Precise Timing Of Action Potentials Research Articles

Simultaneous excitatory and inhibitory dynamics in an excitable laser

Neocortical systems encode information in electrochemical spike timings, not just mean firing rates. Learning and memory in networks of spiking neurons is achieved by the precise timing of action potentials that induces synaptic strengthening (with excitation) or weakening (with inhibition). Inhibition should be incorporated into brain-inspired spike processing in the optical domain to enhance its information-processing capability. We demonstrate the simultaneous excitatory and inhibitory dynamics in an excitable (i.e., a pulsed) laser neuron, both numerically and experimentally. We investigate the bias strength effect, inhibitory strength effect, and excitatory and inhibitory input timing effect, based on the simulation platform of an integrated graphene excitable laser. We further corroborate these analyses with proof-of-principle experiments utilizing a fiber-based graphene excitable laser, where we introduce inhibition by directly modulating the gain of the laser. This technology may potentially open novel spike-processing functionality for future neuromorphic photonic systems.

Natural Firing Patterns Imply Low Sensitivity of Synaptic Plasticity to Spike Timing Compared with Firing Rate.

Synaptic plasticity, the change in efficacy of connections between neurons, is thought to underlie learning and memory. The dominant paradigm posits that the precise timing of neural action potentials (APs) is central for plasticity induction. This concept is based on experiments using highly regular and stereotyped patterns of APs, in stark contrast with natural neuronal activity. Using synaptic plasticity models, we investigated how irregular, in vivo-like activity shapes synaptic plasticity. We found that synaptic changes induced by precise timing of APs are much weaker than suggested by regular stimulation protocols, and can be equivalently induced by modest variations of the AP rate alone. Our results call into question the dominant role of precise AP timing for plasticity in natural conditions.

Synaptic GABAA receptor clustering without the γ2 subunit.

Rapid activation of postsynaptic GABAA receptors (GABAARs) is crucial in many neuronal functions, including the synchronization of neuronal ensembles and controlling the precise timing of action potentials. Although the γ2 subunit is believed to be essential for the postsynaptic clustering of GABAARs, synaptic currents have been detected in neurons obtained from γ2(-/-) mice. To determine the role of the γ2 subunit in synaptic GABAAR enrichment, we performed a spatially and temporally controlled γ2 subunit deletion by injecting Cre-expressing viral vectors into the neocortex of GABAARγ2(77I)lox mice. Whole-cell recordings revealed the presence of miniature IPSCs in Cre(+) layer 2/3 pyramidal cells (PCs) with unchanged amplitudes and rise times, but significantly prolonged decays. Such slowly decaying currents could be evoked in PCs by action potentials in presynaptic fast-spiking interneurons. Freeze-fracture replica immunogold labeling revealed the presence of the α1 and β3 subunits in perisomatic synapses of cells that lack the γ2 subunit. Miniature IPSCs in Cre(+) PCs were insensitive to low concentrations of flurazepam, providing a pharmacological confirmation of the lack of the γ2 subunit. Receptors assembled from only αβ subunits were unlikely because Zn(2+) did not block the synaptic currents. Pharmacological experiments indicated that the αβγ3 receptor, rather than the αβδ, αβε, or αβγ1 receptors, was responsible for the slowly decaying IPSCs. Our data demonstrate the presence of IPSCs and the synaptic enrichment of the α1 and β3 subunits and suggest that the γ3 subunit is the most likely candidate for clustering GABAARs at synapses in the absence of the γ2 subunit.

Reading spike timing without a clock: intrinsic decoding of spike trains

The precise timing of action potentials of sensory neurons relative to the time of stimulus presentation carries substantial sensory information that is lost or degraded when these responses are summed over longer time windows. However, it is unclear whether and how downstream networks can access information in precise time-varying neural responses. Here, we review approaches to test the hypothesis that the activity of neural populations provides the temporal reference frames needed to decode temporal spike patterns. These approaches are based on comparing the single-trial stimulus discriminability obtained from neural codes defined with respect to network-intrinsic reference frames to the discriminability obtained from codes defined relative to the experimenter's computer clock. Application of this formalism to auditory, visual and somatosensory data shows that information carried by millisecond-scale spike times can be decoded robustly even with little or no independent external knowledge of stimulus time. In cortex, key components of such intrinsic temporal reference frames include dedicated neural populations that signal stimulus onset with reliable and precise latencies, and low-frequency oscillations that can serve as reference for partitioning extended neuronal responses into informative spike patterns.

A unifying theory of synaptic long-term plasticity based on a sparse distribution of synaptic strength

Long-term synaptic plasticity is fundamental to learning and network function. It has been studied under various induction protocols and depends on firing rates, membrane voltage, and precise timing of action potentials. These protocols show different facets of a common underlying mechanism but they are mostly modeled as distinct phenomena. Here, we show that all of these different dependencies can be explained from a single computational principle. The objective is a sparse distribution of excitatory synaptic strength, which may help to reduce metabolic costs associated with synaptic transmission. Based on this objective we derive a stochastic gradient ascent learning rule which is of differential-Hebbian type. It is formulated in biophysical quantities and can be related to current mechanistic theories of synaptic plasticity. The learning rule accounts for experimental findings from all major induction protocols and explains a classic phenomenon of metaplasticity. Furthermore, our model predicts the existence of metaplasticity for spike-timing-dependent plasticity Thus, we provide a theory of long-term synaptic plasticity that unifies different induction protocols and provides a connection between functional and mechanistic levels of description.

