Biomedical subjects

P Varona

Publications and source records attributed to P Varona.

11 recordsLinked to original sources

PubMed2003

Dual sensory-motor function for a molluskan statocyst network.

In mollusks, statocyst receptor cells (SRCs) interact with each other forming a neural network; their activity is determined by both the animal's orientation in the gravitational field and multimodal inputs. These two facts suggest that the function of the statocysts is not limited to sensing the animal's orientation. We studied the role of the statocysts in the organization of search motion during hunting behavior in the marine mollusk, Clione limacina. When hunting, Clione swims along a complex trajectory including numerous twists and turns confined within a definite space. Search-like behavior could be evoked pharmacologically by physostigmine; application of physostigmine to the isolated CNS produced "fictive search behavior" monitored by recordings from wing and tail nerves. Both in behavioral and in vitro experiments, we found that the statocysts are necessary for search behavior. The motor program typical of searching could not be produced after removing the statocysts. Simultaneous recordings from single SRCs and motor nerves showed that there was a correlation between the SRCs activity and search episodes. This correlation occurred even though the preparation was fixed and, therefore the sensory stimulus was constant. The excitation of individual SRCs could in some cases precede the beginning of search episodes. A biologically based model showed that, theoretically, the hunting search motor program could be generated by the statocyst receptor network due to its intrinsic dynamics. The results presented support for the idea that the statocysts are actively involved in the production of the motor program underlying search movements during hunting behavior.

Action Potentials↗

PubMed2002

Structural inhomogeneities differentially modulate action currents and population spikes initiated in the axon or dendrites.

Action potentials (APs) in CA1 pyramidal cells propagate in different directions along the somatodendritic axis depending on the activation mode (synaptic or axonal). We studied how the geometrical inhomogeneities along the apical shaft, soma, and initial axon modulate the transmembrane current (I(m)) flow underlying APs, using model and experimental techniques. The computations obtained at the subcellular level during forward- and backpropagation were extrapolated to macroscopic level (field potentials) and compared with the basic in vivo features of the ortho- and antidromic population spike (PS) that reflects the sum total of all elementary currents from synchronously firing cells. The matching of theoretical and experimental results supports the following conclusions. Because the charge carried by axonal APs is almost entirely drained into dendrites, the soma invasion is preceded by little capacitive currents (I(cap)), the ionic currents (I(ion)) dominating I(m) and the depolarizing phase. The subsequent invasion of the tapering apical shaft is preceded, however, by significant I(cap), while I(ion) decayed gradually. A similar pattern occurred during backpropagation of spikes synaptically initiated in the axon. On the contrary, when the AP was apically initiated, the dendritic I(ion) was boosted by the apical flare, it was preceded by weak I(cap) and spread forwardly at a slower velocity. Soma invasion is reliable once the AP reached the main apical shaft but less so distal to the primary bifurcation, where it may be upheld by concurrent synaptic activity. The decreasing internal resistance of the apical shaft guided most axial current into the soma, causing its fast charging. There, I(ion) began later in the depolarizing phase of the AP and the reduced driving force made it smaller. This, in addition to a poor temporal overlapping of somatodendritic inward currents within individual cells, built a smaller extracellular sink, i.e., a smaller PS. In both experiment and model, the antidromic (axon-initiated) PS in the soma layer is approximately 30% larger than an orthodromic (apical shaft-initiated) PS contributed by the same number of firing cells. We conclude that the dominance of capacitive or ionic current components on I(m) is a distinguishing feature of forward and backward APs that is predictable from the geometric inhomogeneities between conducting subregions. Correspondingly, experimental and model APs have a faster rising slope during ortho than antidromic activation. The moderate flare of the apical shaft makes forward AP conduction quite safe. This alternative trigger zone enables two different processing modes for apical inputs.

Action Potentials↗

PubMed2001

Topology selection by chaotic neurons of a pyloric central pattern generator.

The pyloric Central Pattern Generator (CPG) in the lobster has an architecture in which every neuron receives at least one connection from another member of the CPG. We call this a "non-open" network topology. An "open" topology, where at least one neuron does not receive synapses from any other CPG member, is found neither in the pyloric nor in the gastric mill CPG. Here we investigate a possible reason for this topological structure using the ability to perform a biologically functional task as a measure of the efficacy of the network. When the CPG is composed of model neurons that exhibit regular membrane voltage oscillations, open topologies are as able to maximize this functionality as non-open topologies. When we replace these models by neurons which exhibit chaotic membrane voltage oscillations, the functional criterion selects non-open topologies. As isolated neurons from invertebrate CPGs are known in some cases to undergo chaotic oscillations, this suggests that there is a biological basis for the class of non-open network topologies that we observe.

Animals↗

PubMed2001

Dynamics of two electrically coupled chaotic neurons: experimental observations and model analysis.

