There are many active research projects accessing and applying shared ADNI data. Use the search above to find specific research focuses on the active ADNI investigations. This information is requested annually as a requirement for data access.
| Principal Investigator | |
| Principal Investigator's Name: | Junjie Zeng |
| Institution: | Nanchang University |
| Department: | none |
| Country: | |
| Proposed Analysis: | 1. Research Question: Investigating the neural correlates of working memory in individuals with schizophrenia compared to healthy controls. 2. Data: Preprocessed fMRI data acquired from individuals with schizophrenia and a matched control group during a working memory task. 3. Analysis Steps: a. Preprocessing: - Slice timing correction: Correct for the temporal offset between slices. - Motion correction: Correct for head motion during scanning. - Spatial smoothing: Apply a Gaussian filter to improve signal-to-noise ratio. - Registration: Register the functional images to a standard anatomical template. - Intensity normalization: Normalize the intensities of the functional images. b. First-Level Analysis: - Design matrix creation: Construct a design matrix that includes the task paradigm, confound regressors (e.g., motion parameters), and any additional covariates of interest (e.g., age, sex). - Model estimation: Estimate the model parameters using a general linear model (GLM) approach. - Contrast specification: Define contrasts of interest to compare working memory activation between groups. c. Second-Level Analysis: - Group-level analysis: Perform a random-effects analysis to compare working memory activation between individuals with schizophrenia and healthy controls. - Thresholding and correction: Apply appropriate statistical thresholding (e.g., cluster-based thresholding) and correct for multiple comparisons. d. Region of Interest (ROI) Analysis: - Define ROIs: Identify specific brain regions implicated in working memory from previous literature or use data-driven methods (e.g., independent component analysis). - Extract ROI signals: Extract the average time series from the ROIs for each participant. - Statistical analysis: Compare ROI signals between groups using appropriate statistical tests (e.g., t-tests). e. Connectivity Analysis: - Seed-based analysis: Select seed regions implicated in working memory and compute functional connectivity maps with other brain regions. - Network analysis: Apply graph theory measures to assess alterations in functional brain networks between groups. 4. Statistical Analysis: - Statistical software: Utilize statistical packages like SPM, FSL, or AFNI for data analysis. - Statistical tests: Perform appropriate statistical tests, such as t-tests or analysis of variance (ANOVA), to compare group differences. - Correction for multiple comparisons: Apply correction methods such as family-wise error (FWE) or false discovery rate (FDR) correction. 5. Interpretation and Visualization: - Interpret the results in the context of the research question and existing literature. - Create visualizations, such as activation maps, connectivity matrices, or graphs, to aid in result interpretation and presentation. 6. Additional Analyses: - Subgroup analyses: Conduct additional analyses to explore potential subgroup differences within the schizophrenia group (e.g., based on symptom severity or medication status). - Correlation analyses: Investigate relationships between working memory activation/connectivity measures and clinical or cognitive variables. - Mediation/moderation analyses: Explore potential mediating or moderating factors in the relationship between working memory and clinical outcomes. |
| Additional Investigators |
