Neuroimaging increasingly exploits machine learning techniques in an attempt to achieve
clinically relevant single-subject predictions. An alternative to machine learning, which tries …

The exponential rise in the number of functional brain connectivity studies, particularly those
examining intrinsic functional connectivity (iFC) at rest, and the promises of this work for …

Abstract Dynamic Causal Modelling (DCM) is the predominant method for inferring effective
connectivity from neuroimaging data. In the 15 years since its introduction, the neural …

This chapter focuses on the imaging (or distributed) method for implementing EEG/MEG
source reconstruction in SPM. This approach results in a spatial projection of sensor data …

Depleted of dopamine, the dynamics of the parkinsonian brain impact on both 'action'and
'resting'motor behaviour. Deep brain stimulation has become an established means of …

Conceptual knowledge is central to cognition. Previous neuroimaging research indicates
that conceptual processing involves both modality-specific perceptual-motor areas and …

Initially regarded as 'noise', spontaneous (intrinsic) activity accounts for a large portion of the
brain's metabolic cost. Moreover, it is now widely known that infra-slow (less than 0.1 Hz) …

Objective To identify brain regions underlying interictal generalized paroxysmal fast activity
(GPFA), and their causal interactions, in children and adults with Lennox-Gastaut syndrome …

In this study, we examined regions in the left and right hemisphere language network that
were altered in terms of the underlying neural activation and effective connectivity …

In the past two decades, functional Magnetic Resonance Imaging (fMRI) has been used to
relate neuronal network activity to cognitive processing and behavior. Recently this …