation of the human frontal pole Cluster 2 binary mask of right hemisphere 3 cluster solution shown in Fig 2
59104 Right Cluster 3 Co-activation based parcellation of the human frontal pole Cluster 3 binary mask of right hemisphere 3 cluster solution shown in Fig 2
59105 Right Cluster 1 MACM Co-activation based parcellation of the human frontal pole Cluster 1 MACM of right hemisphere 3 cluster solution shown in Fig 3. Cluster-level corrected threshold of p < 0.05 (cluster-forming threshold at voxel-level p < 0.001).
59106 Right Cluster 2 MACM Co-activation based parcellation of the human frontal pole Cluster 2 MACM of right hemisphere 3 cluster solution shown in Fig 3. Cluster-level corrected threshold of p < 0.05 (cluster-forming threshold at voxel-level p < 0.001).
59107 Right Cluster 3 MACM Co-activation based parcellation of the human frontal pole Cluster 3 MACM of right hemisphere 3 cluster solution shown in Fig 3. Cluster-level corrected threshold of p < 0.05 (cluster-forming threshold at voxel-level p < 0.001).
59108 Left Cluster 1 MACM Co-activation based parcellation of the human frontal pole Cluster 1 MACM of left hemisphere 3 cluster solution shown in Fig 3. Cluster-level corrected threshold of p < 0.05 (cluster-forming threshold at voxel-level p < 0.001).
59109 Left Cluster 2 MACM Co-activation based parcellation of the human frontal pole Cluster 2 MACM of left hemisphere 3 cluster solution shown in Fig 3. Cluster-level corrected threshold of p < 0.05 (cluster-forming threshold at voxel-level p < 0.001).
59110 Left Cluster 3 MACM Co-activation based parcellation of the human frontal pole Cluster 3 MACM of left hemisphere 3 cluster solution shown in Fig 3. Cluster-level corrected threshold of p < 0.05 (cluster-forming threshold at voxel-level p < 0.001).
60943 Pezzoli region - meta-analysis result: reduced white matter in bipolar disorder Meta-analysis of regional white matter volume in bipolar disorder with replication in an independent sample using coordinates, T-maps, and individual MRI data Image is a binarized mask where robust reductions in white matter volume were identified in a meta-analysis. It is effectively the Z-score image with a threshold of Z<-3
65114 Thresholded core problem solving network Meta-analytic evidence for a core problem solving network across multiple representational domains Core problem solving ALE conjunction map: Mathematical ∩ Verbal ∩ Visuospatial computed using the conservative minimum statistic.
304313 Meta-analysis of equal probability Go/NoGo tasks (Unthresholded Z score image) Non-selective response inhibition during an equal probability Go/NoGo task: Bayesian analysis of fMRI data ALE Meta-analysis included 20 fMRI studies (452 healthy subjects, mean age of 29 years, 210 foci). The contrast of interest “Go/NoGo > Go-control” within a group of healthy subjects. The meta-analysis was aimed at identifying the brain structures that may be associated with response inhibition and that were previously revealed using equal probability Go/NoGo tasks comparable to the present study. We were searching for papers that, like the paper by Criaud et al. (2017), compared the neuronal activity in the condition of equiprobable Go- and NoGo-stimuli presentation with the control Go-condition, wherein the subject did not need to inhibit prepared action. The meta-analysis was conducted using GingerALE 3.0.2 software with a cluster-forming threshold of 0.001 (uncorrected) and a cluster-level threshold of 0.05 corrected for family-wise error (FWE). All the coordinates were converted into Montreal Neurological Institute (MNI) space. The median full width at half maximum (FWHM) value of Gaussian function was set at a level of 13.5 mm.
60944 Meta-analysis result: Hedges g effect size, White matter volume reduction in bipolar disorder (contrast is Patients>Controls so negative values are reduction in patients) Meta-analysis of regional white matter volume in bipolar disorder with replication in an independent sample using coordinates, T-maps, and individual MRI data Hedges g effect size for reductions in white matter volume in bipolar disorder from a T-map meta-analysis using SDM. Negative values represent white matter volume reductions in bipolar disorder, positive values are white matter volume increases
65108 Thresholded ALE meta-analysis: mathematical problem solving Meta-analytic evidence for a core problem solving network across multiple representational domains Cluster-level FWE-corrected (alpha=0.05, CDT=0.001) ALE map of mathematical problem solving experiments.
