scholarly journals Modulation of motoneuron firing by recurrent inhibition in the adult rat in vivo

2014 ◽  
Vol 112 (9) ◽  
pp. 2302-2315 ◽  
Author(s):  
Ahmed Z. Obeidat ◽  
Paul Nardelli ◽  
Randall K. Powers ◽  
Timothy C. Cope
Keyword(s):  
Firing Rate ◽  
Neural Circuit ◽  
Average Rate ◽  
Spike Timing ◽  
Recurrent Inhibition ◽  
Repetitive Firing ◽  
Synaptic Inhibition ◽  
Adult Rat ◽  
Electrophysiological Studies

Recent reports show that synaptic inhibition can modulate postsynaptic spike timing without having strong effects on firing rate. Thus synaptic inhibition can achieve multiplicity in neural circuit operation through variable modulation of postsynaptic firing rate vs. timing. We tested this possibility for recurrent inhibition (RI) of spinal motoneurons. In in vivo electrophysiological studies of adult Wistar rats anesthetized by isoflurane, we examined repetitive firing of individual lumbosacral motoneurons recorded in current clamp and modulated by synchronous antidromic electrical stimulation of multiple motor axons and their centrally projecting collateral branches. Antidromic stimulation produced recurrent inhibitory postsynaptic potentials (RIPSPs) having properties similar to those detailed in the cat. Although synchronous RI produced marked short-term modulation of motoneuron spike timing and instantaneous firing rate, there was little or no suppression of average firing rate. The bias in firing modulation of timing over average rate was observed even for high-frequency RI stimulation (100 Hz), perhaps because of the brevity of RIPSPs, which were more than twofold shorter during motoneuron firing compared with rest. These findings demonstrate that RI in the mammalian spinal cord has the capacity to support and not impede heightened motor pool activity, possibly during rapid, forceful movements.

scholarly journals Sparse bursts optimize information transmission in a multiplexed neural code

2018 ◽  
Vol 115 (27) ◽  
pp. E6329-E6338 ◽  
Author(s):  
Richard Naud ◽  
Henning Sprekeler
Keyword(s):  
Firing Rate ◽  
Cortical Neurons ◽  
Neural Code ◽  
Spike Timing ◽  
Neural Ensemble ◽  
Multiple Input ◽  
Cortical Hierarchy ◽  
Connectivity Patterns ◽  
Rate Coding

Many cortical neurons combine the information ascending and descending the cortical hierarchy. In the classical view, this information is combined nonlinearly to give rise to a single firing-rate output, which collapses all input streams into one. We analyze the extent to which neurons can simultaneously represent multiple input streams by using a code that distinguishes spike timing patterns at the level of a neural ensemble. Using computational simulations constrained by experimental data, we show that cortical neurons are well suited to generate such multiplexing. Interestingly, this neural code maximizes information for short and sparse bursts, a regime consistent with in vivo recordings. Neurons can also demultiplex this information, using specific connectivity patterns. The anatomy of the adult mammalian cortex suggests that these connectivity patterns are used by the nervous system to maintain sparse bursting and optimal multiplexing. Contrary to firing-rate coding, our findings indicate that the physiology and anatomy of the cortex may be interpreted as optimizing the transmission of multiple independent signals to different targets.

scholarly journals Predicting the response of striatal spiny neurons to sinusoidal input

2017 ◽  
Vol 118 (2) ◽  
pp. 855-873 ◽  
Author(s):  
Charles. J. Wilson
Keyword(s):  
Firing Rate ◽  
Action Potentials ◽  
Interspike Interval ◽  
Spike Timing ◽  
Repetitive Firing ◽  
Phase Resetting ◽  
Spiny Neurons ◽  
Wide Range ◽  
Sinusoidal Input ◽  
Sinusoidal Currents

During repetitive firing, the timing of action potentials is determined by the interaction between the input and voltage-sensitive currents throughout the interspike interval. This interaction is encapsulated in the neuron’s phase-resetting curve. The phase-resetting curve predicted spike timing to small sinusoidal currents over a wide range of stimulus frequencies. Firing patterns were most sensitive to oscillatory components near the cell’s own firing rate, even in the presence of noise and other inputs.

scholarly journals The ionic mechanism of gamma resonance in rat striatal fast-spiking neurons

2011 ◽  
Vol 106 (6) ◽  
pp. 2936-2949 ◽  
Author(s):  
Giuseppe Sciamanna ◽  
Charles J. Wilson
Keyword(s):  
Firing Rate ◽  
Firing Pattern ◽  
Field Potential ◽  
Gamma Oscillations ◽  
Repetitive Firing ◽  
Spike Threshold ◽  
Gamma Frequency ◽  
Subthreshold Oscillations ◽  
Fast Spiking

