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I Segev

Publications and source records attributed to I Segev.

At least 19 recordsLinked to original sources
PubMed1999

Signal transfer in passive dendrites with nonuniform membrane conductance.

In recent years it became clear that dendrites possess a host of ion channels that may be distributed nonuniformly over their membrane surface. In cortical pyramids, for example, it was demonstrated that the resting membrane conductance G(m)(x) is higher (the membrane is "leakier") at distal dendritic regions than at more proximal sites. How does this spatial nonuniformity in G(m)(x) affect the input-output function of the neuron? The present study aims at providing basic insights into this question. To this end, we have analytically studied the fundamental effects of membrane non-uniformity in passive cable structures. Keeping the total membrane conductance over a given modeled structure fixed (i.e., a constant number of passive ion channels), the classical case of cables with uniform membrane conductance is contrasted with various nonuniform cases with the following general conclusions. (1) For cylindrical cables with "sealed ends," monotonic increase in G(m)(x) improves voltage transfer from the input location to the soma. The steeper the G(m)(x), the larger the improvement. (2) This effect is further enhanced when the stimulation is distal and consists of a synaptic input rather than a current source. (3) Any nonuniformity in G(m)(x) decreases the electrotonic length, L, of the cylinder. (4) The system time constant tau(0) is larger in the nonuniform case than in the corresponding uniform case. (5) When voltage transients relax with tau(0), the dendritic tree is not isopotential in the nonuniform case, at variance with the uniform case. The effect of membrane nonuniformity on signal transfer in reconstructed dendritic trees and on the I/f relation of the neuron is also considered, and experimental methods for assessing membrane nonuniformity in dendrites are discussed.

Animals↗
PubMed1999

Dendritic asymmetry cannot account for directional responses of neurons in visual cortex.

A simple model was proposed to account for the direction selectivity of neurons in the primary visual cortex, area V1. In this model, the temporal asymmetries in the summation of inhibition and excitation that produce directionality were generated by structural asymmetries in the tangential organization of the basal dendritic tree of cortical neurons. We reconstructed dendritic trees of neurons with known direction preferences and found no correlation between the small biases of a neuron's dendritic morphology and its direction preference. Detailed simulations indicated that even when the electrotonic asymmetries in the dendrites were extreme, as in cortical Meynert cells, the biophysical properties of single neurons could contribute only partially to the directionality of cortical neurons.

Animals↗
PubMed1999

Taming time in the olfactory bulb.

The biophysics of an unusual synaptic arrangement within the olfactory bulb suggests a way in which rapidly inactivating potassium channels could modulate the timing of oscillations that underlie odor recognition.

Animals↗
PubMed1998

Ion channel stochasticity may be critical in determining the reliability and precision of spike timing.

The firing reliability and precision of an isopotential membrane patch consisting of a realistically large number of ion channels is investigated using a stochastic Hodgkin-Huxley (HH) model. In sharp contrast to the deterministic HH model, the biophysically inspired stochastic model reproduces qualitatively the different reliability and precision characteristics of spike firing in response to DC and fluctuating current input in neocortical neurons, as reported by Mainen & Sejnowski (1995). For DC inputs, spike timing is highly unreliable; the reliability and precision are significantly increased for fluctuating current input. This behavior is critically determined by the relatively small number of excitable channels that are opened near threshold for spike firing rather than by the total number of channels that exist in the membrane patch. Channel fluctuations, together with the inherent bistability in the HH equations, give rise to three additional experimentally observed phenomena: subthreshold oscillations in the membrane voltage for DC input, "spontaneous" spikes for subthreshold inputs, and "missing" spikes for suprathreshold inputs. We suggest that the noise inherent in the operation of ion channels enables neurons to act as "smart" encoders. Slowly varying, uncorrelated inputs are coded with low reliability and accuracy and, hence, the information about such inputs is encoded almost exclusively by the spike rate. On the other hand, correlated presynaptic activity produces sharp fluctuations in the input to the postsynaptic cell, which are then encoded with high reliability and accuracy. In this case, information about the input exists in the exact timing of the spikes. We conclude that channel stochasticity should be considered in realistic models of neurons.

Action Potentials↗
PubMed1998

Reading neuronal synchrony with depressing synapses.

A recent experiment showed that neurons in the primary auditory cortex of the monkey do not change their mean firing rate during an ongoing tone stimulus. The only change was an enhanced correlation among the individual spike trains during the tone. We show that there is an easy way to extract this coherence information in the cortical cell population by projecting the spike trains through depressing synapses onto a postsynaptic neuron.