65134 Untresholded ALE meta-analysis: verbal problem solving Meta-analytic evidence for a core problem solving network across multiple representational domains Unthresholded ALE map of verbal problem solving experiments.
304314 Meta-analysis of equal probability Go/NoGo tasks (Thresholded ALE image) Non-selective response inhibition during an equal probability Go/NoGo task: Bayesian analysis of fMRI data ALE Meta-analysis included 20 fMRI studies (452 healthy subjects, mean age of 29 years, 210 foci). The contrast of interest “Go/NoGo > Go-control” within a group of healthy subjects. The meta-analysis was aimed at identifying the brain structures that may be associated with response inhibition and that were previously revealed using equal probability Go/NoGo tasks comparable to the present study. We were searching for papers that, like the paper by Criaud et al. (2017), compared the neuronal activity in the condition of equiprobable Go- and NoGo-stimuli presentation with the control Go-condition, wherein the subject did not need to inhibit prepared action. The meta-analysis was conducted using GingerALE 3.0.2 software with a cluster-forming threshold of 0.001 (uncorrected) and a cluster-level threshold of 0.05 corrected for family-wise error (FWE). All the coordinates were converted into Montreal Neurological Institute (MNI) space. The median full width at half maximum (FWHM) value of Gaussian function was set at a level of 13.5 mm.
60945 Meta-analysis result: Z- map, Bipolar disorder white matter volume (contrast is Patients>Controls so negatives are reduction) Meta-analysis of regional white matter volume in bipolar disorder with replication in an independent sample using coordinates, T-maps, and individual MRI data Z map relating to the significance of the effect size of white matter volume changes in bipolar disorder compared to controls
65107 Thresholded ALE contrast analysis: mathematical selective Meta-analytic evidence for a core problem solving network across multiple representational domains Mathematical problem solving ALE contrast map: [Mathematical – Verbal] ∩ [Mathematical – Visuospatial]. Voxel-wise thresholding at P < 0.01 (FDR-corrected) using 250 mm3 minimum cluster volumes and 10,000 permutations.
304316 Overlap between meta-analysis and null "NoGo=Go" effect regions revealed by Bayesian analysis (Binary mask) Non-selective response inhibition during an equal probability Go/NoGo task: Bayesian analysis of fMRI data Overlap between increased activity in “Go/NoGo > Go-control” comparison (Meta-analysis of equal probability Go/NoGo tasks) and the practical equivalence of the BOLD signal revealed in “NoGo = Go” comparison (Bayesian analysis of obtained fMRI data).
65109 Thresholded ALE meta-analysis: global problem solving Meta-analytic evidence for a core problem solving network across multiple representational domains Cluster-level FWE-corrected (alpha=0.05, CDT=0.001) ALE map of global problem solving experiments.
65135 Unthresholded ALE meta-analysis: visuospatial problem solving Meta-analytic evidence for a core problem solving network across multiple representational domains Unthreholded ALE map of visuospatial problem solving experiments.
304315 The Null “NoGo = Go” effect regions revealed by Bayesian analysis (Binary mask) Non-selective response inhibition during an equal probability Go/NoGo task: Bayesian analysis of fMRI data The second level of analysis was conducted using Bayesian statistics in SPM12 (Friston, 2002, Friston & Penny, 2003, Neumann & Lohmann, 2003). The beta-coefficients were converted into percent signal change (PSC) following the procedure recommended by (Pernet, 2014). Linear contrasts were used to calculate the difference of the BOLD-signal percent changes in the conditions under study: 1) [“A-P NoGo” – “A-A Go”] (Experiment #1); 2) [“A-A NoGo” – “A-P Go”] (Experiment #2). If the contrast value falls within the interval [-γ; γ] with a posterior probability of over α = 95%, then the hypothesis of null “NoGo = Go” effect can be accepted, supporting similarity or the practical equivalence (more precise statistical term (Kruschke & Liddell, 2015)) of the BOLD signal between compared conditions. Applying such a threshold corresponds to a false discovery rate (FDR) correction for multiple comparisons (Genovese et al., 2002, Friston & Penny, 2003). The effect size threshold γ = 0.1% was used in this study that is a minimal BOLD-signal percent change that represents an “activation” (or “deactivation) in the sense of a hemodynamic response that is typically evoked in an fMRI-experiment (Friston et al., 2002). The interval [-γ; γ] can be thought as the neuronal ‘‘background noise level’’ (Eickhoff et al., 2008) or as a region of practical equivalence that expresses which the contrast values are equivalent to the null value for current practical purposes (Kruschke & Liddell, 2015). Thresholded images were binarized and multiplied (logical AND) between experiment sessions to attain conjunction maps of “NoGo = Go” effects common for both experimental sessions (Nichols et al., 2005).