Conductance-based models of neurons from the lobster stomatogastric ganglion (STG) have been developed to understand the observed chaotic behavior of individual STG neurons. These models identify an additional slow dynamical process calcium exchange and storage in the endoplasmic reticulum as a biologically plausible source for the observed chaos in the oscillations of these cells. In this paper we test these ideas further by exploring the dynamical behavior when two model neurons are coupled by electrical or gap junction connections. We compare in detail the model results to the laboratory measurements of electrically-coupled neurons that we reported earlier. The experiments on the biological neurons varied the strength of the effective coupling by applying a parallel, artificial synapse, which changed both the magnitude and polar-of the conductance between the neurons. We observed a sequence of bifarctions that took the neurons from strongly synchronized in-phase behavior. through uncorrelated chaotic oscillations to strongly synchronized and now regular out-of-phase behavior. The model calculations reproduce these observations quantitatively, indicating that slow subcellular processes could account for the mechanisms involved in the synchronization and regularization of the otherwise individual chaotic activities.

Animals↗

PubMed2000

Interacting biological and electronic neurons generate realistic oscillatory rhythms.

Small assemblies of neurons such as central pattern generators (CPG) are known to express regular oscillatory firing patterns comprising bursts of action potentials. In contrast, individual CPG neurons isolated from the remainder of the network can generate irregular firing patterns. In our study of cooperative behavior in CPGs we developed an analog electronic neuron (EN) that reproduces firing patterns observed in lobster pyloric CPG neurons. Using a tuneable artificial synapse we connected the EN bidirectionally to neurons of this CPG. We found that the periodic bursting oscillation of this mixed assembly depends on the strength and sign of the electrical coupling. Working with identified, isolated pyloric CPG neurons whose network rhythms were impaired, the EN/biological network restored the characteristic CPG rhythm both when the EN oscillations are regular and when they are irregular.

Action Potentials↗

PubMed2000

Synchronous behavior of two coupled electronic neurons.

We report on experimental studies of synchronization phenomena in a pair of analog electronic neurons (ENs). The ENs were designed to reproduce the observed membrane voltage oscillations of isolated biological neurons from the stomatogastric ganglion of the California spiny lobster Panulirus interruptus. The ENs are simple analog circuits which integrate four-dimensional differential equations representing fast and slow subcellular mechanisms that produce the characteristic regular/chaotic spiking-bursting behavior of these cells. In this paper we study their dynamical behavior as we couple them in the same configurations as we have done for their counterpart biological neurons. The interconnections we use for these neural oscillators are both direct electrical connections and excitatory and inhibitory chemical connections: each realized by analog circuitry and suggested by biological examples. We provide here quantitative evidence that the ENs and the biological neurons behave similarly when coupled in the same manner. They each display well defined bifurcations in their mutual synchronization and regularization. We report briefly on an experiment on coupled biological neurons and four-dimensional ENs, which provides further ground for testing the validity of our numerical and electronic models of individual neural behavior. Our experiments as a whole present interesting new examples of regularization and synchronization in coupled nonlinear oscillators.

Animals↗

PubMed2000

Macroscopic and subcellular factors shaping population spikes.

Population spikes (PS) are built by the extracellular summation of action currents during synchronous action potential (AP) firing. In the hippocampal CA1, active dendritic invasion of APs ensures mixed contribution of somatic and dendritic currents to any extracellular location. We investigated the macroscopic and subcellular factors shaping the antidromic PS by fitting its spatiotemporal map with a multineuronal CA1 model in a volume conductor. Decreased summation by temporal scatter of APs reduced less than expected the PS peak in the stratum pyramidale (st. pyr.) but strongly increased the relative contribution of far dendritic currents. Increasing the number of firing cells also augmented the relative dendritic contribution to the somatic PS, an effect caused by the different waveform of somatic and dendritic unitary transmembrane currents (I(m)). Those from somata are short-lasting and spiky, having smaller temporal summation than those from dendrites, which are smoother and longer. The different shape of compartmental I(m)s is imposed by the fitting of backpropagating APs, which are large and fast at the soma and smaller and longer in dendrites. The maximum sodium conductance ((Na)) strongly affects the unitary APs at the soma, but barely the PS at the stratum pyramidale (st. pyr.). This occurred because somatic I(m) saturated at low (Na) due to the strong reduction of driving force during somatic APs, limiting the current contribution to the extracellular space. On the contrary, (Na) effectively defined the PS amplitude in the st. radiatum. The relative contribution of dendritic currents to the st. pyr. increases during the time span of the PS, from approximately 30-40% at the peak up to 100% at its end, a pattern resultant from the timing of active inward currents along the somatodendritic axis, which delay during backpropagation. Extreme changes imposed on dendritic currents caused only moderate effects on the st. pyr. due to reciprocal shunting of active soma and dendrites that partially counterbalance the net amount of instant current. The amplitude of the PS follows an inverse relation to the internal resistance (R(i)), which turned out to be a most critical factor. Low R(i) facilitated the spread of APs into dendrites and accelerated their speed, increasing temporal overlapping of inward currents along the somatodendritic axis and yielding the best PS reproductions. Model reconstruction of field potentials is a powerful tool to understand the interactions between different levels of complexity. The potential use of this approach to restrain the variability of some experimental measurements is discussed.

