Activity-Dependent Regulation of Conductances in Model Neurons

Lemasson, Gwendal; Marder, Eve; Abbott, L. F.

doi:10.1126/science.8456317

Cited by 302 publications

(290 citation statements)

References 18 publications

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“…This question is particularly interesting in the light of recent experimental and theoretical studies of homeostasis of cellular and synaptic properties in the nervous system (Stemmler and Koch, 1999;Turrigiano, 1999;Marder and Prinz, 2002;Turrigiano and Nelson, 2004). These studies suggest that the intrinsic excitability of single neurons and synaptic strengths are subject to slow homeostatic regulation that can stabilize neuronal function despite ongoing turnover of channels and receptors (LeMasson et al, 1993;Turrigiano et al, 1995;Davis and Goodman, 1998;Liu et al, 1998;Desai et al, 1999;Golowasch et al, 1999a,b;Davis and Bezprozvanny, 2001;Aizenman et al, 2003;MacLean et al, 2003;Zhang and Linden, 2003). However, what really matters for the animal is not what the properties of single neurons are or how strong single synapses may be, but how the network performs.…”

Section: Introductionmentioning

confidence: 99%

“…There is experimental evidence that stability of pyloric neuron activity results from activity-dependent homeostatic regulation, both at the level of single neurons (Turrigiano et al, 1994), and on the network level Simmers, 1998, 2000;Golowasch et al, 1999b;Luther et al, 2003). Previous theoretical work has shown that simple homeostatic rules in which Ca 2ϩ concentrations are used to track activity patterns can regulate both intrinsic properties and synaptic strengths (LeMasson et al, 1993;Liu et al, 1998;Golowasch et al, 1999b;Soto-Trevino et al, 2001).…”

Section: Stability Of Network Output With Different Network Configuramentioning

confidence: 99%

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Animal-to-Animal Variability in Motor Pattern Production in Adults and during Growth

Bucher¹,

Prinz²,

Marder³

2005

J. Neurosci.

176

196

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Which features of network output are well preserved during growth of the nervous system and across different preparations of the same size? To address this issue, we characterized the pyloric rhythms generated by the stomatogastric nervous systems of 99 adult and 12 juvenile lobsters (Homarus americanus). Anatomical studies of single pyloric network neurons and of the whole stomatogastric ganglion (STG) showed that the STG and its neurons grow considerably from juvenile to adult. Despite these changes in size, intracellularly recorded membrane potential waveforms of pyloric network neurons and the phase relationships in the pyloric rhythm were very similar between juvenile and adult preparations. Across adult preparations, the cycle period and number of spikes per burst were not tightly maintained, but the mean phase relationships were independent of the period of the rhythm and relatively tightly maintained across preparations. We interpret this as evidence for homeostatic regulation of network activity.

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Section: Introductionmentioning

confidence: 99%

Section: Stability Of Network Output With Different Network Configuramentioning

confidence: 99%

Animal-to-Animal Variability in Motor Pattern Production in Adults and during Growth

Bucher¹,

Prinz²,

Marder³

2005

J. Neurosci.

176

196

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show abstract

“…If channel densities are functionally linked to neuronal activity, as suggested by modeling studies (LeMasson et al 1993;Liu et al 1998), it can be imagined that activity bouts arise as channel densities are altered. An incremental change in one or more membrane conductance may allow a temporary resumption of the pyloric rhythm, but further changes in membrane conductances could result in the network falling silent again.…”

Section: Bout Propertiesmentioning

confidence: 99%

Episodic Bouts of Activity Accompany Recovery of Rhythmic Output By a Neuromodulator- and Activity-Deprived Adult Neural Network

Luther

Robie

Yarotsky

et al. 2003

Journal of Neurophysiology

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. Episodic bouts of activity accompany recovery of rhythmic output by a neuromodulator-and activity-deprived adult neural network. J Neurophysiol 90: 2720 -2730, 2003. First published July 2, 2003 10.1152/jn.00370.2003. The pyloric rhythm of the stomatogastric ganglion of the crab, Cancer borealis, slows or stops when descending modulatory inputs are acutely removed. However, the rhythm spontaneously resumes after one or more days in the absence of neuromodulatory input. We recorded continuously for days to characterize quantitatively this recovery process. Activity bouts lasting 40 -900 s began several hours after removal of neuromodulatory input and were followed by stable rhythm recovery after 1-4 days. Bout duration was not related to the intervals (0.3-800 min) between bouts. During an individual bout, the frequency rapidly increased and then decreased more slowly. Photoablation of back-filled neuromodulatory terminals in the stomatogastric ganglion (STG) neuropil had no effect on activity bouts or recovery, suggesting that these processes are intrinsic to the STG neuronal network. After removal of neuromodulatory input, the phase relationships of the components of the triphasic pyloric rhythm were altered, and then over time the phase relationships moved toward their control values. Although at low pyloric rhythm frequency the phase relationships among pyloric network neurons depended on frequency, the changes in frequency during recovery did not completely account for the change in phase seen after rhythm recovery. We suggest that activity bouts represent underlying mechanisms controlling the restructuring of the pyloric network to allow resumption of an appropriate output after removal of neuromodulatory input.

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“…These are often understood in terms of context-and history-dependent slow modulations of neural response parameters. Several underlying molecular mechanisms support these modulations in an activity-dependent manner (LeMasson et al, 1993;van Ooyen, 1994;Marom, 1998;Wang, 1998;Carr et al, 2003). Such mechanisms are usually understood to operate by adding uniquely defined slow time scales (Marom and Abbot, 1994;Fleidervish et al, 1996;Kim and Rieke, 2003) and cannot capture multiple-time-scale dynamics.…”

Section: Introductionmentioning

confidence: 99%

History-Dependent Multiple-Time-Scale Dynamics in a Single-Neuron Model

Gilboa¹,

Chen²,

Brenner³

2005

J. Neurosci.

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History-dependent characteristic time scales in dynamics have been observed at several levels of organization in neural systems. Such dynamics can provide powerful means for computation and memory. At the level of the single neuron, several microscopic mechanisms, including ion channel kinetics, can support multiple-time-scale dynamics. How the temporally complex channel kinetics gives rise to dynamical properties of the neuron is not well understood. Here, we construct a model that captures some features of the connection between these two levels of organization. The model neuron exhibits history-dependent multiple-time-scale dynamics in several effects: first, after stimulation, the recovery time scale is related to the stimulation duration by a power-law scaling; second, temporal patterns of neural activity in response to ongoing stimulation are modulated over time; finally, the characteristic time scale for adaptation after a step change in stimulus depends on the duration of the preceding stimulus. All these effects have been observed experimentally and are not explained by current single-neuron models. The model neuron here presented is composed of an ensemble of ion channels that can wander in a large pool of degenerate inactive states and thus exhibits multiple-time-scale dynamics at the molecular level. Channel inactivation rate depends on recent neural activity, which in turn depends through modulations of the neural response function on the fraction of active channels. This construction produces a model that robustly exhibits nonexponential history-dependent dynamics, in qualitative agreement with experimental results.

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Activity-Dependent Regulation of Conductances in Model Neurons

Cited by 302 publications

References 18 publications

Animal-to-Animal Variability in Motor Pattern Production in Adults and during Growth

Animal-to-Animal Variability in Motor Pattern Production in Adults and during Growth

Episodic Bouts of Activity Accompany Recovery of Rhythmic Output By a Neuromodulator- and Activity-Deprived Adult Neural Network

History-Dependent Multiple-Time-Scale Dynamics in a Single-Neuron Model

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