Acoustic Stimulation↗
PubMed1998

Excitable dendrites and spines: earlier theoretical insights elucidate recent direct observations.

Important advances in experimental methods have made it possible to measure the electrical events in dendrites directly and to record optically from dendritic spines. These new techniques allow us to focus on the input region of the neuron and highlight the excitable properties of the dendritic membrane. Interestingly, some of the recent experimental findings were anticipated by earlier theoretical research, for example, the observation that some spines possess excitable channels that might generate local all-or-none events. Computer models were used previously to explore the conditions for initiating an action potential at the dendritic tree, in particular, at the spine head, and for active propagation between excitable spines and excitable dendritic arbors. The consequences for synaptic amplification, for the extent of active spread in the tree and for non-linear discriminations between different patterns of synaptic inputs were also considered. Here we review the biophysical insights gained from the theory and demonstrate how these elucidate the recent experimental results.

Animals↗
PubMed1997

Low-amplitude oscillations in the inferior olive: a model based on electrical coupling of neurons with heterogeneous channel densities.

The mechanism underlying subthreshold oscillations in inferior olivary cells is not known. To study this question, we developed a single-compartment, two-variable, Hodgkin-Huxley-like model for inferior olive neurons. The model consists of a leakage current and a low-threshold calcium current, whose kinetics were experimentally measured in slices. Depending on the maximal calcium and leak conductances, we found that a neuron model's response to current injection could be of four qualitatively different types: always stable, spontaneously oscillating, oscillating with injection of current, and bistable with injection of current. By the use of phase plane techniques, numerical integration, and bifurcation analysis, we subdivided the two-parameter space of channel densities into four regions corresponding to these behavioral types. We further developed, with the use of such techniques, an empirical rule of thumb that characterizes whether two cells when coupled electrically can generate sustained, synchronized oscillations like those observed in inferior olivary cells in slices, of low amplitude (0.1-10 mV) in the frequency range 4-10 Hz. We found that it is not necessary for either cell to be a spontaneous oscillator to obtain a sustained oscillation. On the other hand, two spontaneous oscillators always form an oscillating network when electrically coupled with any arbitrary coupling conductance. In the case of an oscillating pair of electrically coupled nonidentical cells, the coupling current varies periodically and is nonzero even for very large coupling values. The coupling current acts as an equalizing current to reconcile the differences between the two cells' ionic currents. It transiently depolarizes one cell and/or hyperpolarizes the other cell to obtain the regenerative response(s) required for the synchronized oscillation. We suggest that the subthreshold oscillations observed in the inferior olive can emerge from the electrical coupling between neurons with different channel densities, even if the inferior olive nucleus contains no or just a small proportion of spontaneously oscillating neurons.

Animals↗
PubMed1996

Organization of octopus arm movements: a model system for studying the control of flexible arms.

Octopus arm movements provide an extreme example of controlled movements of a flexible arm with virtually unlimited degrees of freedom. This study aims to identify general principles in the organization of these movements. Video records of the movements of Octopus vulgaris performing the task of reaching toward a target were studied. The octopus extends its arm toward the target by a wave-like propagation of a bend that travels from the base of the arm toward the tip. Similar bend propagation is seen in other octopus arm movements, such as locomotion and searching. The kinematics (position and velocity) of the midpoint of the bend in three-dimensional space were extracted using the direct linear transformation algorithm. This showed that the bend tends to move within a single linear plane in a simple, slightly curved path connecting the center of the animal's body with the target location. Approximately 70% of the reaching movements demonstrated a stereotyped tangential velocity profile. An invariant profile was observed when movements were normalized for velocity and distance. Two arms, extended together in the same behavioral context, demonstrated identical velocity profiles. The stereotyped features of the movements were also observed in spontaneous arm extensions (not toward an external target). The simple and stereotypic appearance of the bend trajectory suggests that the position of the bend in space and time is the controlled variable. We propose that this strategy reduces the immense redundancy of the octopus arm movements and hence simplifies motor control.

Animals↗
PubMed1996

Modeling back propagating action potential in weakly excitable dendrites of neocortical pyramidal cells.

