Dendritic Na+ Current Inactivation Can Increase Cell Excitability By Delaying a Somatic Depolarizing Afterpotential

2005 ◽  
Vol 94 (6) ◽  
pp. 3836-3848 ◽  
Author(s):  
Fernando R. Fernandez ◽  
W. Hamish Mehaffey ◽  
Ray W. Turner
Keyword(s):  
Pyramidal Cells ◽  
Firing Frequency ◽  
Weakly Electric Fish ◽  
Dynamical Analysis ◽  
Central Neurons ◽  
Electrophysiological Recordings ◽  
A Cell ◽  
Dendritic Spike ◽  
Weakly Electric ◽  
The Relationship

Many central neurons support active dendritic spike backpropagation mediated by voltage-gated currents. Active spikes in dendrites have been shown capable of providing feedback to the soma to influence somatic excitability and firing dynamics through a depolarizing afterpotential (DAP). In pyramidal cells of the electrosensory lobe of weakly electric fish, Na+ spikes in dendrites undergo a frequency-dependent broadening that enhances the DAP to increase somatic firing frequency. We use a combination of dynamical analysis and electrophysiological recordings to demonstrate that spike broadening in dendrites is primarily caused by a cumulative inactivation of dendritic Na+ current. We further show that a reduction in dendritic Na+ current increases excitability by decreasing the interspike interval and promoting burst firing. This process arises when inactivation of dendritic Na+ current shifts the latency of the dendritic spike to delay the arrival of the DAP sufficiently to increase its impact on somatic membrane potential despite a reduction in dendritic excitability. Furthermore, the relationship between dendritic Na+ current density and somatic excitability is nonmonotonic, as intermediate levels of dendritic Na+ current exert the greatest excitatory influence. These results reveal that temporal shifts in dendritic spike firing provide a novel means for backpropagating spikes to influence the final output of a cell.

scholarly journals Persistent Na+ Current Modifies Burst Discharge By Regulating Conditional Backpropagation of Dendritic Spikes

2003 ◽  
Vol 89 (1) ◽  
pp. 324-337 ◽  
Author(s):  
Brent Doiron ◽  
Liza Noonan ◽  
Neal Lemon ◽  
Ray W. Turner
Keyword(s):  
Sodium Current ◽  
Pyramidal Cells ◽  
Weakly Electric Fish ◽  
Burst Frequency ◽  
Burst Discharge ◽  
Dendritic Spikes ◽  
Dendritic Spike ◽  
Time Required ◽  
Weakly Electric ◽  
Spike Bursts

The estimation and detection of stimuli by sensory neurons is affected by factors that govern a transition from tonic to burst mode and the frequency chracteristics of burst output. Pyramidal cells in the electrosensory lobe of weakly electric fish generate spike bursts for the purpose of stimulus detection. Spike bursts are generated during repetitive discharge when a frequency-dependent broadening of dendritic spikes increases current flow from dendrite to soma to potentiate a somatic depolarizing afterpotential (DAP). The DAP eventually triggers a somatic spike doublet with an interspike interval that falls inside the dendritic refractory period, blocking spike backpropagiation and the DAP. Repetition of this process gives rise to a rhythmic dendritic spike failure, termed conditional backpropagation, that converts cell output from tonic to burst discharge. Through in vitrorecordings and compartmental modeling we show that burst frequency is regulated by the rate of DAP potentiation during a burst, which determines the time required to discharge the spike doublet that blocks backpropagation. DAP potentiation is maginfied through a postitve feedback process when an increase in dendritic spike duration activates persistent sodium current ( I NaP). I NaP further promotes a slow depolarization that induces a shift from tonic to burst discharge over time. The results are consistent with a dynamical systems analysis that shows that the threshold separating tonic and burst discharge can be represented as a saddle-node bifurcation. The interaction between dendritic K+ current and I NaP provides a physiological explanation for a variable time scale of bursting dynamics characteristic of such a bifurcation.

scholarly journals Effects of Synaptic Synchrony on the Neuronal Input-Output Relationship

2008 ◽  
Vol 20 (7) ◽  
pp. 1717-1731 ◽  
Author(s):  
Xiaoshen Li ◽  
Giorgio A. Ascoli
Keyword(s):  
Firing Rate ◽  
Pyramidal Cells ◽  
Firing Frequency ◽  
Excitatory Synapses ◽  
Memory Encoding ◽  
Input Output ◽  
High Frequencies ◽  
Dendritic Location ◽  
The Relationship ◽  
Spatiotemporal Integration

