To follow the same behavior while simulating with the sim command, ReturnWorkspaceOutputs is set to On by default.įor Simulink models built in previous releases, ReturnWorkspaceOutputs argument remains off. The Simulink.SimulationOutput object encapsulates all the resulting enabled simulation data (signal, state, output, data store logging, toworkspace block logging, and scope). Return simulation outputs as a single simulation output by default for new Simulink modelsįor simulation of new Simulink models, the output is returned as a single output object, Simulink.SimulationOutput. In the MATLAB /Simulink case, you can even filter to only display the compatibility changes.
If you have problem with a new version of a software (any software)) that you didn’t had before, you should take a look at the release notes. You cannot set Data Dictionary to ' ' unless you select Enable access to base workspace. Other model configuration issues to consider with this change:įor models created in previous releases, Enable access to base workspace is selected only if the model is not currently linked to a data dictionary.
If you have code that is based on the assumption that the model has access to either the base workspace or a data dictionary, this code must be modified to account for models with access to both. If you have Matlab (later version than 2014b) available, we recommend you downloading the source code and simply running the included file BacStalk.m. A new model still has access to the base workspace by default, but does not automatically lose access when it is linked to a data dictionary. This version lacks the Matlab figure editor to modify figures created with BacStalk. In R2019a, this limitation no longer exists. "Before R2019a, a model could have direct access to the base workspace or a data dictionary. Look under "Data Management" -> "Enable model to access data directly from base workspace and data dictionary " CONN can be entirely controlled through a user-friendly GUI, or through batch scripts/commands if preferred.Are you linking the model to a data dictionary? That could be the issue. When used within a distributed cluster or multi-processor environment CONN can automatically parallelize most time consuming steps in the fcMRI processing pipeline, allowing the analyses of hundreds of subjects in minimal time. Random Field Theory), and non-parametric permutation/randomization techniques (e.g. Control for multiple comparisons using parametric (e.g. Group- and population-level inferences and models, including ANOVA, regression, longitudinal, experimental, and mixed within- and between-subject designs. Multiple connectivity analyses and measures, including Seed-Based Correlations (SBC), ROI-to-ROI analyses, complex-network analyses, generalized Psycho-Physiological Interaction models (gPPI), Independent Component Analyses (group-ICA), masked ICA, Amplitude of Low-Frequency Fluctuations (ALFF & fALFF), Intrinsic Connectivity (ICC), Local Homogeneity (LCOR), Global Correlations (GCOR), Multivoxel Pattern Analyses (MVPA), and dynamic connectivity analyses (dyn-ICA, sliding-window correlations) FC histogram plots, BOLD signal carpetplots, Framewise Displacement, GCOR measures, FC-QC correlations) Integrated quality control procedures and measures (e.g. scrubbing, aCompCor, ICA-based denoising, Global Regression, band-pass filtering) Standardized preprocessing pipelines of functional and anatomical volumes powered by SPM12 (including susceptibility distortion correction, motion correction / realignment, slice-timing correction, outlier identification, coregistration, tissue-class segmentation, MNI-normalization, and smoothing)Ĭontrol of residual physiological and motion artifacts (e.g. Automatic import tools for BIDS datasets and fMRIPrep outputs Importing DICOM, ANALYZE, and NIfTI functional and anatomical files, either raw or partially/fully preprocessed volumes. In this post, Ill summarize the other new capabilities. I showed one new capability, visualizing activations in DAG networks, in my 26-March-2018 post. As usual (lately, at least), there are many new capabilities related to deep learning. Processing and analysis steps in CONN include: MathWorks shipped our R2018a release last month. CONN is used to analyze resting state data (rsfMRI) as well as task-related designs. CONN is an open-source Matlab/ SPM-based cross-platform software for the computation, display, and analysis of functional connectivity Magnetic Resonance Imaging (fcMRI).