The digiti quinti sign in hemiplegic migraine: An fMRI study.

BACKGROUND AND PURPOSE: The digiti quinti sign (DQS) consists of a wider angle between the fourth and fifth fingers (ANG) indicative of subtle hemiparesis that has been found interictally in hemiplegic migraine (HM), suggesting a permanent subtle motor dysfunction. The aim of this study was to find a possible cortical origin for the DQS using blood oxygen level dependent (BOLD) functional (f) MRI. METHODS: Eight HM patients and 13 controls entered the cross-sectional study. We examined hand dominance, performed handgrip tests with dynamometry, documented the DQS graphically in two consecutive sessions, and used BOLD-fMRI during a motor task specifically designed to measure the evoked activation in the motor cortex (M1). The brain activation at the symptomatic side was compared with the contralateral hemisphere and with both correspondent hemispheres in controls. RESULTS: Subjects had a normal neurological examination, except for DQS in all HM patients. The activation amplitude (beta values) and the cluster extension (mm3 ) of the activation area in M1 was smaller at the affected side. Besides, the cluster extension correlated negatively with the disease time span. The ANG was wider bilaterally in patients and the fMRI signals were reduced in the patient's group. CONCLUSION: The DQS, a relevant clinical finding in HM, indicates a disrupted cortical activation.

A group analysis using the Multiregression Dynamic Models for fMRI networked time series.

Connectivity studies of the brain are usually based on functional Magnetic Resonance Imaging (fMRI) experiments involving many subjects. These studies need to take into account not only the interaction between areas of a single brain but also the differences amongst those subjects. In this paper we develop a methodology called the group-structure (GS) approach that models possible heterogeneity between subjects and searches for distinct homogeneous sub-groups according to some measure that reflects the connectivity maps. We suggest a GS method that uses a novel distance based on a model selection measure, the Bayes factor. We then develop a new class of Multiregression Dynamic Models to estimate individual networks whilst acknowledging a GS type dependence structure across subjects. We compare the efficacy of this methodology to three other methods, virtual-typical-subject (VTS), individual-structure (IS) and common-structure (CS), used to infer a group network using both synthetic and real fMRI data. We find that the GS approach provides results that are both more consistent with the data and more flexible in their interpretative power than its competitors. In addition, we present two methods, the Individual Estimation of Multiple Networks (IEMN) and the Marginal Estimation of Multiple Networks (MEMN), generated from the GS approach and used to estimate all types of networks informed by an experiment -individual, homogeneous subgroups and group networks. These methods are then compared both from a theoretical perspective and in practice using real fMRI data.

The effects of antiepileptic drugs on cognitive functional magnetic resonance imaging.

The cognitive dysfunction caused by antiepileptic drugs (AEDs) has been extensively described, although the mechanisms underlying such collateral effects are still poorly understood. The combination of functional magnetic resonance imaging (fMRI) studies with pharmacological intervention (pharmaco-MRI or ph-MRI) offers the opportunity to investigate the effect of drugs such as AEDs on brain activity, including cognitive tasks. Here we review the studies that investigated the effects of AEDs [topiramate (TPM), lamotrigine (LMT), carbamazepine (CBZ), pregabalin (PGB), valproate (VPA) and levetiracetam (LEV)] on cognitive fMRI tasks. Despite the scarcity of fMRI studies focusing on the impact of AEDs on cognitive task, the results of recent work have provided important information about specific drug-related changes of brain function.