scholarly journals Variability and Randomness of the Instantaneous Firing Rate

2021 ◽  
Vol 15 ◽  
Author(s):  
Rimjhim Tomar ◽  
Lubomir Kostal
Keyword(s):  
Firing Rate ◽  
Neuronal Activity ◽  
Probability Distributions ◽  
Spike Timing ◽  
Neuronal Firing ◽  
Instantaneous Rate ◽  
Neuronal Coding ◽  
Additional Information ◽  
Rate Analysis ◽  
Statistical Dispersion

The apparent stochastic nature of neuronal activity significantly affects the reliability of neuronal coding. To quantify the encountered fluctuations, both in neural data and simulations, the notions of variability and randomness of inter-spike intervals have been proposed and studied. In this article we focus on the concept of the instantaneous firing rate, which is also based on the spike timing. We use several classical statistical models of neuronal activity and we study the corresponding probability distributions of the instantaneous firing rate. To characterize the firing rate variability and randomness under different spiking regimes, we use different indices of statistical dispersion. We find that the relationship between the variability of interspike intervals and the instantaneous firing rate is not straightforward in general. Counter-intuitively, an increase in the randomness (based on entropy) of spike times may either decrease or increase the randomness of instantaneous firing rate, in dependence on the neuronal firing model. Finally, we apply our methods to experimental data, establishing that instantaneous rate analysis can indeed provide additional information about the spiking activity.

scholarly journals Phasic Neuronal Firing in the Rodent Nucleus of the Solitary Tract ex vivo

2021 ◽  
Vol 12 ◽  
Author(s):  
Lukasz Chrobok ◽  
Michal Wojcik ◽  
Jasmin Daniela Klich ◽  
Kamil Pradel ◽  
Marian Henryk Lewandowski ◽  
...  
Keyword(s):  
Firing Rate ◽  
Neuronal Activity ◽  
Area Postrema ◽  
Ex Vivo ◽  
Electrode Array ◽  
Neuronal Firing ◽  
Solitary Tract ◽  
Downstream Target ◽  
Cardio Vascular ◽  
Vasopressin Neurons

Phasic pattern of neuronal activity has been previously described in detail for magnocellular vasopressin neurons in the hypothalamic paraventricular and supraoptic nuclei. This characteristic bistable pattern consists of alternating periods of electrical silence and elevated neuronal firing, implicated in neuropeptide release. Here, with the use of multi-electrode array recordings ex vivo, we aimed to study the firing pattern of neurons in the nucleus of the solitary tract (NTS) – the brainstem hub for homeostatic, cardio-vascular, and metabolic processes. Our recordings from the mouse and rat hindbrain slices reveal the phasic activity pattern to be displayed by a subset of neurons in the dorsomedial NTS subjacent to the area postrema (AP), with the inter-spike interval distribution closely resembling that reported for phasic magnocellular vasopressin cells. Additionally, we provide interspecies comparison, showing higher phasic frequency and firing rate of phasic NTS cells in mice compared to rats. Further, we describe daily changes in their firing rate and pattern, peaking at the middle of the night. Last, we reveal these phasic cells to be sensitive to α2 adrenergic receptors activation and to respond to electrical stimulation of the AP. This study provides a comprehensive description of the phasic neuronal activity in the rodent NTS and identifies it as a potential downstream target of the AP noradrenergic system.

scholarly journals Movement-related coupling of human subthalamic nucleus spikes to cortical gamma

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Petra Fischer ◽  
Witold J Lipski ◽  
Wolf-Julian Neumann ◽  
Robert S Turner ◽  
Pascal Fries ◽  
...  
Keyword(s):  
Basal Ganglia ◽  
Firing Rate ◽  
Subthalamic Nucleus ◽  
Information Transfer ◽  
Reaction Times ◽  
Spike Timing ◽  
Neuronal Firing ◽  
Gamma Activity ◽  
Gamma Phase ◽  
Phase Coupling

Cortico-basal ganglia interactions continuously shape the way we move. Ideas about how this circuit works are based largely on models those consider only firing rate as the mechanism of information transfer. A distinct feature of neural activity accompanying movement, however, is increased motor cortical and basal ganglia gamma synchrony. To investigate the relationship between neuronal firing in the basal ganglia and cortical gamma activity during movement, we analysed human ECoG and subthalamic nucleus (STN) unit activity during hand gripping. We found that fast reaction times were preceded by enhanced STN spike-to-cortical gamma phase coupling, indicating a role in motor preparation. Importantly, increased gamma phase coupling occurred independent of changes in mean STN firing rates, and the relative timing of STN spikes was offset by half a gamma cycle for ipsilateral vs. contralateral movements, indicating that relative spike timing is as relevant as firing rate for understanding cortico-basal ganglia information transfer.

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 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 α-Synuclein-induced dysregulation of neuronal activity contributes to murine dopamine neuron vulnerability

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Abeer Dagra ◽  
Douglas R. Miller ◽  
Min Lin ◽  
Adithya Gopinath ◽  
Fatemeh Shaerzadeh ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Neuronal Activity ◽  
Dopaminergic Neurons ◽  
Prolonged Exposure ◽  
D2 Receptor ◽  
Neuronal Firing ◽  
Dopamine Neurons ◽  
Loss Of Function ◽  
Therapeutic Implications

AbstractPathophysiological damages and loss of function of dopamine neurons precede their demise and contribute to the early phases of Parkinson’s disease. The presence of aberrant intracellular pathological inclusions of the protein α-synuclein within ventral midbrain dopaminergic neurons is one of the cardinal features of Parkinson’s disease. We employed molecular biology, electrophysiology, and live-cell imaging to investigate how excessive α-synuclein expression alters multiple characteristics of dopaminergic neuronal dynamics and dopamine transmission in cultured dopamine neurons conditionally expressing GCaMP6f. We found that overexpression of α-synuclein in mouse (male and female) dopaminergic neurons altered neuronal firing properties, calcium dynamics, dopamine release, protein expression, and morphology. Moreover, prolonged exposure to the D2 receptor agonist, quinpirole, rescues many of the alterations induced by α-synuclein overexpression. These studies demonstrate that α-synuclein dysregulation of neuronal activity contributes to the vulnerability of dopaminergic neurons and that modulation of D2 receptor activity can ameliorate the pathophysiology. These findings provide mechanistic insights into the insidious changes in dopaminergic neuronal activity and neuronal loss that characterize Parkinson’s disease progression with significant therapeutic implications.

