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Deep brain stimulation in Parkinson’s disease, modelling chromatin dynamics, ant obstacle courses


Check out our Editors-in-Chief’s selection of papers from the May issue of PLOS Computational Biology.


Quantitative theory of deep brain stimulation of the subthalamic nucleus for the suppression of pathological rhythms in Parkinson’s disease

Power spectrum of parkinsonian STN activity as a function of DBS pulse frequency with fstim = 24–28 Hz.
A simulation of 40 s is used with νζx = −1.2 mVs and mVs and the power spectrum of the STN firing rate is calculated over the time window t = 20–40 s.
Image Credit: Müller et al.

Pathological 13-30 Hz (beta) oscillations within the basal ganglia are a characteristic feature of human Parkinson’s disease which seem to correlate with symptom severity. The origin of these oscillations and the suppressive mechanism of effective deep brain stimulation treatments remains to be shown. Eli J. Müller and Peter A. Robinson formulate a physiologically based population model of the corticothalamic-basal ganglia system that produces 13-30 Hz oscillations in the neural circuit formed between the globus pallidus pars externa and the subthalamic nucleus and the hyperdirect corticothalamic-basal ganglia pathway. They then develop a model of deep brain stimulation applied to the corticothalamic-basal ganglia system that permits systematic determination of effective stimulus protocols, which have been estimated by trial and error to date. Their results demonstrate that high pulse frequency (>140 Hz) stimulation is required to effectively suppress the pathological oscillations, which agrees with clinically used values. Interactions between these oscillations and the applied stimulus also lead to complex spectral structure that shows remarkable similarity to that seen in steady-state evoked potential experiments.


How epigenome drives chromatin folding and dynamics, insights from efficient coarse-grained models of chromosomes

The chromosome architecture inside cell nuclei plays important roles in regulating cell functions. Many experimental and modeling efforts are dedicated to deciphering the mechanisms controlling such organization. Many experimental studies report the hierarchical structure of chromosomes but how exactly they physically organize in 3D is not fully understood. In modeling, the main challenges are to develop adequate models and simulation methods to correctly investigate these highly dense long polymer chains. Taking into consideration the fundamental physical characteristics of chromosomes, Surya K. Ghosh and Daniel Jost developed robust and numerically efficient polymer models that enabled them to explore long chromosomes over long time periods with good statistics. They applied this framework to investigate the dynamical folding of chromosome in drosophila. Accounting for the local biochemical information, they were able to reproduce the experimentally-measured contact frequencies between any pairs of genomic loci quantitatively and to track the hierarchical chromosome structure throughout the cell cycle. Their results further support the picture of a very dynamic chromosome organization driven by weak short-range interactions.


Bi-stability in cooperative transport by ants in the presence of obstacles

The May Issue Image:
An investigation of the dynamics of cooperative transport, where the motion of the ants is frustrated by an obstacle that contains a narrow opening that serves as the only available passage to the nest, and through which single ants can pass but not the cargo.
Image Credit: Ehud Fonio

Among animal groups, ants hold what may perhaps be the richest repertoire of collective behavior such as trail formation, nest excavation and food dissemination. The most intriguing of these behaviors is cooperative food transport, where many ants carry items that individuals cannot move. Using experiments and theory, Nir S. Gov and colleagues study cooperative transport when the motion is frustrated by an obstacle which contains a single narrow opening that leads to the nest. They find that the group exhibits two co-existing modes of motion that allow exploration of possible routes to overcome the obstacle; either dwelling near the opening and attempting to pass the cargo through, or performing large excursions that can lead to obstacle circumvention. Previous studies have found that co-existing collective dynamic modes emerge when animal groups interact with constraints, however the origin of the phenomena remains unknown. Here, they provide a detailed theoretical explanation of the source of bi-stability and show how stochastic processes drive the transitions between the two dynamical modes.



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