scholarly journals Slow Spike Frequency Adaptation in Neurons of the Rat Subthalamic Nucleus

2009 ◽  
Vol 102 (6) ◽  
pp. 3689-3697 ◽  
Author(s):  
David Barraza ◽  
Hitoshi Kita ◽  
Charles J. Wilson
Keyword(s):  
Firing Rate ◽  
Subthalamic Nucleus ◽  
Similar Rate ◽  
Excitatory Input ◽  
Spike Frequency ◽  
Spike Frequency Adaptation ◽  
Frequency Adaptation ◽  
Long Duration ◽  
Subthalamic Neurons

Neurons of the subthalamic nucleus (STN) are very sensitive to applied currents, firing at 10–20/s during spontaneous activity, but increasing to peak firing rates of 200/s with applied currents <0.5 nA. They receive a powerful tonic excitatory input from neurons in the cerebral cortex, yet in vivo maintain an irregular firing rate only slightly higher than the autonomous firing rate seen in slices. Spike frequency adaptation acts to normalize background firing rate by removing slow trends in firing due to changes in average input. Subthalamic neurons have been previously described as showing little spike frequency adaptation, but this was based on tests using brief stimuli. We applied long-duration depolarizing current steps to STN neurons in slices and observed a very strong spike frequency adaptation with a time constant of 20 s and that recovered at a similar rate. This adaptation could return firing to near-baseline levels during prolonged current pulses that transiently drove the cells at high rates. The current responsible for adaptation was studied in voltage clamp during and after high-frequency driving of the cell and was determined to be a slowly accumulating K+ current. This current was independent of calcium or sodium entry and could be induced with long-duration voltage steps after blockade of action potentials. In addition to the adaptation current, driven firing produced slow inactivation of the persistent Na+ current, which also contributed to the reduced excitability of STN cells during and after driven firing.

scholarly journals Spike Frequency Adaptation and Neocortical Rhythms

2002 ◽  
Vol 88 (2) ◽  
pp. 761-770 ◽  
Author(s):  
Galit Fuhrmann ◽  
Henry Markram ◽  
Misha Tsodyks
Keyword(s):  
Firing Rate ◽  
Pyramidal Neurons ◽  
Spike Frequency ◽  
Spike Frequency Adaptation ◽  
Patch Clamp Technique ◽  
Response Characteristics ◽  
Frequency Adaptation ◽  
Whole Cell Patch Clamp ◽  
The Mean

Spike-frequency adaptation in neocortical pyramidal neurons was examined using the whole cell patch-clamp technique and a phenomenological model of neuronal activity. Noisy current was injected to reproduce the irregular firing typically observed under in vivo conditions. The response was quantified by computing the poststimulus histogram (PSTH). To simulate the spiking activity of a pyramidal neuron, we considered an integrate-and-fire model to which an adaptation current was added. A simplified model for the mean firing rate of an adapting neuron under noisy conditions is also presented. The mean firing rate model provides a good fit to both experimental and simulation PSTHs and may therefore be used to study the response characteristics of adapting neurons to various input currents. The models enable identification of the relevant parameters of adaptation that determine the shape of the PSTH and allow the computation of the response to any change in injected current. The results suggest that spike frequency adaptation determines a preferred frequency of stimulation for which the phase delay of a neuron's activity relative to an oscillatory input is zero. Simulations show that the preferred frequency of single neurons dictates the frequency of emergent population rhythms in large networks of adapting neurons. Adaptation could therefore be one of the crucial factors in setting the frequency of population rhythms in the neocortex.

scholarly journals Selective attenuation of Ether-a-go-go related K+ currents by endogenous acetylcholine reduces spike-frequency adaptation and network correlation

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Edward D Cui ◽  
Ben W Strowbridge
Keyword(s):  
Late Phase ◽  
Pyramidal Cells ◽  
Spike Frequency ◽  
Spike Frequency Adaptation ◽  
Firing Rates ◽  
Frequency Adaptation ◽  
Rat Neocortex ◽  
Persistent Firing ◽  
K Current

