The influence of non-neuronal cells on catecholamine and acetylcholine synthesis and accumulation in cultures of dissociated sympathetic neurons

The effects of several non-neuronal cell types on neurotransmitter synthesis in cultures of dissociated sympathetic neurons from the new-born rat were studied. Acetylcholine synthesis from radioactive choline was increased 100- to 1000-fold in the presence of non-neuronal cells from sympathetic ganglia. This increase was roughly dependent on the number of ganglionic non-neuronal cells present. The effect did not appear to be due to an increased plating efficiency of neurons, since the non-neuronal cells were capable of increasing acetylcholine synthesis after only 48-hr contact with neurons that had been previously grown without non-neuronal cells for 2 weeks. C6 rat glioma cells were also able to stimulate acetylcholine synthesis, but 3T3 mouse fibroblast cells had little or no effect. None of the non-neuronal cell types synthesized detectable acetylcholine in the absence of the neurons. The ganglionic non-neuronal cells had no significant effect on catecholamine synthesis (which occurs in the absence of non-neuronal cells)

MASH1 activates expression of the paired homeodomain transcription factor Phox2a, and couples pan-neuronal and subtype-specific components of autonomic neuronal identity

We have investigated the genetic circuitry underlying the determination of neuronal identity, using mammalian peripheral autonomic neurons as a model system. Previously, we showed that treatment of neural crest stem cells (NCSCs) with bone morphogenetic protein-2 (BMP-2) leads to an induction of MASH1 expression and consequent autonomic neuronal differentiation. We now show that BMP2 also induces expression of the paired homeodomain transcription factor Phox2a, and the GDNF/NTN signalling receptor tyrosine kinase c-RET. Constitutive expression of MASH1 in NCSCs from a retroviral vector, in the absence of exogenous BMP2, induces expression of both Phox2a and c-RET in a large fraction of infected colonies, and also promotes morphological neuronal differentiation and expression of pan-neuronal markers. In vivo, expression of Phox2a in autonomic ganglia is strongly reduced in Mash1 -/- embryos. These loss- and gain-of-function data suggest that MASH1 positively regulates expression of Phox2a, either directly or indirectly. Constitutive expression of Phox2a, by contrast to MASH1, fails to induce expression of neuronal markers or a neuronal morphology, but does induce expression of c-RET. These data suggest that MASH1 couples expression of pan-neuronal and subtype-specific components of autonomic neuronal identity, and support the general idea that identity is established by combining subprograms involving cascades of transcription factors, which specify distinct components of neuronal phenotype

Revealing ensemble state transition patterns in multi-electrode neuronal recordings using hidden Markov models

In order to harness the computational capacity of dissociated cultured neuronal networks, it is necessary to understand neuronal dynamics and connectivity on a mesoscopic scale. To this end, this paper uncovers dynamic spatiotemporal patterns emerging from electrically stimulated neuronal cultures using hidden Markov models (HMMs) to characterize multi-channel spike trains as a progression of patterns of underlying states of neuronal activity. However, experimentation aimed at optimal choice of parameters for such models is essential and results are reported in detail. Results derived from ensemble neuronal data revealed highly repeatable patterns of state transitions in the order of milliseconds in response to probing stimuli

Neuronal imaging with ultrahigh dynamic range multiphoton microscopy

Multiphoton microscopes are hampered by limited dynamic range, preventing weak sample features from being detected in the presence of strong features, or preventing the capture of unpredictable bursts in sample strength. We present a digital electronic add-on technique that vastly improves the dynamic range of a multiphoton microscope while limiting potential photodamage. The add-on provides real-time negative feedback to regulate the laser power delivered to the sample, and a log representation of the sample strength to accommodate ultrahigh dynamic range without loss of information. No microscope hardware modifications are required, making the technique readily compatible with commercial instruments. Benefits are shown in both structural and in-vivo functional mouse brain imaging applications.R21 EY027549 - NEI NIH HH

