Response Properties and Synchronization of Rhythmically Firing Dendritic Neurons

2007 ◽  
Vol 97 (1) ◽  
pp. 208-219 ◽  
Author(s):  
Joshua A. Goldberg ◽  
Chris A. Deister ◽  
Charles J. Wilson
Keyword(s):  
Pyramidal Neurons ◽  
Phase Response Curve ◽  
Qualitative Difference ◽  
Apical Dendrite ◽  
Neuronal Firing ◽  
Closed Form Expression ◽  
Pass Filter ◽  
Cortical Pyramidal Neurons ◽  
The Impact ◽  
High Pass

The responsiveness of rhythmically firing neurons to synaptic inputs is characterized by their phase-response curve (PRC), which relates how weak somatic perturbations affect the timing of the next action potential. The shape of the somatic PRC is an important determinant of collective network dynamics. Here we study theoretically and experimentally the impact of distally located synapses and dendritic nonlinearities on the synchronization properties of rhythmically firing neurons. By combining the theories of quasi-active cables and phase-coupled oscillators we derive an approximation for the dendritic responsiveness, captured by the neuron's dendritic PRC (dPRC). This closed-form expression indicates that the dPRCs are linearly filtered versions of the somatic PRC and that the filter characteristics are determined by the passive and active properties of the dendrite. The passive properties induce leftward shifts in the dPRCs and attenuate them. Our analysis yields a single dimensionless parameter that classifies active dendritic conductances as either regenerative conductances that counter the passive properties by boosting the dPRCs or restorative conductances that high-pass filter the dPRCs. Thus dendritic properties can generate a qualitative difference between the somatic and dendritic PRCs. As a result collective dynamics can be qualitatively different depending on the location of the synapse, the neuronal firing rates, and the dendritic nonlinearities. Finally, we use dual whole cell recordings from the soma and apical dendrite of cortical pyramidal neurons to test these predictions and find that empirical dPRCs are shifted leftward, as predicted, but may also display high-pass characteristics resulting from the restorative dendritic HCN (h) current.

Effect of Common Anesthetics on Dendritic Properties in Layer 5 Neocortical Pyramidal Neurons

2008 ◽  
Vol 99 (3) ◽  
pp. 1394-1407 ◽  
Author(s):  
Sarah Potez ◽  
Matthew E. Larkum
Keyword(s):  
High Frequency ◽  
Pyramidal Neurons ◽  
Animal Experiments ◽  
Apical Dendrite ◽  
Network Activity ◽  
Calcium Spikes ◽  
Firing Properties ◽  
The Impact

Understanding the impact of active dendritic properties on network activity in vivo has so far been restricted to studies in anesthetized animals. However, to date no study has been made to determine the direct effect of the anesthetics themselves on dendritic properties. Here, we investigated the effects of three types of anesthetics commonly used for animal experiments (urethane, pentobarbital and ketamine/xylazine). We investigated the generation of calcium spikes, the propagation of action potentials (APs) along the apical dendrite and the somatic firing properties in the presence of anesthetics in vitro using dual somatodendritic whole cell recordings. Calcium spikes were evoked with dendritic current injection and high-frequency trains of APs at the soma. Surprisingly, we found that the direct actions of anesthetics on calcium spikes were very different. Two anesthetics (urethane and pentobarbital) suppressed dendritic calcium spikes in vitro, whereas a mixture of ketamine and xylazine enhanced them. Propagation of spikes along the dendrite was not significantly affected by any of the anesthetics but there were various changes in somatic firing properties that were highly dependent on the anesthetic. Last, we examined the effects of anesthetics on calcium spike initiation and duration in vivo using high-frequency trains of APs generated at the cell body. We found the same anesthetic-dependent direct effects in addition to an overall reduction in dendritic excitability in anesthetized rats with all three anesthetics compared with the slice preparation.

Calcium Coding and Adaptive Temporal Computation in Cortical Pyramidal Neurons

1998 ◽  
Vol 79 (3) ◽  
pp. 1549-1566 ◽  
Author(s):  
Xiao-Jing Wang
Keyword(s):  
Current Pulse ◽  
Pyramidal Neurons ◽  
Model Neuron ◽  
Pyramidal Cells ◽  
Spike Frequency ◽  
Neuronal Firing ◽  
Spike Frequency Adaptation ◽  
Synaptic Inputs ◽  
Cortical Pyramidal Neurons ◽  
Intracellular Ca