Most neurons do not simply convert inputs into firing rates. Instead, moment-to-moment firing rates reflect interactions between synaptic inputs and intrinsic currents. Few studies investigated how intrinsic currents function together to modulate output discharges and which of the currents attenuated by synthetic cholinergic ligands are actually modulated by endogenous acetylcholine (ACh). In this study we optogenetically stimulated cholinergic fibers in rat neocortex and find that ACh enhances excitability by reducing Ether-à-go-go Related Gene (ERG) K+ current. We find ERG mediates the late phase of spike-frequency adaptation in pyramidal cells and is recruited later than both SK and M currents. Attenuation of ERG during coincident depolarization and ACh release leads to reduced late phase spike-frequency adaptation and persistent firing. In neuronal ensembles, attenuating ERG enhanced signal-to-noise ratios and reduced signal correlation, suggesting that these two hallmarks of cholinergic function in vivo may result from modulation of intrinsic properties.

scholarly journals Spontaneous Motion on Two-Dimensional Continuous Attractors

2015 ◽  
Vol 27 (3) ◽  
pp. 507-547 ◽  
Author(s):  
C. C. Alan Fung ◽  
S.-i. Amari
Keyword(s):  
Firing Rate ◽  
Synaptic Depression ◽  
Object Motion ◽  
Spike Frequency ◽  
Two Dimensional ◽  
Spike Frequency Adaptation ◽  
Short Term ◽  
Perturbative Approach ◽  
Frequency Adaptation ◽  
Spontaneous Motion

Attractor models are simplified models used to describe the dynamics of firing rate profiles of a pool of neurons. The firing rate profile, or the neuronal activity, is thought to carry information. Continuous attractor neural networks (CANNs) describe the neural processing of continuous information such as object position, object orientation, and direction of object motion. Recently it was found that in one-dimensional CANNs, short-term synaptic depression can destabilize bump-shaped neuronal attractor activity profiles. In this article, we study two-dimensional CANNs with short-term synaptic depression and spike frequency adaptation. We found that the dynamics of CANNs with short-term synaptic depression and CANNs with spike frequency adaptation are qualitatively similar. We also found that in both kinds of CANNs, the perturbative approach can be used to predict phase diagrams, dynamical variables, and speed of spontaneous motion.

A firing-rate model of spike-frequency adaptation in sinusoidally-driven thalamocortical relay neurons

2001 ◽  
Vol 1 (02) ◽  
pp. 135 ◽  
Author(s):  
Gregory D. Smith ◽  
Charles L. Cox ◽  
Murray S. Sherman ◽  
John Rinzel
Keyword(s):  
Firing Rate ◽  
Spike Frequency ◽  
Spike Frequency Adaptation ◽  
Rate Model ◽  
Frequency Adaptation ◽  
Relay Neurons

Electrophysiological Classes of Cat Primary Visual Cortical Neurons In Vivo as Revealed by Quantitative Analyses

2003 ◽  
Vol 89 (3) ◽  
pp. 1541-1566 ◽  
Author(s):  
Lionel G. Nowak ◽  
Rony Azouz ◽  
Maria V. Sanchez-Vives ◽  
Charles M. Gray ◽  
David A. McCormick
Keyword(s):  
Short Duration ◽  
Cortical Neurons ◽  
Action Potentials ◽  
Low Frequency ◽  
Pyramidal Cells ◽  
Spike Frequency ◽  
Spike Frequency Adaptation ◽  
Frequency Adaptation ◽  
Layer 4

To facilitate the characterization of cortical neuronal function, the responses of cells in cat area 17 to intracellular injection of current pulses were quantitatively analyzed. A variety of response variables were used to separate the cells into subtypes using cluster analysis. Four main classes of neurons could be clearly distinguished: regular spiking (RS), fast spiking (FS), intrinsic bursting (IB), and chattering (CH). Each of these contained significant subclasses. RS neurons were characterized by trains of action potentials that exhibited spike frequency adaptation. Morphologically, these cells were spiny stellate cells in layer 4 and pyramidal cells in layers 2, 3, 5, and 6. FS neurons had short-duration action potentials (<0.5 ms at half height), little or no spike frequency adaptation, and a steep relationship between injected current intensity and spike discharge frequency. Morphologically, these cells were sparsely spiny or aspiny nonpyramidal cells. IB neurons typically generated a low frequency (<425 Hz) burst of spikes at the beginning of a depolarizing current pulse followed by a tonic train of action potentials for the remainder of the pulse. These cells were observed in all cortical layers, but were most abundant in layer 5. Finally, CH neurons generated repetitive, high-frequency (350–700 Hz) bursts of short-duration (<0.55 ms) action potentials. Morphologically, these cells were layer 2–4 (mainly layer 3) pyramidal or spiny stellate neurons. These results indicate that firing properties do not form a continuum and that cortical neurons are members of distinct electrophysiological classes and subclasses.