The firing rate of individual neurons depends on the firing frequency of their distributed synaptic inputs, with linear and nonlinear relations subserving different computational functions. This letter explores the relationship between the degree of synchrony among excitatory synapses and the linearity of the response using detailed compartmental models of cortical pyramidal cells. Synchronous input resulted in a linear input-output relationship, while asynchronous stimulation yielded sub- and supraproportional outputs at low and high frequencies, respectively. The dependence of input-output linearity on synchrony was sigmoidal and considerably robust with respect to dendritic location, stimulus irregularity, and alteration of active and synaptic properties. Moreover, synchrony affected firing rate differently at lower and higher input frequencies. A reduced integrate-and-fire model suggested a mechanism explaining these results based on spatiotemporal integration, with fundamental implications relating synchrony to memory encoding.

scholarly journals Population Coding by Electrosensory Neurons

2008 ◽  
Vol 99 (4) ◽  
pp. 1825-1835 ◽  
Author(s):  
Maurice J. Chacron ◽  
Joseph Bastian
Keyword(s):  
Time Window ◽  
Population Coding ◽  
Weakly Electric Fish ◽  
Critical Feature ◽  
Sensory Stimuli ◽  
Biologically Relevant ◽  
Central Neurons ◽  
Correlated Activity ◽  
The Individual ◽  
Weakly Electric

Sensory stimuli typically activate many receptors at once and therefore should lead to increases in correlated activity among central neurons. Such correlated activity could be a critical feature in the encoding and decoding of information in central circuits. Here we characterize correlated activity in response to two biologically relevant classes of sensory stimuli in the primary electrosensory nuclei, the electrosensory lateral line lobe, of the weakly electric fish Apteronotus leptorhynchus. Our results show that these neurons can display significant correlations in their baseline activities that depend on the amount of receptive field overlap. A detailed analysis of spike trains revealed that correlated activity resulted predominantly from a tendency to fire synchronous or anti-synchronous bursts of spikes. We also explored how different stimulation protocols affected correlated activity: while prey-like stimuli increased correlated activity, conspecific-like stimuli decreased correlated activity. We also computed the correlations between the variabilities of each neuron to repeated presentations of the same stimulus (noise correlations) and found lower amounts of noise correlation for communication stimuli. Therefore the decrease in correlated activity seen with communication stimuli is caused at least in part by reduced noise correlations. This differential modulation in correlated activity occurred because of changes in burst firing at the individual neuron level. Our results show that different categories of behaviorally relevant input will differentially affect correlated activity. In particular, we show that the number of correlated bursts within a given time window could be used by postsynaptic neurons to distinguish between both stimulus categories.

Interval Coding. I. Burst Interspike Intervals as Indicators of Stimulus Intensity

2007 ◽  
Vol 97 (4) ◽  
pp. 2731-2743 ◽  
Author(s):  
Anne-Marie M. Oswald ◽  
Brent Doiron ◽  
Leonard Maler
Keyword(s):  
Stimulus Intensity ◽  
Information Transfer ◽  
Pyramidal Cells ◽  
Sensory Stimulation ◽  
Weakly Electric Fish ◽  
Interspike Intervals ◽  
Direct Stimulation ◽  
Distinct Features ◽  
Weakly Electric

Short interspike intervals such as those that occur during burst firing are hypothesized to be distinct features of the neural code. Although a number of correlations between the occurrence of burst events and aspects of the stimulus have been identified, the relationship between burst characteristics and information transfer is uncertain. Pyramidal cells in the electrosensory lobe of the weakly electric fish, Apteronotus leptorhynchus, respond to dynamic broadband electrosensory stimuli with bursts and isolated spikes. In the present study, we mimic synaptic input during sensory stimulation by direct stimulation of electrosensory pyramidal cells with broadband current in vitro. The pyramidal cells respond to this stimulus with burst interspike intervals (ISIs) that are reliably and precisely correlated with the intensity of stimulus upstrokes. We found burst ISIs must differ by a minimum of 2 ms to discriminate, with low error, differences in stimulus intensity. Based on these results, we define and quantify a candidate interval code for the processing of sensory input. Finally, we demonstrate that interval coding is restricted to short ISIs such as those generated in burst events and that the proposed interval code is distinct from rate and timing codes.

