Spike timing and reliability in cortical pyramidal neurons: effects of EPSC kinetics, input synchronization and background noise on spike timing

In vivo studies have shown that neurons in the neocortex can generate action potentials at high temporal precision. The mechanisms controlling timing and reliability of action potential generation in neocortical neurons, however, are still poorly understood. Here we investigated the temporal precision and reliability of spike firing in cortical layer V pyramidal cells at near-threshold membrane potentials. Timing and reliability of spike responses were a function of EPSC kinetics, temporal jitter of population excitatory inputs, and of background synaptic noise. We used somatic current injection to mimic population synaptic input events and measured spike probability and spike time precision (STP), the latter defined as the time window (Deltat) holding 80% of response spikes. EPSC rise and decay times were varied over the known physiological spectrum. At spike threshold level, EPSC decay time had a stronger influence on STP than rise time. Generally, STP was highest (6 ms) triggered spikes at lower temporal precision (>or=6.58 ms). We found an overall linear relationship between STP and spike delay. The difference in STP between fast and slow compound EPSCs could be reduced by incrementing the amplitude of slow compound EPSCs. The introduction of a temporal jitter to compound EPSCs had a comparatively small effect on STP, with a tenfold increase in jitter resulting in only a five fold decrease in STP. In the presence of simulated synaptic background activity, precisely timed spikes could still be induced by fast EPSCs, but not by slow EPSCs.     

Inhibitory postsynaptic potentials carry synchronized frequency information in active cortical networks

Temporal precision in spike timing is important in cortical function, interactions, and plasticity. We found that, during periods of recurrent network activity (UP states), cortical pyramidal cells in vivo and in vitro receive strong barrages of both excitatory and inhibitory postsynaptic potentials, with the inhibitory potentials showing much higher power at all frequencies above approximately 10 Hz and more synchrony between nearby neurons. Fast-spiking inhibitory interneurons discharged strongly in relation to higher-frequency oscillations in the field potential in vivo and possess membrane, synaptic, and action potential properties that are advantageous for transmission of higher-frequency activity. Intracellular injection of synaptic conductances having the characteristics of the recorded EPSPs and IPSPs reveal that IPSPs are important in controlling the timing and probability of action potential generation in pyramidal cells. Our results support the hypothesis that inhibitory networks are largely responsible for the dissemination of higher-frequency activity in cortex.     

Pre & postsynaptic tuning of action potential timing by spontaneous GABAergic activity

Frequency and timing of action potential discharge are key elements for coding and transfer of information between neurons. The nature and location of the synaptic contacts, the biophysical parameters of the receptor-operated channels and their kinetics of activation are major determinants of the firing behaviour of each individual neuron. Ultimately the intrinsic excitability of each neuron determines the input-output function. Here we evaluate the influence of spontaneous GABAergic synaptic activity on the timing of action potentials in Layer 2/3 pyramidal neurones in acute brain slices from the somatosensory cortex of young rats. Somatic dynamic current injection to mimic synaptic input events was employed, together with a simple computational model that reproduce subthreshold membrane properties. Besides the well-documented control of neuronal excitability, spontaneous background GABAergic activity has a major detrimental effect on spike timing. In fact, GABA(A) receptors tune the relationship between the excitability and fidelity of pyramidal neurons via a postsynaptic (the reversal potential for GABA(A) activity) and a presynaptic (the frequency of spontaneous activity) mechanism. GABAergic activity can decrease or increase the excitability of pyramidal neurones, depending on the difference between the reversal potential for GABA(A) receptors and the threshold for action potential. In contrast, spike time jitter can only be increased proportionally to the difference between these two membrane potentials. Changes in excitability by background GABAergic activity can therefore only be associated with deterioration of the reliability of spike timing.     

