Interoperable atlases of the human brain.

The last two decades have seen an unprecedented development of human brain mapping approaches at various spatial and temporal scales. Together, these have provided a large fundus of information on many different aspects of the human brain including micro- and macrostructural segregation, regional specialization of function, connectivity, and temporal dynamics. Atlases are central in order to integrate such diverse information in a topographically meaningful way. It is noteworthy, that the brain mapping field has been developed along several major lines such as structure vs. function, postmortem vs. in vivo, individual features of the brain vs. population-based aspects, or slow vs. fast dynamics. In order to understand human brain organization, however, it seems inevitable that these different lines are integrated and combined into a multimodal human brain model. To this aim, we held a workshop to determine the constraints of a multi-modal human brain model that are needed to enable (i) an integration of different spatial and temporal scales and data modalities into a common reference system, and (ii) efficient data exchange and analysis. As detailed in this report, to arrive at fully interoperable atlases of the human brain will still require much work at the frontiers of data acquisition, analysis, and representation. Among them, the latter may provide the most challenging task, in particular when it comes to representing features of vastly different scales of space, time and abstraction. The potential benefits of such endeavor, however, clearly outweigh the problems, as only such kind of multi-modal human brain atlas may provide a starting point from which the complex relationships between structure, function, and connectivity may be explored.

Modeling of a segmented electrode for desynchronizing deep brain stimulation.

Deep brain stimulation (DBS) is an effective therapy for medically refractory movement disorders like Parkinson's disease. The electrodes, implanted in the target area within the human brain, generate an electric field which activates nerve fibers and cell bodies in the vicinity. Even though the different target nuclei display considerable differences in their anatomical structure, only few types of electrodes are currently commercially available. It is desirable to adjust the electric field and in particular the volume of tissue activated around the electrode with respect to the corresponding target nucleus in a such way that side effects can be reduced. Furthermore, a more selective and partial activation of the target structure is desirable for an optimal application of novel stimulation strategies, e.g., coordinated reset neuromodulation. Hence we designed a DBS electrode with a segmented design allowing a more selective activation of the target structure. We created a finite element model (FEM) of the electrode and analyzed the volume of tissue activated for this electrode design. The segmented electrode activated an area in a targeted manner, of which the dimension and position relative to the electrode could be controlled by adjusting the stimulation parameters for each electrode contact. According to our computational analysis, this directed stimulation might be superior with respect to the occurrence of side effects and it enables the application of coordinated reset neuromodulation under optimal conditions.

Periodic patterns in a ring of delay-coupled oscillators.

We describe the appearance and stability of spatiotemporal periodic patterns (rotating waves) in unidirectional rings of coupled oscillators with delayed couplings. We show how delays in the coupling lead to the splitting of each rotating wave into several new ones. The appearance of rotating waves is mediated by the Hopf bifurcations of the symmetric equilibrium. We also conclude that the coupling delays can be effectively replaced by increasing the number of oscillators in the chain. The phenomena are shown for the Stuart-Landau oscillators as well as for the coupled FitzHugh-Nagumo systems modeling an ensemble of spiking neurons interacting via excitatory chemical synapses.

External trial deep brain stimulation device for the application of desynchronizing stimulation techniques.

In the past decade deep brain stimulation (DBS)-the application of electrical stimulation to specific target structures via implanted depth electrodes-has become the standard treatment for medically refractory Parkinson's disease and essential tremor. These diseases are characterized by pathological synchronized neuronal activity in particular brain areas. We present an external trial DBS device capable of administering effectively desynchronizing stimulation techniques developed with methods from nonlinear dynamics and statistical physics according to a model-based approach. These techniques exploit either stochastic phase resetting principles or complex delayed-feedback mechanisms. We explain how these methods are implemented into a safe and user-friendly device.

Long-lasting desynchronization in rat hippocampal slice induced by coordinated reset stimulation.

In computational models it has been shown that appropriate stimulation protocols may reshape the connectivity pattern of neural or oscillator networks with synaptic plasticity in a way that the network learns or unlearns strong synchronization. The underlying mechanism is that a network is shifted from one attractor to another, so that long-lasting stimulation effects are caused which persist after the cessation of stimulation. Here we study long-lasting effects of multisite electrical stimulation in a rat hippocampal slice rendered epileptic by magnesium withdrawal. We show that desynchronizing coordinated reset stimulation causes a long-lasting desynchronization between hippocampal neuronal populations together with a widespread decrease in the amplitude of the epileptiform activity. In contrast, periodic stimulation induces a long-lasting increase in both synchronization and amplitude.

Cumulative and after-effects of short and weak coordinated reset stimulation: a modeling study.

We show that the dynamical multistability of a network of bursting subthalamic neurons, caused by synaptic plasticity has a strong impact on the stimulus-response properties when exposed to weak and short desynchronizing stimuli. Intriguingly, such stimuli can reliably shift the network from a stable state with pathological synchrony and connectivity to a stable desynchronized state with down-regulated connectivity. However, unlike in the case of stronger coordinated reset stimulation, after termination of weaker stimulation the network may undergo a transient rebound of synchrony. When the coordinated reset stimulation is even weaker and/or shorter, so that a single stimulation epoch is not effective, the network dynamics and connectivity can still be reshaped in a cumulative manner by repetitive stimulation delivery.

Anti-kindling achieved by stimulation targeting slow synaptic dynamics.