Wang, Xiao-Jing. Calcium coding and adaptive temporal computation in cortical pyramidal neurons. J. Neurophysiol. 79: 1549–1566, 1998. In this work, we present a quantitative theory of temporal spike-frequency adaptation in cortical pyramidal cells. Our model pyramidal neuron has two-compartments (a “soma” and a “dendrite”) with a voltage-gated Ca2+ conductance ( g Ca) and a Ca2+-dependent K+ conductance ( g AHP) located at the dendrite or at both compartments. Its frequency-current relations are comparable with data from cortical pyramidal cells, and the properties of spike-evoked intracellular [Ca2+] transients are matched with recent dendritic [Ca2+] imaging measurements. Spike-frequency adaptation in response to a current pulse is characterized by an adaptation time constant τadap and percentage adaptation of spike frequency F adap [% (peak − steady state)/peak]. We show how τadap and F adap can be derived in terms of the biophysical parameters of the neural membrane and [Ca2+] dynamics. Two simple, experimentally testable, relations between τadap and F adap are predicted. The dependence of τadap and F adap on current pulse intensity, electrotonic coupling between the two compartments, g AHP as well the [Ca2+] decay time constant τCa, is assessed quantitatively. In addition, we demonstrate that the intracellular [Ca2+] signal can encode the instantaneous neuronal firing rate and that the conductance-based model can be reduced to a simple calcium-model of neuronal activity that faithfully predicts the neuronal firing output even when the input varies relatively rapidly in time (tens to hundreds of milliseconds). Extensive simulations have been carried out for the model neuron with random excitatory synaptic inputs mimicked by a Poisson process. Our findings include 1) the instantaneous firing frequency (averaged over trials) shows strong adaptation similar to the case with current pulses; 2) when the g AHP is blocked, the dendritic g Ca could produce a hysteresis phenomenon where the neuron is driven to switch randomly between a quiescent state and a repetitive firing state. The firing pattern is very irregular with a large coefficient of variation of the interspike intervals (ISI CV > 1). The ISI distribution shows a long tail but is not bimodal. 3) By contrast, in an intrinsically bursting regime (with different parameter values), the model neuron displays a random temporal mixture of single action potentials and brief bursts of spikes. Its ISI distribution is often bimodal and its power spectrum has a peak. 4) The spike-adapting current I AHP, as delayed inhibition through intracellular Ca2+ accumulation, generates a “forward masking” effect, where a masking input dramatically reduces or completely suppresses the neuronal response to a subsequent test input. When two inputs are presented repetitively in time, this mechanism greatly enhances the ratio of the responses to the stronger and weaker inputs, fulfilling a cellular form of lateral inhibition in time. 5) The [Ca2+]-dependent I AHP provides a mechanism by which the neuron unceasingly adapts to the stochastic synaptic inputs, even in the stationary state following the input onset. This creates strong negative correlations between output ISIs in a frequency-dependent manner, while the Poisson input is totally uncorrelated in time. Possible functional implications of these results are discussed.

scholarly journals Spike initiation properties in the axon support high-fidelity signal transmission

2021 ◽  
Author(s):  
Mohammad Amin Kamaleddin ◽  
Nooshin Abdollahi ◽  
Stephanie Ratte ◽  
Steven A Prescott
Keyword(s):  
Pyramidal Neurons ◽  
Signal To Noise Ratio ◽  
Signal Transmission ◽  
Digital Signal ◽  
Axial Current ◽  
High Fidelity ◽  
Pass Filter ◽  
Analog To Digital ◽  
Spike Initiation ◽  
High Pass

The axon initial segment (AIS) converts graded depolarization into all-or-none spikes that are transmitted by the axon to downstream neurons. Analog-to-digital transduction and digital signal transmission call for distinct spike initiation properties (filters) and those filters should, therefore, differ between the AIS and distal axon. Here we show that unlike the AIS, which spikes repetitively during sustained depolarization, the axon spikes transiently and only if depolarization reaches threshold before KV1 channels activate. Rate of depolarization is critical. This was shown by optogenetically evoking spikes in the distal axon of CA1 pyramidal neurons using different photostimulus waveforms and pharmacological conditions while recording antidromically propagated spikes at the soma, thus circumventing the prohibitive difficulty of patching intact axons. Computational modeling shows that KV1 channels in the axon implement a high-pass filter that is matched to the axial current waveform associated with spike propagation, thus maximizing the signal-to-noise ratio to ensure high-fidelity transmission of spike-based signals.

scholarly journals Spectral reconstruction of phase response curves reveals the synchronization properties of mouse globus pallidus neurons

