In a modeling study we show that desynchronization stimulation may have powerful anti-kindling effects. For this, we incorporate spike-timing-dependent plasticity into a generic network of coupled phase oscillators, which serves as a model network of synaptically interacting neurons. Two states may coexist under spontaneous conditions: a state of uncorrelated firing and a state of pathological synchrony. Appropriate stimulation protocols make the network learn or unlearn the pathological synaptic interactions, respectively. Low-frequency periodic pulse train stimulation causes a kindling. Permanent high-frequency stimulation, used as golden standard for deep brain stimulation in medically refractory movement disorders, basically freezes the synaptic weights. In contrast, desynchronization stimulation, e.g., by means of a multi-site coordinated reset, has powerful long-term anti-kindling effects and enables the network to unlearn pathologically strong synaptic interactions. We propose desynchronization stimulation for the therapy of movement disorders and epilepsies.
The wealth of competing parcellations with limited cross-correspondence between atlases of the human thalamus raises problems in a time when the usefulness of neuroanatomical methods is increasingly appreciated for modern computational analyses of the brain. An unequivocal nomenclature is, however, compulsory for the understanding of the organization of the thalamus. This situation cannot be improved by renewed discussion but with implementation of neuroinformatics tools. We adopted a new volumetric approach to characterize the significant subdivisions and determined the relationships between the parcellation schemes of nine most influential atlases of the human thalamus. The volumes of each atlas were 3d-reconstructed and spatially registered to the standard MNI/ICBM2009b reference volume of the Human Brain Atlas in the MNI (Montreal Neurological Institute) space (Mai and Majtanik, 2017). This normalization of the individual thalamus shapes allowed for the comparison of the nuclear regions delineated by the different authors. Quantitative cross-comparisons revealed the extent of predictability of territorial borders for 11 area clusters. In case of discordant parcellations we re-analyzed the underlying histological features and the original descriptions. The final scheme of the spatial organization provided the frame for the selected terms for the subdivisions of the human thalamus using on the (modified) terminology of the Federative International Programme for Anatomical Terminology (FIPAT). Waiving of exact individual definition of regional boundaries in favor of the statistical representation within the open MNI platform provides the common and objective (standardized) ground to achieve concordance between results from different sources (microscopy, imaging etc.).
We present a noninvasive technique which allows the anatomical localization of phase synchronized neuronal populations in the human brain with magnetoencephalography. We study phase synchronization between the reconstructed current source density (CSD) of different brain areas as well as between the CSD and muscular activity. We asked four subjects to tap their fingers in synchrony with a rhythmic tone, and to continue tapping at the same rate after the tone was switched off. The phase synchronization behavior of brain areas relevant for movement coordination, inner voice, and time estimation changes drastically when the transition to internal pacing occurs, while their averaged amplitudes remain unchanged. Information of this kind cannot be derived with standard neuroimaging techniques like functional magnetic resonance imaging or positron emission tomography. [5,6] systems. In animals, phase synchronization has been demonstrated to be a fundamental mechanism for motor control [7]. Active neuronal populations in the brain generate currents which, in turn, produce a magnetic field that can noninvasively be measured by means of magnetoencephalography (MEG) with a time resolution in the millisecond range. Phase synchronization can be detected in noisy, nonstationary MEG signals [5]. However, the spatial resolution of this approach has so far been severely limited, since MEG sensors measure the magnetic field which may originate from different brain areas. To study normal brain function as well as pathological synchronization (e.g., in Parkinson's disease and epilepsy) a correct anatomical localization of synchronization processes is crucial. We here present a novel method which allows a reliable 3D localization of phase synchronization in the human brain with MEG.We first reconstructed the cerebral current source density jx; t, which generates the measured magnetic field, in each volume element (voxel) for all times t with magnetic field tomography [8]. x denotes the spatial coordinates representing the center of a voxel. We then analyzed phase synchronization voxel by voxel: To detect cerebro-muscular synchronization (CMS) we determined phase synchronization between the muscular activity recorded with electromyography (EMG) and jx; t in each of the voxels representing the brain. To detect cerebrocerebral synchronization (CCS) we determined phase synchronization of jx; t in all pairs of voxels.We applied our approach to study internal rhythm generation in humans. The latter is essential for performing rhythmic movements without external stimulus, e.g., during locomotion or skilled actions like playing muscial instruments. We performed a paced finger tapping (PFT) experiment [9], where subjects are first asked to tap with their index finger in synchrony with a periodic train of tones (external pacing). After discontinuing the tones, the subjects then have to continue the tapping at the same pace (internal pacing), by generating the rhythm alone.Behavioral studies of movement timing in PFT studies revealed an inte...
We apply a quantitative method for the identification of asymmetric relations between weakly interacting self-sustained oscillators to the study of rhythmic neural electrical activity. We begin by testing the method on biophysically motivated neural oscillator models considering first two diffusively coupled Hindmarsh-Rose oscillators, and then two ensembles of globally coupled neurons interacting through their mean fields. Next, we consider the more complex case of interactions among several oscillatory units. The method is further applied to the analysis of the control of externally vs internally paced movements in humans. A pilot study in one healthy subject reveals that asymmetry of interactions between different brain areas may strongly change with the transition from external to internal pacing, while the degree of synchronization hardly changes. Furthermore, our preliminary results highlight the important role of the secondary auditory cortex in internal rhythm generation. at University of Washington Libraries on March 15, 2015 http://ptps.oxfordjournals.org/ Downloaded from
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