Coupled Hodgkin Huxley Neurons with Stochastic Synaptic Inputs

1995 ◽  
pp. 233-242
Author(s):  
Roger Rodriguez
Keyword(s):  
Synaptic Inputs

Postsynaptic neuronal geometry and synaptic effectiveness

1987 ◽  
Vol 45 ◽  
pp. 690-697
Author(s):  
C.J. Wilson
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
Synaptic Function ◽  
Postsynaptic Neuron ◽  
Synaptic Inputs ◽  
Partial Analysis ◽  
Postsynaptic Cell ◽  
Neuronal Geometry ◽  
The Relationship ◽  
Complex Scale

Most central nervous system neurons receive synaptic input from hundreds or thousands of other neurons, and the computational function of such neurons results from the interactions of inputs on a large and complex scale. In most situations that have yielded to a partial analysis, the synaptic inputs to a neuron are not alike in function, but rather belong to distinct categories that differ qualitatively in the nature of their effect on the postsynaptic cell, and quantitatively in the strength of their influence. Many factors have been demonstrated to contribute to synaptic function, but one of the simplest and best known of these is the geometry of the postsynaptic neuron. The fundamental nature of the relationship between neuronal shape and synaptic effectiveness was established on theoretical grounds prior to its experimental verification.

Synaptic Inputs of Neural Afferent Pathways to Vasopressin- and Oxytocin-Secreting Neurons of Supraoptic and Paraventricular Hypothalamic Nuclei

2017 ◽  
Vol 16 (4) ◽  
pp. 276-287 ◽  
Author(s):  
Michele Iovino ◽  
Vito Giagulli ◽  
Brunella Licchelli ◽  
Emanuela Iovino ◽  
Edoardo Guastamacchia ◽  
...  
Keyword(s):  
Afferent Pathways ◽  
Synaptic Inputs ◽  
Hypothalamic Nuclei

Comparison of the responses of AII amacrine cells in the dark- and light-adapted rabbit retina

1999 ◽  
Vol 16 (4) ◽  
pp. 653-665 ◽  
Author(s):  
DAIYAN XIN ◽  
STEWART A. BLOOMFIELD
Keyword(s):  
Receptive Field ◽  
Light Adaptation ◽  
Amacrine Cells ◽  
Bipolar Cells ◽  
Rabbit Retina ◽  
Response Component ◽  
Synaptic Inputs ◽  
Field Organization ◽  
Receptive Field Organization ◽  
Aii Amacrine Cells

We studied the light-evoked responses of AII amacrine cells in the rabbit retina under dark- and light-adapted conditions. In contrast to the results of previous studies, we found that AII cells display robust responses to light over a 6–7 log unit intensity range, well beyond the operating range of rod photoreceptors. Under dark adaptation, AII cells showed an ON-center/OFF-surround receptive-field organization. The intensity–response profile of the center-mediated response component followed a dual-limbed sigmoidal function indicating a transition from rod to cone mediation as stimulus intensities were increased. Following light adaptation, the receptive-field organization of AII cells changed dramatically. Light-adapted AII cells showed both ON- and OFF-responses to stimulation of the center receptive field, but we found no evidence for an antagonistic surround. Interestingly, the OFF-center response appeared first following rapid light adaptation and was then replaced gradually over a 1–4 min period by the emerging ON-center response component. Application of the metabotropic glutamate receptor agonist APB, the ionotropic glutamate blocker CNQX, 8-bromo-cGMP, and the nitric oxide donor SNAP all showed differential effects on the various center-mediated responses displayed by dark- and light-adapted AII cells. Taken together, these pharmacological results indicated that different synaptic circuits are responsible for the generation of the different AII cell responses. Specifically, the rod-driven ON-center responses are apparently derived from rod bipolar cell synaptic inputs, whereas the cone-driven ON-center responses arise from signals crossing the gap junctions between AII cells and ON-center cone bipolar cells. Additionally, the OFF-center response of light-adapted AII cells reflects direct synaptic inputs from OFF-center cone bipolar cells to AII dendritic processes in the distal inner plexiform layer.

scholarly journals 3D Ultrastructure of Synaptic Inputs to Distinct GABAergic Neurons in the Mouse Primary Visual Cortex

2020 ◽  
Author(s):  
Yang-Sun Hwang ◽  
Catherine Maclachlan ◽  
Jérôme Blanc ◽  
Anaëlle Dubois ◽  
Carl C H Petersen ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Pyramidal Neuron ◽  
Cell Types ◽  
Gabaergic Neurons ◽  
Inhibitory Synapses ◽  
Synaptic Inputs ◽  
Neuronal Types ◽  
The Difference ◽  
Ultrastructure Of Synapses