Neuronal synchrony: peculiarity and generality

Synchronization in neuronal systems is a new and intriguing application of dynamical systems theory. Why are neuronal systems different as a subject for synchronization? (1) Neurons in themselves are multidimensional nonlinear systems that are able to exhibit a wide variety of different activity patterns. Their “dynamical repertoire” includes regular or chaotic spiking, regular or chaotic bursting, multistability, and complex transient regimes. (2) Usually, neuronal oscillations are the result of the cooperative activity of many synaptically connected neurons (a neuronal circuit). Thus, it is necessary to consider synchronization between different neuronal circuits as well. (3) The synapses that implement the coupling between neurons are also dynamical elements and their intrinsic dynamics influences the process of synchronization or entrainment significantly. In this review we will focus on four new problems: (i) the synchronization in minimal neuronal networks with plastic synapses (synchronization with activity dependent coupling), (ii) synchronization of bursts that are generated by a group of nonsymmetrically coupled inhibitory neurons (heteroclinic synchronization), (iii) the coordination of activities of two coupled neuronal networks (partial synchronization of small composite structures), and (iv) coarse grained synchronization in larger systems (synchronization on a mesoscopic scale

Critical Changes in Cortical Neuronal Interactions in Anesthetized and Awake Rats

Background: Neuronal interactions are fundamental for information processing, cognition and consciousness. Anesthetics reduce spontaneous cortical activity; however, neuronal reactivity to sensory stimuli is often preserved or augmented. How sensory stimulus-related neuronal interactions change under anesthesia has not been elucidated. Here we investigated visual stimulus-related cortical neuronal interactions during stepwise emergence from desflurane anesthesia. Methods: Parallel spike trains were recorded with 64-contact extracellular microelectrode arrays from the primary visual cortex of chronically instrumented, unrestrained rats (N=6) at 8%, 6%, 4%, 2% desflurane anesthesia and wakefulness. Light flashes were delivered to the retina by transcranial illumination at 5-15s randomized intervals. Information theoretical indices, integration and interaction complexity, were calculated from the probability distribution of coincident spike patterns and used to quantify neuronal interactions before and after flash stimulation. Results: Integration and complexity showed significant negative associations with desflurane concentration (N=60). Flash stimulation increased integration and complexity at all anesthetic levels (N=60); the effect on complexity was reduced in wakefulness. During stepwise withdrawal of desflurane, the largest increase in integration (74%) and post-stimulus complexity (35%) occurred prior to reaching 4% desflurane concentration – a level associated with the recovery of consciousness according to the rats\u27 righting reflex. Conclusions: Neuronal interactions in the cerebral cortex are augmented during emergence from anesthesia. Visual flash stimuli enhance neuronal interactions in both wakefulness and anesthesia; the increase in interaction complexity is attenuated as post-stimulus complexity reaches plateau. The critical changes in cortical neuronal interactions occur during transition to consciousness

Growth-Driven Percolations: The Dynamics of Community Formation in Neuronal Systems

The quintessential property of neuronal systems is their intensive patterns of selective synaptic connections. The current work describes a physics-based approach to neuronal shape modeling and synthesis and its consideration for the simulation of neuronal development and the formation of neuronal communities. Starting from images of real neurons, geometrical measurements are obtained and used to construct probabilistic models which can be subsequently sampled in order to produce morphologically realistic neuronal cells. Such cells are progressively grown while monitoring their connections along time, which are analysed in terms of percolation concepts. However, unlike traditional percolation, the critical point is verified along the growth stages, not the density of cells, which remains constant throughout the neuronal growth dynamics. It is shown, through simulations, that growing beta cells tend to reach percolation sooner than the alpha counterparts with the same diameter. Also, the percolation becomes more abrupt for higher densities of cells, being markedly sharper for the beta cells.Comment: 8 pages, 10 figure