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Idan Segev

Publications and source records attributed to Idan Segev.

13 recordsLinked to original sources
PubMed2006

The endurance and selectivity of spatial patterns of long-term potentiation/depression in dendrites under homeostatic synaptic plasticity.

We investigated analytically and numerically the interplay between two opposing forms of synaptic plasticity: positive-feedback, long-term potentiation/depression (LTP/LTD), and negative-feedback, homeostatic synaptic plasticity (HSP). A detailed model of a CA1 pyramidal neuron, with numerous HSP-modifiable dendritic synapses, demonstrates that HSP may have an important role in selecting which spatial patterns of LTP/LTD are to last. Several measures are developed for predicting the net residual potentiation/depression after HSP from the initial spatial pattern of LTP/LTD. Under a local dendritic HSP mechanism, sparse patterns of LTP/LTD, which we show, using information theoretical tools, to have a significant impact on the output of the postsynaptic neuron, will persist. In contrast, spatially clustered patterns with a smaller impact on the output will diminish. A global somatic HSP mechanism, conversely, will favor distally occurring LTP/LTDs over proximal ones. Despite the negative-feedback nature of HSP, under both local and global HSP, numerous synaptic potentiations/depressions can persist. These experimentally testable results imply that HSP could be significantly involved in shaping the spatial distribution of synaptic weights in the dendrites and not just normalizing it, as is currently believed.

Dendrites↗
PubMed2006

The interplay between homeostatic synaptic plasticity and functional dendritic compartments.

Homeostatic synaptic plasticity (HSP) is an important mechanism attributed with the slow regulation of the neuron's activity. Whenever activity is chronically enhanced, HSP weakens the weights of the synapses in the dendrites and vice versa. Because dendritic morphology and its electrical properties partition the dendritic tree into functional compartments, we set out to explore the interplay between HSP and dendritic compartmentalization. For this purpose, we used a detailed model of a CA1 pyramidal neuron receiving a large number of activity-dependent plastic synapses and developed a novel approach for specifying functional dendritic subunits. We found that the degree of dendritic compartmentalization and the location-specificity of HSP are strongly tied. A local HSP mechanism, operating at the level of the individual synapse, will regard the neuron as a multiunit distributed system, each unit consisting of many synapses, and will thus support dendritic compartmentalization, whereas a global HSP mechanism, modifying all synapses in unison, will treat the neuron as a single centralized unit. Both local and global HSP can successfully counterbalance persistent, cell-wide perturbations of dendritic activity. The spatial distribution of synaptic weights throughout the dendrites will markedly differ under the local versus global HSP mechanisms. We suggest an experimental paradigm to unravel which type of HSP mechanism operates in the dendritic tree. The answer to this question will have important implications to our understanding of the functional organization of the neuron.

Animals↗
PubMed2006

Spike propagation in dendrites with stochastic ion channels.

We investigate the effects of the stochastic nature of ion channels on the faithfulness, precision and reproducibility of electrical signal transmission in weakly active, dendritic membrane under in vitro conditions. The properties of forward and backpropagating action potentials (BPAPs) in the dendritic tree of pyramidal cells are the subject of intense empirical work and theoretical speculation (Larkum et al., 1999; Zhu, 2000; Larkum et al., 2001; Larkum and Zhu, 2002; Schaefer et al., 2003; Williams, 2004; Waters et al., 2005). We numerically simulate the effects of stochastic ion channels on the forward and backward propagation of dendritic spikes in Monte-Carlo simulations on a reconstructed layer 5 pyramidal neuron. We report that in most instances there is little variation in timing or amplitude for a single BPAP, while variable backpropagation can occur for trains of action potentials. Additionally, we find that the generation and forward propagation of dendritic Ca(2+) spikes are susceptible to channel variability. This indicates limitations on computations that depend on the precise timing of Ca(2+) spikes.

Action Potentials↗
PubMed2006

What do dendrites and their synapses tell the neuron?