Learning of Precise Spike Times with Homeostatic Membrane Potential Dependent Synaptic Plasticity

Precise spatio-temporal patterns of neuronal action potentials underly e.g. sensory representations and control of muscle activities. However, it is not known how the synaptic efficacies in the neuronal networks of the brain adapt such that they can reliably generate spikes at specific points in time. Existing activity-dependent plasticity rules like Spike-Timing-Dependent Plasticity are agnostic to the goal of learning spike times. On the other hand, the existing formal and supervised learning algorithms perform a temporally precise comparison of projected activity with the target, but there is no known biologically plausible implementation of this comparison. Here, we propose a simple and local unsupervised synaptic plasticity mechanism that is derived from the requirement of a balanced membrane potential. Since the relevant signal for synaptic change is the postsynaptic voltage rather than spike times, we call the plasticity rule Membrane Potential Dependent Plasticity (MPDP). Combining our plasticity mechanism with spike after-hyperpolarization causes a sensitivity of synaptic change to pre- and postsynaptic spike times which can reproduce Hebbian spike timing dependent plasticity for inhibitory synapses as was found in experiments. In addition, the sensitivity of MPDP to the time course of the voltage when generating a spike allows MPDP to distinguish between weak (spurious) and strong (teacher) spikes, which therefore provides a neuronal basis for the comparison of actual and target activity. For spatio-temporal input spike patterns our conceptually simple plasticity rule achieves a surprisingly high storage capacity for spike associations. The sensitivity of the MPDP to the subthreshold membrane potential during training allows robust memory retrieval after learning even in the presence of activity corrupted by noise. We propose that MPDP represents a biophysically plausible mechanism to learn temporal target activity patterns.     

Effects of temperan a central synapse between identified motor neurons in the locust

Summary Changing the temperature from 10–40 °C modifies the transmission at an established monosynaptic connection between the fast extensor tibiae (FETi) and flexor tibiae motor neurons in the metathoracic ganglion of the locustSchistocerca gregaria (Forskål). Striking changes occur to the shape of the spikes, to membrane resistance, to the synaptic delay, and to the evoked synaptic potentials.In the presynaptic FETi motor neuron, raising the temperature reduces the amplitude of an antidromic spike recorded in the soma by a factor of 10 (40 mV to 4 mV), reduces the time taken to reach peak amplitude by 5 (3.5 to 0.7 ms) and decreases the duration at half maximum amplitude by 0.5. The conduction velocity of the spike in the axon is increased by 50% from 10 °C to 40 °C. Orthodromic spikes are affected by temperature in a similar way to the antidromic spikes.The membrane resistance of both pre- and postsynaptic motor neurons falls as the temperature is raised. The membrane resistance of FETi falls by a factor of 4 (about 4 M at 10 °C to 1 M at 40 °C). A contributory component to this fall could be the increase in the frequency of synaptic potentials generated as a result of inputs from other neurons. No temperature dependence could be demonstrated on the voltage threshold relative to resting potential for evoking orthodromic spikes, but because the resistance changes, the current needed to achieve this voltage must be increased at higher temperatures.The latency measured from the peak of the spike in the soma of FETi to the start of the EPSP in the soma of a flexor motor neuron decreases by a factor of 20 (10 ms at 10 °C to 0.5 ms at 40 °C).In a postsynaptic flexor tibiae motor neuron, the amplitude of the evoked synaptic potential increases by a factor of 3.4 (5 mV to 17 mV), its duration at half maximum amplitude decreases by 3 (7 ms at 12 °C to 2.3 ms at 32 °C) and its rate of rise increases by 3. An increased likelihood that spikes will occur in the flexor contributes to the enhanced amplitude of the compound EPSP at temperatures above 20 °C.Abbreviation FETi fast extensor tibiae motor neuron     

Electrical properties of neurons recorded from the rat supraoptic nucleus in vitro

