Spm12

Manufactured by IBM

Sourced in United States

The SPM12 is a scanning probe microscope (SPM) designed and manufactured by IBM. The SPM12 is capable of high-resolution imaging and analysis of surfaces at the nanoscale level. It utilizes a sharp probe that scans the surface, providing detailed information about the topography and other properties of the sample being studied.

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Lab products found in correlation

Spss v26, by IBM (2 mentions) Matlab, by MathWorks (1 mentions) Spss version 25, by IBM (1 mentions) Spss process macro, by IBM (1 mentions) Spss v24, by IBM (1 mentions) Spss version 22, by IBM (1 mentions)

7 protocols using spm12

Relationships between [18F]-FEOBV and Cerebral Blood Flow

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Statistical analyses were conducted in SPM12 and SPSS 27.
Relationships between [¹⁸F]‐FEOBV in VOIs and sub-regional cBF volumes were assessed with two-tailed bivariate Pearson’s correlations, with family-wise error (FWE) correction for multiple comparisons across all cortical and subcortical VOIs. Significant outcomes were further assessed with control for age, and surviving outcomes were further controlled for age and disease duration using partial correlations.
We repeated the analysis above for participants with MCI as defined above. These outcomes were qualitatively compared with those from a similarly sized (N=38) group of participants without any evidence of MCI (i.e. with MoCA ⩾ 26). Please note that these results have not been corrected for multiple comparisons as they are presented for comparison with the full dataset only, and not findings in their own right.

Rao C.Y., Brain J.D, & Burge H.A. (2000). Reduction of Pulmonary Toxicity of Stachybotrys chartarum Spores by Methanol Extraction of Mycotoxins. Applied and Environmental Microbiology, 66(7), 2817-2821.

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Multivariate Neuroimaging Analysis of Cognitive Processing

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All statistical tests were performed across 42 participants (20 males, 22 females), with no between-subject factors. Behavioral analyses used repeated measures ANOVA to compare conditions. Univariate fMRI analyses used one-sample (paired-sample) two-tailed t tests to compare responses against baseline, between conditions, or linear contrasts of regression coefficients, and repeated measures ANOVA to compare multiple conditions. RSA fMRI analyses used one-sample one-tailed t tests to test for greater-than-chance representation of each information type, paired-sample two-tailed t tests to compare networks, and repeated measures ANOVA to test the interaction of information type and network. Within-subject factors are detailed in the relevant Results sections. For each analysis, multiple comparisons (across networks, component ROIs, or brain voxels) were accounted for by controlling the FDR at 0.05, unless noted otherwise. Effect sizes were calculated using partial η-squared for ANOVAs and Cohen's d for t tests. Analyses were performed using MATLAB (The MathWorks), SPM 12 (http://www.fil.ion.ucl.ac.uk/spm), and SPSS (version 25). In repeated measures ANOVA, Greenhouse–Geisser correction was used to adjust for non-sphericity. Data are available on request.

Wen T., Duncan J, & Mitchell D.J. (2020). Hierarchical Representation of Multistep Tasks in Multiple-Demand and Default Mode Networks. The Journal of Neuroscience, 40(40), 7724-7738.

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Synaptic Density Differences in APOE ε4 Carriers

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Group comparisons between ε4 carriers and ε4 non‐carriers were performed using Fisher's exact test for categorical variables and the two‐sample T test for continuous variables such as scores on neuropsychological assessments, age, and education years. The voxelwise and ROI‐wise differences in synaptic density among ε4 carriers and ε4 non‐carriers were analyzed by a general linear model (GLM) using SPM12 and SPSS (IBM version 26.0), respectively. Age, sex, and educational level were set as covariates, and a value of p < 0.001 was set as the significance threshold for the voxelwise analysis. Voxelwise analyses were repeated using partial volume‐corrected data.
For ROI‐wise analysis, association coefficients were calculated by partial correlation after adjusting for age, sex, and educational level. Fisher's Z test was used to compare coefficients between ε4 carriers and ε4 non‐carriers. Statistical significance was defined as an unadjusted two‐sided p value less than 0.05. Mediation effects were assessed using the SPSS PROCESS macro (version 3.3). Interaction effects were calculated with the R package stargazer (version 5.2.3).

He K., Li B., Wang J., Wang Y., You Z., Chen X., Chen H., Li J., Huang Q., Guo Q., Huang Y.H., Guan Y., Chen K., Zhao J., Deng Y, & Xie F. (2024). APOE ε4 is associated with decreased synaptic density in cognitively impaired participants. Alzheimer's & Dementia, 20(5), 3157-3166.

