Dendritic Modulation of Burst-Like Firing in Sensory Neurons

2001 ◽  
Vol 85 (1) ◽  
pp. 10-22 ◽  
Author(s):  
Joseph Bastian ◽  
Jerry Nguyenkim
Keyword(s):  
Spike Train ◽  
Sensory Neurons ◽  
Lateral Line ◽  
Interspike Interval ◽  
Pyramidal Cells ◽  
Spike Trains ◽  
Firing Frequency ◽  
Dendritic Morphology ◽  
Spontaneous Firing ◽  
Apical Dendrites

This report describes the variability of spontaneous firing characteristics of sensory neurons, electrosensory lateral line lobe (ELL) pyramidal cells, within the electrosensory lateral line lobe of weakly electric fish in vivo. We show that these cells' spontaneous firing frequency, measures of spike train regularity (interspike interval coefficient of variation), and the tendency of these cells to produce bursts of action potentials are correlated with the size of the cell's apical dendritic arbor. We also show that bursting behavior may be influenced or controlled by descending inputs from higher centers that provide excitatory and inhibitory inputs to the pyramidal cells' apical dendrites. Pyramidal cells were classified as “bursty” or “nonbursty” according to whether or not spike trains deviated significantly from the expected properties of random (Poisson) spike trains of the same average firing frequency, and, in the case of bursty cells, the maximum within-burst interspike interval characteristic of bursts was determined. Each cell's probability of producing bursts above the level expected for a Poisson spike train was determined and related to spontaneous firing frequency and dendritic morphology. Pyramidal cells with large apical dendritic arbors have lower rates of spontaneous activity and higher probabilities of producing bursts above the expected level, while cells with smaller apical dendrites fire at higher frequencies and are less bursty. The effect of blocking non- N-methyl-d-aspartate (non-NMDA) glutamatergic synaptic inputs to the apical dendrites of these cells, and to local inhibitory interneurons, significantly reduced the spontaneous occurrence of spike bursts and intracellular injection of hyperpolarizing current mimicked this effect. The results suggest that bursty firing of ELL pyramidal cells may be under descending control allowing activity in electrosensory feedback pathways to influence the firing properties of sensory neurons early in the processing hierarchy.

Single-unit analysis of different hippocampal cell types during classical conditioning of rabbit nictitating membrane response

1983 ◽  
Vol 50 (5) ◽  
pp. 1197-1219 ◽  
Author(s):  
T. W. Berger ◽  
P. C. Rinaldi ◽  
D. J. Weisz ◽  
R. F. Thompson
Keyword(s):  
Classical Conditioning ◽  
Pyramidal Cell ◽  
Action Potentials ◽  
Pyramidal Cells ◽  
Cell Types ◽  
Firing Frequency ◽  
Spontaneous Firing ◽  
Nictitating Membrane ◽  
Nictitating Membrane Response ◽  
Firing Characteristics

Extracellular single-unit recordings from neurons in the CA1 and CA3 regions of the dorsal hippocampus were monitored during classical conditioning of the rabbit nictitating membrane response. Neurons were classified as different cell types using response to fornix stimulation (i.e., antidromic or orthodromic activation) and spontaneous firing characteristics as criteria. Results showed that hippocampal pyramidal neurons exhibit learning-related neural plasticity that develops gradually over the course of classical conditioning. The learning-dependent pyramidal cell response is characterized by an increase in frequency of firing within conditioning trials and a within-trial pattern of discharge that correlates strongly with amplitude-time course of the behavioral response. In contrast, pyramidal cell activity recorded from control animals given unpaired presentations of the conditioned and unconditioned stimulus (CS and UCS) does not show enhanced discharge rates with repeated stimulation. Previous studies of hippocampal cellular electrophysiology have described what has been termed a theta-cell (19-21, 45), the activity of which correlates with slow-wave theta rhythm generated in the hippocampus. Neurons classified as theta-cells in the present study exhibit responses during conditioning that are distinctly different than pyramidal cells. theta-Cells respond during paired conditioning trials with a rhythmic bursting; the between-burst interval occurs at or near 8 Hz. In addition, two different types of theta-cells were distinguishable. One type of theta-cell increases firing frequency above pretrial levels while displaying the theta bursting pattern. The other type decreases firing frequency below pretrial rates while showing a theta-locked discharge. In addition to pyramidal and theta-neurons, several other cell types recorded in or near the pyramidal cell layer could be distinguished. One cell type was distinctive in that it could be activated with a short, invariant latency following fornix stimulation, but spontaneous action potentials of such neurons could not be collided with fornix shock-induced action potentials. These neurons exhibit a different profile of spontaneous firing characteristics than those of antidromically identified pyramidal cells. Nevertheless, neurons in this noncollidable category display the same learning-dependent response as pyramidal cells. It is suggested that the noncollidable neurons represent a subpopulation of pyramidal cells that do not project an axon via the fornix but project, instead, to other limbic cortical regions.(ABSTRACT TRUNCATED AT 400 WORDS)

