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BASCO: a toolbox for task-related functional connectivity.

Göttlich M, Beyer F, Krämer UM - Front Syst Neurosci (2015)

Bottom Line: BASCO supports seed-based functional connectivity as well as brain network analyses.Thus, BASCO allows investigating task-specific rather than resting-state networks.Here, we summarize the main features of the toolbox and describe the methods and algorithms.

View Article: PubMed Central - PubMed

Affiliation: Department of Neurology, University of Lübeck Lübeck, Germany.

ABSTRACT
BASCO (BetA Series COrrelation) is a user-friendly MATLAB toolbox with a graphical user interface (GUI) which allows investigating functional connectivity in event-related functional magnetic resonance imaging (fMRI) data. Connectivity analyses extend and compliment univariate activation analyses since the actual interaction between brain regions involved in a task can be explored. BASCO supports seed-based functional connectivity as well as brain network analyses. Although there are a multitude of advanced toolboxes for investigating resting-state functional connectivity, BASCO is the first toolbox for evaluating task-related whole-brain functional connectivity employing a large number of network nodes. Thus, BASCO allows investigating task-specific rather than resting-state networks. Here, we summarize the main features of the toolbox and describe the methods and algorithms.

No MeSH data available.


(A) Experimental design. (B) SPM design matrix. (C) GLM fit in the occipital cortex.
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Figure 2: (A) Experimental design. (B) SPM design matrix. (C) GLM fit in the occipital cortex.

Mentions: In the following, we illustrate the functionality of the BASCO toolbox using the tutorial data set available from the project pages. The tutorial data contains measurements from two different subjects who performed a paradigm employing social-emotional stimuli. The participants viewed line drawings depicting either one or two persons (social factor) in an emotionally neutral or negative scene (emotional factor). Three experimental runs employing a slow event-related design were conducted (Figure 2A). Pictures were presented in random order but with no more than two successive pictures of the same condition. Each picture was presented for 6 s, followed by a fixation cross (always 10 s). Each run comprised 40 drawing, eight per condition. The data was acquired using a 3-T Siemens Magnetom Trio scanner employing a single-shot gradient echo echo-planar imaging (EPI) sequence (repetition time 2 s). The data was preprocessed using SPM. Preprocessing included slice time correction, motion correction, spatial normalization and spatial smoothing (Gaussian kernel with 8 mm FWHM). The functional data was resampled to 3 × 3 × 3 mm3. For more details on the paradigm, the data acquisition and the preprocessing we refer to Krämer et al. (2010).


BASCO: a toolbox for task-related functional connectivity.

Göttlich M, Beyer F, Krämer UM - Front Syst Neurosci (2015)

(A) Experimental design. (B) SPM design matrix. (C) GLM fit in the occipital cortex.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4565057&req=5

Figure 2: (A) Experimental design. (B) SPM design matrix. (C) GLM fit in the occipital cortex.
Mentions: In the following, we illustrate the functionality of the BASCO toolbox using the tutorial data set available from the project pages. The tutorial data contains measurements from two different subjects who performed a paradigm employing social-emotional stimuli. The participants viewed line drawings depicting either one or two persons (social factor) in an emotionally neutral or negative scene (emotional factor). Three experimental runs employing a slow event-related design were conducted (Figure 2A). Pictures were presented in random order but with no more than two successive pictures of the same condition. Each picture was presented for 6 s, followed by a fixation cross (always 10 s). Each run comprised 40 drawing, eight per condition. The data was acquired using a 3-T Siemens Magnetom Trio scanner employing a single-shot gradient echo echo-planar imaging (EPI) sequence (repetition time 2 s). The data was preprocessed using SPM. Preprocessing included slice time correction, motion correction, spatial normalization and spatial smoothing (Gaussian kernel with 8 mm FWHM). The functional data was resampled to 3 × 3 × 3 mm3. For more details on the paradigm, the data acquisition and the preprocessing we refer to Krämer et al. (2010).

Bottom Line: BASCO supports seed-based functional connectivity as well as brain network analyses.Thus, BASCO allows investigating task-specific rather than resting-state networks.Here, we summarize the main features of the toolbox and describe the methods and algorithms.

View Article: PubMed Central - PubMed

Affiliation: Department of Neurology, University of Lübeck Lübeck, Germany.

ABSTRACT
BASCO (BetA Series COrrelation) is a user-friendly MATLAB toolbox with a graphical user interface (GUI) which allows investigating functional connectivity in event-related functional magnetic resonance imaging (fMRI) data. Connectivity analyses extend and compliment univariate activation analyses since the actual interaction between brain regions involved in a task can be explored. BASCO supports seed-based functional connectivity as well as brain network analyses. Although there are a multitude of advanced toolboxes for investigating resting-state functional connectivity, BASCO is the first toolbox for evaluating task-related whole-brain functional connectivity employing a large number of network nodes. Thus, BASCO allows investigating task-specific rather than resting-state networks. Here, we summarize the main features of the toolbox and describe the methods and algorithms.

No MeSH data available.