scholarly journals Nonlinear Information Processing in a Model Sensory System

2006 ◽  
Vol 95 (5) ◽  
pp. 2933-2946 ◽  
Author(s):  
Maurice J. Chacron
Keyword(s):  
Pyramidal Cell ◽  
Sensory System ◽  
Sensory Information ◽  
Pyramidal Cells ◽  
Spike Trains ◽  
Weakly Electric Fish ◽  
Synaptic Noise ◽  
Optimal Linear ◽  
Pharmacological Blockade ◽  
Weakly Electric

Understanding the mechanisms by which sensory neurons encode and decode information remains an important goal in neuroscience. We quantified the performance of optimal linear and nonlinear encoding models in a well-characterized sensory system: the electric sense of weakly electric fish. We show that linear encoding models generally perform better under spatially localized stimulation than under spatially diffuse stimulation. Through pharmacological blockade of feedback input and spatial saturation of the receptive field center, we show that there is significantly less synaptic noise under spatially diffuse stimuli as compared with spatially localized stimuli. Modeling results suggest that pyramidal cells nonlinearly encode sensory information through shunting in their dendrites and clarify the influence of synaptic noise on the performance of linear encoding models. Finally, we used information theory to quantify the performance of linear decoders. While the optimal linear decoder for spatially localized stimuli could capture 60% of the information in pyramidal cell spike trains, the optimal linear decoder for spatially diffuse stimuli could only capture 40% of the information. These results show that nonlinear decoders are necessary to fully access information in pyramidal cell spike trains, and we discuss potential mechanisms by which higher-order neurons could decode this information.

scholarly journals Descending pathways mediate adaptive optimized coding of natural stimuli in weakly electric fish

2019 ◽  
Vol 5 (10) ◽  
pp. eaax2211 ◽  
Author(s):  
Chengjie G. Huang ◽  
Michael G. Metzen ◽  
Maurice J. Chacron
Keyword(s):  
Environmental Changes ◽  
Behavioral Responses ◽  
Sensory Systems ◽  
Weakly Electric Fish ◽  
Descending Pathways ◽  
Natural Stimuli ◽  
Central Neurons ◽  
Power Spectral ◽  
Underlying Mechanisms ◽  
Weakly Electric

Biological systems must be flexible to environmental changes to survive. This is exemplified by the fact that sensory systems continuously adapt to changes in the environment to optimize coding and behavioral responses. However, the nature of the underlying mechanisms remains poorly understood in general. Here, we investigated the mechanisms mediating adaptive optimized coding of naturalistic stimuli with varying statistics depending on the animal’s velocity during movement. We found that central neurons adapted their responses to stimuli with different power spectral densities such as to optimally encode them, thereby ensuring that behavioral responses are, in turn, better matched to the new stimulus statistics. Sensory adaptation further required descending inputs from the forebrain as well as the raphe nuclei. Our findings thus reveal a previously unknown functional role for descending pathways in mediating adaptive optimized coding of natural stimuli that is likely generally applicable across sensory systems and species.

scholarly journals Conditional Spike Backpropagation Generates Burst Discharge in a Sensory Neuron

2000 ◽  
Vol 84 (3) ◽  
pp. 1519-1530 ◽  
Author(s):  
N. Lemon ◽  
R. W. Turner
Keyword(s):  
Refractory Period ◽  
Interspike Interval ◽  
Pyramidal Cells ◽  
Weakly Electric Fish ◽  
Interspike Intervals ◽  
Frequency Dependent ◽  
Spike Discharge ◽  
Burst Discharge ◽  
Dendritic Spike

Backpropagating dendritic Na+spikes generate a depolarizing afterpotential (DAP) at the soma of pyramidal cells in the electrosensory lateral line lobe (ELL) of weakly electric fish. Repetitive spike discharge is associated with a progressive depolarizing shift in somatic spike afterpotentials that eventually triggers a high-frequency spike doublet and subsequent burst afterhyperpolarization (bAHP). The rhythmic generation of a spike doublet and bAHP groups spike discharge into an oscillatory burst pattern. This study examined the soma-dendritic mechanisms controlling the depolarizing shift in somatic spike afterpotentials, and the mechanism by which spike doublets terminate spike discharge. Intracellular recordings were obtained from ELL pyramidal somata and apical dendrites in an in vitro slice preparation. The pattern of spike discharge was equivalent in somatic and dendritic regions, reflecting the backpropagation of spikes from soma to dendrites. There was a clear frequency-dependent threshold in the transition from tonic to burst discharge, with bursts initiated when interspike intervals fell between ∼3–7 ms. Removal of all backpropagating spikes by dendritic TTX ejection revealed that the isolated somatic AHPs were entirely stable at the interspike intervals that generated burst discharge. As such, the depolarizing membrane potential shift during repetitive discharge could be attributed to a potentiation of DAP amplitude. Potentiation of the DAP was due to a frequency-dependent broadening and temporal summation of backpropagating dendritic Na+ spikes. Spike doublets were generated with an interspike interval close to, but not within, the somatic spike refractory period. In contrast, the interspike interval of spike doublets always fell within the longer dendritic refractory period, preventing backpropagation of the second spike of the doublet. The dendritic depolarization was thus abruptly removed from one spike to the next, allowing the burst to terminate when the bAHP hyperpolarized the membrane. The transition from tonic to burst discharge was dependent on the number and frequency of spikes invoking dendritic spike summation, indicating that burst threshold depends on the immediate history of cell discharge. Spike frequency thus represents an important condition that determines the success of dendritic spike invasion, establishing an intrinsic mechanism by which backpropagating spikes can be used to generate a rhythmic burst output.