Relationships Between Intracellular Calcium and Afterhyperpolarizations in Neocortical Pyramidal Neurons

2004 ◽  
Vol 91 (1) ◽  
pp. 324-335 ◽  
Author(s):  
H. J. Abel ◽  
J.C.F. Lee ◽  
J. C. Callaway ◽  
R. C. Foehring
Keyword(s):  
Intracellular Calcium ◽  
Linear Relationship ◽  
Pyramidal Neurons ◽  
Pyramidal Cells ◽  
Firing Frequency ◽  
Discharge Activity ◽  
Apical Dendrites ◽  
Neocortical Pyramidal Neurons

We examined the effects of recent discharge activity on [Ca2+]i in neocortical pyramidal cells. Our data confirm and extend the observation that there is a linear relationship between plateau [Ca2+]i and firing frequency in soma and proximal apical dendrites. The rise in [Ca2+] activates K+ channels underlying the afterhyperpolarization (AHP), which consists of 2 Ca2+-dependent components: the medium AHP (mAHP) and the slow AHP (sAHP). The mAHP is blocked by apamin, indicating involvement of SK-type Ca2+-dependent K+ channels. The identity of the apamin-insensitive sAHP channel is unknown. We compared the sAHP and the mAHP with regard to: 1) number and frequency of spikes versus AHP amplitude; 2) number and frequency of spikes versus [Ca2+]i; 3) IAHP versus [Ca2+]i. Our data suggest that sAHP channels require an elevation of [Ca2+]i in the cytoplasm, rather than at the membrane, consistent with a role for a cytoplasmic intermediate between Ca2+ and the K+ channels. The mAHP channels appear to respond to a restricted Ca2+ domain.

scholarly journals Electrophysiological Diversity of Layer 5 Pyramidal Cells in the Prefrontal Cortex of the Rhesus Monkey: In Vitro Slice Studies

2007 ◽  
Vol 98 (5) ◽  
pp. 2622-2632 ◽  
Author(s):  
Yu-Ming Chang ◽  
Jennifer I. Luebke
Keyword(s):  
Prefrontal Cortex ◽  
Rhesus Monkey ◽  
Spike Train ◽  
Pyramidal Cells ◽  
Cell Types ◽  
Dendritic Morphology ◽  
Firing Patterns ◽  
Electrophysiological Properties ◽  
Whole Cell Patch Clamp

Whole cell patch-clamp recordings were employed to characterize the electrophysiological properties of layer 5 pyramidal cells in slices of the prefrontal cortex (Area 46) of the rhesus monkey. Four electrophysiologically distinct cell types were discriminated based on distinctive repetitive action potential (AP) firing patterns and single AP characteristics: regular-spiking slowly adapting type-1 cells (RS1; 62%), regular-spiking slowly adapting type-2 cells (RS2; 18%), regular-spiking fast-adapting cells (FA; 15%), and intrinsically bursting cells (IB; 5%). These cells did not differ with regard to their location in layer 5 nor in their dendritic morphology. In RS1 cells, AP threshold and amplitude did not change significantly during a 2-s spike train, whereas in RS2 and FA cells, AP threshold increased significantly and AP amplitude decreased significantly during the train. In FA cells, complete adaptation of AP firing was observed within 600 ms. IB cells displayed an all-or-none burst of three to six APs, followed by RS1-type firing behavior. RS1 cells could be further subdivided into three subtypes. Low-threshold spiking (LTS) RS1 cells exhibited an initial doublet riding on a depolarizing potential at the onset of a spike train and a prominent depolarizing afterpotential (DAP); intermediate RS1 cells (IM) exhibited a DAP, but no initial doublet, and non-LTS RS1 cells exhibited neither a DAP nor an initial doublet. RS2 and FA cells did not exhibit a DAP or initial doublets. The distinctive firing patterns of these diverse layer 5 pyramidal cells may reflect different roles played by these cells in the mediation of subcortical neuronal activity by the dorsolateral PFC.