65112 Thresholded ALE meta-analysis: visuospatial problem solving Meta-analytic evidence for a core problem solving network across multiple representational domains Cluster-level FWE-corrected (alpha=0.05, CDT=0.001) ALE map of visuospatial problem solving experiments.
65136 Unthresholded ALE meta-analysis: global problem solving Meta-analytic evidence for a core problem solving network across multiple representational domains Unthresholded ALE map of global problem solving experiments.
65113 Thresholded ALE meta-analysis: problem demand Meta-analytic evidence for a core problem solving network across multiple representational domains Cluster-level FWE-corrected (alpha=0.05, CDT=0.001) ALE map of problem demand.
65137 Unthresholded ALE meta-analysis: problem demand Meta-analytic evidence for a core problem solving network across multiple representational domains Unthresholded ALE map of problem demand.
12015 Figure 1 (Morality) Parsing the neural correlates of moral cognition: ALE meta-analysis on morality, theory of mind, and empathy Figure 1, Column 1: Morality. ALE meta-analysis of neuroimaging studies on moral cognition, theory of mind, and empathy. Significant meta-analysis results displayed on frontal, right, and left surface view as well as sagittal, coronal, and axial sections of the MNI single-subject template. Coordinates in MNI space. All results were significant at a clusterforming threshold of p\0.05 and an extent threshold of k = 10 voxels (to exclude presumably incidental results).
12016 Figure 1 (ToM) Parsing the neural correlates of moral cognition: ALE meta-analysis on morality, theory of mind, and empathy Figure 1, Column 2: Theory of Mind. ALE meta-analysis of neuroimaging studies on moral cognition, theory of mind, and empathy. Significant meta-analysis results displayed on frontal, right, and left surface view as well as sagittal, coronal, and axial sections of the MNI single-subject template. Coordinates in MNI space. All results were significant at a clusterforming threshold of p\0.05 and an extent threshold of k = 10 voxels (to exclude presumably incidental results).
12017 Figure 1 (Empathy) Parsing the neural correlates of moral cognition: ALE meta-analysis on morality, theory of mind, and empathy Figure 1, Column 3: Empathy. ALE meta-analysis of neuroimaging studies on moral cognition, theory of mind, and empathy. Significant meta-analysis results displayed on frontal, right, and left surface view as well as sagittal, coronal, and axial sections of the MNI single-subject template. Coordinates in MNI space. All results were significant at a clusterforming threshold of p\0.05 and an extent threshold of k = 10 voxels (to exclude presumably incidental results).
12020 Figure 1, third column ALE meta-analysis on facial judgments of trustworthiness and attractiveness All neuroimaging experiments labeled as attractiveness judgment
12021 Figure 1, first column ALE meta-analysis on facial judgments of trustworthiness and attractiveness All neuroimaging experiments labeled as trustworthiness or attractiveness judgment
12022 Figure 1, second column ALE meta-analysis on facial judgments of trustworthiness and attractiveness All neuroimaging experiments labeled as trustworthiness judgment
12023 Meta_Observation ALE meta-analysis of action observation and imitation in the human brain corresponding to Fig. 1The file contains the significant meta-analysis results (p < 0.05, cluster-level corrected) showing convergent activation of brain regions across all studies reporting action observation experiments included in the meta-analysis (cf. Table 1).