scholarly journals Theta oscillations coincide with sustained hyperpolarization in CA3 pyramidal cells, underlying decreased firing

2019 ◽  
Author(s):  
Meryl Malezieux ◽  
Ashley L. Kees ◽  
Christophe Mulle
Keyword(s):  
Membrane Potential ◽  
Signal To Noise Ratio ◽  
Pyramidal Cells ◽  
Small Population ◽  
Theta Oscillations ◽  
Brain State ◽  
Electrophysiological Recordings ◽  
Hippocampal Ca3 ◽  
Ca3 Pyramidal Cells ◽  
The Relationship

SummaryBrain-state fluctuations modulate membrane potential dynamics of neurons, influencing the functional repertoire of the network. Pyramidal cells (PCs) in hippocampal CA3 are necessary for rapid memory encoding, preferentially occurring during exploratory behavior in the high-arousal theta state. However, the relationship between the membrane potential dynamics of CA3 PCs and theta has not been explored. Here, we characterize the changes in the membrane potential of PCs in relation to theta using electrophysiological recordings in awake mice. During theta, most PCs behave in a stereotypical manner, consistently hyperpolarizing time-locked to the duration of theta. Additionally, PCs display lower membrane potential variance and reduced firing rate. In contrast, during large irregular activity, a low-arousal state, PCs show heterogeneous changes in membrane potential. This suggests coordinated hyperpolarization of PCs during theta, possibly caused by increased inhibition. This could lead to higher signal-to-noise ratio in the small population of PCs active during theta as observed in ensemble recordings.

scholarly journals Sparse and dense coding of natural stimuli by distinct midbrain neuron subpopulations in weakly electric fish

2011 ◽  
Vol 106 (6) ◽  
pp. 3102-3118 ◽  
Author(s):  
Katrin Vonderschen ◽  
Maurice J. Chacron
Keyword(s):  
Sparse Coding ◽  
Electric Fish ◽  
Neural Representation ◽  
Weakly Electric Fish ◽  
Torus Semicircularis ◽  
Dense Coding ◽  
Natural Stimuli ◽  
Central Neurons ◽  
Weakly Electric ◽  
Peripheral Sensory

While peripheral sensory neurons respond to natural stimuli with a broad range of spatiotemporal frequencies, central neurons instead respond sparsely to specific features in general. The nonlinear transformations leading to this emergent selectivity are not well understood. Here we characterized how the neural representation of stimuli changes across successive brain areas, using the electrosensory system of weakly electric fish as a model system. We found that midbrain torus semicircularis (TS) neurons were on average more selective in their responses than hindbrain electrosensory lateral line lobe (ELL) neurons. Further analysis revealed two categories of TS neurons: dense coding TS neurons that were ELL-like and sparse coding TS neurons that displayed selective responses. These neurons in general responded to preferred stimuli with few spikes and were mostly silent for other stimuli. We further investigated whether information about stimulus attributes was contained in the activities of ELL and TS neurons. To do so, we used a spike train metric to quantify how well stimuli could be discriminated based on spiking responses. We found that sparse coding TS neurons performed poorly even when their activities were combined compared with ELL and dense coding TS neurons. In contrast, combining the activities of as few as 12 dense coding TS neurons could lead to optimal discrimination. On the other hand, sparse coding TS neurons were better detectors of whether their preferred stimulus occurred compared with either dense coding TS or ELL neurons. Our results therefore suggest that the TS implements parallel detection and estimation of sensory input.

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