scholarly journals Designing optimal stimuli to control neuronal spike timing

2011 ◽  
Vol 106 (2) ◽  
pp. 1038-1053 ◽  
Author(s):  
Yashar Ahmadian ◽  
Adam M. Packer ◽  
Rafael Yuste ◽  
Liam Paninski
Keyword(s):  
Spike Train ◽  
Laser Light ◽  
Pyramidal Cells ◽  
Electrical Current ◽  
Optimization Methods ◽  
Spike Trains ◽  
Spike Timing ◽  
Safety Measures ◽  
Physiological Constraints ◽  
Cortical Slices

Recent advances in experimental stimulation methods have raised the following important computational question: how can we choose a stimulus that will drive a neuron to output a target spike train with optimal precision, given physiological constraints? Here we adopt an approach based on models that describe how a stimulating agent (such as an injected electrical current or a laser light interacting with caged neurotransmitters or photosensitive ion channels) affects the spiking activity of neurons. Based on these models, we solve the reverse problem of finding the best time-dependent modulation of the input, subject to hardware limitations as well as physiologically inspired safety measures, that causes the neuron to emit a spike train that with highest probability will be close to a target spike train. We adopt fast convex constrained optimization methods to solve this problem. Our methods can potentially be implemented in real time and may also be generalized to the case of many cells, suitable for neural prosthesis applications. With the use of biologically sensible parameters and constraints, our method finds stimulation patterns that generate very precise spike trains in simulated experiments. We also tested the intracellular current injection method on pyramidal cells in mouse cortical slices, quantifying the dependence of spiking reliability and timing precision on constraints imposed on the applied currents.

Plasticity in an electrosensory system. I. General features of a dynamic sensory filter

1996 ◽  
Vol 76 (4) ◽  
pp. 2483-2496 ◽  
Author(s):  
J. Bastian
Keyword(s):  
Synaptic Plasticity ◽  
Pyramidal Cell ◽  
Electric Fish ◽  
Pyramidal Cells ◽  
Afferent Input ◽  
Firing Frequency ◽  
Negative Image ◽  
Local Stimulus ◽  
Adaptive Cancellation ◽  
Apical Dendrites

1. In this study we describe changes in neuronal responses within the primary electrosensory processing nucleus of a weakly electric fish that occur when the fish are exposed to repetitive patterns of electrosensory stimuli. Extracellular single-unit recordings show that pyramidal cells within the electrosensory lateral line lobe develop, over a time course of several minutes, an insensitivity to repetitive stimuli applied to a cell's receptive field (local stimulus). The pyramidal cell response cancellation only develops if the local stimulus is applied simultaneously with a diffuse pattern of electrosensory stimulation that affects the entire fish, or with proprioceptive stimuli. 2. The mechanism by which responses to repetitive afferent inputs are canceled relies on the central generation of "negative image inputs" that provide increased inhibitory input to a cell's apical dendrites at times when excitatory afferent input is increased. The negative image input becomes excitatory when afferent excitation is reduced or when input from inhibitory interneurons is predominant. The integration of a specific pattern of receptor afferent input with the complementary negative image input results in strong attenuation of pyramidal cell responses. The negative image inputs are plastic, so that a single pyramidal cell can learn to reject a variety of afferent input patterns. 3. These electric fish commonly experience repetitive electrosensory signals as a result of changes in posture. Because the electric organ is located in the trunk and tail, cyclical movements associated with exploratory behaviors result in amplitude modulations (AMs) of the electric field, and these AMs alter electroreceptor afferent firing frequency but not the firing frequency of second-order pyramidal cells. The adaptive cancellation mechanism described in this study can account for the insensitivity of pyramidal cells to reafferent electrosensory stimulation caused by tail movements and other postural changes. 4. The tail movements generate proprioceptive as well as electrosensory inputs, and either of these signals alone provides sufficient information for the generation of negative image inputs. The size of the negative image is larger, however, if both inputs are active. 5. The synaptic plasticity underlying the development of negative image inputs has a long-term component; under appropriate conditions changes in synaptic efficacy persist for > 30 min. 6. Normally functioning glutamatergic synapses are necessary for the expression of the synaptic plasticity associated with this cancellation mechanism. The development of negative image responses is blocked by micropressure ejection of the glutamate antagonist 6,7-dinitroquinoxaline-2,3-dione into the neighborhood of the pyramidal cell apical dendrites. 7. The adaptive cancellation of repetitive inputs is based on anti-Hebbian mechanisms; that is, correlated pre- and postsynaptic activity lead to a reduction in the excitatory input provided by the plastic synapses. As has been shown for several other systems, the cancellation mechanism reduces the cells responses to reafferent patterns of sensory input. In addition, the results of this study indicate that the mechanism may be more general, enabling the system to also cancel patterns of input resulting from exogenous stimuli.