Abstract Synapses are the fundamental elements of the brain’s complicated neural networks. Although the ultrastructure of synapses has been extensively studied, the difference in how synaptic inputs are organized onto distinct neuronal types is not yet fully understood. Here, we examined the cell-type-specific ultrastructure of proximal processes from the soma of parvalbumin-positive (PV+) and somatostatin-positive (SST+) GABAergic neurons in comparison with a pyramidal neuron in the mouse primary visual cortex (V1), using serial block-face scanning electron microscopy. Interestingly, each type of neuron organizes excitatory and inhibitory synapses in a unique way. First, we found that a subset of SST+ neurons are spiny, having spines on both soma and dendrites. Each of those spines has a highly complicated structure that has up to eight synaptic inputs. Next, the PV+ and SST+ neurons receive more robust excitatory inputs to their perisoma than does the pyramidal neuron. Notably, excitatory synapses on GABAergic neurons were often multiple-synapse boutons, making another synapse on distal dendrites. On the other hand, inhibitory synapses near the soma were often single-targeting multiple boutons. Collectively, our data demonstrate that synaptic inputs near the soma are differentially organized across cell types and form a network that balances inhibition and excitation in the V1.

Phase Selective Oscillations in Two Noise Driven Synaptically Coupled Spiking Neurons

2015 ◽  
Vol 25 (07) ◽  
pp. 1540005
Author(s):  
Ilya Prokin ◽  
Ivan Tyukin ◽  
Victor Kazantsev
Keyword(s):  
Numerical Simulations ◽  
Coupled System ◽  
External Noise ◽  
Noise Signal ◽  
Feedback Mechanism ◽  
Spike Timing ◽  
Spiking Neurons ◽  
Time Lags ◽  
Tuning Parameters ◽  
Synaptic Inputs

The work investigates the influence of spike-timing dependent plasticity (STDP) mechanisms on the dynamics of two synaptically coupled neurons driven by additive external noise. In this setting, the noise signal models synaptic inputs that the pair receives from other neurons in a larger network. We show that in the absence of STDP feedbacks the pair of neurons exhibit oscillations and intermittent synchronization. When the synapse connecting the neurons is supplied with a phase selective feedback mechanism simulating STDP, induced dynamics of spikes in the coupled system resembles a phase locked mode with time lags between spikes oscillating about a specific value. This value, as we show by extensive numerical simulations, can be set arbitrary within a broad interval by tuning parameters of the STDP feedback.

scholarly journals Concurrent recordings of hippocampal neuronal spikes and prefrontal synaptic inputs from an awake rat

2021 ◽  
Vol 2 (2) ◽  
pp. 100572
Author(s):  
Yuya Nishimura ◽  
Yuji Ikegaya ◽  
Takuya Sasaki
Keyword(s):  
Synaptic Inputs ◽  
Awake Rat ◽  
Neuronal Spikes

scholarly journals Simulation of Dendritic CaV1.3 Channels in Cat Lumbar Motoneurons: Spatial Distribution

2005 ◽  
Vol 94 (6) ◽  
pp. 3961-3974 ◽  
Author(s):  
Sherif M. ElBasiouny ◽  
David J. Bennett ◽  
Vivian K. Mushahwar
Keyword(s):  
Spatial Distribution ◽  
Low Voltage ◽  
Dendritic Tree ◽  
Triceps Surae ◽  
Spinal Motoneurons ◽  
Functional Interaction ◽  
Intermediate Band ◽  
Synaptic Inputs ◽  
Persistent Inward Current ◽  
Adult Cat

We used computer simulations to study the dendritic spatial distribution of low voltage-activated L-type calcium (CaV1.3 type) channels, which mediate hysteretic persistent inward current (PIC) in spinal motoneurons. This study was prompted by the growing experimental evidence of the functional interactions between synaptic inputs and active conductances over the motoneuron dendritic tree. A compartmental cable model of an adult cat α-motoneuron was developed in NEURON simulation environment constituting the detailed morphology of type-identified triceps surae α-motoneuron and realistic distribution of group Ia afferent-to-motoneuron contacts. Simulations of different distributions of CaV1.3 channels were conducted and the resultant behavior was compared to experimental data. Our results suggest that CaV1.3 channels do not uniformly cover the whole motoneuron dendritic tree. Instead, their distribution is similar to that of synaptic contacts. We found that CaV1.3 channels are primarily localized to a wide intermediate band overlapping with the dendritic Ia-synaptic territory at dendritic distances of 300 to 850 μm (0.62 ± 0.21λ) from the soma in triceps surae α-motoneurons. These findings explain the functional interaction between synaptic inputs and the CaV1.3 channels over the motoneuron dendritic tree.

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