Elvis Silva

Neuropsychiatric symptoms in Alzheimer's disease are related to functional connectivity alterations in the salience network

Neuropsychiatric syndromes are highly prevalent in Alzheimers disease (AD), but their neurobiology is not completely understood. New methods in functional magnetic resonance imaging, such as intrinsic functional connectivity or “resting‐state” analysis, may help to clarify this issue. Using such approaches, alterations in the default‐mode and salience networks (SNs) have been described in Alzheimers, although their relationship with specific symptoms remains unclear. We therefore carried out resting‐state functional connectivity analysis with 20 patients with mild to moderate AD, and correlated their scores on neuropsychiatric inventory syndromes (apathy, hyperactivity, affective syndrome, and psychosis) with maps of connectivity in the default mode network and SN. In addition, we compared network connectivity in these patients with that in 17 healthy elderly control subjects. All analyses were controlled for gray matter density and other potential confounds. Alzheimers patients showed increased functional connectivity within the SN compared with controls (right anterior cingulate cortex and left medial frontal gyrus), along with reduced functional connectivity in the default‐mode network (bilateral precuneus). A correlation between increased connectivity in anterior cingulate cortex and right insula areas of the SN and hyperactivity syndrome (agitation, irritability, aberrant motor behavior, euphoria, and disinhibition) was found. These findings demonstrate an association between specific network changes in AD and particular neuropsychiatric symptom types. This underlines the potential clinical significance of resting state alterations in future diagnosis and therapy. Hum Brain Mapp 35:1237–1246, 2014.

Music versus motor imagery for BCI systems a study using fMRI and EEG: Preliminary results

The development of brain-computer interfaces (BCIs) for disabled patients is currently a growing field of research. Most BCI systems are based on electroencephalography (EEG) signals, and within this group, systems using motor imagery (MI) are amongst the most flexible. However, for stroke patients, the motor areas of the brain are not always available for use in these types of devices. The aim of this work was to evaluate a set of imagery-based cognitive tasks (right-hand MI versus music imagery, with rest or “blank” periods in between), using functional Magnetic Resonance Imaging (fMRI) and EEG. Eleven healthy subjects (control group) and four stroke patients were evaluated with fMRI, and nine of the healthy subjects also underwent an EEG test. The fMRI results for the control group showed specific and statistically differentiable activation patterns for motor versus music imagery (t-test, p <; 0.001). For stroke patients the fMRI results showed a very large variability, with no common activation pattern for either of the imagery tasks. Corroborating this fact, EEG results concerning feature selection for minimizing the classification error (using the Davies-Bouldin index) have also found no common activation pattern, although a well-defined set of meaningful electrodes and frequencies was found for some subjects. In terms of classification performance using EEG data, this work has detected a group of subjects with classifier rate of success up to 60%, which is promising in view of the cognitive complexity of the adopted tasks.

Emotional Face Perception in Healthy Subjects and Parkinson’s Disease: An Effective Connectivity Study

We investigated the neural connectivity induced by face presentation with different emotional valences in Parkinson’s disease (PD) patients and a control group of healthy, drug-free volunteers, using event-related fMRI in a parametric design. The focus of this work was applying Dynamic Causal Modelling (DCM), an approach that allows the assessment of effective connectivity within cortical networks [1], to the study of effective connectivity between maximally activated brain regions in response to passive viewing of facial stimuli. A connectivity model was built based on the literature and in our fMRI analyses, which included the fusiform gyrus (FG), the anterior cingulate cortex (ACG), the dorsolateral prefrontal cortex (DLPFC) and the dorso-medial pre-frontal cortex (DMPFC) areas. The results showed differences in connectivity between the PD group and the control group. We found that the intrinsic connectivities among DLPFC/DMPFC and FG, DLPFC/DMPFC and ACG, were higher in PD patients than in healthy subjects, while the effective connectivity among FG and ACG was lower in PD patients.