The electrical properties of neurons in the supraoptic nucleus (so.n.) have been studied in the hypothalamic slice preparation by intracellular and extracellular recording techniques, with Lucifer Yellow CH dye injection to mark the recording site as being the so.n. Intracellular recordings from so.n. neurons revealed them to have an average membrane potential of -67 +/- 0.8 mV (mean +/- s.e.m.), membrane resistance of 145 +/- 9 M omega with linear current-voltage relations from 40 mV in the hyperpolarizing direction to the level of spike threshold in the depolarizing direction. Average cell time constant was 14 +/- 2.2 ms. So.n. action potentials ranged in amplitude from 55 to 95 mV, with a mean of 76 +/- 2 mV, and a spike width of 2.6 +/- 0.5 ms at 30% of maximal spike height. Both single spikes and trains of spikes were followed by a strong, long-lasting hyperpolarization with a decay fitted by a single exponential having a time constant of 8.6 +/- 1.8 ms. Action potentials could be blocked by 10(-6) M tetrodotoxin. Spontaneously active so.n. neurons were characterized by synaptic input in the form of excitatory and inhibitory postsynaptic potentials, the latter being apparently blocked when 4 M KCl electrodes were used. Both forms of synaptic activity were blocked by application of divalent cations such as Mg2+, Mn2+ or Co2+. 74% of so.n. neurons fired spontaneously at rates exceeding 0.1 spikes per second, with a mean for all cells of 2.9 +/- 0.2 s-1. Of these cells, 21% fired slowly and continuously at 0.1 - 1.0 s-1, 45% fired continuously at greater than 1 Hz, and the remaining 34% fired phasically in bursts of activity followed by silence or low frequency firing. Spontaneously firing phasic cells showed a mean burst length of 16.7 +/- 4.5 s and a silent period of 28.2 +/- 4.2 s. Intracellular recordings revealed the presence of slow variations in membrane potential which modified the neuron's proximity to spike threshold, and controlled phasic firing. Variations in synaptic input were not observed to influence firing in phasic cells.     

Properties of synaptic noise in tonically active human motoneurons

The objective of these experiments was to determine the amount of synaptic noise on the cell membrane at various intervals after an action potential in a motoneuron firing at a specified frequency. Sources of noise such as variations in the level of voluntary drive were minimized by selecting only segments of the spike train in which the unit was running within prescribed frequency limits. The level of the membrane potential of the motoneuron during these intervals was determined using two test “pulses” (compound Ia excitatory postsynaptic potentials) of known amplitude. This enabled the probability of the membrane potential falling within a voltage “window” of known size at known times after the preceding spike to be determined. The probability density histograms showed that the fluctuations of membrane potential about a target interspike trajectory (i.e., the membrane noise) increased with time after the preceding spike. These fluctuations in the membrane potential can be accounted for by a one-dimensional “random walk” model of membrane noise. This model explains the salient features of the interval histograms, such as positive skewness at low target frequencies. A quantitative test of the model demonstrated its applicability to the motor pools of tibialis and masseter.     

Variability and coding efficiency of noisy neural spike encoders

Encoding synaptic inputs as a train of action potentials is a fundamental function of nerve cells. Although spike trains recorded in vivo have been shown to be highly variable, it is unclear whether variability in spike timing represents faithful encoding of temporally varying synaptic inputs or noise inherent in the spike encoding mechanism. It has been reported that spike timing variability is more pronounced for constant, unvarying inputs than for inputs with rich temporal structure. This could have significant implications for the nature of neural coding, particularly if precise timing of spikes and temporal synchrony between neurons is used to represent information in the nervous system. To study the potential functional role of spike timing variability, we estimate the fraction of spike timing variability which conveys information about the input for two types of noisy spike encoders--an integrate and fire model with randomly chosen thresholds and a model of a patch of neuronal membrane containing stochastic Na(+) and K(+) channels obeying Hodgkin-Huxley kinetics. The quality of signal encoding is assessed by reconstructing the input stimuli from the output spike trains using optimal linear mean square estimation. A comparison of the estimation performance of noisy neuronal models of spike generation enables us to assess the impact of neuronal noise on the efficacy of neural coding. The results for both models suggest that spike timing variability reduces the ability of spike trains to encode rapid time-varying stimuli. Moreover, contrary to expectations based on earlier studies, we find that the noisy spike encoding models encode slowly varying stimuli more effectively than rapidly varying ones.     

Adaptive Spike Threshold Enables Robust and Temporally Precise Neuronal Encoding

Neural processing rests on the intracellular transformation of information as synaptic inputs are translated into action potentials. This transformation is governed by the spike threshold, which depends on the history of the membrane potential on many temporal scales. While the adaptation of the threshold after spiking activity has been addressed before both theoretically and experimentally, it has only recently been demonstrated that the subthreshold membrane state also influences the effective spike threshold. The consequences for neural computation are not well understood yet. We address this question here using neural simulations and whole cell intracellular recordings in combination with information theoretic analysis. We show that an adaptive spike threshold leads to better stimulus discrimination for tight input correlations than would be achieved otherwise, independent from whether the stimulus is encoded in the rate or pattern of action potentials. The time scales of input selectivity are jointly governed by membrane and threshold dynamics. Encoding information using adaptive thresholds further ensures robust information transmission across cortical states i.e. decoding from different states is less state dependent in the adaptive threshold case, if the decoding is performed in reference to the timing of the population response. Results from in vitro neural recordings were consistent with simulations from adaptive threshold neurons. In summary, the adaptive spike threshold reduces information loss during intracellular information transfer, improves stimulus discriminability and ensures robust decoding across membrane states in a regime of highly correlated inputs, similar to those seen in sensory nuclei during the encoding of sensory information.     

