Similar network activity from disparate circuit parameters

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

It is often assumed that cellular and synaptic properties need to be regulated to specific values to allow a neuronal network to function properly. To determine how tightly neuronal properties and synaptic strengths need to be tuned to produce a given network output, we simulated more than 20 million versions of a three-cell model of the pyloric network of the crustacean stomatogastric ganglion using different combinations of synapse strengths and neuron properties. We found that virtually indistinguishable network activity can arise from widely disparate sets of underlying mechanisms, suggesting that there could be considerable animal-to-animal variability in many of the parameters that control network activity, and that many different combinations of synaptic strengths and intrinsic membrane properties can be consistent with appropriate network performance.

Related collections

Most cited references 37

Record: found
Abstract: found
Article: not found

Altered electrical properties in Drosophila neurons developing without synaptic transmission.

Richard Baines, Jay P. Uhler, Annemarie Thompson … (2001)

We examine the role of synaptic activity in the development of identified Drosophila embryonic motorneurons. Synaptic activity was blocked by both pan-neuronal expression of tetanus toxin light chain (TeTxLC) and by reduction of acetylcholine (ACh) using a temperature-sensitive allele of choline acetyltransferase (Cha(ts2)). In the absence of synaptic activity, aCC and RP2 motorneurons develop with an apparently normal morphology and retain their capacity to form synapses. However, blockade of synaptic transmission results in significant changes in the electrical phenotype of these neurons. Specifically, increases are seen in both voltage-gated inward Na(+) and voltage-gated outward K(+) currents. Voltage-gated Ca(2+) currents do not change. The changes in conductances appear to promote neuron excitability. In the absence of synaptic activity, the number of action potentials fired by a depolarizing ramp (-60 to +60 mV) is increased and, in addition, the amplitude of the initial action potential fired is also significantly larger. Silencing synaptic input to just aCC, without affecting inputs to other neurons, demonstrates that the capability to respond to changing levels of synaptic excitation is intrinsic to these neurons. The alteration to electrical properties are not permanent, being reversed by restoration of normal synaptic function. Whereas our data suggest that synaptic activity makes little or no contribution to the initial formation of embryonic neural circuits, the electrical development of neurons that constitute these circuits seems to depend on a process that requires synaptic activity.

0 comments Cited 199 times – based on 0 reviews      Review now

Record: found
Abstract: found
Article: not found

Hebb and homeostasis in neuronal plasticity.

G G Turrigiano, Peter Nelson (2000)

The positive-feedback nature of Hebbian plasticity can destabilize the properties of neuronal networks. Recent work has demonstrated that this destabilizing influence is counteracted by a number of homeostatic plasticity mechanisms that stabilize neuronal activity. Such mechanisms include global changes in synaptic strengths, changes in neuronal excitability, and the regulation of synapse number. These recent studies suggest that Hebbian and homeostatic plasticity often target the same molecular substrates, and have opposing effects on synaptic or neuronal properties. These advances significantly broaden our framework for understanding the effects of activity on synaptic function and neuronal excitability.

0 comments Cited 149 times – based on 0 reviews      Review now

Record: found
Abstract: found
Article: not found

Alternative to hand-tuning conductance-based models: construction and analysis of databases of model neurons.

Eve Marder, Astrid A. Prinz, Cyrus Billimoria (2003)

Conventionally, the parameters of neuronal models are hand-tuned using trial-and-error searches to produce a desired behavior. Here, we present an alternative approach. We have generated a database of about 1.7 million single-compartment model neurons by independently varying 8 maximal membrane conductances based on measurements from lobster stomatogastric neurons. We classified the spontaneous electrical activity of each model neuron and its responsiveness to inputs during runtime with an adaptive algorithm and saved a reduced version of each neuron's activity pattern. Our analysis of the distribution of different activity types (silent, spiking, bursting, irregular) in the 8-dimensional conductance space indicates that the coarse grid of conductance values we chose is sufficient to capture the salient features of the distribution. The database can be searched for different combinations of neuron properties such as activity type, spike or burst frequency, resting potential, frequency-current relation, and phase-response curve. We demonstrate how the database can be screened for models that reproduce the behavior of a specific biological neuron and show that the contents of the database can give insight into the way a neuron's membrane conductances determine its activity pattern and response properties. Similar databases can be constructed to explore parameter spaces in multicompartmental models or small networks, or to examine the effects of changes in the voltage dependence of currents. In all cases, database searches can provide insight into how neuronal and network properties depend on the values of the parameters in the models.