PURPOSE: Different stimulation techniques are introduced which specifically modulate the slow synaptic dynamics in a neuronal network model of the subthalamic nucleus with activity dependent synaptic plasticity. METHODS: A modeling approach is utilized to investigate the effects of the different stimulation techniques. In particular, the short-term and long-term outcome is studied in a mathematical model for a population of bursting STN neurons subject to synaptic plasticity with symmetric spike timing characteristics. In our mathematical model in the absence of stimulation synchronized network states with strong connectivity (modeling disease states) as well as desynchronized states with weak connectivity (modeling healthy states) are stable. RESULTS: We demonstrate that different stimulation techniques induce an anti-kindling by shifting the target population to a weakly connected, desynchronized state. Intriguingly, long-term anti-kindling can even be achieved although during stimulus delivery the neuronal synchrony hardly decreases or even slightly increases. The therapeutic index and the impact of inhibition, calculated to compare the different stimulation techniques, indicate that coordinated rest stimulation might be particularly robust and reliable. CONCLUSIONS: The presented stimulation strategies and the results of our modeling study might have strong implications in the context of deep brain stimulation.

Control of spatially patterned synchrony with multisite delayed feedback.

We present an analytical study describing a method for the control of spatiotemporal patterns of synchrony in networks of coupled oscillators. Delayed feedback applied through a small number of electrodes effectively induces spatiotemporal dynamics at minimal stimulation intensities. Different arrangements of the delays cause different spatial patterns of synchrony, comparable to central pattern generators (CPGs), i.e., interacting clusters of oscillatory neurons producing patterned output, e.g., for motor control. Multisite delayed feedback stimulation might be used to restore CPG activity in patients with incomplete spinal cord injury or gait ignition disorders.

Effectively desynchronizing deep brain stimulation based on a coordinated delayed feedback stimulation via several sites: a computational study.

In detailed simulations we present a coordinated delayed feedback stimulation as a particularly robust and mild technique for desynchronization. We feed back the measured and band-pass filtered local filed potential via several or multiple sites with different delays, respectively. This yields a resounding desynchronization in a naturally demand-controlled way. Our novel approach is superior to previously developed techniques: It is robust against variations of system parameters, e.g., the mean firing rate. It does not require time-consuming calibration. It also prevents intermittent resynchronization typically caused by all methods employing repetitive administration of shocks. We suggest our novel technique to be used for deep brain stimulation in patients suffering from neurological diseases with pathological synchronization, such as Parkinsonian tremor, essential tremor or epilepsy.

Mechanism of desynchronization in the finite-dimensional Kuramoto model.

We study how a decrease of the coupling strength causes a desynchronization in the Kuramoto model of N globally coupled phase oscillators. We show that, if the natural frequencies are distributed uniformly or close to that, the synchronized state can robustly split into any number of phase clusters with different average frequencies, even culminating in complete desynchronization. In the simplest case of N=3 phase oscillators, the course of the splitting is controlled by a Cherry flow. The general N-dimensional desynchronization mechanism is numerically illustrated for N=5.

Synchronization tomography: a method for three-dimensional localization of phase synchronized neuronal populations in the human brain using magnetoencephalography.

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.

Desynchronizing double-pulse phase resetting and application to deep brain stimulation.

Based on a stochastic phase-resetting approach, three different double-pulse stimulation techniques are presented here which make it possible to effectively desynchronize a population of phase oscillators in the presence of noise. In the three sorts of double pulses the first, stronger pulse restarts the cluster independent of its initial dynamic state. The three methods differ with respect to the mechanism through which the second, weaker pulse desynchronizes the cluster. Both first and second pulses are delivered to the same site. Because of the oscillators' global couplings in the model under consideration, the incoherent state is unstable, so that after the desynchronization the cluster tends to resynchronize. However, resynchronization is effectively blocked by repeated administration of a double pulse. The experimental application of double-pulse stimulation is explained in detail. In particular, demand-controlled deep brain double-pulse stimulation is suggested for the therapy of patients suffering from Parkinson's disease or essential tremor.

Cortico-muscular synchronization during isometric muscle contraction in humans as revealed by magnetoencephalography.

Magnetoencephalographic (MEG) and electromyographic (EMG) signals were recorded from six subjects during isometric contraction of four different muscles. Cortical sources were located from the MEG signal which was averaged time-locked to the onset of motor unit potentials. A spatial filtering algorithm was used to estimate the source activity. Sources were found in the primary motor cortex (M1) contralateral to the contracted muscle. Significant coherence between rectified EMG and M1 activity was seen in the 20 Hz frequency range in all subjects. Interactions between the motor cortex and spinal motoneuron pool were investigated by separately studying the non-stationary phase and amplitude dynamics of M1 and EMG signals. Delays between M1 and EMG signals, computed from their phase difference, were found to be in agreement with conduction times from the primary motor cortex to the respective muscle. The time-dependent cortico-muscular phase synchronization was found to be correlated with the time course of both M1 and EMG signals. The findings demonstrate that the coupling between the primary motor cortex and motoneuron pool is at least partly due to phase synchronization of 20 Hz oscillations which varies over time. Furthermore, the consistent phase lag between M1 and EMG signals, compatible with conduction time between M1 and the respective muscle with the M1 activity preceding EMG activity, supports the conjecture that the motor cortex drives the motoneuron pool.