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Comparing Neurological Entropy Patterns

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The SPM12 and the IBM statistical package for social sciences (IBM SPSS v26, Armonk, New York) were employed for statistical analyses. Chi-square and independent-samples t-tests were used to examine group differences in demographic and other clinical data. We considered a p-value less than 0.05 as statistically significant.
The smoothed entropy maps were compared voxel-by-voxel between groups using analysis of covariance (ANCOVA), with age and sex included as covariates (SPM12, family-wise error correction for multiple comparisons, p<0.01). The global brain mask was used to restrict the analysis within brain regions only, and sites with significant differences between groups were overlaid onto background images for structural identification.

Ogren J.A., Allen L.A., Roy B., Diehl B., Stern J.M., Eliashiv D.S., Lhatoo S.D., Harper R.M, & Kumar R. (2022). Regional variation in brain tissue texture in patients with tonic-clonic seizures. PLoS ONE, 17(9), e0274514.

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Examining fALFF Changes in ECT Therapy

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Differences in patient clinical and demographic characteristics before and after treatment, continuous variables were compared using paired t-tests. Paired sample t-tests were used to examine changes in fALFF before and after ECT therapy in SPM12, and SPSS v26.0 (IBM, Chicago, NY, United States) was used for all other analyses with a false discovery rate (FDR)-corrected P value < 0.05 as the cutoff for significance. Significant variations in patient clinical symptoms, as defined by HAMD scores, were correlated with mean values for specified parameters in various brain areas using Pearson correlation analysis. Similarly, Pearson correlation analyses were used to determine whether there was a statistically significant relationship between fALFF values and the degree to which clinical symptom changes (ΔHAMD = pre-ECT HAMD – post-ECT HAMD).

Wang X.Y., Tan H., Li X., Dai L.Q., Zhang Z.W., Lv F.J, & Yu R.Q. (2022). Resting-state functional magnetic resonance imaging-based identification of altered brain the fractional amplitude of low frequency fluctuation in adolescent major depressive disorder patients undergoing electroconvulsive therapy. Frontiers in Psychiatry, 13, 972968.

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Entropy-based Brain Imaging Analysis

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The SPM12 and the IBM statistical package for social sciences (IBM SPSS v24, Armonk, New York) were employed for statistical analyses. Chi-square test and independent-samples t-tests were used to examine group differences in demographic and other data.
The smoothed entropy maps were compared voxel-by-voxel between groups using analysis of covariance (ANCOVA), with age and sex included as covariates (p<0.005, uncorrected). The global brain mask was used to restrict the analysis within brain regions only, and sites with significant differences between groups were overlaid onto background image for structural identification.
The mean entropy values, derived from ROI analyses, were compared between groups using ANCOVA (covariates, age and sex) and effect sizes were calculated. We considered a p-value less than 0.05 as statistically significant.

Kheirandish-Gozal L., Sahib A.K., Macey P.M., Philby M.F., Gozal D, & Kumar R. (2018). Regional Brain Tissue Integrity in Pediatric Obstructive Sleep Apnea. Neuroscience letters, 682, 118-123.

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Functional Connectivity Patterns in Positive and Negative Affect

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All statistical analyses were performed using SPSS version 22 (IBM Corp.) and SPM 12. Gender differences of PA/NA were examined with an independent-samples t test, and Pearson correlation analyses were used to detect the relationships of PA/NA with age, SEN connectivity, DMN connectivity, and FC between ROIs of the intrinsic network. The threshold of statistical significance (p) was set at .05 for all analyses. For the relationship of PA with the FC between ROIs within the SEN, we conducted a multiple comparison correction (Bonferroni correction) within these six families: the FC between Amyg and aIns, the FC between Amyg and VS (including VSi and VSs), the FC between aIns and VS, the FC between dACC and Amyg, the FC between dACC and VS, and the FC between dACC and aIns. Multiple linear regressions were conducted to test the relationships of PA with the FC between each ROI of the SEN and the whole brain. Since separate multiple linear regression analyses were conducted for the 10 ROIs within the SEN, we applied the false discovery rate (FDR) correction at p < .005 (.05/10), and cluster size >10 (Lieberman and Cunningham 2009 (link)).

Qi D., Lam C.L., Wong J.J., Chang D.H, & Lee T.M. (2020). Positive affect is inversely related to the salience and emotion network’s connectivity. Brain Imaging and Behavior, 15(4), 2031-2039.

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