Leukoaraiosis (LA) describes diffuse white matter abnormalities on CT or MR brain scans, often seen in the normal elderly and in association with vascular risk factors such as hypertension, or in the context of cognitive impairment. The mechanism of cognitive dysfunction is still unclear. The recent clinical studies have revealed that the severity of LA was not corresponding to the cognitive level, and functional connectivity analysis is an appropriate method to detect the relation between LA and cognitive decline. However, existing functional connectivity analyses of LA have been mostly limited to linear associations. In this investigation, a novel measure utilizing the extended maximal information coefficient (eMIC) was applied to construct non-linear functional connectivity in 44 LA subjects (9 dementia, 25 mild cognitive impairment (MCI) and 10 cognitively normal (CN)). The strength of non-linear functional connections for the first 1% of discriminative power increased in MCI compared with CN and dementia, which was opposed to its linear counterpart. Further functional network analysis revealed that the changes of the non-linear and linear connectivity have similar but not completely the same spatial distribution in human brain. In the multivariate pattern analysis with multiple classifiers, the non-linear functional connectivity mostly identified dementia, MCI and CN from LA with a relatively higher accuracy rate than the linear measure. Our findings revealed the non-linear functional connectivity provided useful discriminative power in classification of LA, and the spatial distributed changes between the non-linear and linear measure may indicate the underlying mechanism of cognitive dysfunction in LA.
Motor tasks, in our daily life, could be performed through execution and imagination. The brain response underlying
these movements has been investigated by many studies. Neuroimaging studies have reported that both execution and imagination could activate several brain regions including supplementary motor area (SMA), premotor area (PMA),
primary sensorimotor area (M1/S1), posterior parietal lobe (PPL), striatum, thalamus and cerebellum. These findings
were based on the regional activation, and brain regions have been indicated to functionally interact with each other
when performing tasks. Therefore further investigation in these brain regions with functional connectivity measurements may provide new insights into the neural mechanism of execution and imagination. As a fundamental measurement of functional connectivity, connection strength of graph theory has been used to identify the key nodes of connection and their strength-priorities. Thus, we performed a comparative investigation between execution and imagination tasks with functional magnetic resonance imaging (fMRI), and further explored the key nodes of connection and their strength-priorities based on the results of functional activations. Our results revealed that bilateral SMA, contralateral PMA, thalamus and M1/S1 were involved in both tasks as key nodes of connection. These nodes may play important roles in motor control and motor coordination during execution and imagination. Notably, the strength-priorities of contralateral PMA and thalamus were different between the two tasks. Higher strength-priority was detected in PMA for imagination, implicating that motor planning may be more involved in the imagination task.