12024 Meta_Imitation ALE meta-analysis of action observation and imitation in the human brain corresponding to Fig. 5The file contains the significant meta-analysis results (p < 0.05, cluster-level corrected) showing convergent activation of brain regions across all studies reporting action imitation experiments included in the meta-analysis.
12025 Conjunction_Observation-Imitation ALE meta-analysis of action observation and imitation in the human brain corresponding to Fig. 7AThe file contains the significant results of the conjunction (p < 0.05, cluster-level corrected) between the meta-analysis results for action observation and action imitation, thus the conjunction between the files in no. 1 and 2.
12030 Figure 1 Three key regions for supervisory attentional control: Evidence from neuroimaging meta-analyses ALE result for conflict minus that for no conflict
12031 Figure 2A Three key regions for supervisory attentional control: Evidence from neuroimaging meta-analyses ALE result for the Stroop task
12032 Figure 2B Three key regions for supervisory attentional control: Evidence from neuroimaging meta-analyses ALE result for Spatial Interference Tasks
12033 Figure 2C Three key regions for supervisory attentional control: Evidence from neuroimaging meta-analyses ALE result for the Stop-Signal Task
12034 Figure 2D Three key regions for supervisory attentional control: Evidence from neuroimaging meta-analyses ALE result for the Go/No-Go Task
12035 Figure 3 Three key regions for supervisory attentional control: Evidence from neuroimaging meta-analyses Conjunction across all four task types
12036 Figure 4 Three key regions for supervisory attentional control: Evidence from neuroimaging meta-analyses Conjunction across Stroop, Spatial Interference and Stop-Signal Tasks
12080 All Pain Studies Coordinate-based meta-analysis of experimentally induced and chronic persistent neuropathic pain ALE result for all pain studies
12081 Experimental Pain Studies Coordinate-based meta-analysis of experimentally induced and chronic persistent neuropathic pain ALE result for all experimentally induced pain studies
12082 Experimental - Neuropathic Coordinate-based meta-analysis of experimentally induced and chronic persistent neuropathic pain ALE results of all experimentally induced pain studies, minus that of all neuropathic pain studies. Thresholded at uncorrected p < 0.05.
12083 Neuropathic ∪ Experimental Coordinate-based meta-analysis of experimentally induced and chronic persistent neuropathic pain Conjunction of ALEs for experimentally induced and neuropathic pain. Thresholded at uncorrected p < 0.05.
12084 All Neuropathic Studies Coordinate-based meta-analysis of experimentally induced and chronic persistent neuropathic pain ALE result for all neuropathic pain studies
12085 All Non-thermal Pain Studies Coordinate-based meta-analysis of experimentally induced and chronic persistent neuropathic pain ALE result for all non-thermally induced pain studies
12086 Non-thermal - Thermal Coordinate-based meta-analysis of experimentally induced and chronic persistent neuropathic pain ALE for non-thermally induced pain studies, minus that for thermally induced pain studies. Thresholded at uncorrected p < 0.05.
12087 Thermal ∪ Non-thermal Coordinate-based meta-analysis of experimentally induced and chronic persistent neuropathic pain Conjunction of ALEs for all thermally and non-thermally induced pain studies. Thresholded at uncorrected p < 0.05.
12088 All Thermal Studies Coordinate-based meta-analysis of experimentally induced and chronic persistent neuropathic pain ALE result for all thermally induced pain studies.
12089 Figure 2C - Left anterior insula Identification of a Common Neurobiological Substrate for Mental Illness Conjunction showing common grey matter loss across diagnoses in the left anterior insula.
12090 Figure 2C - Right anterior insula Identification of a Common Neurobiological Substrate for Mental Illness Conjunction showing common grey matter loss across diagnoses in the right anterior insula.
12091 Figure 2C - Dorsal ACC Identification of a Common Neurobiological Substrate for Mental Illness Conjunction showing common grey matter loss across diagnoses in the dorsal anterior cingulate cortex (dACC).
12151 Figure 1 Sustaining attention to simple tasks: A meta-analytic review of the neural mechanisms of vigilant attention. The Nifti file "Attention_cFWE05_001_103.nii" contains the thresholded results of the ALE main effect, as shown in Fig. 1 of the associated paper.