Active control of spike-timing dependent synaptic plasticity in an electrosensory system.

A spike timing dependent learning rule is present at the synapse between parallel fibers and Purkinje-like medium ganglion cells in the electrosensory lobe of mormyrid electric fish. The synapse is depressed when a postsynaptic dendritic spike occurs within 50 ms of the onset of a parallel fiber excitatory postsynaptic potential, but is enhanced at all other timing relations. Operation of this learning rule results in the cancellation of predictable membrane potential changes, driving the cell towards a constant output frequency. But medium ganglion cells show a strong and predictable response to corollary discharge signals associated with the motor command that initiates the electric organ discharge. The modeling study presented here resolves this conflict by proposing an active control of dendritic spike threshold during the brief period of medium ganglion cell response.     

Intracellular recordings from spinal neurons during 'swimming' in paralysed amphibian embryos

Intracellular microelectrode recordings have been made from probable motoneurons in the spinal cord of Xenopus laevis embryos during fictive 'swimming' in preparations paralysed with the neuromuscular blocking agent tubocurarine. These cells had resting potentials of -50 mV or more. During spontaneous or stimulus-evoked 'swimming' episodes: (a) the cells were tonically excited; the level of tonic synaptic excitation and the conductance increase underlying it were both inversely related to the 'swimming' cycle period; (b) the cells usually fired one spike per cycle in phase with the motor root burst on the same side; spikes did not overshoot zero and were evoked by phasic excitatory synaptic input on each cycle, superimposed on the tonic excitation; (c) in phase with motor root discharge on the opposite side of the body, the cells were hyperpolarized by a chloride-dependent inhibitory postsynaptic potential. The nature of synaptic potentials during 'swimming' was evaluated by means of intracellular current injections. The 'swimming' activity could be controlled by natural stimuli. The results provide clear evidence on the relation of tonic excitation to rhythmic locomotory pattern generation, and indirect evidence for reciprocal inhibitory coupling between antagonistic motor systems.     

Integrative Synaptic Mechanisms in the Caudal Ganglion of the Crayfish

A study of activity recorded with intracellular micropipettes was undertaken in the caudal abdominal ganglion of the crayfish in order to gain information about central fiber to fiber synaptic mechanisms. This synaptic system has well developed integrative properties. Excitatory post-synaptic potentials can be graded, and synaptic potentials from different inputs can sum to initiate spike discharge. In most impaled units, the spike discharge fails to destroy the synaptic potential, thereby allowing sustained depolarization and multiple spike discharge following single pulse stimulation to an afferent input. Some units had characteristics which suggest a graded threshold for spike generation along the post-synaptic fiber membrane. Other impaled units responded to afferent stimulation with spike discharges of two distinct amplitudes. The smaller or "abortive" spikes in such units may represent non-invading activity in branches of the post-synaptic axon. On a few occasions one afferent input was shown to inhibit the spike discharge initiated by another presynaptic input.     

Synaptic potential in the motor giant axon of the crayfish

Some electrical properties of the synapses between central giant axons (presynaptic) and the motor giant axon (postsynaptic) of the crayfish abdominal nerve cord have been investigated. Postsynaptic potential change in response to presynaptic volleys contains two components: a spike potential and a synaptic potential of very long time course. Amplitude of the synaptic potential is graded according to the number of active presynaptic axons. Conductance increase in the synaptic membrane endures over most of the period of potential change, and it is this rather than the "electrical time constant" of the membrane that in large measure determines the form of the synaptic potential. Temporal summation of synaptic potential occurs during repetitive presynaptic stimulation, and after such stimulation the rate of decay of synaptic potential is greatly slowed.     

