Structural and resting state functional connectivity of the subthalamic nucleus: identification of motor STN parts and the hyperdirect pathway

Deep brain stimulation (DBS) for Parkinson's disease often alleviates the motor symptoms, but causes cognitive and emotional side effects in a substantial number of cases. Identification of the motor part of the subthalamic nucleus (STN) as part of the presurgical workup could minimize these adverse effects. In this study, we assessed the STN's connectivity to motor, associative, and limbic brain areas, based on structural and functional connectivity analysis of volunteer data. For the structural connectivity, we used streamline counts derived from HARDI fiber tracking. The resulting tracks supported the existence of the so-called "hyperdirect" pathway in humans. Furthermore, we determined the connectivity of each STN voxel with the motor cortical areas. Functional connectivity was calculated based on functional MRI, as the correlation of the signal within a given brain voxel with the signal in the STN. Also, the signal per STN voxel was explained in terms of the correlation with motor or limbic brain seed ROI areas. Both right and left STN ROIs appeared to be structurally and functionally connected to brain areas that are part of the motor, associative, and limbic circuit. Furthermore, this study enabled us to assess the level of segregation of the STN motor part, which is relevant for the planning of STN DBS procedures.

Alterations of white matter connectivity in first episode schizophrenia

Cerebral disconnectivity due to white matter alterations in patients with chronic schizophrenia assessed by diffusion tensor imaging has been reported previously. The aim of this preliminary study is to investigate whether cerebral disconnectivity can be detected as early as the first episode of schizophrenia. Intervoxel coherence values were compared by voxel-based t test in 12 patients with first episode schizophrenia and 12 age- and gender-matched control groups. We detected 14 circumscribed significant clusters (P < 0.02), 3 of them with higher, and 11 of them with lower IC values for patients with schizophrenia than for healthy control groups. We interpret these white matter alterations in different regions to be disconnected fiber tracts already present early in schizophrenic disease progression.

Cerebral connectivity and psychotic personality traits : A diffusion tensor imaging study

This study aims to investigate the relationship between regional connectivity in the brain white matter and the presence of psychotic personality traits, in healthy subjects with psychotic traits. Thirteen healthy controls were administered the MMPI-2, to assess psychotic traits and, according to MMPI results, a dichotomization into a group of "high-psychotic" and "low-psychotic" was performed. Diffusion tensor imaging (DTI) was used as a non-invasive measure, in order to obtain information about the fractional anisotropy (FA), an intravoxel index of local connectivity and, by means of a voxelwise approach, the between-group differences of the FA values were calculated. The "high-psychotic" group showed higher FA in the left arcuate fasciculus. Subjects with low scores for psychotic traits had significantly higher FA in the corpus callosum, right arcuate fasciculus, and fronto-parietal fibers. In line with previous brain imaging studies of schizophrenia spectrum disorders, our results suggest that psychotic personality traits are related to altered connectivity and brain asymmetry.

Brain connectivity at different time-scales measured with EEG

We present an overview of different methods for decomposing a multichannel spontaneous electroencephalogram (EEG) into sets of temporal patterns and topographic distributions. All of the methods presented here consider the scalp electric field as the basic analysis entity in space. In time, the resolution of the methods is between milliseconds (time-domain analysis), subseconds (time- and frequency-domain analysis) and seconds (frequency-domain analysis). For any of these methods, we show that large parts of the data can be explained by a small number of topographic distributions. Physically, this implies that the brain regions that generated one of those topographies must have been active with a common phase. If several brain regions are producing EEG signals at the same time and frequency, they have a strong tendency to do this in a synchronized mode. This view is illustrated by several examples (including combined EEG and functional magnetic resonance imaging (fMRI)) and a selective review of the literature. The findings are discussed in terms of short-lasting binding between different brain regions through synchronized oscillations, which could constitute a mechanism to form transient, functional neurocognitive networks.

Hippocampal functional connectivity reflects verbal episodic memory network integrity

Using functional magnetic resonance imaging during a verbal memory task, we investigated correlations of signal fluctuations within the hippocampus and ipsilateral frontal as well as temporal areas in temporal lobe epilepsy patients. Declarative memory abilities were additionally examined before and after temporal lobe epilepsy surgery. A significant difference exists in functional connectivity between patients whose mnemonic functions deteriorated and those who remained stable or improved. Univariate analyses showed significantly higher preoperative coupling between the hippocampus and Brodmann area 22 for the group that decreased in verbal learning. We suggest greater coupling to reflect higher functional network integrity. Postoperatively reduced learning ability in patients with higher preoperative coupling underlines the importance of hippocampal interaction with cortical areas for successful memory formation.