scholarly journals Neuronal Transmission of Subthreshold Periodic Stimuli Via Symbolic Spike Patterns

Entropy ◽  
2020 ◽  
Vol 22 (5) ◽  
pp. 524
Author(s):  
Maria Masoliver ◽  
Cristina Masoller
Keyword(s):  
Spike Train ◽  
Sensory Neurons ◽  
Action Potentials ◽  
Temporal Structure ◽  
Spike Trains ◽  
Periodic Signal ◽  
Stimulus Information ◽  
Neural Noise ◽  
Neuronal Transmission ◽  
Spike Patterns

We study how sensory neurons detect and transmit a weak external stimulus. We use the FitzHugh–Nagumo model to simulate the neuronal activity. We consider a sub-threshold stimulus, i.e., the stimulus is below the threshold needed for triggering action potentials (spikes). However, in the presence of noise the neuron that perceives the stimulus fires a sequence of action potentials (a spike train) that carries the stimulus’ information. To yield light on how the stimulus’ information can be encoded and transmitted, we consider the simplest case of two coupled neurons, such that one neuron (referred to as neuron 1) perceives a subthreshold periodic signal but the second neuron (neuron 2) does not perceive the signal. We show that, for appropriate coupling and noise strengths, both neurons fire spike trains that have symbolic patterns (defined by the temporal structure of the inter-spike intervals), whose frequencies of occurrence depend on the signal’s amplitude and period, and are similar for both neurons. In this way, the signal information encoded in the spike train of neuron 1 propagates to the spike train of neuron 2. Our results suggest that sensory neurons can exploit the presence of neural noise to fire spike trains where the information of a subthreshold stimulus is encoded in over expressed and/or in less expressed symbolic patterns.

scholarly journals Encoding and processing of sensory information in neuronal spike trains

1999 ◽  
Vol 202 (10) ◽  
pp. 1267-1279 ◽  
Author(s):  
F. Gabbiani ◽  
W. Metzner
Keyword(s):  
Sensory Neurons ◽  
Pyramidal Cells ◽  
Statistical Signal Processing ◽  
Spike Trains ◽  
Weakly Electric Fish ◽  
Accurate Information ◽  
Signal Processing Technique ◽  
Detection Techniques ◽  
First Order ◽  
Temporal Features

Recently, a statistical signal-processing technique has allowed the information carried by single spike trains of sensory neurons on time-varying stimuli to be characterized quantitatively in a variety of preparations. In weakly electric fish, its application to first-order sensory neurons encoding electric field amplitude (P-receptor afferents) showed that they convey accurate information on temporal modulations in a behaviorally relevant frequency range (<80 Hz). At the next stage of the electrosensory pathway (the electrosensory lateral line lobe, ELL), the information sampled by first-order neurons is used to extract upstrokes and downstrokes in the amplitude modulation waveform. By using signal-detection techniques, we determined that these temporal features are explicitly represented by short spike bursts of second-order neurons (ELL pyramidal cells). Our results suggest that the biophysical mechanism underlying this computation is of dendritic origin. We also investigated the accuracy with which upstrokes and downstrokes are encoded across two of the three somatotopic body maps of the ELL (centromedial and lateral). Pyramidal cells of the centromedial map, in particular I-cells, encode up- and downstrokes more reliably than those of the lateral map. This result correlates well with the significance of these temporal features for a particular behavior (the jamming avoidance response) as assessed by lesion experiments of the centromedial map.