Information processing by nonspiking interneurons: passive and active properties of dendritic membrane determine synaptic integration

Nonspiking interneurons control activities of postsynaptic cells without generating action potentials in the central nervous system of many invertebrates. Physiological characteristics of their dendritic membrane have been analyzed in previous studies using single electrode current- and voltage-clamp techniques. We constructed a single compartment model of an identified nonspiking interneuron of crayfish. Experimental results allowed us to simulate how the passive and active properties of the dendritic membrane influence the integrative processing of synaptic inputs. The results showed that not only the peak amplitude but also the time course of synaptic potentials were dependent on the membrane potential level at which the synaptic activity was evoked. When the synaptic input came sequentially, each individual input was still discernible at depolarized levels at which the membrane time constant was short due to depolarization-dependent membrane conductances. In contrast, synaptic potentials merged with each other to develop a sustained potential at hyperpolarized levels where the membrane behaved passively. Thus, synaptic integration in a single nonspiking interneuron depends on the value of membrane potential at which it occurs. This probably reflects the temporal resolution required for specific types of information processing.     

Coding with spike shapes and graded potentials in cortical networks

In cortical neurones, analogue dendritic potentials are thought to be encoded into patterns of digital spikes. According to this view, neuronal codes and computations are based on the temporal patterns of spikes: spike times, bursts or spike rates. Recently, we proposed an 'action potential waveform code' for cortical pyramidal neurones in which the spike shape carries information. Broader somatic action potentials are reliably produced in response to higher conductance input, allowing for four times more information transfer than spike times alone. This information is preserved during synaptic integration in a single neurone, as back-propagating action potentials of diverse shapes differentially shunt incoming postsynaptic potentials and so participate in the next round of spike generation. An open question has been whether the information in action potential waveforms can also survive axonal conduction and directly influence synaptic transmission to neighbouring neurones. Several new findings have now brought new light to this subject, showing cortical information processing that transcends the classical models.     

Characterization of respiratory-related neurons in the isolated brainstem of the frog

Using intra- and extracellular recording techniques we examined the spontaneous discharge and membrane properties of respiratory-related neurons in isolated brainstem preparations of the frogs Rana catesbeiana and Rana pipiens that display spontaneous respiratory related activity in vitro. We observed neurons that depolarize during the fictive lung ventilation cycle as well as neurons that depolarize during the non-lung ventilation phase. Respiratory-related neurons demonstrated significant decreases in membrane input resistance during the fictive lung ventilation cycle but showed no evidence of voltage-dependent membrane conductances activated near resting membrane potential. Furthermore, respiratory neurons showed little spike frequency adaptation, their oscillatory activity was not dissociated from the global respiratory motor output following imposed changes in membrane potential, and spontaneous fluctuations in membrane potential were not observed following reversible interruption of respiratory burst activity by application of solutions low in calcium and high in magnesium. Taken together these results suggest that bulbar respiratory neurons in the isolated frog brainstem sampled in our study do not display endogenous bursting characteristics. Rather, they are strongly influenced by synaptic input. Accepted: 20 March 1997     

Feed-forward, feedback and lateral interactions in membrane potentials and spike trains from the visual cortex in vivo.

Neurons in the visual cortex receive input from the lateral geniculate nucleus (feed-forward), higher order visual areas (feedback) and local neurons in the surroundings (lateral interactions). Here we first briefly review the approximate timing and proportion of these three types of influences on the membrane potentials in visual areas 17, 18 and 19. Then we present original results from an independent component analysis of multiunit spike trains in the same visual areas to resolve the contribution from these three sources. We stimulated the visual cortex of the ferret with a small transient contrast square stimulus and recorded the multiunit activity in areas 17, 18 and 19 with single or multiple electrodes. The spike trains had three reproducible components having their maxima at 40, 55 and 105ms after the start of the presentation of the stimulus. The time course of the third component was significantly correlated with the population membrane potential in the supragranular layers of areas 17, 18 and 19. The first spike train component was interpreted as a feed-forward response, the second spike train component as driving the laterally spreading depolarization and the third spike train component as the firing caused by the lateral spreading- and the feedback depolarization.     

