scholarly journals Response to Comment on ”Two types of asynchronous activity in networks of excitatory and inhibitory spiking neurons”

2015 ◽  
Author(s):  
Srdjan Ostojic
Keyword(s):  
Action Potentials ◽  
Spiking Neurons ◽  
Inhibitory Neurons ◽  
Synaptic Coupling ◽  
Process Information ◽  
Integrate And Fire ◽  
Different Types ◽  
Dominant Paradigm

Networks of excitatory and inhibitory neurons form the basic computational units in the mammalian cortex. Within the dominant paradigm, neurons in such networks encode and process information by asynchronously emitting action potentials. In a recent publication, I argued that unstructured, sparsely connected networks of integrate-and-fire neurons display a transition between two qualitatively different types of asynchronous activity as the synaptic coupling is increased. A comment by Engelken et al (bioRxiv doi: 10.1101/017798) disputes this finding. Here I provide additional evidence for a transition between two qualitatively different types of asynchronous activity and address the criticism raised in the comment. The claims that the original paper is "factually incorrect" and "conceptually misleading" are unsubstantiated and inappropriate.

scholarly journals Spontaneous Electrical Activity and Spikes in the Tail of Marine Cercariae

2013 ◽  
Vol 2013 ◽  
pp. 1-4 ◽  
Author(s):  
O. O. Tolstenkov ◽  
M. I. Zhukovskaya ◽  
V. V. Prokofiev ◽  
M. K. S. Gustafsson
Keyword(s):  
Electrical Activity ◽  
Action Potentials ◽  
High Amplitude ◽  
Spiking Neurons ◽  
Field Potentials ◽  
Spontaneous Electrical Activity ◽  
Swimming Pattern ◽  
Different Types ◽  
Low Amplitude ◽  
First Time

Spontaneous electrical activity is recorded in two species of marine cercariae, Cryptocotyle lingua and Himasthla elongata, with different types of swimming—by glass microelectrode recordings. Slow local field potentials (sLFPs) of low amplitude and fast high amplitude action potentials (APs) are found. The shape of the sLFPs is different in the species and correlates with the type of swimming. Fast high amplitude APs are recorded for the first time in cercariae. The limited number of APs included in the swimming pattern of larva suggests a key role for the spiking neurons in initiating the motility pattern in the cercaria and needs further research.

Simulator for neural networks and action potentials: description and application

1994 ◽  
Vol 71 (1) ◽  
pp. 294-308 ◽  
Author(s):  
I. Ziv ◽  
D. A. Baxter ◽  
J. H. Byrne
Keyword(s):  
Neural Networks ◽  
Central Pattern Generator ◽  
Action Potentials ◽  
Modular Design ◽  
Second Messenger ◽  
Pattern Generator ◽  
Slow Inward Current ◽  
Synaptic Connections ◽  
Different Types ◽  
Voltage Dependent

1. We describe a simulator for neural networks and action potentials (SNNAP) that can simulate up to 30 neurons, each with up to 30 voltage-dependent conductances, 30 electrical synapses, and 30 multicomponent chemical synapses. Voltage-dependent conductances are described by Hodgkin-Huxley type equations, and the contributions of time-dependent synaptic conductances are described by second-order differential equations. The program also incorporates equations for simulating different types of neural modulation and synaptic plasticity. 2. Parameters, initial conditions, and output options for SNNAP are passed to the program through a number of modular ASCII files. These modules can be modified by commonly available text editors that use a conventional (i.e., character based) interface or by an editor incorporated into SNNAP that uses a graphical interface. The modular design facilitates the incorporation of existing modules into new simulations. Thus libraries can be developed of files describing distinctive cell types and files describing distinctive neural networks. 3. Several different types of neurons with distinct biophysical properties and firing properties were simulated by incorporating different combinations of voltage-dependent Na+, Ca2+, and K+ channels as well as Ca(2+)-activated and Ca(2+)-inactivated channels. Simulated cells included those that respond to depolarization with tonic firing, adaptive firing, or plateau potentials as well as endogenous pacemaker and bursting cells. 4. Several types of simple neural networks were simulated that included feed-forward excitatory and inhibitory chemical synaptic connections, a network of electrically coupled cells, and a network with feedback chemical synaptic connections that simulated rhythmic neural activity. In addition, with the use of the equations describing electrical coupling, current flow in a branched neuron with 18 compartments was simulated. 5. Enhancement of excitability and enhancement of transmitter release, produced by modulatory transmitters, were simulated by second-messenger-induced modulation of K+ currents. A depletion model for synaptic depression was also simulated. 6. We also attempted to simulate the features of a more complicated central pattern generator, inspired by the properties of neurons in the buccal ganglia of Aplysia. Dynamic changes in the activity of this central pattern generator were produced by a second-messenger-induced modulation of a slow inward current in one of the neurons.