Simultaneous recordings from the soma and apical dendrite of layer V neocortical pyramidal cells of young rats show that, for any location of current input, an evoked action potential (AP) always starts at the axon and then propagates actively, but decrementally, backward into the dendrites. This back-propagating AP is supported by a low density (-gNa = approximately 4 mS/cm2) of rapidly inactivating voltage-dependent Na+ channels in the soma and the apical dendrite. Investigation of detailed, biophysically constrained, models of reconstructed pyramidal cells shows the following. (i) The initiation of the AP first in the axon cannot be explained solely by morphological considerations; the axon must be more excitable than the soma and dendrites. (ii) The minimal Na+ channel density in the axon that fully accounts for the experimental results is about 20-times that of the soma. If -gNa in the axon hillock and initial segment is the same as in the soma [as recently suggested by Colbert and Johnston [Colbert, C. M. & Johnston, D. (1995) Soc. Neurosci. Abstr. 21, 684.2]], then -gNa in the more distal axonal regions is required to be about 40-times that of the soma. (iii) A backward propagating AP in weakly excitable dendrites can be modulated in a graded manner by background synaptic activity. The functional role of weakly excitable dendrites and a more excitable axon for forward synaptic integration and for backward, global, communication between the axon and the dendrites is discussed.

Animals↗
PubMed1995

Subthreshold oscillations and resonant frequency in guinea-pig cortical neurons: physiology and modelling.

1. Intracellular recordings were made from neurons in slices from guinea-pig frontal cortex. In 50% of the cells, sustained subthreshold voltage oscillations were evoked by long (> 6 s) depolarizing pulses. The peak-to-peak amplitude of these oscillations was less than 5 mV and the frequency was voltage dependent, increasing with depolarization from 4 (near rest) to 20 Hz (at 30 mV depolarization). 2. The impedance-frequency relationship of both oscillating and non-oscillating cells was studied by intracellular injection of sinusoidal current with linearly changing frequency. In most cells, a peak in the impedance magnitude (resonant behaviour) was observed at depolarized levels. The frequency of the peak impedance (peak frequency) increased with depolarization from 3 (near rest) to 15 Hz (at 30 mV depolarization). 3. Application of TTX (10(-6) M) significantly decreased the impedance magnitude near the peak frequency. The subthreshold oscillations, however, as well as the action potentials, were fully blocked by TTX. On the other hand, TEA (15 mM) and Cs+ (5 mM) abolished both the subthreshold oscillations and the resonant behaviour. Replacing Ca2+ with Co2+ (5 mM) or Ni2+ (1 mM) did not abolish the subthreshold oscillations. The peak in the frequency-response curve was only slightly reduced. 4. An isopotential membrane model, consisting of a leak current, a fast persistent sodium current, a slow non-inactivating potassium current (with the kinetics of the M-current) and membrane capacitance, is sufficient to produce both voltage oscillations and resonant behaviour. The kinetics of the K+ current by itself is sufficient to produce resonance behaviour. The Na+ current amplifies the peak impedance magnitude and is essential for the generation of subthreshold oscillation. The model correctly predicted the behaviour of the frequency response before and after TTX and TEA application, as well as the relation between the expected passive impedance and the experimental impedance. 5. We speculate that the tendency of the neurons to generate voltage signals at a certain frequency (as a result of the subthreshold oscillations) and to preferentially respond to inputs arriving at the same frequency (the resonance behaviour) promotes population activity at that preferred frequency.

Animals↗
PubMed1995

Electrical consequences of spine dimensions in a model of a cortical spiny stellate cell completely reconstructed from serial thin sections.

We built a passive compartmental model of a cortical spiny stellate cell from the barrel cortex of the mouse that had been reconstructed in its entirety from electron microscopic analysis of serial thin sections (White and Rock, 1980). Morphological data included dimensions of soma and all five dendrites, neck lengths and head diameters of all 380 spines (a uniform neck diameter of 0.1 micron was assumed), locations of all symmetrical and asymmetrical (axo-spinous) synapses, and locations of all 43 thalamocortical (TC) synapses (as identified from the consequences of a prior thalamic lesion). In the model, unitary excitatory synaptic inputs had a peak conductance change of 0.5 nS at 0.2 msec; conclusions were robust over a wide range of assumed passive-membrane parameters. When recorded at the soma, all unitary EPSPs, which were initiated at the spine heads, were relatively iso-efficient; each produced about 1 mV somatic depolarization regardless of spine location or geometry. However, in the spine heads there was a twentyfold variation in EPSP amplitudes, largely reflecting the variation in spine neck lengths. Synchronous activation of the TC synapses produced a somatic depolarization probably sufficient to fire the neuron; doubling or halving the TC spine neck diameters had only minimal effect on the amplitude of the composite TC-EPSP. As have others, we also conclude that from a somato-centric viewpoint, changes in spine geometry would have relatively little direct influence on amplitudes of EPSPs recorded at the soma, especially for a distributed, synchronously activated input such as the TC pathway. However, consideration of the detailed morphology of an entire neuron indicates that, from a dendro-centric point of view, changes in spine dimension can have a very significant electrical impact on local processing near the sites of input.