A Model of Reverse Spike Frequency Adaptation and Repetitive Firing of Subthalamic Nucleus Neurons

2004 ◽  
Vol 91 (5) ◽  
pp. 1963-1980 ◽  
Author(s):  
Charles J. Wilson ◽  
Angela Weyrick ◽  
David Terman ◽  
Nicholas E. Hallworth ◽  
Mark D. Bevan
Keyword(s):  
Steady State ◽  
Subthalamic Nucleus ◽  
Spike Frequency ◽  
Calcium Currents ◽  
Repetitive Firing ◽  
Spike Frequency Adaptation ◽  
Firing Rates ◽  
Spike Threshold ◽  
Secondary Range ◽  
Frequency Adaptation

Subthalamic nucleus neurons exhibit reverse spike-frequency adaptation. This occurs only at firing rates of 20–50 spikes/s and higher. Over this same frequency range, there is an increase in the steady-state frequency–intensity ( F– I) curve's slope (the secondary range). Specific blockade of high-voltage activated calcium currents reduced the F– I curve slope and reverse adaptation. Blockade of calcium-dependent potassium current enhanced secondary range firing. A simple model that exhibited these properties used spike-triggered conductances similar to those in subthalamic neurons. It showed: 1) Nonaccumulating spike afterhyperpolarizations produce positively accelerating F– I curves and spike-frequency adaptation that is complete after the second spike. 2) Combinations of accumulating aftercurrents result in a linear F– I curve, whose slope depends on the relative contributions of inward and outward currents. Spike-frequency adaptation can be gradual. 3) With both accumulating and nonaccumulating aftercurrents, primary and secondary ranges will be present in the F– I curve. The slope of the primary range is determined by the nonaccumulating conductance; the accumulating conductances govern the secondary range. The transition is determined by the relative strengths of accumulating and nonaccumulating currents. 4) Spike-threshold accommodation contributes to the secondary range, reducing its slope at high firing rates. Threshold accommodation can stabilize firing when inward aftercurrents exceed outward ones. 5) Steady-state reverse adaptation results when accumulated inward aftercurrents exceed outward ones. This requires spike-threshold accommodation. Transient speedup arises when inward currents are smaller than outward ones at steady state, but accumulate more rapidly. 6) The same mechanisms alter firing in response to irregular patterns of synaptic conductances, as cell excitability fluctuates with changes in firing rate.

Encoder Adaptation Modulates the Visual Responses of Crayfish Interneurons

2004 ◽  
Vol 92 (1) ◽  
pp. 327-340 ◽  
Author(s):  
Raymon M. Glantz ◽  
John P. Schroeter
Keyword(s):  
Firing Rate ◽  
Time Course ◽  
Light Flash ◽  
Time Derivative ◽  
Input Resistance ◽  
Spike Frequency ◽  
Visual Response ◽  
Spike Frequency Adaptation ◽  
Visual Responses ◽  
Frequency Adaptation

The responses of sustaining and dimming fibers were characterized by the time varying firing rates elicited by extrinsic current and flashes of light. These data were simulated by an adaptive integrate-and-fire model. A postimpulse shunt conductance simulated spike-frequency adaptation. The correlation between observed and model current-elicited impulse rates was 0.94–0.98. However, except for a difference in input resistance (both measured and simulated), the voltage to impulse encoders of the two cell groups was similar and exhibited comparable degrees of spike-frequency adaptation (40 to 45%). The encoder model derived from current-elicited responses (with fixed parameters) was used to simulate visual responses elicited by light flashes. These simulations included a synaptic current derived from the time course of the postsynaptic potential (PSP). The sustaining fiber visual response consisted of a large excitatory PSP and high-frequency transient burst that adapted (by ∼80%) to a low-frequency plateau discharge. The simulations indicated that spike-frequency adaptation had no effect on the transient discharge but reduced the plateau firing rate by ∼60%. Encoder adaptation enhances the sustaining fiber response to the time derivative of the stimulus. In dimming fibers, the light flash elicits an inhibitory PSP that interrupts the “dark discharge” and an off response following the end of the flash. The simulations indicated that spike-frequency adaptation reduces the firing rate of both the dark discharge and the off response. Thus the model suggests that different effects of encoder adaptation on the two cell types arise from the same encoder mechanisms, but different actions are determined by differences in impulse rate and the time course of the discharge.

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