2013 ◽  
Vol 110 (10) ◽  
pp. 2497-2506 ◽  
Author(s):  
Joshua A. Goldberg ◽  
Jeremy F. Atherton ◽  
D. James Surmeier
Keyword(s):  
Pyramidal Neurons ◽  
Phase Response Curve ◽  
Numerical Models ◽  
Low Noise ◽  
Phase Response ◽  
Response Curves ◽  
Spectral Reconstruction ◽  
Cortical Pyramidal Neurons ◽  
Low Dimensional

The propensity of a neuron to synchronize is captured by its infinitesimal phase response curve (iPRC). Determining whether an iPRC is biphasic, meaning that small depolarizing perturbations can actually delay the next spike, if delivered at appropriate phases, is a daunting experimental task because negative lobes in the iPRC (unlike positive ones) tend to be small and may be occluded by the normal discharge variability of a neuron. To circumvent this problem, iPRCs are commonly derived from numerical models of neurons. Here, we propose a novel and natural method to estimate the iPRC by direct estimation of its spectral modes. First, we show analytically that the spectral modes of the iPRC of an arbitrary oscillator are readily measured by applying weak harmonic perturbations. Next, applying this methodology to biophysical neuronal models, we show that a low-dimensional spectral reconstruction is sufficient to capture the structure of the iPRC. This structure was preserved reasonably well even with added physiological scale jitter in the neuronal models. To validate the methodology empirically, we applied it first to a low-noise electronic oscillator with a known design and then to cortical pyramidal neurons, recorded in whole cell configuration, that are known to possess a monophasic iPRC. Finally, using the methodology in conjunction with perforated-patch recordings from pallidal neurons, we show, in contrast to recent modeling studies, that these neurons have biphasic somatic iPRCs. Biphasic iPRCs would cause lateral somatically targeted pallidal inhibition to desynchronize pallidal neurons, providing a plausible explanation for their lack of synchrony in vivo.

Glutamate Receptors Form Hot Spots on Apical Dendrites of Neocortical Pyramidal Neurons

2001 ◽  
Vol 86 (3) ◽  
pp. 1412-1421 ◽  
Author(s):  
A. Frick ◽  
W. Zieglgänsberger ◽  
H.-U. Dodt
Keyword(s):  
Glutamate Receptors ◽  
Hot Spots ◽  
Pyramidal Neurons ◽  
Flash Photolysis ◽  
Apical Dendrite ◽  
Brain Regions ◽  
Branch Points ◽  
Cortical Pyramidal Neurons ◽  
Layer V ◽  
Apical Dendrites

Apical dendrites of layer V cortical pyramidal neurons are a major target for glutamatergic synaptic inputs from cortical and subcortical brain regions. Because innervation from these regions is somewhat laminar along the dendrites, knowing the distribution of glutamate receptors on the apical dendrites is of prime importance for understanding the function of neural circuits in the neocortex. To examine this issue, we used infrared-guided laser stimulation combined with whole cell recordings to quantify the spatial distribution of glutamate receptors along the apical dendrites of layer V pyramidal neurons. Focally applied (<10 μm) flash photolysis of caged glutamate on the soma and along the apical dendrite revealed a highly nonuniform distribution of glutamate responsivity. Up to four membrane areas (extent 22 μm) of enhanced glutamate responsivity (hot spots) were detected on the dendrites with the amplitude and integral of glutamate-evoked responses at hot spots being three times larger than responses evoked at neighboring sites. We found no association of these physiological hot spots with dendritic branch points. It appeared that the larger responses evoked at hot spots resulted from an increase in activation of both α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) and N-methyl-d-aspartate (NMDA) receptors and not a recruitment of voltage-activated sodium or calcium conductances. Stimulation of hot spots did, however, facilitate the triggering of both Na+ spikes and Ca2+ spikes, suggesting that hot spots may serve as dendritic initiation zones for regenerative spikes.

Altered dendritic complexity affects firing properties of cortical layer 2/3 pyramidal neurons in mice lacking the 5-HT3A receptor

2012 ◽  
Vol 108 (5) ◽  
pp. 1521-1528 ◽  
Author(s):  
Luuk van der Velden ◽  
Johannes A. van Hooft ◽  
Pascal Chameau
Keyword(s):  
Firing Pattern ◽  
Neuronal Excitability ◽  
Pyramidal Neurons ◽  
Dendritic Morphology ◽  
Neuronal Firing ◽  
Specific Class ◽  
Postnatal Maturation ◽  
Layer 2 ◽  
The Impact ◽  
Dendritic Complexity

