Task-Modulated Corticocortical Synchrony in the Cognitive-Motor Network Supporting Handwriting.

Both motor and cognitive aspects of behavior depend on dynamic, accurately timed neural processes in large-scale brain networks. Here, we studied synchronous interplay between cortical regions during production of cognitive-motor sequences in humans. Specifically, variants of handwriting that differed in motor variability, linguistic content, and memorization of movement cues were contrasted to unveil functional sensitivity of corticocortical connections.

Louse-borne relapsing fever in Finland in two asylum seekers from Somalia.

We report two cases of louse-borne relapsing fever (LBRF) in young Somali asylum seekers having recently arrived to Finland. They had sought medical attention for a febrile illness. Blood smears were examined for suspected malaria, but instead, spirochete shaped bacteria were observed.

Relapsing fever.

Relapsing fewer is an infection to be considered in the differential diagnosis of an immigrant´s febrile illness. It is a severe, tick-borne or body louse-borne infection caused by the relapsing fever associated borrelia species. The body louse-borne infection is in particular encountered in the Horn of Africa region due to poor hygiene, and has during the past year been described in several European countries as imported by refugees coming from this region.

Task-sensitive reconfiguration of corticocortical 6-20 Hz oscillatory coherence in naturalistic human performance.

Electrophysiological oscillatory coherence between brain regions has been proposed to facilitate functional long-range connectivity within neurocognitive networks. This notion is supported by intracortical recordings of coherence in singled-out corticocortical connections in the primate cortex. However, the manner in which this operational principle manifests in the task-sensitive connectivity that supports human naturalistic performance remains undercharacterized.

Optimal spatial filtering for brain oscillatory activity using the Relevance Vector Machine.

Over the past decade, various techniques have been proposed for localization of cerebral sources of oscillatory activity on the basis of magnetoencephalography (MEG) or electroencephalography recordings. Beamformers in the frequency domain, in particular, have proved useful in this endeavor. However, the localization accuracy and efficacy of such spatial filters can be markedly limited by bias from correlation between cerebral sources and short duration of source activity, both essential issues in the localization of brain data.