1,283 research outputs found
Clique of functional hubs orchestrates population bursts in developmentally regulated neural networks
It has recently been discovered that single neuron stimulation can impact
network dynamics in immature and adult neuronal circuits. Here we report a
novel mechanism which can explain in neuronal circuits, at an early stage of
development, the peculiar role played by a few specific neurons in
promoting/arresting the population activity. For this purpose, we consider a
standard neuronal network model, with short-term synaptic plasticity, whose
population activity is characterized by bursting behavior. The addition of
developmentally inspired constraints and correlations in the distribution of
the neuronal connectivities and excitabilities leads to the emergence of
functional hub neurons, whose stimulation/deletion is critical for the network
activity. Functional hubs form a clique, where a precise sequential activation
of the neurons is essential to ignite collective events without any need for a
specific topological architecture. Unsupervised time-lagged firings of
supra-threshold cells, in connection with coordinated entrainments of
near-threshold neurons, are the key ingredients to orchestrateComment: 39 pages, 15 figures, to appear in PLOS Computational Biolog
An Instruction Language for Self-Construction in the Context of Neural Networks
Biological systems are based on an entirely different concept of construction than human artifacts. They construct themselves by a process of self-organization that is a systematic spatio-temporal generation of, and interaction between, various specialized cell types. We propose a framework for designing gene-like codes for guiding the self-construction of neural networks. The description of neural development is formalized by defining a set of primitive actions taken locally by neural precursors during corticogenesis. These primitives can be combined into networks of instructions similar to biochemical pathways, capable of reproducing complex developmental sequences in a biologically plausible way. Moreover, the conditional activation and deactivation of these instruction networks can also be controlled by these primitives, allowing for the design of a “genetic code” containing both coding and regulating elements. We demonstrate in a simulation of physical cell development how this code can be incorporated into a single progenitor, which then by replication and differentiation, reproduces important aspects of corticogenesis
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Single-Cell RNA Sequencing of hESC-Derived 3D Retinal Organoids Reveals Novel Genes Regulating RPC Commitment in Early Human Retinogenesis.
The development of the mammalian retina is a complicated process involving the generation of distinct types of neurons from retinal progenitor cells (RPCs) in a spatiotemporal-specific manner. The progression of RPCs during retinogenesis includes RPC proliferation, cell-fate commitment, and specific neuronal differentiation. In this study, by performing single-cell RNA sequencing of cells isolated from human embryonic stem cell (hESC)-derived 3D retinal organoids, we successfully deconstructed the temporal progression of RPCs during early human retinogenesis. We identified two distinctive subtypes of RPCs with unique molecular profiles, namely multipotent RPCs and neurogenic RPCs. We found that genes related to the Notch and Wnt signaling pathways, as well as chromatin remodeling, were dynamically regulated during RPC commitment. Interestingly, our analysis identified that CCND1, a G1-phase cell-cycle regulator, was coexpressed with ASCL1 in a cell-cycle-independent manner. Temporally controlled overexpression of CCND1 in retinal organoids demonstrated a role for CCND1 in promoting early retinal neurogenesis. Together, our results revealed critical pathways and novel genes in early retinogenesis of humans
Model-free reconstruction of neuronal network connectivity from calcium imaging signals
A systematic assessment of global neural network connectivity through direct
electrophysiological assays has remained technically unfeasible even in
dissociated neuronal cultures. We introduce an improved algorithmic approach
based on Transfer Entropy to reconstruct approximations to network structural
connectivities from network activity monitored through calcium fluorescence
imaging. Based on information theory, our method requires no prior assumptions
on the statistics of neuronal firing and neuronal connections. The performance
of our algorithm is benchmarked on surrogate time-series of calcium
fluorescence generated by the simulated dynamics of a network with known
ground-truth topology. We find that the effective network topology revealed by
Transfer Entropy depends qualitatively on the time-dependent dynamic state of
the network (e.g., bursting or non-bursting). We thus demonstrate how
conditioning with respect to the global mean activity improves the performance
of our method. [...] Compared to other reconstruction strategies such as
cross-correlation or Granger Causality methods, our method based on improved
Transfer Entropy is remarkably more accurate. In particular, it provides a good
reconstruction of the network clustering coefficient, allowing to discriminate
between weakly or strongly clustered topologies, whereas on the other hand an
approach based on cross-correlations would invariantly detect artificially high
levels of clustering. Finally, we present the applicability of our method to
real recordings of in vitro cortical cultures. We demonstrate that these
networks are characterized by an elevated level of clustering compared to a
random graph (although not extreme) and by a markedly non-local connectivity.Comment: 54 pages, 8 figures (+9 supplementary figures), 1 table; submitted
for publicatio
Excess of serotonin affects neocortical pyramidal neuron migration
The serotonin transporter (SERT) is a key molecule involved in the homeostasis of extracellular levels of serotonin and is regulated developmentally. Genetic deletion of SERT in rodents increases extracellular levels of serotonin and affects cellular processes involved in neocortical circuit assembly such as barrel cortex wiring and cortical interneuron migration. Importantly, pharmacological blockade of SERT during brain development leads to phenotypes relevant to psychiatry in rodents and to an increased risk for autism spectrum disorders in humans. Furthermore, developmental adversity interacts with genetically-driven variations of serotonin function in humans and nonhuman primates to increase the risk for a variety of stress-related phenotypes. In this study, we investigate whether an excess of serotonin affects the migration of neocortical pyramidal neurons during development. Using in utero electroporation combined with time-lapse imaging to specifically monitor pyramidal neurons during late mouse embryogenesis, we show that an excess of serotonin reversibly affects the radial migration of pyramidal neurons. We further identify that the serotonin receptor 5-HT6 is expressed in pyramidal neuron progenitors and that 5-HT6 receptor activation replicates the effects of serotonin stimulation. Finally, we show that the positioning of superficial layer pyramidal neurons is altered in vivo in SERT knockout mice. Taken together, these results indicate that a developmental excess of serotonin decreases the migration speed of cortical pyramidal neurons, affecting a fundamental step in the assembly of neural circuits. These findings support the hypothesis that developmental dysregulation of serotonin homeostasis has detrimental effects on neocortical circuit formation and contributes to increased vulnerability to psychiatric disorders
Progress toward an understanding of cortical computation
The additional data, perspectives, questions, and criticisms contributed by the commentaries strengthen our view that local cortical processors coordinate their activity with the context in which it occurs using contextual fields and synchronized population codes. We therefore predict that whereas the specialization of function has been the keynote of this century the coordination of function will be the keynote of the next
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