scholarly journals Differences in sodium channel densities in the apical dendrites of pyramidal cells of the electrosensory lateral line lobe

2019 ◽  
Author(s):  
Sree I. Motipally ◽  
Kathryne M. Allen ◽  
Daniel K. Williamson ◽  
Gary Marsat
Keyword(s):  
Lateral Line ◽  
Pyramidal Cells ◽  
Receptor Expression ◽  
Weakly Electric Fish ◽  
Sk Channels ◽  
Voltage Gated ◽  
Channel Density ◽  
Lateral Segment ◽  
Medial Segment ◽  
Apical Dendrites

AbstractHeterogeneity of neural properties within a given neural class is ubiquitous in the nervous system and permits different sub-classes of neurons to specialize for specific purposes. This principle has been thoroughly investigated in the hindbrain of the weakly electric fish A. leptorhynchus in the primary electrosensory area, the Electrosensory Lateral Line lobe (ELL). The pyramidal cells that receive inputs from tuberous electroreceptors are organized in three maps in distinct segments of the ELL. The properties of these cells vary greatly across maps due to differences in connectivity, receptor expression, and ion channel composition. These cells are a seminal example of bursting neurons and their bursting dynamic relies on the presence of voltage-gated Na+ channels in the extensive apical dendrites of the superficial pyramidal cells. Other ion channels can affect burst generation and their expression varies across ELL neurons and segments. For example, SK channels cause hyperpolarizing after-potentials decreasing the likelihood of bursting, yet bursting propensity is similar across segments. We question whether the depolarizing mechanism that generates the bursts presents quantitative differences across segments that could counterbalance other differences having the opposite effect. Although their presence and role are established, the distribution and density of the apical dendrites’ Na+ channels have not been quantified and compared across ELL maps. Therefore, we test the hypothesis that Na+ channel density varies across segment by quantifying their distribution in the apical dendrites of immunolabeled ELL sections. We found the Na+ channels to be two-fold denser in the lateral segment than in the centro-medial segment, the centro-lateral segment being intermediate. Our results imply that this differential expression of voltage-gated Na+ channels could counterbalance or interact with other aspects of neuronal physiology that vary across segments (e.g. SK channels). We argue that burst coding of sensory signals, and the way the network regulates bursting, should be influenced by these variations in Na+ channel density.

scholarly journals A Biologically Plausible Computational Model for Auditory Object Recognition

2009 ◽  
Vol 101 (1) ◽  
pp. 323-331 ◽  
Author(s):  
Eric Larson ◽  
Cyrus P. Billimoria ◽  
Kamal Sen
Keyword(s):  
Object Recognition ◽  
Spike Train ◽  
Nearest Neighbor ◽  
Primary Auditory Cortex ◽  
Spike Trains ◽  
Coincidence Detection ◽  
Model Based ◽  
Plausible Model ◽  
Field L ◽  
Song Discrimination

Object recognition is a task of fundamental importance for sensory systems. Although this problem has been intensively investigated in the visual system, relatively little is known about the recognition of complex auditory objects. Recent work has shown that spike trains from individual sensory neurons can be used to discriminate between and recognize stimuli. Multiple groups have developed spike similarity or dissimilarity metrics to quantify the differences between spike trains. Using a nearest-neighbor approach the spike similarity metrics can be used to classify the stimuli into groups used to evoke the spike trains. The nearest prototype spike train to the tested spike train can then be used to identify the stimulus. However, how biological circuits might perform such computations remains unclear. Elucidating this question would facilitate the experimental search for such circuits in biological systems, as well as the design of artificial circuits that can perform such computations. Here we present a biologically plausible model for discrimination inspired by a spike distance metric using a network of integrate-and-fire model neurons coupled to a decision network. We then apply this model to the birdsong system in the context of song discrimination and recognition. We show that the model circuit is effective at recognizing individual songs, based on experimental input data from field L, the avian primary auditory cortex analog. We also compare the performance and robustness of this model to two alternative models of song discrimination: a model based on coincidence detection and a model based on firing rate.

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