Quantitative Analysis of Abducens Neuron Discharge Dynamics During Saccadic and Slow Eye Movements

1999 ◽  
Vol 82 (5) ◽  
pp. 2612-2632 ◽  
Author(s):  
Pierre A. Sylvestre ◽  
Kathleen E. Cullen
Keyword(s):  
Eye Movements ◽  
Firing Rate ◽  
Eye Movement ◽  
Neuronal Activity ◽  
Smooth Pursuit ◽  
Slow Phase ◽  
Vestibular Nystagmus ◽  
Firing Rates ◽  
Rapid Eye Movements ◽  
Eye Velocity

The mechanics of the eyeball and its surrounding tissues, which together form the oculomotor plant, have been shown to be the same for smooth pursuit and saccadic eye movements. Hence it was postulated that similar signals would be carried by motoneurons during slow and rapid eye movements. In the present study, we directly addressed this proposal by determining which eye movement–based models best describe the discharge dynamics of primate abducens neurons during a variety of eye movement behaviors. We first characterized abducens neuron spike trains, as has been classically done, during fixation and sinusoidal smooth pursuit. We then systematically analyzed the discharge dynamics of abducens neurons during and following saccades, during step-ramp pursuit and during high velocity slow-phase vestibular nystagmus. We found that the commonly utilized first-order description of abducens neuron firing rates (FR = b + kE + rE˙, where FR is firing rate, E and E˙ are eye position and velocity, respectively, and b, k, and r are constants) provided an adequate model of neuronal activity during saccades, smooth pursuit, and slow phase vestibular nystagmus. However, the use of a second-order model, which included an exponentially decaying term or “slide” (FR = b + kE + rE˙ + uË − c[Formula: see text]), notably improved our ability to describe neuronal activity when the eye was moving and also enabled us to model abducens neuron discharges during the postsaccadic interval. We also found that, for a given model, a single set of parameters could not be used to describe neuronal firing rates during both slow and rapid eye movements. Specifically, the eye velocity and position coefficients ( r and k in the above models, respectively) consistently decreased as a function of the mean (and peak) eye velocity that was generated. In contrast, the bias ( b, firing rate when looking straight ahead) invariably increased with eye velocity. Although these trends are likely to reflect, in part, nonlinearities that are intrinsic to the extraocular muscles, we propose that these results can also be explained by considering the time-varying resistance to movement that is generated by the antagonist muscle. We conclude that to create realistic and meaningful models of the neural control of horizontal eye movements, it is essential to consider the activation of the antagonist, as well as agonist motoneuron pools.

scholarly journals Exercise training normalizes elevated firing rate of hypothalamic presympathetic neurons in heart failure rats

2019 ◽  
Vol 316 (2) ◽  
pp. R110-R120 ◽  
Author(s):  
Yiming Shen ◽  
Jin Bong Park ◽  
So Yeong Lee ◽  
Seong Kyu Han ◽  
Pan Dong Ryu
Keyword(s):  
Heart Failure ◽  
Exercise Training ◽  
Firing Rate ◽  
Gaba Release ◽  
Neuronal Firing ◽  
Ventrolateral Medulla ◽  
Patch Clamp Technique ◽  
Electrophysiological Properties ◽  
Beneficial Effects ◽  
Underlying Mechanisms

Exercise training (ExT) normalizes elevated sympathetic nerve activity in heart failure (HF), but the underlying mechanisms are not well understood. In this study, we examined the effects of 3 wk of ExT on the electrical activity of the hypothalamic presympathetic neurons in the brain slice of HF rats. HF rats were prepared by ligating the left descending coronary artery. The electrophysiological properties of paraventricular nucleus neurons projecting to the rostral ventrolateral medulla (PVN-RVLM) were examined using the slice patch-clamp technique. The neuronal firing rate was elevated in HF rats, and ExT induced a reduction in the firing rate ( P < 0.01). This ExT-induced decrease in the firing rate was associated with an increased frequency of spontaneous and miniature inhibitory postsynaptic current (IPSCs; P < 0.05). There was no significant change in excitatory postsynaptic current. Replacing Ca2+ with Mg2+ in the recording solution reduced the elevated IPSC frequency in HF rats with ExT ( P < 0.01) but not in those without ExT, indicating an increase in the probability of GABA release. In contrast, ExT did not restore the reduced GABAA receptor-mediated tonic inhibitory current in HF rats. A GABAA receptor blocker (bicuculline, 20 μM) increased the firing rate in HF rats with ExT ( P < 0.01) but not in those without ExT. Collectively, these results show that ExT normalized the elevated firing activity by increasing synaptic GABA release in PVN-RVLM neurons in HF rats. Our findings provide a brain mechanism underlying the beneficial effects of ExT in HF, which may shed light on the pathophysiology of other diseases accompanied by sympathetic hyperactivation.

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