This essay looks at the historical significance of four APS classic papers that are freely available online: Rall W. Distinguishing theoretical synaptic potentials computed for different soma-dendritic distributions of synaptic input. J Neurophysiol 30: 1138-1168, 1967 (http://jn.physiology.org/cgi/reprint/30/5/1138). Rall W, Burke RE, Smith TG, Nelson PG, and Frank K. Dendritic location of synapses and possible mechanisms for the monosynaptic EPSP in motoneurons. J Neurophysiol 30: 1169-1193, 1967 (http://jn.physiology.org/cgi/reprint/30/5/1169). Rall W and Shepherd GM. Theoretical reconstruction of field potentials and dendrodendritic synaptic interactions in olfactory bulb. J Neurophysiol 31: 884-915, 1968 (http://jn.physiology.org/cgi/reprint/31/6/884). Segev I and Rall W. Computational study of an excitable dendritic spine. J Neurophysiol 60: 499-523, 1988 (http://jn.physiology.org/cgi/reprint/60/2/499).

Dendrites↗
PubMed2005

Depressed responses of facilitatory synapses.

We show that when temporal summation takes place, depression of postsynaptic responses may ensue when the underlying synaptic conductance change is constant or even facilitatory. We term this phenomenon "apparent depression." Such apparent depression is most notable for slow synaptic conductance changes, for high frequency, and when the synapse is located at distal dendritic sites. We show that, when temporal summation ensues, the erroneous estimation of short-term synaptic plasticity arises partially from the conventional measurement of synaptic dynamics at postsynaptic potential peak time. This can be corrected when measuring overlapping synaptic responses at fixed intervals after stimulus time. Somatic voltage clamp also helps to partially correct for the apparent depression, but a good model of the neuron can do even better in providing a more accurate view of the underlying synaptic conductances.

Action Potentials↗
PubMed2005

Subthreshold voltage noise of rat neocortical pyramidal neurones.

Neurones are noisy elements. Noise arises from both intrinsic and extrinsic sources, and manifests itself as fluctuations in the membrane potential. These fluctuations limit the accuracy of a neurone's output but have also been suggested to play a computational role. We present a detailed study of the amplitude and spectrum of voltage noise recorded at the soma of layer IV-V pyramidal neurones in slices taken from rat neocortex. The dependence of the noise on holding potential, synaptic activity and Na+ conductance is systematically analysed. We demonstrate that voltage noise increases non-linearly as the cell depolarizes (from a standard deviation (s.d.) of 0.19 mV at -75 mV to an s.d. of 0.54 mV at -55 mV). The increase in voltage noise is accompanied by an increase in the cell impedance, due to voltage dependence of Na+ conductance. The impedance increase accounts for the majority (70%) of the voltage noise increase. The increase in voltage noise and impedance is restricted to the low-frequency range (0.2-2 Hz). At the high frequency range (5-100 Hz) the voltage noise is dominated by synaptic activity. In our slice preparation, synaptic noise has little effect on the cell impedance. A minimal model reproduces qualitatively these data. Our results imply that ion channel noise contributes significantly to membrane voltage fluctuations at the subthreshold voltage range, and that Na+ conductance plays a key role in determining the amplitude of this noise by acting as a voltage-dependent amplifier of low-frequency transients.

Animals↗
PubMed2004

Multiple mechanisms govern the dynamics of depression at neocortical synapses of young rats.

Synaptic transmission between pairs of excitatory neurones in layers V (N= 38) or IV (N= 6) of somatosensory cortex was examined in a parasagittal slice preparation obtained from young Wistar rats (14-18 days old). A combined experimental and theoretical approach reveals two characteristics of short-term synaptic depression. Firstly, as well as a release-dependent depression, there is a release-independent component that is evident in smaller postsynaptic responses even following failure to release transmitter. Secondly, recovery from depression is activity dependent and is faster at higher input frequencies. Frequency-dependent recovery is a Ca(2+)-dependent process and does not reflect an underlying augmentation. Frequency-dependent recovery and release-independent depression are correlated, such that at those connections with a large amount of release-independent depression, recovery from depression is faster. In addition, both are more pronounced in experiments performed at physiological temperatures. Simulations demonstrate that these homeostatic properties allow the transfer of rate information at all frequencies, essentially linearizing synaptic responses at high input frequencies.

