Article Figures & Data
Figures
- Figure 1.
Overview of HTSSR framework and analyses, including (a1) training dataset, (b1) dictionary learning and TSR on training set to obtain D1 and α1, (c1) dictionary learning and spatial sparse representation (SSR) on training set to obtain D2 and α2, (a2) testing dataset, (b2) using D1 from training stage to obtain
- Figure 2.
Classification analysis on testing set. a, Classification accuracies for 10 independent experiments via hybrid temporal and spatial sparse representations (HTSSR) framework. The blue bar represents the classification accuracy of each experiment, and the orange bar is the average accuracy of 10 experiments. The dotted line represents the probability of random guesses (1/7 ≈ 14.29%). b, Classification rate for SVM-based classification on testing dataset using different number of components sorted by their ROA values. The different colored lines represent the ROA curves for 10 independent experiments. The x-axis is the number of components selected for the classification, and the y-axis is classification accuracy. See also Extended Data Figures 2-1, 2-2.
- Figure 3.
Identified task-evoked functional components of seven tasks (results of one experiment). a, Identified task-evoked components by hybrid temporal and spatial sparse representations (HTSSR) framework. b, Corresponding GLM-derived activation maps. c, Learned time courses of the task-evoked components (yellow) and task design paradigms curves (red). d, frequency spectrum of the components (yellow) and frequency spectrum of the task design (red). See also Extended Data Figures 3-1, 3-2, 3-3, 3-4, 3-5, 3-6, 3-7, 3-8, 3-9.
- Figure 4.
Six RSNs in the tfMRI dataset identified by our method, including (a) primary visual network, (b) default mode network (DMN), (c) cerebellum, (d) executive control network, (e) left frontoparietal network (lFPN), and (f) right frontoparietal network (rFPN).
- Figure 5.
Three integrated functional networks identified by our framework, including (a) bilateral frontoparietal network (FPN), (b) network blend with a default mode network (DMN), dorsolateral prefrontal cortex (dlPFC), and frontopolar area, and (c) salience network (SN).
- Figure 6.
Artifact-related components detected by our framework, including (a) head movement, (b) white-matter, (c) cardiac-related, and (d) magnetic resonance imaging (MRI) acquisition/reconstruction related.
- Figure 7.
Correlation between classification performance and spatial overlap rate of each functional network. Red points present k2 components (total 50 in our work) derived from SSR stage, and the blue line presents the regression line of these components.
Tables
- Table 1
The average Pearson correlation coefficients of the time courses (PCCTC) and the overlap rates of the functional networks of seven tasks for 10 experiments (mean ± SD)
Task Emotion Motor Gambling Language Relational Social WM Event 1 6 2 2 2 1 2 PCCTC 0.81 ± 0.05 0.91 ± 0.02 0.51 ± 0.09 0.87 ± 0.02 0.63 ± 0.04 0.66 ± 0.10 0.66 ± 0.06 Overlap 0.89 ± 0.05 0.70 ± 0.09 0.49 ± 0.13 0.62 ± 0.14 0.54 ± 0.13 0.79 ± 0.11 0.63 ± 0.08 - Table 2
The classification rates on testing set using different parameter settings of HTSSR model
λ1\λ2 0.05 0.1 0.5 0.05 99.05% 98.57% 99.52% 0.1 99.52% 99.52% 99.05% 0.5 14.29% 14.29% 14.29%
Extended Data Figure 1-1
Truncation of six task designs. Download Figure 1-1, TIF file.
Extended Data 1
The code. Download Extended Data 1, ZIP file.
Extended Data Figure 2-1
Classification rate of eliminating resting state and artifact components. Download Figure 2-1, TIF file.
Extended Data Figure 2-2
Examples of functional activations derived by λ1 = 0.5. Download Figure 2-2, TIF file.
Extended Data Figure 3-1
Brain activation of seven tasks for 10 experiments. Download Figure 3-1, TIF file.
Extended Data Figure 3-2
Representative temporal patterns of seven tasks for 10 experiments. Download Figure 3-2, TIF file.
Extended Data Figure 3-3
Task-evoked network for the emotion task. a, Identified task-evoked components by HTSSR framework. b, Corresponding GLM-derived activation maps. c, Learned time courses of the task-evoked components (yellow), task design paradigms curves (red). d, frequency spectrum of the components (yellow), frequency spectrum of the task design (red). Download Figure 3-3, TIF file.
Extended Data Figure 3-4
Task-evoked network for the motor task. a, Identified task-evoked components by HTSSR framework. b, Corresponding GLM-derived activation maps. c, Learned time courses of the task-evoked components (yellow), task design paradigms curves (red). d, frequency spectrum of the components (yellow), frequency spectrum of the task design (red). Download Figure 3-4, TIF file.
Extended Data Figure 3-5
Task-evoked network for the gambling task. a, Identified task-evoked components by HTSSR framework. b, Corresponding GLM-derived activation maps. c, Learned time courses of the task-evoked components (yellow), task design paradigms curves (red). d, frequency spectrum of the components (yellow), frequency spectrum of the task design (red). Download Figure 3-5, TIF file.
Extended Data Figure 3-9
The brain activation and temporal patterns of relational task (the enlarged view of the relational task of Fig. 3). Download Figure 3-9, TIF file.
Extended Data Figure 3-8
Task-evoked network for the WM task. a, Identified task-evoked components by HTSSR framework. b, Corresponding GLM-derived activation maps. c, Learned time courses of the task-evoked components (yellow), task design paradigms curves (red). d, frequency spectrum of the components (yellow), frequency spectrum of the task design (red). Download Figure 3-8, TIF file.
Extended Data Figure 3-7
Task-evoked network for the relational task. a, Identified task-evoked components by HTSSR framework. b, Corresponding GLM-derived activation maps. c, Learned time courses of the task-evoked components (yellow), task design paradigms curves (red). d, frequency spectrum of the components (yellow), frequency spectrum of the task design (red). Download Figure 3-7, TIF file.
Extended Data Figure 3-6
Task-evoked network for the language task. a, Identified task-evoked components by HTSSR framework. b, Corresponding GLM-derived activation maps. c, Learned time courses of the task-evoked components (yellow), task design paradigms curves (red). d, frequency spectrum of the components (yellow), frequency spectrum of the task design (red). Download Figure 3-6, TIF file.
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