Striatal fast-spiking (FS) cells in slices fire in the gamma frequency range and in vivo are often phase-locked to gamma oscillations in the field potential. We studied the firing patterns of these cells in slices from rats ages 16–23 days to determine the mechanism of their gamma resonance. The resonance of striatal FS cells was manifested as a minimum frequency for repetitive firing. At rheobase, cells fired a doublet of action potentials or doublets separated by pauses, with an instantaneous firing rate averaging 44 spikes/s. The minimum rate for sustained firing was also responsible for the stuttering firing pattern. Firing rate adapted during each episode of firing, and bursts were terminated when firing was reduced to the minimum sustainable rate. Resonance and stuttering continued after blockade of Kv3 current using tetraethylammonium (0.1–1 mM). Both gamma resonance and stuttering were strongly dependent on Kv1 current. Blockade of Kv1 channels with dendrotoxin-I (100 nM) completely abolished the stuttering firing pattern, greatly lowered the minimum firing rate, abolished gamma-band subthreshold oscillations, and slowed spike frequency adaptation. The loss of resonance could be accounted for by a reduction in potassium current near spike threshold and the emergence of a fixed spike threshold. Inactivation of the Kv1 channel combined with the minimum firing rate could account for the stuttering firing pattern. The resonant properties conferred by this channel were shown to be adequate to account for their phase-locking to gamma-frequency inputs as seen in vivo.

scholarly journals Synaptic plasticity is predicted by spatiotemporal firing rate patterns and robust to in vivo-like variability

2021 ◽  
Author(s):  
Dan B Dorman ◽  
Kim T Blackwell
Keyword(s):  
Synaptic Plasticity ◽  
Firing Rate ◽  
Dendritic Tree ◽  
Spike Timing ◽  
Synaptic Activity ◽  
Data Driven ◽  
Synaptic Inputs ◽  
The Brain

Synaptic plasticity, the experience-induced change in connections between neurons, underlies learning and memory in the brain. Most of our understanding of synaptic plasticity derives from in vitro experiments with precisely repeated stimulus patterns; however, neurons exhibit significant variability in vivo during repeated experiences. Further, the spatial pattern of synaptic inputs to the dendritic tree influences synaptic plasticity, yet is not considered in most synaptic plasticity rules. Here, we address the sensitivity of plasticity to trial-to-trial variability and delineate how spatiotemporal synaptic input patterns produce plasticity with in vivo-like conditions using a data-driven computational model with a calcium-based plasticity rule. Using in vivo spike train recordings as inputs, we show that plasticity is strongly robust to trial-to-trial variability of spike timing, and derive general synaptic plasticity rules describing how spatiotemporal patterns of synaptic inputs control the magnitude and direction of plasticity. Specifically, a high temporal input firing rate to a synapse late in a trial correlated with neighboring synaptic activity produces potentiation, while an earlier, moderate firing rate that is negatively correlated with neighboring synaptic activity produces depression. Together, our results reveal that calcium dynamics can unify diverse plasticity rules and reveal how spatiotemporal firing rate patterns control synaptic plasticity.

scholarly journals Recording and neural circuit-based manipulation of the maternal oxytocin pulses in mice

2021 ◽  
Author(s):  
Hiroko Yukinaga ◽  
Mitsue Hagihara ◽  
Kazuko Tsujimoto ◽  
Hsiao-Ling Chiang ◽  
Shigeki Kato ◽  
...  
Keyword(s):  
Uterine Contraction ◽  
Neural Circuit ◽  
Genetic Manipulation ◽  
Activity Patterns ◽  
Milk Ejection ◽  
Pulsatile Release ◽  
Synaptic Structure ◽  
Electrophysiological Studies ◽  
Neuroendocrine Functions

For mammals, successful parturition and breastfeeding are critical to the survival of offspring. Pulsatile release of the hormone oxytocin mediates uterine contraction during parturition and milk ejection during lactation. These oxytocin pulses are generated by unique activity patterns of the central neuroendocrine oxytocin neurons located in the paraventricular and supraoptic hypothalamus. However, the maternal activities of oxytocin neurons remain elusive because most classical electrophysiological studies in anesthetized rats have lacked the genetically defined cell identity of oxytocin neurons. We herein introduce viral genetic approaches in mice to characterize the maternal pulsatile activities of oxytocin neurons by fiber-photometry-based chronic in vivo Ca2+ imaging. We also demonstrate the pharmaco-genetic manipulation of oxytocin pulses during lactation via activating a prominent pre-synaptic structure of oxytocin neurons defined by retrograde trans-synaptic tracing. Collectively, our study opens a new avenue for the neuroscience of maternal neuroendocrine functions.

scholarly journals Acetylcholine-gated current translates wake neuronal firing rate information into a spike timing-based code in Non-REM sleep, stabilizing neural network dynamics during memory consolidation

2021 ◽  
Vol 17 (9) ◽  
pp. e1009424
Author(s):  
Quinton M. Skilling ◽  
Bolaji Eniwaye ◽  
Brittany C. Clawson ◽  
James Shaver ◽  
Nicolette Ognjanovski ◽  
...  
Keyword(s):  
Firing Rate ◽  
Memory Consolidation ◽  
Neuronal Excitability ◽  
Network Models ◽  
Nrem Sleep ◽  
Spike Timing ◽  
Neuronal Firing ◽  
Information Encoding ◽  
Firing Rates

