Spiking attractor model of motor cortex explains modulation of neural and behavioral variability by prior target information.

When preparing a movement, we often rely on partial or incomplete information, which can decrement task performance. In behaving monkeys we show that the degree of cued target information is reflected in both, neural variability in motor cortex and behavioral reaction times. We study the underlying mechanisms in a spiking motor-cortical attractor model.

Efficient parameter calibration and real-time simulation of large-scale spiking neural networks with GeNN and NEST.

Spiking neural networks (SNNs) represent the state-of-the-art approach to the biologically realistic modeling of nervous system function. The systematic calibration for multiple free model parameters is necessary to achieve robust network function and demands high computing power and large memory resources. Special requirements arise from closed-loop model simulation in virtual environments and from real-time simulation in robotic application.

Visualization of learning-induced synaptic plasticity in output neurons of the Drosophila mushroom body γ-lobe.

By learning, through experience, which stimuli coincide with dangers, it is possible to predict outcomes and act pre-emptively to ensure survival. In insects, this process is localized to the mushroom body (MB), the circuitry of which facilitates the coincident detection of sensory stimuli and punishing or rewarding cues and, downstream, the execution of appropriate learned behaviors. Here, we focused our attention on the mushroom body output neurons (MBONs) of the γ-lobes that act as downstream synaptic partners of the MB γ-Kenyon cells (KCs) to ask how the output of the MB γ-lobe is shaped by olfactory associative conditioning, distinguishing this from non-associative stimulus exposure effects, and without the influence of downstream modulation.

Evaluation of the Effects of Cement and Lime with Rice Husk Ash as an Additive on Strength Behavior of Coastal Soil.

Coastal accretion and erosion are unavoidable processes as some coastal sediments undergo modification and stabilization. This study was conducted to investigate the geotechnical behavior of soil collected from Bagan Lalang coast and treated with lime, cement, and rice husk ash (RHA) to design a low-cost alternative mixture with environmentally friendly characteristics. Laboratory tests were carried out to analyze the physical properties of the soil (Atterberg limits and compaction properties), together with mechanical characteristics (direct shear and unconfined compressive strength (UCS) tests) to determine the effect of different ratios of stabilizer/pozzolan on the coastal soil and the optimum conditions for each mixture.

Methods for identification of spike patterns in massively parallel spike trains.

Temporally, precise correlations between simultaneously recorded neurons have been interpreted as signatures of cell assemblies, i.e., groups of neurons that form processing units.

Sustainable computational science: the ReScience initiative.

Computer science offers a large set of tools for prototyping, writing, running, testing, validating, sharing and reproducing results; however, computational science lags behind. In the best case, authors may provide their source code as a compressed archive and they may feel confident their research is reproducible. But this is not exactly true.

Bistability, non-ergodicity, and inhibition in pairwise maximum-entropy models.

Pairwise maximum-entropy models have been used in neuroscience to predict the activity of neuronal populations, given only the time-averaged correlations of the neuron activities. This paper provides evidence that the pairwise model, applied to experimental recordings, would produce a bimodal distribution for the population-averaged activity, and for some population sizes the second mode would peak at high activities, that experimentally would be equivalent to 90% of the neuron population active within time-windows of few milliseconds. Several problems are connected with this bimodality: 1.