Steroids and Brain Cell Activity During the Menstrual Cycle
Diana L. Taylor, Nancy F. Woods in Menstruation, Health, and Illness, 2019
When 17β-estradiol was applied on a number of spontaneously active rat cerebral cortical neurons, the most frequently observed responses were either a decrease in the rate of spontaneous firing (44%) occurring within 1–2 min of the onset of steroid application or the absence of any change in the spontaneous activity (47%) (Phillis & O’Regan, 1988). An increase in firing rate was observed with a few neurons (9%). Firing rates returned to control levels within a few minutes of the cessation of steroid application. 17α-estradiol, a weak or inactive estrogen with no effect on reproductive function, was used as a control for the effects of the 17β-isomer. It also had a mild depressant action on the firing cerebral cortical neurons, which may have been a result of its weak ability to inhibit adenosine transport (Phillis et al., 1985).
Neuronal Firing Patterns and Models
Nassir H. Sabah in Neuromuscular Fundamentals, 2020
Neuronal models, both dynamical and biophysical, are introduced in the remaining part of the chapter, the goal being to explain the nature of these models and their main characteristic features rather than delve into the mathematical details. The description of dynamical models starts with the basic integrate-and-fire model and progresses through the resonate-and-fire model, the fast–slow reduced Hodgkin–Huxley model, the Fitzhugh–Nagumo model, the quadratic model, and the Morris–Lecar model. As for biophysical models, the basic equivalent cylinder model of a dendritic tree is first presented as an example of a morphological-to-electrotonic transformation, followed by a description of the popular and versatile compartmental models. The chapter ends by considering modelling of neuronal networks, including the firing rate model.
Auditory nerve
Stanley A. Gelfand in Hearing, 2017
Let us briefly review a number of simple definitions and concepts about neural activity before we proceed. Nerve fibers elicit all-or-none electrical discharges called action potentials, which are picked up by electrodes and typically appear on recording devices as “spikes” at certain points in time (Figure 5.1). For obvious reasons, action potentials are often called spikes or spike potentials, and the discharging of a spike potential is also called firing. Similarly, the number of action potentials discharged per second is known as the firing rate or discharge rate, and the manner in which spikes are elicited over time is known as the discharge pattern or firing pattern. Figure 5.1 shows a number of idealized auditory nerve firing patterns. The rate at which a neuron fires “on its own” when there is no stimulation is called its spontaneous rate, and is illustrated in frame (a) of the figure. Activation of the neuron by a stimulus is associated with an increase in its firing rate above its spontaneous rate (frames [b] and [c]). Finally, an increase in the level of a stimulus is typically associated with an increase in the firing rate (frame [b] versus frame [c]), at least within certain limits.
Distinctions among electroconvulsion- and proconvulsant-induced seizure discharges and native motor patterns during flight and grooming: quantitative spike pattern analysis in Drosophila flight muscles
Published in Journal of Neurogenetics, 2019
Jisue Lee, Atulya Iyengar, Chun-Fang Wu
Firing rate was analyzed using two measures: instantaneous firing frequency and overall spiking rate over a specified time window of interest. The instantaneous firing frequency was defined as the reciprocal of the inter-spike interval (ISI) measured in seconds, between successive spikes (Knight, 1972; Lansky, Rodriguez, & Sacerdote, 2004), referred to as ISI−1 with units of Hz. For sequential ISI−1s in a spike train, the occurrence of the first spike is used to mark the temporal location of the particular ISI. The overall spike rate was defined as the total spike count during the specified time window divided by its duration. Poincaré trajectories (Figures 4, 7, and 9) were constructed by plotting the time series of ISI−1 within a spike train, with each ISI−1 against the ISI−1 of the subsequent interval, i.e. ISI−1ivs. ISI−1i+1. Therefore, for a spike train of n spikes, there will be n-1 data points in the Poincaré trajectory.
5-HT1B receptor-AC-PKA signal pathway in the lateral habenula is involved in the regulation of depressive-like behaviors in 6-hydroxydopamine-induced Parkinson’s rats
Published in Neurological Research, 2023
Guo Yi Tang, Run Jia Wang, Yuan Guo, Jian Liu
In this study, only rats verified the location of the cannula, recording site, probe, and a near complete loss of TH immunoreactive (TH-ir) neurons in the right SNc were used to analyze behavioral, electrophysiological, and microdialysis data. Additionally, only rats with reduced striatal DA by >90% were considered for the analysis of Western blotting data. For electrophysiological data, basal firing activity of LHb neurons was recorded for 5 min before any treatment, and the following parameters were calculated: (i) mean firing rate; and (ii) coefficient of variation (COV, the ratio between standard deviation of the interspike interval and mean interspike interval, reflecting the degree of regularity of neuronal firing) [34]. After intra-LHb injection of CP93129 or SB216641, changes in the firing rate of the neurons were analyzed per 5 min epoch up to 25 min. The COV of the neurons was compared in a period of 5 min before and after injection of the drugs. For microdialysis data, the average of three consecutive dialysates before injection of the drugs was defined as 100% of basal transmitter release. In TH immunohistochemistry, three representative sections per rat were used to count TH-ir neurons in the SNc and VTA.
Consciousness in a Rotor? Science and Ethics of Potentially Conscious Human Cerebral Organoids
Published in AJOB Neuroscience, 2023
Federico Zilio, Andrea Lavazza
A recent study showed for the first time that cortical organoids can spontaneously develop periodic and regular oscillatory network electrical activity very similar to the EEG patterns of preterm babies (Trujillo et al. 2019). Even in the absence of external or subcortical inputs, ten-month-old HCOs can grow according to a specific genetic program, like all human beings, and manifest complex brain activity recorded with a multi-microelectrode array. “The spontaneous network formation displayed periodic and regular oscillatory events that were dependent on glutamatergic and GABAergic signaling” (ibidem). The firing rate, up to two or three per second, and the kind of waves—gamma, alpha, and delta—are all typical signs of a vital human brain. Indeed, a machine-learning model based on a preterm newborn’s EEG (ranging from 24–38 weeks) features was able to predict the organoid culture’s age based on the latter’s electrical activity. The software found no significant differences in EEG between the patterns of preterm infants and the patterns of HCOs. These results, although very relevant, do not mean that the recorded activity patterns give rise to the same subjective states as that can be found in preterm babies, such as pain sensations that fetuses after 24 weeks can likely experience.
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