Animals↗
PubMed1995

The morphoelectrotonic transform: a graphical approach to dendritic function.

Electrotonic structure of dendrites plays a critical role in neuronal computation and plasticity. In this article we develop two novel measures of electrotonic structure that describe intraneuronal signaling in dendrites of arbitrary geometry. The log-attenuation Lij measures the efficacy, and the propagation delay Pij the speed, of signal transfer between any two points i and j. These measures are additive, in the sense that if j lies between i and k, the total distance Lik is just the sum of the partial distances: Lik = Lij + Ljk, and similarly Pik = Pij + Pjk. This property serves as the basis for the morphoelectrotonic transform (MET), a graphical mapping from morphological into electrotonic space. In a MET, either Pij or Lij replace anatomical distance as the fundamental unit and so provide direct functional measures of intraneuronal signaling. The analysis holds for arbitrary transient signals, even those generated by nonlinear conductance changes underlying both synaptic and action potentials. Depending on input location and the measure of interest, a single neuron admits many METs, each emphasizing different functional consequences of the dendritic electrotonic structure. Using a single layer 5 cortical pyramidal neuron, we illustrate a collection of METs that lead to a deeper understanding of the electrical behavior of its dendritic tree. We then compare this cortical cell to representative neurons from other brain regions (cortical layer 2/3 pyramidal, region CA1 hippocampal pyramidal, and cerebellar Purkinje). Finally, we apply the MET to electrical signaling in dendritic spines, and extend this analysis to calcium signaling within spines. Our results demonstrate that the MET provides a powerful tool for obtaining a rapid and intuitive grasp of the functional properties of dendritic trees.

Brain↗
PubMed1994

Physiology, morphology and detailed passive models of guinea-pig cerebellar Purkinje cells.

1. Purkinje cells (PCs) from guinea-pig cerebellar slices were physiologically characterized using intracellular techniques. Extracellular caesium ions were used to linearize the membrane properties of PCs near the resting potential. Under these conditions the average input resistance, RN, was 29 M omega, the average system time constant, tau 0, was 82 ms and the average cable length, LN, was 0.59. 2. Three PCs were fully reconstructed following physiological measurements and staining with horseradish peroxidase. Assuming that each spine has an area of 1 micron 2 and that the spine density over the spiny dendrites is ten spines per micrometre length, the total membrane area of each PC is approximately 150,000 microns 2, of which approximately 100,000 microns 2 is in the spines. 3. Detailed passive cable and compartmental models were built for each of the three reconstructed PCs. Computational methods were devised to incorporate globally the huge number of spines into these models. In all three cells the models predict that the specific membrane resistivity, Rm, of the soma is much lower than the dendritic Rm (approximately 500 and approximately 100,000 omega cm2 respectively). The specific membrane capacitance, Cm, is estimated to be 1.5-2 muF cm-2 and the specific cytoplasm resistivity, Ri, is 250 omega cm. 4. The average cable length of the dendrites according to the model is 0.13 lambda, suggesting that under caesium conditions PCs are electrically very compact. Brief somatic spikes, however, are expected to attenuate 30-fold when spreading passively into the dendritic terminals. A simulated 200 Hz train of fast, 90 mV somatic spikes produced a smooth 12 mV steady depolarization at the dendritic terminals. 5. A transient synaptic conductance increase, with a 1 nS peak at 0.5 ms and a driving force of 60 mV, is expected to produce approximately 20 mV peak depolarization at the spine head membrane. This EPSP then attenuates between 200- and 900-fold into the soma. Approximately 800 randomly distributed and synchronously activated spiny inputs are required to fire the soma. 6. The passive model of the PC predicts a poor resolution of the spatio-temporal pattern of the parallel fibre input. An equally sized, randomly distributed group of approximately 1% of the parallel fibres, activated within a time window of a few milliseconds, would result in approximately the same composite EPSP at the soma.

Animals↗
PubMed1993

Signal delay and input synchronization in passive dendritic structures.