scholarly journals Influence of Autapses on Synchronization in Neural Networks With Chemical Synapses

2020 ◽  
Vol 14 ◽  
Author(s):  
Paulo R. Protachevicz ◽  
Kelly C. Iarosz ◽  
Iberê L. Caldas ◽  
Chris G. Antonopoulos ◽  
Antonio M. Batista ◽  
...  
Keyword(s):  
Neural Networks ◽  
Random Network ◽  
Inhibitory Neurons ◽  
Neural Dynamics ◽  
Excitatory Synapses ◽  
Closed Loops ◽  
Integrate And Fire ◽  
Network Topologies ◽  
Chemical Synapses ◽  
Synchronous Behavior

A great deal of research has been devoted on the investigation of neural dynamics in various network topologies. However, only a few studies have focused on the influence of autapses, synapses from a neuron onto itself via closed loops, on neural synchronization. Here, we build a random network with adaptive exponential integrate-and-fire neurons coupled with chemical synapses, equipped with autapses, to study the effect of the latter on synchronous behavior. We consider time delay in the conductance of the pre-synaptic neuron for excitatory and inhibitory connections. Interestingly, in neural networks consisting of both excitatory and inhibitory neurons, we uncover that synchronous behavior depends on their synapse type. Our results provide evidence on the synchronous and desynchronous activities that emerge in random neural networks with chemical, inhibitory and excitatory synapses where neurons are equipped with autapses.

Excitable Membrane Properties of Neurons

2020 ◽  
Author(s):  
Leonard K. Kaczmarek
Keyword(s):  
Action Potential ◽  
Action Potentials ◽  
Cell Biology ◽  
Neuronal Firing ◽  
Membrane Properties ◽  
Potassium Ions ◽  
Single Action ◽  
Sodium Calcium ◽  
Different Types ◽  
Order Of Magnitude

The intrinsic electrical properties of neurons are extremely varied. For example, the width of action potentials in different neurons varies by more than an order of magnitude. In response to prolonged stimulation, some neurons generate repeated action potential hundreds of times a second, while others fire only a single action potential or adapt very rapidly. These differences result from the expression of different types of ion channels in the plasma membrane. The dominant channels that shape neuronal firing patterns are those that are selective for sodium, calcium, and potassium ions. This chapter provides a brief overview of the biophysical properties of each of these classes of channel, their role in shaping the electrical personality of a neuron, and how interactions of these channels with cytoplasmic factors shape the overall cell biology of a neuron.

Interspike interval distributions of spiking neurons driven by fluctuating inputs

2011 ◽  
Vol 106 (1) ◽  
pp. 361-373 ◽  
Author(s):  
Srdjan Ostojic
Keyword(s):  
Coefficient Of Variation ◽  
Cortical Neurons ◽  
Interspike Interval ◽  
Full Range ◽  
Spiking Neurons ◽  
Neuron Models ◽  
Integrate And Fire ◽  
Gamma Distributions ◽  
Spiking Neuron Models ◽  
Analytical Tools

Interspike interval (ISI) distributions of cortical neurons exhibit a range of different shapes. Wide ISI distributions are believed to stem from a balance of excitatory and inhibitory inputs that leads to a strongly fluctuating total drive. An important question is whether the full range of experimentally observed ISI distributions can be reproduced by modulating this balance. To address this issue, we investigate the shape of the ISI distributions of spiking neuron models receiving fluctuating inputs. Using analytical tools to describe the ISI distribution of a leaky integrate-and-fire (LIF) neuron, we identify three key features: 1) the ISI distribution displays an exponential decay at long ISIs independently of the strength of the fluctuating input; 2) as the amplitude of the input fluctuations is increased, the ISI distribution evolves progressively between three types, a narrow distribution (suprathreshold input), an exponential with an effective refractory period (subthreshold but suprareset input), and a bursting exponential (subreset input); 3) the shape of the ISI distribution is approximately independent of the mean ISI and determined only by the coefficient of variation. Numerical simulations show that these features are not specific to the LIF model but are also present in the ISI distributions of the exponential integrate-and-fire model and a Hodgkin-Huxley-like model. Moreover, we observe that for a fixed mean and coefficient of variation of ISIs, the full ISI distributions of the three models are nearly identical. We conclude that the ISI distributions of spiking neurons in the presence of fluctuating inputs are well described by gamma distributions.

