Multistability in the Kuramoto model with synaptic plasticity

We present a simplified phase model for neuronal dynamics with spike timing-dependent plasticity (STDP). For asymmetric, experimentally observed STDP we find multistability: a coexistence of a fully synchronized, a fully desynchronized, and a variety of cluster states in a wide enough range of the parameter space. We show that multistability can occur only for asymmetric STDP, and we study how the coexistence of synchronization and desynchronization and clustering depends on the distribution of the eigenfrequencies. We test the efficacy of the proposed method on the Kuramoto model which is, de facto, one of the sample models for a description of the phase dynamics in neuronal ensembles

Multistability in the Kuramoto model with synaptic plasticity

We present a simplified phase model for neuronal dynamics with spike timing-dependent plasticity (STDP). For asymmetric, experimentally observed STDP we find multistability: a coexistence of a fully synchronized, a fully desynchronized, and a variety of cluster states in a wide enough range of the parameter space. We show that multistability can occur only for asymmetric STDP, and we study how the coexistence of synchronization and desynchronization and clustering depends on the distribution of the eigenfrequencies. We test the efficacy of the proposed method on the Kuramoto model which is, de facto, one of the sample models for a description of the phase dynamics in neuronal ensembles

Co existence of numerous synchronized and desynchronized states in a model of two phase oscillators coupled with delay

When two phase oscillators interact with a time-delay, new synchronized and desynchronized regimes appear, in this way giving rise to the phenomenon of multistability. The number of coexisting stable states grows with an increase of the delay, and their frequencies quantize. We show that, while the number of synchronized solutions grows linearly with the delay and/or coupling, the set of the desynchronized solutions, i.e. those with different average frequencies of the individual oscillators, raises quadratically with increasing delay. For the synchronized states, we analyze the mutual arrangement of the basins of attraction, and conclude that the structure and size of the basins are apparently the same for each state. We discuss possible implications for desynchronizing brain stimulation techniques

Computational Model-Based Development of Novel Stimulation Algorithms

In the context of this entry, the model-based development of stimulation algorithms designatesa process of creation and computational testing of new techniques for control and modulation ofundesirable (pathological) neuronal dynamics. Abnormal brain activity has been observed in severalneurological disorders including Parkinson’s disease, essential tremor, epilepsy, tinnitus, and others.Brain stimulation is used for the therapy of patients suffering, for example, from Parkinson’s disease,epilepsy, or mental disorders. Brain stimulation is called deep brain stimulation (DBS) if structuresdeeply inside the brain are targeted, cortical stimulation (intracortical or epicortical) if the electricalcontacts of the stimulator are positioned within the cortex or on its surface, or noninvasivetranscranial stimulation if the neurons are stimulated by electrical currents induced across scalp byeither external magnetic field (transcranial magnetic stimulation, TMS) or electrical current admin-istered via scalp electrodes (transcranial direct-current stimulation, tDCS). Apart from direct brainstimulation, other stimulation forms and targets may also be used, such as spinal cord stimulation(e.g., for the treatment of pain), vagus nerve stimulation (for the treatment of epilepsy), or acousticstimulation (for the treatment of tinnitus). Novel, model-based approaches, which use methods fromsynergetics, nonlinear dynamics, and statistical physics to specifically restore brain function andconnectivity, demonstrate how insights into the dynamics of complex systems contribute to thedevelopment of novel therapies

Impact of apical foreshortening on deformation measurements: A report from the EACVI-ASE Strain Standardization Task Force

Aims Foreshortening of apical views is a common problem in echocardiography. It results in an abnormally thick false apex and a shortened left ventricular (LV) long axis. We sought to evaluate the impact of foreshortened (FS) on LV ejection fraction (LVEF) and layer-specific 2D speckle tracking based segmental (S) and global (G) longitudinal strain (LS) measurements. Methods and results We examined 72 participants using a GE Vivid E9 system. FS apical views were collected from an imaging window one rib-space higher than the optimal images. Ejection fraction as well as layer-specific GLS and SLS measurements were analysed by GE EchoPAC v201 and TomTec Image Arena 4.6 and compared between optimal and FS images. On average, LV long axis was 10\% shorter in FS images than in optimal images. FS induced a relative change in LVEF of 3.3\% and 6.9\% for GE and TomTec, respectively (both, P < 0.001). Endocardial GLS was 9.0\% higher with GE and 23.2\% with TomTec (P < 0.001). Midwall GLS measurements were less affected (7.8\% for GE and 14.1\% for TomTec, respectively, both P< 0.001). Segmental strain analysis revealed that the mid-ventricular and apical segments were more affected by foreshortening, and endocardial measurements were more affected than midwall. Conclusion Optimal image geometry is crucial for accurate LV function assessment. Foreshorhening of apical views has a substantial impact on longitudinal strain measurements, predominantly in the apex and in the endocardial layer. Our data suggest that measuring midwall strain might therefore be the more robust approach for clinical routine use