Animals↗
PubMed2003

On the transmission of rate code in long feedforward networks with excitatory-inhibitory balance.

The capability of feedforward networks composed of multiple layers of integrate-and-fire neurons to transmit rate code was examined. Synaptic connections were made only from one layer to the next, and excitation was balanced by inhibition. When time is discrete and the synaptic potentials rise instantaneously, we show that, for random uncorrelated input to layer one, the mean rate of activity in deep layers is essentially independent of input firing rate. This implies that the input rate cannot be transmitted reliably in such feedforward networks because neurons in a given layer tend to synchronize partially with each other because of shared inputs. As a result of this synchronization, the average firing rate in deep layers will either decay to zero or reach a stable fixed point, depending on model parameters. When time is treated continuously and the synaptic potentials rise instantaneously, these effects develop slowly, and rate transmission over a limited number of layers is possible. However, the correlations among neurons at the same layer hamper reliable assessment of firing rate by averaging over 100 msec (or less). When the synaptic potentials develop gradually, as is the realistic case, transmission of rate code fails. In a network in which inhibition only balances the mean excitation but is not timed precisely with it, neurons in each layer fire together, and this volley successively propagates from layer to layer. We conclude that the transmission of rate code in feedforward networks is highly unlikely.

Animals↗
PubMed2002

Playing the devil's advocate: is the Hodgkin-Huxley model useful?

Hodgkin and Huxley (H-H) model for action potential generation has held firm for half a century because this relatively simple and experimentally testable model embodies the major features of membrane nonlinearity: namely, voltage-dependent ionic currents that activate and inactivate in time. However, experimental and theoretical developments of the past 20 years force one to re-evaluate its usefulness. First, the H-H model is, in its original form, limited to the two voltage-dependent currents found in the squid giant axon and it must be extended significantly if it is to deal with the excitable soma and dendrites of neurons. Second, the macroscopic and deterministic H-H model does not capture correctly the kinetics of the Na(+) channel and it cannot account for the stochastic response to current injection that arises from the discrete nature of ion channels. Third, much simpler integrate-and-fire-type models seem to be more useful for exploring collective phenomena in neuronal networks. Is the H-H model threatened, or will it continue to set the fundamental framework for exploring neuronal excitability?

Action Potentials↗
PubMed2002

The information efficacy of a synapse.

We provide a functional measure, the synaptic information efficacy (SIE), to assess the impact of synaptic input on spike output. SIE is the mutual information shared by the presynaptic input and postsynaptic output spike trains. To estimate SIE we used a method based on compression algorithms. This method detects the effect of a single synaptic input on the postsynaptic spike output in the presence of massive background synaptic activity in neuron models of progressively increasing realism. SIE increased with increases either in time locking between the input synapse activity and the output spike or in the average number of output spikes. SIE depended on the context in which the synapse operates. We also measured SIE experimentally. Systematic exploration of the effect of synaptic and dendritic parameters on the SIE offers a fresh look at the synapse as a communication device and a quantitative measure of how much the dendritic synapse informs the axon.

Action Potentials↗
PubMed2002

Coding of temporal information by activity-dependent synapses.

Synaptic transmission in the neocortex is dynamic, such that the magnitude of the postsynaptic response changes with the history of the presynaptic activity. Therefore each response carries information about the temporal structure of the preceding presynaptic input spike train. We quantitatively analyze the information about previous interspike intervals, contained in single responses of dynamic synapses, using methods from information theory applied to experimentally based deterministic and probabilistic phenomenological models of depressing and facilitating synapses. We show that for any given dynamic synapse, there exists an optimal frequency of presynaptic spike firing for which the information content is maximal; simple relations between this optimal frequency and the synaptic parameters are derived. Depressing neocortical synapses are optimized for coding temporal information at low firing rates of 0.5-5 Hz, typical to the spontaneous activity of cortical neurons, and carry significant information about the timing of up to four preceding presynaptic spikes. Facilitating synapses, however, are optimized to code information at higher presynaptic rates of 9-70 Hz and can represent the timing of over eight presynaptic spikes.

Action Potentials↗