There are to date four CONN extensions that have been developed combining different aspects of SPM and CONN functionality for the analyses of arbitrary (non-connectivity) neuroimaging data, which are available/included as part of CONN releases:
Provides streamlined access to all of CONN's preprocessing and denoising steps (e.g. aCompCor) to prepare your functional/anatomical data for arbitrary (non-connectivity) analyses
A simple and powerful tool for group-level General Linear Model analyses of arbitrary data. Data sources may include 3D-volume, 3D-surface, or 2D-matrix NIFTI files, with arbitrary values/measures ( e.g. task-activation responses, volumetric measures, DTI-based anatomical connectivity measures, etc.). The GLM module provides simple access to all inferential methods available in CONN, including parametric cluster statistics (SPM Random Field Theory), non-parametric randomization/permutation analyses, Threshold Free Cluster Enhancement analyses, etc.
EvLab (evlab.mit.edu) fMRI pipeline for subject-centric task-activation analyses. A preprocessing and analysis pipeline that combines CONN preprocessing and denoising steps (e.g. scrubbing, aCompCor), SPM first-level task-activation analyses (including block-designs, event-related designs, and parametric modulation analyses), and including options for SPM_SS localizer and subject-specific analyses.
FrankLab (sites.bu.edu/guentherlab) fMRI pipeline for group-centric task-activation analyses. A preprocessing and analysis pipeline that combines a BIDS-compatible data organization, CONN preprocessing and denoising steps, SPM first-level task-activation analyses, as well as all group-level analyses options available in conn_module GLM.