Classification of Correlated Patterns with a Configurable Analog VLSI Neural Network of Spiking Neurons and Self-Regulating Plastic Synapses

2009 ◽  
Vol 21 (11) ◽  
pp. 3106-3129 ◽  
Author(s):  
Massimilian Giulioni ◽  
Mario Pannunzi ◽  
Davide Badoni ◽  
Vittorio Dante ◽  
Paolo Del Giudice
Keyword(s):  
Marked Improvement ◽  
Analog Vlsi ◽  
Spiking Neurons ◽  
Learning Performance ◽  
Event Representation ◽  
Plasticity Mechanism ◽  
Integrate And Fire ◽  
Correlated Patterns ◽  
Synaptic Changes

We describe the implementation and illustrate the learning performance of an analog VLSI network of 32 integrate-and-fire neurons with spike-frequency adaptation and 2016 Hebbian bistable spike-driven stochastic synapses, endowed with a self-regulating plasticity mechanism, which avoids unnecessary synaptic changes. The synaptic matrix can be flexibly configured and provides both recurrent and external connectivity with address-event representation compliant devices. We demonstrate a marked improvement in the efficiency of the network in classifying correlated patterns, owing to the self-regulating mechanism.

scholarly journals Inhibitory control of the excitatory/inhibitory balance in psychiatric disorders

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 23 ◽  
Author(s):  
Martijn Selten ◽  
Hans van Bokhoven ◽  
Nael Nadif Kasri
Keyword(s):  
Psychiatric Disorders ◽  
Relative Strength ◽  
Inhibitory Neurons ◽  
Specific Class ◽  
Post Mortem ◽  
Inhibitory System ◽  
Network Function ◽  
Different Types ◽  
Flow Of Information

Neuronal networks consist of different types of neurons that all play their own role in order to maintain proper network function. The two main types of neurons segregate in excitatory and inhibitory neurons, which together regulate the flow of information through the network. It has been proposed that changes in the relative strength in these two opposing forces underlie the symptoms observed in psychiatric disorders, including autism and schizophrenia. Here, we review the role of alterations to the function of the inhibitory system as a cause of psychiatric disorders. First, we explore both patient and post-mortem evidence of inhibitory deficiency. We then discuss the function of different interneuron subtypes in the network and focus on the central role of a specific class of inhibitory neurons, parvalbumin-positive interneurons. Finally, we discuss genes known to be affected in different disorders and the effects that mutations in these genes have on the inhibitory system in cortex and hippocampus. We conclude that alterations to the inhibitory system are consistently identified in animal models of psychiatric disorders and, more specifically, that mutations affecting the function of parvalbumin-positive interneurons seem to play a central role in the symptoms observed in these disorders.

Swallow-evoked action potentials in vagal preganglionic efferents

1984 ◽  
Vol 52 (6) ◽  
pp. 1169-1180 ◽  
Author(s):  
J. S. Gidda ◽  
R. K. Goyal
Keyword(s):  
Action Potentials ◽  
Discharge Rate ◽  
Stimulus Frequency ◽  
Superior Laryngeal Nerve ◽  
Bimodal Distribution ◽  
Short Latency ◽  
The Body ◽  
Inhibitory Neurons ◽  
Discharge Rates ◽  
Long Latency

Swallow<evoked potentials in the preganglionic vagal fibers were studied using the single<fiber recording technique in anesthetized opossums. Swallows were evoked by tactile pharyngeal stimulation or electrical stimulation of the cut central end of the superior laryngeal nerve (SLN). Swallowing activity was recorded by the mylohyoid electromyogram and esophageal motility. Sixty<six fibers were studied in which swallowing evoked action potentials. The latencies (from the onset of mylohyoid activity) of evoked responses in different fibers varied from 100 ms to 5 s. The discharge rate of the evoked response was 3<8 action potentials per burst. Each burst lasted 1.1 +/- 0.02 (SE)s. The latencies of evoked spike bursts showed a bimodal distribution. In 34 fibers the latencies were less than 1 s, and in 32 fibers the latencies ranged between 1 and 5 s; these are the short- and long-latency fibers, respectively. Short-latency fibers could easily be distinguished from long-latency fibers based on the influence of SLN-stimulus frequency. Short-latency discharges had low thresholds of activation and were sensitive to changes in the frequency of SLN stimulation, since their latencies decreased and their discharge rate increased with increasing SLN-stimulus frequency. On the other hand, the latencies and discharge rates of long-latency discharges were not modified with changing SLN stimulus frequencies. The conduction velocities of 6 short- and 9 long-latency fibers were 5.64 +/- 0.12 and 5.78 +/- 0.12 (SE) m/s, respectively (P greater than 0.05). The relationship between the latencies of swallow-evoked discharges in the short- and long-latency fibers and the esophageal smooth muscle responses suggested that the short-latency discharges may correlate with the latency of initial inhibition, and the long-latency fibers may correlate with latencies of peristaltic contractions. Based on these temporal relationships, we speculate that vagal efferent fibers showing swallow-evoked, short-latency discharges make contact with intramural inhibitory neurons. They may mediate deglutitive inhibition in the body of the esophagus, relaxation of the lower esophageal sphincter, and receptive relaxation of the fundus of the stomach. The fibers showing late discharges make contact with intramural excitatory neurons and participate in their sequential activation. This dual pathway of activation may be responsible for physiological esophageal peristalsis.

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