Lévy walk dynamics explain gamma burst patterns in primate cerebral cortex

Lévy walks describe patterns of intermittent motion with variable step sizes. In complex biological systems, Lévy walks (non-Brownian, superdiffusive random walks) are associated with behaviors such as search patterns of animals foraging for food. Here we show that Lévy walks also describe patterns of oscillatory activity in primate cerebral cortex. We used a combination of empirical observation and modeling to investigate high-frequency (gamma band) local field potential activity in visual motion-processing cortical area MT of marmoset monkeys. We found that gamma activity is organized as localized burst patterns that propagate across the cortical surface with Lévy walk dynamics. Lévy walks are fundamentally different from either global synchronization, or regular propagating waves, because they include large steps that enable activity patterns to move rapidly over cortical modules. The presence of Lévy walk dynamics therefore represents a previously undiscovered mode of brain activity, and implies a novel way for the cortex to compute. We apply a biophysically realistic circuit model to explain that the Lévy walk dynamics arise from critical-state transitions between asynchronous and localized propagating wave states, and that these dynamics yield optimal spatial sampling of the cortical sheet. We hypothesise that Lévy walk dynamics could help the cortex to efficiently process variable inputs, and to find links in patterns of activity among sparsely spiking populations of neurons.

Predicting Social Unrest Events with Hidden Markov Models Using GDELT

Proactive handling of social unrest events which are common happenings in both democracies and authoritarian regimes requires that the risk of upcoming social unrest event is continuously assessed. Most existing approaches comparatively pay little attention to considering the event development stages. In this paper, we use autocoded events dataset GDELT (Global Data on Events, Location, and Tone) to build a Hidden Markov Models (HMMs) based framework to predict indicators associated with country instability. The framework utilizes the temporal burst patterns in GDELT event streams to uncover the underlying event development mechanics and formulates the social unrest event prediction as a sequence classification problem based on Bayes decision. Extensive experiments with data from five countries in Southeast Asia demonstrate the effectiveness of this framework, which outperforms the logistic regression method by 7% to 27% and the baseline method 34% to 62% for various countries.

Zebrafish needle EMG: a new tool for high-throughput drug screens

Zebrafish models have recently been highlighted as a valuable tool in studying the molecular basis of neuromuscular diseases and developing new pharmacological treatments. Needle electromyography (EMG) is needed not only for validating transgenic zebrafish models with muscular dystrophies (MD), but also for assessing the efficacy of therapeutics. However, performing needle EMG on larval zebrafish has not been feasible due to the lack of proper EMG sensors and systems for such small animals. We introduce a new type of EMG needle electrode to measure intramuscular activities of larval zebrafish, together with a method to hold the animal in position during EMG, without anesthetization. The silicon-based needle electrode was found to be sufficiently strong and sharp to penetrate the skin and muscles of zebrafish larvae, and its shape and performance did not change after multiple insertions. With the use of the proposed needle electrode and measurement system, EMG was successfully performed on zebrafish at 30 days postfertilization (dpf) and at 5 dpf. Burst patterns and spike morphology of the recorded EMG signals were analyzed. The measured single spikes were triphasic with an initial positive deflection, which is typical for motor unit action potentials, with durations of ∼10 ms, whereas the muscle activity was silent during the anesthetized condition. These findings confirmed the capability of this system of detecting EMG signals from very small animals such as 5 dpf zebrafish. The developed EMG sensor and system are expected to become a helpful tool in validating zebrafish MD models and further developing therapeutics.