Tonic neuronal activation during simple and complex finger movements analyzed by DC-magnetoencephalography.

Functional neuroimaging techniques map neuronal activation indirectly via local concomitant cortical vascular/metabolic changes. In a complementary approach, DC-magnetoencephalography measures neuronal activation dynamics directly, notably in a time range of the slow vascular/metabolic response. Here, using this technique neuronal activation dynamics and patterns for simple and complex finger movements are characterized intraindividually: in 6/6 right-handed subjects contralateral prolonged (30 s each) complex self-paced sequential finger movements revealed stronger field amplitudes over the pericentral sensorimotor cortex than simple movements. A consistent lateralization for contralateral versus ipsilateral finger movements was not found (4/6). A subsequent sensory paradigm focused on somatosensory afferences during the motor tasks and the reliability of the measuring technique. In all six subjects stable sustained neuronal activation during electrical median nerve stimulation was recorded. These neuronal quasi-tonic activation characteristics provide a new non-invasive neurophysiological measure to interpret signals mapped by functional neuroimaging techniques.

Magnetoencephalography discriminates modality-specific infraslow signals less than 0.1 Hz.

DC-magnetoencephalography (DC-MEG) technique has been refined and allows to record cortical activity in the infraslow frequency range less than 0.1 Hz noninvasively. Important questions however, remained, especially, how specific these infraslow activations can be recorded and whether different activations, for example, motor versus acoustic, can be separated. To clarify these questions, in the present DC-MEG study, cortical infraslow activity was investigated intraindividually in response to different activation modalities, that is, motor versus acoustic: in 13 individuals, 30-s periods of finger movement or listening to concert music, were interleaved for 60 min. DC-MEG was capable to resolve intermodal differences concerning the relative amplitudes, field patterns, and source localizations. These results clarify that DC-MEG allows to identify and to discriminate modality-specific infraslow cortical neuronal signals.