Action Potentials↗

PubMed1999

Expression and function of Gdf-5 during digit skeletogenesis in the embryonic chick leg bud.

Bone morphogenetic proteins (BMPs) constitute a large family of secreted signals involved in the formation of the skeleton but the specific function of each member of this family remains elusive. GDF-5 is a member of the BMP family which has been implicated in several skeletogenic events including the induction and growth of the appendicular cartilages, the determination of joint forming regions, and the establishment of tendons. Here, we have studied the function of GDF-5 in digit skeletogenesis by analyzing the effects of its local administration in the developing autopod of embryonic chick and the regulation of its pattern of gene expression by other signals involved in digit morphogenesis. As reported in the mouse, the gdf-5 gene exhibits a precise distribution in the joint-forming regions of the developing chicken digital rays. GDF-5 beads implanted at the tip of the digits promote intense cartilage growth and fail to induce morphological or molecular signs of joint formation. Furthermore, GDF-5 beads implanted in the interdigits inhibit the formation of joints in the adjacent digits. These data suggest that the role of GDF-5 in joint formation is the control of growth and differentiation of the cartilage of the epiphyseal regions of the phalanges rather than accounting for the differentiation of the sinovial joint tissues. The interdigital mesoderm in spite of its potential to form ectopic digits with their tendinous apparatus failed to form either ectopic cartilages or ectopic tendons after the implantation of GDF-5 beads in the stages preceding cell death. At difference with other BMPs, GDF-5 exhibited only a weak cell death promoting effect. The BMP antagonist Noggin binds to GDF-5 and is able to inhibit all the observed effects of this growth factor in vivo. Potential interactions of GDF-5 with other signals involved in digits morphogenesis were also explored. BMP-7 regulates negatively the expression of gdf-5 gene in the joint forming regions and local treatment with Noggin induces the ectopic expression of gdf-5 in the interdigital mesoderm. Retroviral-induced misexpression of Indian or Sonic Hedgehog genes in the developing digits leads to the formation of digits without joints in which gdf-5 expression occurs throughout the entire perichondrial surface. In conclusion, this study indicates that GDF-5 is a signal regulated by other BMPs which controls the growth and differentiation of the epiphyses of the digital cartilages acting in close relationship with Hedgehog signaling.

Animals↗

PubMed1999

Origin of coherent structures in a discrete chaotic medium.

Using as an example a large lattice of locally interacting Hindmarsh-Rose chaotic neurons, we disclose the origin of ordered structures in a discrete nonequilibrium medium with fast and slow chaotic oscillations. The origin of the ordering mechanism is related to the appearance of a periodic average dynamics in the group of chaotic neurons whose individual slow activity is significantly synchronized by the group mean field. Introducing the concept of a "coarse grain" as a cluster of neuron elements with periodic averaged behavior allows consideration of the dynamics of a medium composed of these clusters. A study of this medium reveals spatially ordered patterns in the periodic and slow dynamics of the coarse grains that are controlled by the average intensity of the fast chaotic pulsation.

Journal Article↗

PubMedDate not supplied

Regularization mechanisms of spiking-bursting neurons.

An essential question raised after the observation of highly variable bursting activity in individual neurons of Central Pattern Generators (CPGs) is how an assembly of such cells can cooperatively act to produce regular signals to motor systems. It is well known that some neurons in the lobster stomatogastric ganglion have a highly irregular spiking-bursting behavior when they are synaptically isolated from any connection in the CPG. Experimental recordings show that periodic stimuli on a single neuron can regulate its firing activity. Other evidence demonstrates that specific chemical and/or electrical synapses among neurons also induce the regularization of the rhythms. In this paper we present a modeling study in which a slow subcellular dynamics, the exchange of calcium between an intracellular store and the cytoplasm, is responsible for the origin and control of the irregular spiking-bursting activity. We show this in simulations of single cells under periodic driving and in minimal networks where the cooperative activity can induce regularization. While often neglected in the description of realistic neuron models, subcellular processes with slow dynamics may play an important role in information processing and short-term memory of spiking-bursting neurons.

Action Potentials↗

PubMedDate not supplied

Reliable circuits from irregular neurons: a dynamical approach to understanding central pattern generators.

Central pattern generating neurons from the lobster stomatogastric ganglion were analyzed using new nonlinear methods. The LP neuron was found to have only four or five degrees of freedom in the isolated condition and displayed chaotic behavior. We show that this chaotic behavior could be regularized by periodic pulses of negative current injected into the neuron or by coupling it to another neuron via inhibitory connections. We used both a modified Hindmarsh-Rose model to simulate the neurons behavior phenomenologically and a more realistic conductance-based model so that the modeling could be linked to the experimental observations. Both models were able to capture the dynamics of the neuron behavior better than previous models. We used the Hindmarsh-Rose model as the basis for building electronic neurons which could then be integrated into the biological circuitry. Such neurons were able to rescue patterns which had been disabled by removing key biological neurons from the circuit.

Animals↗