Sleep is critical for memory consolidation, although the exact mechanisms mediating this process are unknown. Combining reduced network models and analysis of in vivo recordings, we tested the hypothesis that neuromodulatory changes in acetylcholine (ACh) levels during non-rapid eye movement (NREM) sleep mediate stabilization of network-wide firing patterns, with temporal order of neurons’ firing dependent on their mean firing rate during wake. In both reduced models and in vivo recordings from mouse hippocampus, we find that the relative order of firing among neurons during NREM sleep reflects their relative firing rates during prior wake. Our modeling results show that this remapping of wake-associated, firing frequency-based representations is based on NREM-associated changes in neuronal excitability mediated by ACh-gated potassium current. We also show that learning-dependent reordering of sequential firing during NREM sleep, together with spike timing-dependent plasticity (STDP), reconfigures neuronal firing rates across the network. This rescaling of firing rates has been reported in multiple brain circuits across periods of sleep. Our model and experimental data both suggest that this effect is amplified in neural circuits following learning. Together our data suggest that sleep may bias neural networks from firing rate-based towards phase-based information encoding to consolidate memories.

scholarly journals Effects of Glutamate andγ-Aminobutyric Acid on Spontaneously Active Intraocular Spinal Cord Graft Neurons

1991 ◽  
Vol 2 (2) ◽  
pp. 101-111
Author(s):  
J. G. Broton ◽  
R. P. Yezierski ◽  
Å. Seiger
Keyword(s):  
Spinal Cord ◽  
Firing Rate ◽  
Gaba Receptor ◽  
Aminobutyric Acid ◽  
Lumbar Spinal Cord ◽  
Adult Rat ◽  
Fetal Rat ◽  
Single Unit Recordings ◽  
Lumbar Spinal

Pieces of fetal rat lumbar spinal cord were transplanted into the anterior eye chamber of adult rat hosts. At least seven months later, extracellular single-unit recordings of spontaneously active graft neurons were made prior to and during the superfusion of either glutamate orγ-aminobutyric acid (GABA). Superfusion of glutamate produced an increase (five cells), decrease (three cells), or had no effect (two cells) on the firing rate of neurons tested. Superfusion of GABA decreased the firing rate of all twelve neurons tested, while superfusion of the GABA receptor antagonist bicuculline increased the firing rates of all eight neurons tested. The latency and magnitude of the responses to glutamate and GABA were not related to depth of the recording electrode below the graft surface. Together, these data suggest that the intraocular spinal cord graft is suitable for thein vivostudy of GABA and glutamate neuropharmacology.

scholarly journals A deep convolutional visual encoding model of neuronal responses in the LGN

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Eslam Mounier ◽  
Bassem Abdullah ◽  
Hani Mahdi ◽  
Seif Eldawlatly
Keyword(s):  
Firing Rate ◽  
Visual Information ◽  
Visual Stimulation ◽  
Neuronal Population ◽  
Neuronal Firing ◽  
Electrode Arrays ◽  
Deep Convolutional Neural Networks ◽  
Firing Rates ◽  
Spatiotemporal Representation

AbstractThe Lateral Geniculate Nucleus (LGN) represents one of the major processing sites along the visual pathway. Despite its crucial role in processing visual information and its utility as one target for recently developed visual prostheses, it is much less studied compared to the retina and the visual cortex. In this paper, we introduce a deep learning encoder to predict LGN neuronal firing in response to different visual stimulation patterns. The encoder comprises a deep Convolutional Neural Network (CNN) that incorporates visual stimulus spatiotemporal representation in addition to LGN neuronal firing history to predict the response of LGN neurons. Extracellular activity was recorded in vivo using multi-electrode arrays from single units in the LGN in 12 anesthetized rats with a total neuronal population of 150 units. Neural activity was recorded in response to single-pixel, checkerboard and geometrical shapes visual stimulation patterns. Extracted firing rates and the corresponding stimulation patterns were used to train the model. The performance of the model was assessed using different testing data sets and different firing rate windows. An overall mean correlation coefficient between the actual and the predicted firing rates of 0.57 and 0.7 was achieved for the 10 ms and the 50 ms firing rate windows, respectively. Results demonstrate that the model is robust to variability in the spatiotemporal properties of the recorded neurons outperforming other examined models including the state-of-the-art Generalized Linear Model (GLM). The results indicate the potential of deep convolutional neural networks as viable models of LGN firing.

scholarly journals In vivo phosphorylation sites in fetal and adult rat tau.

1993 ◽  
Vol 268 (34) ◽  
pp. 25712-25717
Author(s):  
A Watanabe ◽  
M Hasegawa ◽  
M Suzuki ◽  
K Takio ◽  
M Morishima-Kawashima ◽  
...  
Keyword(s):  
Phosphorylation Sites ◽  
Adult Rat
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