[Network-wide effects of pallidal deep brain stimulation normalised abnormal cerebellar cortical activity in the dystonic animal model.

Background: Deep brain stimulation (DBS) targeting globus pallidus internus (GPi) is a recognised therapy for drug-refractory dystonia. However, the mechanisms underlying this effect are not fully understood. This study explores how pallidal DBS alters spatiotemporal pattern formation of neuronal dynamics within the cerebellar cortex in a dystonic animal model, the dt hamster.

Data-driven and equation-free methods for neurological disorders: analysis and control of the striatum network.

The striatum as part of the basal ganglia is central to both motor, and cognitive functions. Here, we propose a large-scale biophysical network for this part of the brain, using modified Hodgkin-Huxley dynamics to model neurons, and a connectivity informed by a detailed human atlas. The model shows different spatio-temporal activity patterns corresponding to lower (presumably normal) and increased cortico-striatal activation (as found in, e.

Towards an optimised deep brain stimulation using a large-scale computational network and realistic volume conductor model.

. Constructing a theoretical framework to improve deep brain stimulation (DBS) based on the neuronal spatiotemporal patterns of the stimulation-affected areas constitutes a primary target..

Optimal vaccine roll-out strategies including social distancing for pandemics.

Non-pharmacological interventions (NPIs), principally social distancing, in combination with effective vaccines, aspire to develop a protective immunity shield against pandemics and particularly against the COVID-19 pandemic. In this study, an agent-based network model with small-world topology is employed to find optimal policies against pandemics, including social distancing and vaccination strategies. The agents' states are characterized by a variation of the SEIR model (susceptible, exposed, infected, recovered).

Deep brain stimulation for movement disorder treatment: exploring frequency-dependent efficacy in a computational network model.

A large-scale computational model of the basal ganglia network and thalamus is proposed to describe movement disorders and treatment effects of deep brain stimulation (DBS). The model of this complex network considers three areas of the basal ganglia region: the subthalamic nucleus (STN) as target area of DBS, the globus pallidus, both pars externa and pars interna (GPe-GPi), and the thalamus. Parkinsonian conditions are simulated by assuming reduced dopaminergic input and corresponding pronounced inhibitory or disinhibited projections to GPe and GPi.

Multiscale modeling of brain dynamics: from single neurons and networks to mathematical tools.

The extreme complexity of the brain naturally requires mathematical modeling approaches on a large variety of scales; the spectrum ranges from single neuron dynamics over the behavior of groups of neurons to neuronal network activity. Thus, the connection between the microscopic scale (single neuron activity) to macroscopic behavior (emergent behavior of the collective dynamics) and vice versa is a key to understand the brain in its complexity. In this work, we attempt a review of a wide range of approaches, ranging from the modeling of single neuron dynamics to machine learning.

Coarse-grained particle model for pedestrian flow using diffusion maps.

Interacting particle systems constitute the dynamic model of choice in a variety of application areas. A prominent example is pedestrian dynamics, where good design of escape routes for large buildings and public areas can improve evacuation in emergency situations, avoiding exit blocking and the ensuing panic. Here we employ diffusion maps to study the coarse-grained dynamics of two pedestrian crowds trying to pass through a door from opposite sides.

Independent component analysis of high-resolution imaging data identifies distinct functional domains.

In the vertebrate brain external stimuli are often represented in distinct functional domains distributed across the cortical surface. Fast imaging techniques used to measure patterns of population activity record movies with many pixels and many frames, i.e.

Visualization of individual growth-related craniofacial changes based on cephalometric landmark data: a pilot study.

Objective: An approach based on Euclidean distances between cephalometric landmarks is presented (1) to visualize and localize the individual shape changes of the complex craniofacial skeleton during growth and (2) to depict the individual dynamic behavior of developmental size and shape changes.

Patients And Method: Growth-related craniofacial changes were investigated exemplarily for two male orthodontically untreated subjects from the Belfast Growth Study on the basis of lateral cephalograms at 7, 9, 11, 13, and 15 years. The interlandmark distances among seven skeletal cephalometric landmarks served as a database for the study.