Short latency activation of cortex during clinically effective subthalamic deep brain stimulation for Parkinson's disease

Subthalamic deep brain stimulation (DBS) is superior to medical therapy for the motor symptoms of advanced Parkinson's disease (PD), and additional evidence suggests that it improves refractory symptoms of essential tremor, primary generalized dystonia, and obsessive-compulsive disorder. Despite this, its therapeutic mechanism is unknown. We hypothesized that subthalamic stimulation activates the cerebral cortex at short latencies after stimulus onset during clinically effective stimulation for PD. In 5 subjects (six hemispheres), EEG measured the response of cortex to subthalamic stimulation across a range of stimulation voltages and frequencies. Novel analytical techniques reversed the anode and cathode electrode contacts and summed the resulting pair of event-related potentials to suppress the stimulation artifact. We found that subthalamic brain stimulation at 20 Hz activates the somatosensory cortex at discrete latencies (mean latencies: 1.0 ± 0.4, 5.7 ± 1.1, and 22.2 ± 1.8 ms, denoted as R1, R2, and R3, respectively). The amplitude of the short latency peak (R1) during clinically effective high-frequency stimulation is nonlinearly dependent on stimulation voltage (P < 0.001; repeated-measures analysis of variance), and its latency is less variable than that of R3 (1.02 versus 19.46 ms; P < 0.001, Levene's test). We conclude that clinically effective subthalamic brain stimulation in humans with PD activates the cerebral cortex at 1 ms after stimulus onset, most likely by antidromic activation. These findings suggest that alteration of the precise timing of action potentials in cortical neurons with axonal projections to the subthalamic region may be an important component of the therapeutic mechanism of subthalamic brain stimulation.

Theta-Band Phase Locking of Orbitofrontal Neurons during Reward Expectancy

The expectancy of a rewarding outcome following actions and cues is coded by a network of brain structures including the orbitofrontal cortex. Thus far, predicted reward was considered to be coded by time-averaged spike rates of neurons. However, besides firing rate, the precise timing of action potentials in relation to ongoing oscillations in local field potentials is thought to be of importance for effective communication between brain areas. We performed multineuron and field potential recordings in orbitofrontal cortex of rats performing olfactory discrimination learning to study the temporal structure of coding predictive of outcome. After associative learning, field potentials were marked by theta oscillations, both in advance and during delivery of reward. Orbitofrontal neurons, especially those coding information about upcoming reward with their firing rate, phase locked to these oscillations in anticipation of reward. When established associations were reversed, phase locking collapsed in the anticipatory task phase, but returned when reward became predictable again after relearning. Behaviorally, the outcome anticipation phase was marked by licking responses, but the frequency of lick responses was dissociated from the strength of theta-band phase locking. The strength of theta-band phase locking by orbitofrontal neurons robustly follows the dynamics of associative learning as measured by behavior and correlates with the rat's current outcome expectancy. Theta-band phase locking may facilitate communication of outcome-related information between reward-related brain areas and offers a novel mechanism for coding value signals during reinforcement learning.

Stochastic Emergence of Repeating Cortical Motifs in Spontaneous Membrane Potential Fluctuations In Vivo

It was recently discovered that subthreshold membrane potential fluctuations of cortical neurons can precisely repeat during spontaneous activity, seconds to minutes apart, both in brain slices and in anesthetized animals. These repeats, also called cortical motifs, were suggested to reflect a replay of sequential neuronal firing patterns. We searched for motifs in spontaneous activity, recorded from the rat barrel cortex and from the cat striate cortex of anesthetized animals, and found numerous repeating patterns of high similarity and repetition rates. To test their significance, various statistics were compared between physiological data and three different types of stochastic surrogate data that preserve dynamical characteristics of the recorded data. We found no evidence for the existence of deterministically generated cortical motifs. Rather, the stochastic properties of cortical motifs suggest that they appear by chance, as a result of the constraints imposed by the coarse dynamics of subthreshold ongoing activity.

Spatiotemporal Specificity of Neuronal Activity Directs the Modification of Receptive Fields in the Developing Retinotectal System

The precise temporal relation between pre- and postsynaptic activity modulates the strength of synaptic connections. Despite its extensive characterization in vivo and in vitro, the degree to which spike timing-dependent plasticity can shape receptive field properties is unclear. We use in vivo patch-clamp recordings of tectal neurons in developing Xenopus tadpoles to control the precise timing of action potentials with respect to the arrival of a subset of visual inputs evoked by local light stimulation on the retina. The pattern of visual inputs onto a tectal neuron was tracked over time by rapid reverse correlation mapping of receptive fields. Spike timing-dependent potentiation or depression of a subset of synapses reliably shifts the spatial receptive fields toward or away from the trained subregion of visual space, respectively. These results demonstrate that natural patterns of activity evoked by sensory stimuli play an instructive role in the developing nervous system.

