Table 1.
Overview of rs-fMRI study groups.
Fig 1.
Block diagram of the AD diagnosing model using CorrTF features and CNN.
Table 2.
The ROIs extracted from the different based on 116 AAL template.
Fig 2.
Representation of the transfer function H(f) for the system in time and frequency domain.
Fig 3.
Hierarchical classification scheme to identify the stage of Alzheimer’s disease into NC, EMCI, LMCI, and AD.
Table 3.
Binary classification result accuracies (mean ± standard deviation).
Table 4.
Classification performance of our model using CorrTF features (mean ± standard deviation).
Table 5.
Confusion matrix for: (a) Flat multi-classification, (b) Hierarchical multi-classification scheme.
Table 6.
Comparison with recently published work using ADNI dataset.
Fig 4.
Brain connectivity networks for (a) CN, (b) EMCI, (c) LMCI, and (d) AD at threshold = 0.1, the color code defines the connection’s strength.
Fig 5.
Number of connections with strength >0.1 grouped by input-output networks with connection’s directionality ignored.
Sensorimotor Cortex (SMC), Visual Cortex (VC), Executive Attention Network (EAN), Default-Mode Network (DMN), Subcortical Nuclei (SN), and Cerebellum (Cereb).
Fig 6.
Localization of brain regions that have significant change in connections’ strength in case of AD compared to NC subjects AD, (a) Sagittal view, (b) Axial view, and (d) Coronal view.
yellow: default-mode network; orange: regions of the subcortical nuclei; dark blue: regions of the sensorimotor cortex; blue: regions of the visual cortex; cyan: regions involved in the executive attention network; red: regions in the cerebellum.
Table 7.
The most discriminative connections between CN and AD.