Membrane Potential Fluctuations Determine the Precision of Spike Timing and Synchronous Activity: A Model Study

It is much debated on what time scale information is encoded by neuronal spike activity. With a phenomenological model that transforms time-dependent membrane potential fluctuations into spike trains, we investigate constraints for the timing of spikes and for synchronous activity of neurons with common input. The model of spike generation has a variable threshold that depends on the time elapsed since the previous action potential and on the preceding membrane potential changes. To ensure that the model operates in a biologically meaningful range, the model was adjusted to fit the responses of a fly visual interneuron to motion stimuli. The dependence of spike timing on the membrane potential dynamics was analyzed. Fast membrane potential fluctuations are needed to trigger spikes with a high temporal precision. Slow fluctuations lead to spike activity with a rate about proportional to the membrane potential. Thus, for a given level of stochastic input, the frequency range of membrane potential fluctuations induced by a stimulus determines whether a neuron can use a rate code or a temporal code. The relationship between the steepness of membrane potential fluctuations and the timing of spikes has also implications for synchronous activity in neurons with common input. Fast membrane potential changes must be shared by the neurons to produce synchronous activity.     

Activation of Nuclear Calcium Dynamics by Synaptic Stimulation in Cultured Cortical Neurons

L-type voltage-sensitive Ca2+ channels (VSCCs) are enriched on the neuronal soma and trigger gene expression during synaptic activity. To understand better how these channels regulate somatic and nuclear Ca2+ dynamics, we have investigated Ca2+ influx through L-type VSCCs following synaptic stimulation, using the long-wavelength Ca2+ indicator fluo-3 combined with laser scanning confocal microscopy. Single synaptic stimuli resulted in rapid Ca2+ transients in somatic cytoplasmic compartments (<5 ms rise time). Nuclear Ca2+ elevations lagged behind cytoplasmic levels by approximately 60 ms, consistent with a dependence on diffusion from a cytoplasmic source. Pharmacological experiments indicated that L-type VSCCs mediated approximately 50% of the nuclear and somatic (cytoplasmic) Ca2+ elevation in response to strong synaptic stimulation. In contrast, relatively weak excitatory postsynaptic potentials (EPSPs; approximately 15 mV) or single action potentials were much less effective at activating L-type VSCCs. Antagonist experiments indicated that activation of the NMDA-type glutamate receptor leads to a long-lasting somatic depolarization necessary to activate L-type VSCCs effectively during synaptic stimuli. Simulation of action potential and somatic EPSP depolarization using voltage-clamp pulses indicated that nuclear Ca2+ transients mediated by L-type VSCCs were produced by sustained depolarization positive to -25 mV. In the absence of synaptic stimulation, action potential stimulation alone led to elevations in nuclear Ca2+ mediated by predominantly non-L-type VSCCs. Our results suggest that action potentials, in combination with long-lived synaptic depolarizations, facilitate the activation of L-type VSCCs. This activity elevates somatic Ca2+ levels that spread to the nucleus.     

Dynamical changes and temporal precision of synchronized spiking activity in monkey motor cortex during movement preparation.

Movement preparation is considered to be based on central processes which are responsible for improving motor performance. For instance, it has been shown that motor cortical neurones change their activity selectively in relation to prior information about movement parameters. However, it is not clear how groups of neurones dynamically organize their activity to cope with computational demands. The aim of the study was to compare the firing rate of multiple simultaneously recorded neurones with the interaction between them by describing not only the frequency of occurrence of epochs of significant synchronization, but also its modulation in time and its changes in temporal precision during an instructed delay. Multiple single-neurone activity was thus recorded in monkey motor cortex during the performance of two different delayed multi-directional pointing tasks. In order to detect conspicuous spike coincidences in simultaneously recorded spike trains by tolerating temporal jitter ranging from 0 to 20 ms and to calculate their statistical significance, a modified method of the 'Unitary Events' analysis was used. Two main results were obtained. First, simultaneously recorded neurones synchronize their spiking activity in a highly dynamic way. Synchronization becomes significant only during short periods (about 100 to 200 ms). Several such periods occurred during a behavioural trial more or less regularly. Second, in many pairs of neurones, the temporal precision of synchronous activity was highest at the end of the preparatory period. As a matter of fact, at the beginning of this period, after the presentation of the preparatory signal, neurones significantly synchronize their spiking activity, but with low temporal precision. As time advances, significant synchronization becomes more precise. Data indicate that not only the discharge rate is involved in preparatory processes, but also temporal aspects of neuronal activity as expressed in the precise synchronization of individual action potentials.