173 research outputs found
Reliable Sequential Activation of Neural Assemblies by Single Pyramidal Cells in a Three-Layered Cortex
Recent studies reveal the occasional impact of single neurons on surround firing statistics and even simple behaviors. Exploiting the advantages of a simple cortex, we examined the influence of single pyramidal neurons on surrounding cortical circuits. Brief activation of single neurons triggered reliable sequences of firing in tens of other excitatory and inhibitory cortical neurons, reflecting cascading activity through local networks, as indicated by delayed yet precisely timed polysynaptic subthreshold potentials. The evoked patterns were specific to the pyramidal cell of origin, extended over hundreds of micrometers from their source, and unfolded over up to 200 ms. Simultaneous activation of pyramidal cell pairs indicated balanced control of population activity, preventing paroxysmal amplification. Single cortical pyramidal neurons can thus trigger reliable postsynaptic activity that can propagate in a reliable fashion through cortex, generating rapidly evolving and non-random firing sequences reminiscent of those observed in mammalian hippocampus during "replay" and in avian song circuits
Consensus-Based Sorting of Neuronal Spike Waveforms
Optimizing spike-sorting algorithms is difficult because sorted clusters can rarely be
checked against independently obtained “ground truth” data. In most spike-sorting algorithms
in use today, the optimality of a clustering solution is assessed relative to some
assumption on the distribution of the spike shapes associated with a particular single unit
(e.g., Gaussianity) and by visual inspection of the clustering solution followed by manual
validation. When the spatiotemporal waveforms of spikes from different cells overlap, the
decision as to whether two spikes should be assigned to the same source can be quite subjective,
if it is not based on reliable quantitative measures. We propose a new approach,
whereby spike clusters are identified from the most consensual partition across an ensemble
of clustering solutions. Using the variability of the clustering solutions across successive
iterations of the same clustering algorithm (template matching based on K-means clusters),
we estimate the probability of spikes being clustered together and identify groups of spikes
that are not statistically distinguishable from one another. Thus, we identify spikes that are
most likely to be clustered together and therefore correspond to consistent spike clusters.
This method has the potential advantage that it does not rely on any model of the spike
shapes. It also provides estimates of the proportion of misclassified spikes for each of the
identified clusters. We tested our algorithm on several datasets for which there exists a
ground truth (simultaneous intracellular data), and show that it performs close to the optimum
reached by a support vector machine trained on the ground truth. We also show that
the estimated rate of misclassification matches the proportion of misclassified spikes measured
from the ground truth data
A new class of pluripotent stem cell cytotoxic small molecules
10.1371/journal.pone.0085039PLoS ONE93-POLN
Nicotinamide alone accelerates the conversion of mouse embryonic stem cells into mature neuronal populations.
Vitamin B3 has been shown to play an important role during embryogenesis. Specifically, there is growing evidence that nicotinamide, the biologically active form of vitamin B3, plays a critical role as a morphogen in the differentiation of stem cells to mature cell phenotypes, including those of the central nervous system (CNS). Detailed knowledge of the action of small molecules during neuronal differentiation is not only critical for uncovering mechanisms underlying lineage-specification, but also to establish more effective differentiation protocols to obtain clinically relevant cells for regenerative therapies for neurodegenerative conditions such as Huntington's disease (HD). Thus, this study aimed to investigate the potential of nicotinamide to promote the conversion of stem cells to mature CNS neurons. METHODS: Nicotinamide was applied to differentiating mouse embryonic stem cells (mESC; Sox1GFP knock-in 46C cell line) during their conversion towards a neural fate. Cells were assessed for changes in their proliferation, differentiation and maturation; using immunocytochemistry and morphometric analysis methods. RESULTS: Results presented indicate that 10 mM nicotinamide, when added at the initial stages of differentiation, promoted accelerated progression of ESCs to a neural lineage in adherent monolayer cultures. By 14 days in vitro (DIV), early exposure to nicotinamide was shown to increase the numbers of differentiated βIII-tubulin-positive neurons. Nicotinamide decreased the proportion of pluripotent stem cells, concomitantly increasing numbers of neural progenitors at 4 DIV. These progenitors then underwent rapid conversion to neurons, observed by a reduction in Sox 1 