Oscillations in Endogenous Inputs to Neurons Affect Excitability and Signal Processing

Synchrony and oscillations in neuronal firing play important roles in information processing in the mammalian brain. Here, we evaluate their role in controlling neuronal output in a well defined motor behavior, breathing, using an in vitro preparation from neonatal rat that generates respiratory-related motor output. In this preparation, phrenic motoneurons (PMNs) receive endogenous rhythmic inspiratory currents with prominent oscillations in the 20-50 Hz range. We recorded these inspiratory currents in individual PMNs and used them as test inputs for the same motoneuron (MN) during the normally silent expiratory periods. The impact of the oscillations on MN output was evaluated by filtering the currents before injection. Responses to unfiltered inspiratory currents were indistinguishable from voltage changes during spontaneous inspiratory periods. More than 90% of action potentials occurred within milliseconds [-2 to +4] of the oscillation peaks. The timing of action potentials was highly reproducible in response to unfiltered currents. Attenuation of the oscillations by low-pass filtering (<50 Hz) decreased the precision in action potential timing and significantly reduced the number of action potentials by approximately 35%. The adrenergic agonist phenylephrine increased instantaneous firing frequency in responses evoked by square-wave or low-pass filtered inspiratory currents but had no effect on firing frequency evoked by unfiltered currents. We conclude that oscillations control the precise timing of action potentials, help to maximize synaptic drive efficiency, and constrain MN firing frequencies to those optimal for muscle contraction.

Translation-invariant pattern recognition based on Synfire chains.

Most of current neural network architectures are not suited to recognize a pattern at various displaced positions. This lack seems due to the prevailing neuron model which reduces a neuron's information transmission to its firing rate. With this information code, a neuronal assembly cannot distinguish between different combinations of its entities and therefore fails to represent the fine structure within a pattern. In our approach, the main idea of the correlation theory is accepted that spatial relationships in a pattern should be coded by temporal relations in the timing of action potentials. However, we do not assume that synchronized spikes are a sign for strong synapses between the neurons concerned. Instead, the synchronization of Synfire chains can be exploited to produce the relevant timing relationships between the neuronal signals. Therefore, we do not require fast synaptic plasticity to account for the precise timing of action potentials. In order to illustrate this claim, we propose a model for translation-invariant pattern recognition which does not depend on any changes in synaptic efficacies.

Influence of low and high frequency inputs on spike timing in visual cortical neurons.

Cortical neurons in vivo respond to sensory stimuli with the generation of action potentials that can show a high degree of variability in both their number and timing with repeated presentations as wells as, on occasion, a high degree of synchronization with other cortical neurons, including in the gamma frequency range of 30-70 Hz. Here we examined whether or not this variability may arise from the intrinsic mechanisms of action potential generation in cortical regular spiking, fast spiking and intrinsic burst-generating neurons maintained in vitro. For this purpose, we performed intracellular recordings in slices of ferret visual cortex and activated these cells with the intracellular injection of various current waveforms. Some of these waveforms were derived from barrages of postsynaptic potentials evoked by visual stimulation recorded in vivo; others were artificially created and contained various amounts of gamma range fluctuations; finally, others consisted of swept-sinewave current (ZAP current) functions. Using such stimuli, we found that, as expected given the resistive and capacitive properties of cortical neurons, low frequencies have a larger effect on the membrane potential of cortical neurons than do higher frequencies. However, increasing the amount of gamma range fluctuations in a stimulus leads to more precise timing of action potentials. This suggests that different frequencies play different roles, low frequencies being efficient for depolarizing cells with high frequencies increasing the precision of action potential timing. In parallel to increases in temporal precision, the addition of higher frequency components increases the range of interspike intervals present in the action potential discharge. These results suggest that higher frequency components such as gamma range fluctuations may facilitate the generation of action potentials with a high temporal precision while at the same time exhibiting a high degree of variability in interspike intervals on single trials. This temporal precision may facilitate the use of temporal codes or the generation of precise synchronization for the transmission and analysis of information within cortical networks.

Synchronization of neuronal activity in hippocampus by individual GABAergic interneurons

SYNCHRONIZATION of neuronal activity is fundamental in the operation of cortical networks. With respect to an ongoing synchronized oscillation, the precise timing of action potentials is an attractive candidate mechanism for information coding. Networks of inhibitory interneurons have been proposed to have a role in entraining cortical, synchronized 40-Hz activity. Here we demonstrate that individual GABAergic interneurons can effectively phase spontaneous firing and subthreshold oscillations in hippocampal pyramidal cells at 0 frequencies (4-7 Hz). The efficiency of this entrainment is due to interaction of GABAA-receptor-mediated hyperpolarizing synaptic events with intrinsic oscillatory mechanisms tuned to this frequency range in pyramidal cells. Moreover, this GABAergic mechanism is sufficient to synchronize the firing of pyramidal cells. Thus, owing to the divergence of each GABAergic interneuron, more than a thousand pyramidal cells may share a common temporal reference established by an individual interneuron.