fMRI study of mesial temporal lobe epilepsy using amplitude of low‐frequency fluctuation analysis

Abstract

Various functional imaging tools have been used to detect epileptic activity in the neural network underlying mesial temporal lobe epilepsy (mTLE). In the present fMRI study, a data-driven approach was employed to map interictal epileptic activity in mTLE patients by measuring the amplitude of low-frequency fluctuation (ALFF) of the blood oxygen level-dependent (BOLD) signal. Twenty-four left mTLE patients and 26 right mTLE patients were investigated by comparing with 25 healthy subjects. In the patients, the regions showing increased ALFF were consistently distributed in the mesial temporal lobe, thalamus, and a few of other cortical and subcortical structures composing a mesial temporal epilepsy network proposed previously, while the regions showing decreased ALFF were mostly located in the areas of so-called default-mode network. Data of simultaneous EEG-fMRI from a portion of the patients suggested that the increases in ALFF might be associated with the interictal epileptic activity. Individual analyses based on statistic parametric mapping revealed a moderate sensitivity and a fairly high specificity for the lateralization of unilateral mTLE. We conclude that the ALFF analysis may provide a useful tool in fMRI study of epilepsy.

Altered physiological brain variation in drug‐resistant epilepsy

“…Both mesial temporal lobe and idiopathic generalized epilepsy have shown increased amplitude of low‐frequency BOLD signal fluctuations in thalami, temporal cortices, and default mode network (DMN) (Wang et al., 2014; Zhang et al., 2010). It is also shown that there might be relation between VLF differences on white matter and BOLD signal detection (Gawryluk, Mazerolle, & D'Arcy, 2014).…”

Local synchronization and amplitude of the fluctuation of spontaneous brain activity in attention-deficit/hyperactivity disorder: a resting-state fMRI study

“…ALFF measures the amplitude of fl uctuation of individual voxels [6] . It has been used to differentiate two resting conditions [7] and differentiate patients with epilepsy from normal controls [8] . During the resting state, regions exhibiting higher ReHo [3] and ALFF [6,7] than other regions are in line with the location of the default mode network and have the highest metabolic rate as measured by positron emission tomography.…”

Seizure Frequency Can Alter Brain Connectivity: Evidence from Resting-State fMRI

“…[1][2][3][4]6 Graph-theory analysis of resting-state fMRI data from patients with epilepsy also revealed decreased functional nodal topologic properties of the DMN that were positively correlated with disease duration. 8,[11][12][13][14] Regional homogeneity analysis of resting-state fMRI data was even used as a presurgical tool for seizure identification in patients with MR-negative focal epilepsy. 15 Thus, various models of data analysis have helped in understanding epilepsy further, and now there is increasing interest in using these models to reclassify epilepsy as a focal epileptogenic area 10,15 or as a network of seizure-generating areas.…”