We have previously shown that the serotonergic input on Cajal-Retzius cells, mediated by 5-HT3 receptors, plays an important role in the early postnatal maturation of the apical dendritic trees of layer 2/3 pyramidal neurons. We reported that knockout mice lacking the 5-HT3A receptor showed exuberant apical dendrites of these cortical pyramidal neurons. Because model studies have shown the role of dendritic morphology on neuronal firing pattern, we used the 5-HT3A knockout mouse to explore the impact of dendritic hypercomplexity on the electrophysiological properties of this specific class of neurons. Our experimental results show that hypercomplexity of the apical dendritic tuft of layer 2/3 pyramidal neurons affects neuronal excitability by reducing the amount of spike frequency adaptation. This difference in firing pattern, related to a higher dendritic complexity, was accompanied by an altered development of the afterhyperpolarization slope with successive action potentials. Our abstract and realistic neuronal models, which allowed manipulation of the dendritic complexity, showed similar effects on neuronal excitability and confirmed the impact of apical dendritic complexity. Alterations of dendritic complexity, as observed in several pathological conditions such as neurodegenerative diseases or neurodevelopmental disorders, may thus not only affect the input to layer 2/3 pyramidal neurons but also shape their firing pattern and consequently alter the information processing in the cortex.

scholarly journals Whole-neuron synaptic mapping reveals local balance between excitatory and inhibitory synapse organization

2018 ◽  
Author(s):  
Daniel Maxim Iascone ◽  
Yujie Li ◽  
Uygar Sümbül ◽  
Michael Doron ◽  
Hanbo Chen ◽  
...  
Keyword(s):  
Spatial Organization ◽  
Pyramidal Neurons ◽  
Neural Circuits ◽  
Dendritic Tree ◽  
Neuronal Firing ◽  
Source Reconstruction ◽  
Domain Specific ◽  
Absolute Density ◽  
Cortical Pyramidal Neurons

SUMMARYThe balance between excitatory and inhibitory (E and I) synaptic inputs is thought to be critical for information processing in neural circuits. However, little is known about the principles of spatial organization of E and I synapses across the entire dendritic tree of mammalian neurons. We developed a new, open-source, reconstruction platform for mapping the size and spatial distribution of E and I synapses received by individual, genetically-labeled, layer 2/3 cortical pyramidal neurons (PNs) in vivo. We mapped over 90,000 E and I synapses across twelve L2/3 PNs and uncovered structured organization of E and I synapses across dendritic domains as well as within individual dendritic segments in these cells. Despite significant, domain-specific, variations in the absolute density of E and I synapses, their ratio is strikingly balanced locally across dendritic segments. Computational modeling indicates that this spatially-precise E/I balance dampens dendritic voltage fluctuations and strongly impacts neuronal firing output.

scholarly journals Motion Cueing Algorithm Online Parameter Switching in a Blink of an Eye—A Time-Variant Approach

2011 ◽  
Vol 11 (4) ◽  
Author(s):  
Tobias Lorenz ◽  
Klaus Jaschke ◽  
Frank Köster
Keyword(s):  
Output Signal ◽  
The State ◽  
Corner Frequency ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Pass Filter ◽  
Motion Cueing ◽  
Assistance Systems ◽  
The Impact ◽  
High Pass

The development and evaluation of human centered driver assistance systems is one major research focus within the automotive domain of the Institute of Transportation Systems (TS) at the German Aerospace Center (DLR). To investigate the impact of new driver assistance systems on driver behavior different research facilities from simulations to real car environments are used. One research facility at TS is the dynamic driving simulator with a hexapod structure. Using dynamic driving simulators to reproduce real car motion is a major challenge as the workspace is limited. Within this paper a method of state adaption is presented. This method enables a discrete switching of high-pass filter corner frequencies within one single simulation time step. Thereby discontinuities of the filter output signal as well as in the derivatives of the output signal are avoidable. Thus, it is possible to adapt corner frequencies of high-pass filters of a Motion Cueing Algorithm (MCA), according to the current driving situation. The paper starts with a description of the MCA currently used for the motion rendering at TS. Afterward the state adaption method is described including the challenges for adapting this method to the current MCA structure. In the end of the new structure for the time-variant MCA as well as the boundary conditions for corner frequency switching and the test results of the new time-variant approach using the state adaption method are outlined.

A V-Band Two Pole High-Pass Filter for Frequency Quadrupler Design

2016 ◽  
Vol 6 (1) ◽  
pp. 56
Author(s):  
Maryam Abata ◽  
Mahmoud Mehdi ◽  
Said Mazer ◽  
Moulhime El Bekkali ◽  
Catherine Algani
Keyword(s):  
Pass Filter ◽  
High Pass Filter ◽  
V Band ◽  
High Pass
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