expression and decreased numbers of neural progenitors in the cultures at 14 DIV. Furthermore, GABAergic neurons generated in the presence of nicotinamide showed increased maturity and complexity of neurites at 14 DIV. Therefore, addition of nicotinamide alone caused an accelerated passage of pluripotent cells through lineage specification and further to non-dividing mature neurons. CONCLUSIONS: Our results show that, within an optimal dose range, nicotinamide is able to singly and selectively direct the conversion of embryonic stem cells to mature neurons, and therefore may be a critical factor for normal brain development, thus supporting previous evidence of the fundamental role of vitamins and their metabolites during early CNS development. In addition, nicotinamide may offer a simple effective supplement to enhance the conversion of stem cells to clinically relevant neurons
Promises of stem cell therapy for retinal degenerative diseases
With the development of stem cell technology, stem cell-based therapy for retinal degeneration has been proposed to restore the visual function. Many animal studies and some clinical trials have shown encouraging results of stem cell-based therapy in retinal degenerative diseases. While stem cell-based therapy is a promising strategy to replace damaged retinal cells and ultimately cure retinal degeneration, there are several important challenges which need to be overcome before stem cell technology can be applied widely in clinical settings. In this review, different types of donor cell origins used in retinal treatments, potential target cell types for therapy, methods of stem cell delivery to the eye, assessments of potential risks in stem cell therapy, as well as future developments of retinal stem cells therapy, will be discussed
Human Induced Pluripotent Stem Cells Differentiation into Oligodendrocyte Progenitors and Transplantation in a Rat Model of Optic Chiasm Demyelination
BACKGROUND: This study aims to differentiate human induced pluripotent stem cells (hiPSCs) into oligodendrocyte precursors and assess their recovery potential in a demyelinated optic chiasm model in rats. METHODOLOGY/PRINCIPAL FINDINGS: We generated a cell population of oligodendrocyte progenitors from hiPSCs by using embryoid body formation in a defined medium supplemented with a combination of factors, positive selection and mechanical enrichment. Real-time polymerase chain reaction and immunofluorescence analyses showed that stage-specific markers, Olig2, Sox10, NG2, PDGFRα, O4, A2B5, GalC, and MBP were expressed following the differentiation procedure, and enrichment of the oligodendrocyte lineage. These results are comparable with the expression of stage-specific markers in human embryonic stem cell-derived oligodendrocyte lineage cells. Transplantation of hiPSC-derived oligodendrocyte progenitors into the lysolecithin-induced demyelinated optic chiasm of the rat model resulted in recovery from symptoms, and integration and differentiation into oligodendrocytes were detected by immunohistofluorescence staining against PLP and MBP, and measurements of the visual evoked potentials. CONCLUSIONS/SIGNIFICANCE: These results showed that oligodendrocyte progenitors generated efficiently from hiPSCs can be used in future biomedical studies once safety issues have been overcome
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
Emergent Functional Properties of Neuronal Networks with Controlled Topology
The interplay between anatomical connectivity and dynamics in neural networks plays a key role in the functional properties of the brain and in the associated connectivity changes induced by neural diseases. However, a detailed experimental investigation of this interplay at both cellular and population scales in the living brain is limited by accessibility. Alternatively, to investigate the basic operational principles with morphological, electrophysiological and computational methods, the activity emerging from large in vitro networks of primary neurons organized with imposed topologies can be studied. Here, we validated the use of a new bio-printing approach, which effectively maintains the topology of hippocampal cultures in vitro and investigated, by patch-clamp and MEA electrophysiology, the emerging functional properties of these grid-confined networks. In spite of differences in the organization of physical connectivity, our bio-patterned grid networks retained the key properties of synaptic transmission, short-term plasticity and overall network activity with respect to random networks. Interestingly, the imposed grid topology resulted in a reinforcement of functional connections along orthogonal directions, shorter connectivity links and a greatly increased spiking probability in response to focal stimulation. These results clearly demonstrate that reliable functional studies can nowadays be performed on large neuronal networks in the presence of sustained changes in the physical network connectivity
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