100,377 research outputs found
Tonic activation of GABA-B receptors reduces release probability at inhibitory connections in the cerebellar glomerulus
No full textMapelli L, Rossi P, Nieus T, D'Angelo E. Tonic activation of GABA(B) receptors reduces release probability at inhibitory connections in the cerebellar glomerulus. J Neurophysiol 101: 3089-3099, 2009. First published April 1, 2009; doi:10.1152/jn.91190.2008. In the cerebellum, granule cells are inhibited by Golgi cells through GABAergic synapses generating complex responses involving both phasic neurotransmitter release and the establishment of ambient gamma-aminobutyric acid (GABA) levels. Although at this synapse the mechanisms of postsynaptic integration have been clarified to a considerable extent, the mechanisms of neurotransmitter release remained largely unknown. Here we have investigated the quantal properties of release during repetitive neurotransmission, revealing that tonic GABA(B) receptor activation by ambient GABA regulates release probability. Blocking GABA(B) receptors with CGP55845 enhanced the first inhibitory postsynaptic current (IPSC) and short-term depression in a train while reducing trial-to-trial variability and failures. The changes caused by CGP55845 were similar to those caused by increasing extracellular Ca2+ concentration, in agreement with a presynaptic GABA(B) receptor modulation of release probability. However, the slow tail following IPSC peak demonstrated a remarkable temporal summation and was not modified by CGP55845 or extracellular Ca2+ increase. This result shows that tonic activation of presynaptic GABA(B) receptors by ambient GABA selectively regulates the onset of inhibition bearing potential consequences for the dynamic regulation of signal transmission through the mossy fibergranule cell pathway of the cerebellum
Spontaneous and Perturbational Complexity in Cortical Cultures
No full textDissociated cortical neurons in vitro display spontaneously synchronized, low-frequency firing patterns, which can resemble the slow wave oscillations characterizing sleep in vivo. Experiments in humans, rodents, and cortical slices have shown that awakening or the administration of activating neuromodulators decrease slow waves, while increasing the spatio-temporal complexity of responses to perturbations. In this study, we attempted to replicate those findings using in vitro cortical cultures coupled with micro-electrode arrays and chemically treated with carbachol (CCh), to modulate sleep-like activity and suppress slow oscillations. We adapted metrics such as neural complexity (NC) and the perturbational complexity index (PCI), typically employed in animal and human brain studies, to quantify complexity in simplified, unstructured networks, both during resting state and in response to electrical stimulation. After CCh administration, we found a decrease in the amplitude of the initial response and a marked enhancement of the complexity during spontaneous activity. Crucially, unlike in cortical slices and intact brains, PCI in cortical cultures displayed only a moderate increase. This dissociation suggests that PCI, a measure of the complexity of causal interactions, requires more than activating neuromodulation and that additional factors, such as an appropriate circuit architecture, may be necessary. Exploring more structured in vitro networks, characterized by the presence of strong lateral connections, recurrent excitation, and feedback loops, may thus help to identify the features that are more relevant to support causal complexity
A realistic large-scale model of the cerebellum granular layer predicts circuit spatio-temporal filtering properties
No full textThe way the cerebellar granular layer transforms incoming mossy fiber signals into new spike patterns to be related to Purkinje cells is not yet clear. Here, a realistic computational model of the granular layer was developed and used to address four main functional hypotheses: center-surround organization, time-windowing, high-pass filtering in responses to spike bursts and coherent oscillations in response to diffuse random activity. The model network was activated using patterns inspired by those recorded in vivo. Burst stimulation of a small mossy fiber bundle resulted in granule cell bursts delimited in time (time windowing) and space (center-surround) by network inhibition. This burst-burst transmission showed marked frequency-dependence configuring a high-pass filter with cut-off frequency around 100 Hz. The contrast between center and surround properties was regulated by the excitatory-inhibitory balance. The stronger excitation made the center more responsive to 10-50 Hz input frequencies and enhanced the granule cell output (with spikes occurring earlier and with higher frequency and number) compared to the surround. Finally, over a certain level of mossy fiber background activity, the circuit generated coherent oscillations in the theta-frequency band. All these processes were fine-tuned by NMDA and GABA-A receptor activation and neurotransmitter vesicle cycling in the cerebellar glomeruli. This model shows that available knowledge on cellular mechanisms is sufficient to unify the main functional hypotheses on the cerebellum granular layer and suggests that this network can behave as an adaptable spatio-temporal filter coordinated by theta-frequency oscillation
Exergaming for Autonomous Rehabilitation
No full textNovel gaming devices, like the Nintendo balance board and the Microsoft Kinect, have opened the possibility to do autonomous rehabilitation at home, where patients are guided by adequate video-games that are named therapeutic exer-games. To ensure safety and effectiveness, it has become soon evident that some form of supervision through technology itself is required. This has led to the development of a three-layers architecture designed inside the EC funded REWIRE project constituted of a hospital station (HS), a networking station (NS), and a patient station (PS). In this paper we define the challenges for the Patient Station and how these could be addressed. The PS is installed at patientâ€TMs home to guide him/her in the rehabilitation exercises through video-games designed to train a specific function. The PS is constituted of a classical game engine, on top of which several functions, specifically devoted to autonomous rehabilitation at home, have been added: configuration and real-time adaptation of the level of difficulty of the exer-games, monitoring the healthiness of motion pattern used by the patient, capability of interfacing different tracking device and log motion data. Moreover, a virtual therapist avatar has been fully integrated to maximize compliance, along with randomization of assets and background music
