Innate Synchronous Oscillations in Freely-Organized Small Neuronal Circuits

BACKGROUND: Information processing in neuronal networks relies on the network's ability to generate temporal patterns of action potentials. Although the nature of neuronal network activity has been intensively investigated in the past several decades at the individual neuron level, the underlying principles of the collective network activity, such as the synchronization and coordination between neurons, are largely unknown. Here we focus on isolated neuronal clusters in culture and address the following simple, yet fundamental questions: What is the minimal number of cells needed to exhibit collective dynamics? What are the internal temporal characteristics of such dynamics and how do the temporal features of network activity alternate upon crossover from minimal networks to large networks? METHODOLOGY/PRINCIPAL FINDINGS: We used network engineering techniques to induce self-organization of cultured networks into neuronal clusters of different sizes. We found that small clusters made of as few as 40 cells already exhibit spontaneous collective events characterized by innate synchronous network oscillations in the range of 25 to 100 Hz. The oscillation frequency of each network appeared to be independent of cluster size. The duration and rate of the network events scale with cluster size but converge to that of large uniform networks. Finally, the investigation of two coupled clusters revealed clear activity propagation with master/slave asymmetry. CONCLUSIONS/SIGNIFICANCE: The nature of the activity patterns observed in small networks, namely the consistent emergence of similar activity across networks of different size and morphology, suggests that neuronal clusters self-regulate their activity to sustain network bursts with internal oscillatory features. We therefore suggest that clusters of as few as tens of cells can serve as a minimal but sufficient functional network, capable of sustaining oscillatory activity. Interestingly, the frequencies of these oscillations are similar those observed in vivo

Causal Measures of Structure and Plasticity in Simulated and Living Neural Networks

A major goal of neuroscience is to understand the relationship between neural structures and their function. Recording of neural activity with arrays of electrodes is a primary tool employed toward this goal. However, the relationships among the neural activity recorded by these arrays are often highly complex making it problematic to accurately quantify a network's structural information and then relate that structure to its function. Current statistical methods including cross correlation and coherence have achieved only modest success in characterizing the structural connectivity. Over the last decade an alternative technique known as Granger causality is emerging within neuroscience. This technique, borrowed from the field of economics, provides a strong mathematical foundation based on linear auto-regression to detect and quantify “causal” relationships among different time series. This paper presents a combination of three Granger based analytical methods that can quickly provide a relatively complete representation of the causal structure within a neural network. These are a simple pairwise Granger causality metric, a conditional metric, and a little known computationally inexpensive subtractive conditional method. Each causal metric is first described and evaluated in a series of biologically plausible neural simulations. We then demonstrate how Granger causality can detect and quantify changes in the strength of those relationships during plasticity using 60 channel spike train data from an in vitro cortical network measured on a microelectrode array. We show that these metrics can not only detect the presence of causal relationships, they also provide crucial information about the strength and direction of that relationship, particularly when that relationship maybe changing during plasticity. Although we focus on the analysis of multichannel spike train data the metrics we describe are applicable to any stationary time series in which causal relationships among multiple measures is desired. These techniques can be especially useful when the interactions among those measures are highly complex, difficult to untangle, and maybe changing over time

Testis-specific glyceraldehyde-3-phosphate dehydrogenase: origin and evolution

<p>Abstract</p> <p>Background</p> <p>Glyceraldehyde-3-phosphate dehydrogenase (GAPD) catalyses one of the glycolytic reactions and is also involved in a number of non-glycolytic processes, such as endocytosis, DNA excision repair, and induction of apoptosis. Mammals are known to possess two homologous GAPD isoenzymes: GAPD-1, a well-studied protein found in all somatic cells, and GAPD-2, which is expressed solely in testis. GAPD-2 supplies energy required for the movement of spermatozoa and is tightly bound to the sperm tail cytoskeleton by the additional N-terminal proline-rich domain absent in GAPD-1. In this study we investigate the evolutionary history of GAPD and gain some insights into specialization of GAPD-2 as a testis-specific protein.</p> <p>Results</p> <p>A dataset of GAPD sequences was assembled from public databases and used for phylogeny reconstruction by means of the Bayesian method. Since resolution in some clades of the obtained tree was too low, syntenic analysis was carried out to define the evolutionary history of GAPD more precisely. The performed selection tests showed that selective pressure varies across lineages and isoenzymes, as well as across different regions of the same sequences.</p> <p>Conclusions</p> <p>The obtained results suggest that GAPD-1 and GAPD-2 emerged after duplication during the early evolution of chordates. GAPD-2 was subsequently lost by most lineages except lizards, mammals, as well as cartilaginous and bony fishes. In reptilians and mammals, GAPD-2 specialized to a testis-specific protein and acquired the novel N-terminal proline-rich domain anchoring the protein in the sperm tail cytoskeleton. This domain is likely to have originated by exonization of a microsatellite genomic region. Recognition of the proline-rich domain by cytoskeletal proteins seems to be unspecific. Besides testis, GAPD-2 of lizards was also found in some regenerating tissues, but it lacks the proline-rich domain due to tissue-specific alternative splicing.</p

Empirical Validation of a Procedure to Correct Position and Stimulus Biases in Matching-to-Sample

The development of position and stimulus biases often occurs during initial training on matching-to-sample tasks. Furthermore, without intervention, these biases can be maintained via intermittent reinforcement provided by matching-to-sample contingencies. The present study evaluated the effectiveness of a correction procedure designed to eliminate both position and stimulus biases. Following key-peck training, a group of 6 pigeons had extended exposure to matching-to-sample contingencies without a correction procedure, a group of 4 pigeons was briefly exposed to a simultaneous matching-to-sample procedure to assess biases prior to exposure to the correction procedure, and a group of 5 pigeons was exposed directly to the correction procedure. The correction procedure arranged that every time an incorrect match was made, the trial configuration was repeated on the subsequent trial until a correct match was made. Extended exposure to matching-to-sample contingencies without a correction procedure was associated with reduced biases eventually for most subjects, but rapid development of near-perfect accuracy and bias-free performance was observed upon the implementation of the correction procedure regardless of the type of bias. Bias-free performance was maintained following subsequent exposure to a zero-delay MTS procedure

High-density electrode array for imaging in vitro electrophysiological activity

The development of a high-density active microelectrode array for in vitro electrophysiology is reported. Based on the Active Pixel Sensor (APS) concept, the array integrates 4096 gold microelectrodes (electrode separation 20 microm) on a surface of 2.5 mmx2.5 mm as well as a high-speed random addressing logic allowing the sequential selection of the measuring pixels. Following the electrical characterization in a phosphate solution, the functional evaluation has been carried out by recording the spontaneous electrical activity of neonatal rat cardiomyocytes. Signals with amplitudes from 130 microVp-p to 300 microVp-p could be recorded from different pixels. The results demonstrate the suitability of the APS concept for developing a new generation of high-resolution extracellular recording devices for in vitro electrophysiology