Sloppiness in spontaneously active neuronal networks

Various plasticity mechanisms, including experience-dependent, spontaneous, as well as homeostatic ones, continuously remodel neural circuits. Yet, despite fluctuations in the properties of single neurons and synapses, the behavior and function of neuronal assemblies are generally found to be very stable over time. This raises the important question of how plasticity is coordinated across the network. To address this, we investigated the stability of network activity in cultured rat hippocampal neurons recorded with high-density multielectrode arrays over several days. We used parametric models to characterize multineuron activity patterns and analyzed their sensitivity to changes. We found that the models exhibited sloppiness, a property where the model behavior is insensitive to changes in many parameter combinations, but very sensitive to a few. The activity of neurons with sloppy parameters showed faster and larger fluctuations than the activity of a small subset of neurons associated with sensitive parameters. Furthermore, parameter sensitivity was highly correlated with firing rates. Finally, we tested our observations from cell cultures on an in vivo recording from monkey visual cortex and we confirm that spontaneous cortical activity also shows hallmarks of sloppy behavior and firing rate dependence. Our findings suggest that a small subnetwork of highly active and stable neurons supports group stability, and that this endows neuronal networks with the flexibility to continuously remodel without compromising stability and function

Unsupervised spike sorting for large-scale, high-density multielectrode arrays

electrophysiology; high-density multielectrode array; neural cultures; retina; spike sortin

Spike Detection for Large Neural Populations Using High Density Multielectrode Arrays

An emerging generation of high-density microelectrode arrays (MEAs) is now capable of recording spiking activity simultaneously from thousands of neurons with closely spaced electrodes. Reliable spike detection and analysis in such recordings is challenging due to the large amount of raw data, and the dense sampling of spikes with closely spaced electrodes.Here, we present a highly efficient, online capable spike detection algorithm, and an offline method with improved detection rates, which enables estimation of spatial event locations at a resolution higher than that provided by the array by combining information from multiple electrodes. Data acquired with a 4,096 channel MEA from neuronal cultures and the neonatal retina, as well as synthetic data was used to test and validate these methods.We demonstrate that these algorithms outperform conventional methods due to a better noise estimate and an improved signal-to-noise ratio through combining information from multiple electrodes. Finally, we present a new approach for analyzing population activity based on the characterization of the spatio-temporal event profile, which does not require the isolation of single units.Overall, we show how the improved spatial resolution provided by high density, large scale microelectrode arrays can be reliably exploited to characterize activity from large neural populations and brain circuits

Following the Ontogeny of Retinal Waves: Pan-Retinal Recordings of Population Dynamics in the Neonatal Mouse

The immature retina generates spontaneous waves of spiking activity that sweep across the ganglion cell layer during a limited period of development before the onset of visual experience. The spatiotemporal patterns encoded in the waves are believed to be instructive for the wiring of functional connections throughout the visual system. However, the ontogeny of retinal waves is still poorly documented as a result of the relatively low resolution of conventional recording techniques. Here, we characterize the spatiotemporal features of mouse retinal waves from birth until eye opening in unprecedented detail using a large-scale, dense, 4096-channel multielectrode array that allowed us to record from the entire neonatal retina at near cellular resolution. We found that early cholinergic waves propagate with random trajectories over large areas with low ganglion cell recruitment. They become slower, smaller and denser when GABA(A) signalling matures, as occurs beyond postnatal day (P) 7. Glutamatergic influences dominate from P10, coinciding with profound changes in activity dynamics. At this time, waves cease to be random and begin to show repetitive trajectories confined to a few localized hotspots. These hotspots gradually tile the retina with time, and disappear after eye opening. Our observations demonstrate that retinal waves undergo major spatiotemporal changes during ontogeny. Our results support the hypotheses that cholinergic waves guide the refinement of retinal targets and that glutamatergic waves may also support the wiring of retinal receptive fields

Structural and temporal dynamics of the bee curtain in the open-nesting honey bee species, Apis florea

International audienceAbstractWorkers of open-nesting honey bee species form a bee curtain to cover the comb and protect it against adverse environmental conditions and predators. We studied different aspects of structural and temporal dynamics of the bee curtain in Apis florea. First, in the course of daily observations, we discovered massed flight activity (MFA) of A. florea colonies similar to that previously described for A. dorsata. The MFAs started with the opening of gaps in the curtain and appearance of chains of bees shortly before the massed take off. Second, monitoring the worker movement patterns in the outer layer indicated a constant turnover of bees in the curtain. Finally, introduction of marked 1-day-old workers showed that workers joined the curtain at a very young age. First flight activity appeared around day 20, but the majority of workers started to fly after day 47, which is twice the age at which A. mellifera workers start to forage