12154 Figure 1A - MCI>HC during memory encoding Specific and disease stage-dependent episodic memory-related brain activation patterns in Alzheimer’s disease: a coordinate-based meta-analysis Increased right hippocampal activation in MCI patients compared to age-matched control subjects during memory encoding of visual or verbal stimuli.
12155 Figure 1B - MCI<HC during imagery retrieval Specific and disease stage-dependent episodic memory-related brain activation patterns in Alzheimer’s disease: a coordinate-based meta-analysis Decreased left hippocampal activation in MCI patients compared to age-matched control subjects during retrieval of previously learned image stimuli.
12156 Figure 1C - AD<HC during retrieval Specific and disease stage-dependent episodic memory-related brain activation patterns in Alzheimer’s disease: a coordinate-based meta-analysis Decreased right hippocampal activation in AD patients compared to age-matched control subjects during retrieval of visual or verbal stimuli.
12157 Figure 2 - MCI<HC during verbal retrieval Specific and disease stage-dependent episodic memory-related brain activation patterns in Alzheimer’s disease: a coordinate-based meta-analysis Decreased right insula and inferior frontal gyrus activation in MCI patients compared to age-matched control subjects during verbal episodic-memory retrieval tasks.
12158 Figure 3 - AD>HC during visual retrieval Specific and disease stage-dependent episodic memory-related brain activation patterns in Alzheimer’s disease: a coordinate-based meta-analysis Stronger, bilateral (right>left) precuneus activation in AD patients compared to age-matched control subjects during image encoding.
12191 Figure 2 - EMO Network Introspective Minds: Using ALE Meta-Analyses to Study Commonalities in the Neural Correlates of Emotional Processing, Social & Unconstrained Cognition Significant results of the ALE meta-analysis of emotional processing tasks (EMO).
12192 Figure 4 - SOC ∩ EMO Introspective Minds: Using ALE Meta-Analyses to Study Commonalities in the Neural Correlates of Emotional Processing, Social & Unconstrained Cognition Significant results of the conjunction analysis of SOC ∩ EMO.
12193 Figure 5 - SOC ∩ DMN Introspective Minds: Using ALE Meta-Analyses to Study Commonalities in the Neural Correlates of Emotional Processing, Social & Unconstrained Cognition Significant results of the conjunction analysis of SOC ∩ DMN.
12194 Supplemental Figure 1 - EMO ∩ DMN Introspective Minds: Using ALE Meta-Analyses to Study Commonalities in the Neural Correlates of Emotional Processing, Social & Unconstrained Cognition Significant results of the conjunction analysis of EMO ∩ DMN.
12195 Supplemental Figure 2 - (SOC ∪ EMO) ∩ DMN Introspective Minds: Using ALE Meta-Analyses to Study Commonalities in the Neural Correlates of Emotional Processing, Social & Unconstrained Cognition Significant results of the conjunction analysis of (SOC ∪ EMO) ∩ DMN.
12196 Figure 1 - SOC Network Introspective Minds: Using ALE Meta-Analyses to Study Commonalities in the Neural Correlates of Emotional Processing, Social & Unconstrained Cognition Significant results of the ALE meta-analysis for social cognition tasks (SOC).
12197 Figure 3 - DMN network Introspective Minds: Using ALE Meta-Analyses to Study Commonalities in the Neural Correlates of Emotional Processing, Social & Unconstrained Cognition Significant results of the ALE meta-analysis of unconstrained cognition (DMN).
12198 Figure 6 - SOC ∩ EMO ∩ DMN Introspective Minds: Using ALE Meta-Analyses to Study Commonalities in the Neural Correlates of Emotional Processing, Social & Unconstrained Cognition Significant results of the conjunction analysis of SOC ∩ EMO ∩ DMN.
65110 Thresholded ALE contrast analysis: verbal selective Meta-analytic evidence for a core problem solving network across multiple representational domains Verbal problem solving ALE contrast map: [Verbal – Mathematical] ∩ [Verbal – Visuospatial]. Voxel-wise thresholding at P < 0.01 (FDR-corrected) using 250 mm3 minimum cluster volumes and 10,000 permutations.