From dynamics to links: a sparse reconstruction of the topology of a neural network
No full textOne major challenge in neuroscience is the identification of interrelations between signals reflecting neural activity and how information processing occurs in the neural circuits. At the cellular and molecular level, mechanisms of signal transduction have been studied intensively and a better knowledge and understanding of some basic processes of information handling by neurons has been achieved. In contrast, little is known about the organization and function of complex neuronal networks. Experimental methods are now available to simultaneously monitor electrical activity of a large number of neurons in real time. Then, the qualitative and quantitative analysis of the spiking activity of individual neurons is a very valuable tool for the study of the dynamics and architecture of the neural networks. Such activity is not due to the sole intrinsic properties of the individual neural cells but it is mostly the consequence of the direct influence of other neurons. The deduction of the effective connectivity between neurons, whose experimental spike trains are observed, is of crucial importance in neuroscience: first for the correct interpretation of the electro-physiological activity of the involved neurons and neural networks, and, for correctly relating the electrophysiological activity to the functional tasks accomplished by the network. In this work, we propose a novel method for the identification of connectivity of neural networks using recorded voltages. Our approach is based on the assumption that the network has a topology with sparse connections. After a brief description of our method, we will report the performances and compare it to the cross-correlation computed on the spike trains, which represents a gold standard method in the field
CAV2.1 EF-HAND SPLICE ISOFORMS DIFFERENTIALLY AFFECT NEUROTRANSMITTER RELEASE AND SHORT-TERM SYNAPTIC PLASTICITY
No full textHierarchical electrochemical modeling and simulation of bio-hybrid interfaces
No full textIn this article we propose and investigate a hierarchy of mathematical models based on partial differential equations (PDE)
and ordinary differential equations (ODE) for the simulation of the biophysical phenomena occurring in the electrolyte fluid that
connects a biological component (a single cell or a system of cells) and a solid-state device (a single silicon transistor or an array
of transistors). The three members of the hierarchy, ordered by decreasing complexity, are: (i) a 3D Poisson–Nernst–Planck (PNP)
PDE system for ion concentrations and electric potential; (ii) a 2D reduced PNP system for the same dependent variables as in
(i); (iii) a 2D area-contact PDE system for electric potential coupled with a system of ODEs for ion concentrations. The backward
Euler method is adopted for temporal semi-discretization and a fixed-point iteration based on Gummel’s map is used to decouple
system equations. Spatial discretization is performed using piecewise linear triangular finite elements stabilized via edge-based
exponential fitting. Extensively conducted simulation results are in excellent agreement with existing analytical solutions of the
PNP problem in radial coordinates and experimental and simulated data using simplified lumped parameter models
Compartmentalized expression of P/Q-type Ca2+ channel splice isoforms shapes short-term synaptic plasticity
No full textLetter, [Author unclear] to Paulina T. Merritt
No full textHandwritten letter to Paulina Merritt from an unknown author, October 1, 1876.
Recurrently connected and localized neuronal communities initiate coordinated spontaneous activity in neuronal networks.
No full textDeveloping neuronal systems intrinsically generate coordinated spontaneous activity that propagates by involving a large number of synchronously firing neurons. In vivo, waves of spikes transiently characterize the activity of developing brain circuits and are fundamental for activity-dependent circuit formation. In vitro, coordinated spontaneous spiking activity, or network bursts (NBs), interleaved within periods of asynchronous spikes emerge during the development of 2D and 3D neuronal cultures. Several studies have investigated this type of activity and its dynamics, but how a neuronal system generates these coordinated events remains unclear. Here, we investigate at a cellular level the generation of network bursts in spontaneously active neuronal cultures by exploiting high-resolution multielectrode array recordings and computational network modelling. Our analysis reveals that NBs are generated in specialized regions of the network (functional neuronal communities) that feature neuronal links with high cross-correlation peak values, sub-millisecond lags and that share very similar structural connectivity motifs providing recurrent interactions. We show that the particular properties of these local structures enable locally amplifying spontaneous asynchronous spikes and that this mechanism can lead to the initiation of NBs. Through the analysis of simulated and experimental data, we also show that AMPA currents drive the coordinated activity, while NMDA and GABA currents are only involved in shaping the dynamics of NBs. Overall, our results suggest that the presence of functional neuronal communities with recurrent local connections allows a neuronal system to generate spontaneous coordinated spiking activity events. As suggested by the rules used for implementing our computational model, such functional communities might naturally emerge during network development by following simple constraints on distance-based connectivity
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