1. A novel approach for analyzing transients in passive structures called "the method of moments" is introduced. It provides, as a special case, an analytic method for calculating the time delay and speed of propagation of electrical signals in any passive dendritic tree without the need for numerical simulations. 2. Total dendritic delay (TD) between two points (y, x) is defined as the difference between the centroid (the center of gravity) of the transient current input, I, at point y[tI(y)] and the centroid of the transient voltage response, V, at point x [tV(x)]. The TD measured at the input points is nonzero and is called the local delay (LD). Propagation delay, PD(y, x), is then defined as TD(y, x)--LD(y) whereas the net dendritic delay, NDD(y, 0), of an input point, y, is defined as TD(y, 0) - LD(0), where 0 is the target point, typically the soma. The signal velocity at a point x0 in the tree, theta(x0), is defined as [1/(dtv(x)/dx)[x = x0. 3. With the use of these definitions, several properties of dendritic delay exist. First, the delay between any two points in a given tree is independent of the properties (shape and duration) of the transient current input. Second, the velocity of the signal at any given point (y) in a given direction from (y) does not depend on the morphology of the tree "behind" the signal, and of the input location. Third, TD(y, x) = TD(x, y), for any two points, x, y. 4. Two additional properties are useful for efficiently calculating delays in arbitrary passive trees. 1) The subtrees connected at the ends of any dendritic segment can each be functionally lumped into an equivalent isopotential R-C compartment. 2) The local delay at any given point (y) in a tree is the mean of the local delays of the separate structures (subtrees) connected at y, weighted by the relative input conductance of the corresponding subtrees. 5. Because the definitions for delays utilize difference between centroids, the local delay and the total delay can be interpreted as measures for the time window in which synaptic inputs affect the voltage response at a target/decision point. Large LD or TD is closely associated with a relatively wide time window, whereas small LD or TD imply that inputs have to be well synchronized to affect the decision point. The net dendritic delay may be interpreted as the cost (in terms of delay) of moving a synapse away from the target point.(ABSTRACT TRUNCATED AT 400 WORDS)

Animals↗
PubMed1992

Single neurone models: oversimple, complex and reduced.

The single neurone stands in the midst of a controversy among modelers. Some believe that its details are functionally superfluous when the neurone operates in a large network, and very simple models can be used to represent the input/output characteristics of neurones. Others claim that the unique morphology and electrical properties of neurones do play an important role. Complicated models of neurones are developed to reveal how the various kinds of 'neurone-ware' (dendrites, spines, axons, membrane channels and synapses) create a computationally powerful unit. Various models are discussed, including new carefully reduced models that retain essential features of more complex models. Such intermediate models will play a central role in our efforts to understand information processing in large neuronal networks.

Dendrites↗
PubMed1992

Interpretation of time constant and electrotonic length estimates in multicylinder or branched neuronal structures.

1. We have investigated the theoretical and practical problems associated with the interpretation of time constants and the estimation of electrotonic length with equivalent cylinder formulas for neurons best represented as multiple cylinders or branched structures. Two analytic methods were used to compute the time constants and coefficients of passive voltage transients (and time constants of current transients under voltage clamp). One method, suitable for simple geometries, involves analytic solutions to boundary value problems. The other, suitable for neurons of any geometric complexity, is an algebraic approach based on compartmental models. Neither of these methods requires the simulation of transients. 2. We computed the time constants and coefficients of voltage transients for several hypothetical neurons and also for a spinal motoneuron whose morphology was characterized from serial reconstructions. These time constants and coefficients were used to generate voltage transients. Then exponential peeling, nonlinear regression, and transform methods were applied to these transients to test how well these procedures estimate the underlying time constants and coefficients. 3. For a serially reconstructed motoneuron with 732 compartments, we found that the theoretical and peeled tau 0 values were nearly equal, but the theoretical tau 1 was much larger than the peeled tau 1. The theoretical tau 1 could not be peeled because it was associated with a coefficient, C1, that had a very small value. In fact, there were 156 time constants between 1.0 and 6.0 ms, most of which had very small coefficients; none had a coefficient larger than 2% of the signal. The peeled value of tau 1 (called tau 1 peel) can be viewed as some sort of a weighted average of the time constants having the largest coefficients. 4. We studied simple hypothetical neurons to determine what interpretation could be applied to the multitude of theoretical time constants. We found that after tau 0, there was a group of time constants associated with eigenfunctions that were odd (or approximately odd) functions with respect to the soma. These time constants could be interpreted as "equalizing" time constants along particular paths between different pairs of dendritic terminals in the neuron. After this group of time constants, there was one that we call tau even because it was associated with an eigen-function that was approximately even with respect to the soma. This tau even could be interpreted as an equalizing time constant for charge equalization between proximal membrane (soma and proximal dendrites) and distal membrane (including all distal dendrites).4=

Animals↗