Biology subjects

Dervinis, M.

Publications and source records attributed to Dervinis, M..

6 recordsLinked to original sources

bioRxiv2024

Novel quantal analysis method reveals conservation of injected charge by excitatory synapses across cortical cells of different sizes

In chemical synapses of the central nervous system (CNS), information is transmitted via the presynaptic release of a vesicle (or quantum) of neurotransmitter, which elicits a postsynaptic electrical response with an amplitude termed the quantal size. Measuring amplitudes of miniature postsynaptic currents (mPSCs) or potentials (mPSPs) at the cell soma is generally thought to offer a technically straightforward way to estimate quantal sizes, as each of these miniature responses (or minis) is generally thought to be elicited by the spontaneous release of a single neurotransmitter vesicle. However, in large highly-branched neurons, a somatically recorded mini is typically massively attenuated compared with at its input site, and a significant fraction are indistinguishable from (or cancelled out by) background noise fluctuations. Here, using a new software package (also) called minis, we describe a novel quantal analysis method that estimates the electrical size of the synapse by comparing events detected in somatic recordings from the same neuron of (a) real minis and (b) background noise (with minis blocked pharmacologically) with simulated minis added by a genetic algorithm. The estimated minis distributions reveal a striking inverse dependence of mean excitatory mPSP amplitude on total cell membrane capacitance (proportional to cell size, or more exactly, extracellular membrane surface area) suggesting that, in rats at least, the average charge injected by single excitatory synapses (ca. 30 fC) is conserved across neocortical pyramidal neurons of very different sizes (across a more than three-fold range).

neuroscience↗

bioRxiv2022

Sleep waves in a large-scale corticothalamic model constrained by activities intrinsic to neocortical networks and single thalamic neurons

AimMany biophysical and non-biophysical models have been able to reproduce the corticothalamic activities underlying different EEG sleep rhythms but none of them included the known ability of neocortical networks and single thalamic neurons to generate some of these waves intrinsically. MethodsWe built a large-scale corticothalamic model with a high fidelity in anatomical connectivity consisting of a single cortical column and first- and higher-order thalamic nuclei. The model is constrained by different neocortical excitatory and inhibitory neuronal populations eliciting slow (<1 Hz) oscillations and by thalamic neurons generating sleep waves when isolated from the neocortex. ResultsOur model faithfully reproduces all EEG sleep waves and the transition from a desynchronized EEG to spindles, slow (<1 Hz) oscillations and delta waves by progressively increasing neuronal membrane hyperpolarization as it occurs in the intact brain. Moreover, our model shows that slow (<1 Hz) waves most often start in a small assembly of thalamocortical neurons though occasionally they originate in cortical layer 5. Moreover, thalamocortical neuron input increases the frequency of slow (<1 Hz) waves compared to those generated by isolated cortical networks. ConclusionOur simulations challenge current mechanistic understanding of the temporal dynamics of sleep wave generation and suggest testable predictions.

neuroscience↗

bioRxiv2022

Spike-and-wave discharges of absence seizures in a sleep waves-constrained corticothalamic model

AimsRecurrent network activity in corticothalamic circuits generates physiological and pathological EEG waves. Many computer models have simulated spike-and-wave discharges (SWDs), the EEG hallmark of absence seizures (ASs). However, these models either provided detailed simulated activity only in a selected territory (i.e. cortical or thalamic) or did not test whether their corticothalamic networks could reproduce the physiological activities that are generated by these circuits. MethodsUsing a biophysical large-scale corticothalamic model that reproduces the full extent of EEG sleep waves, including sleep spindles, delta and slow (<0.1 Hz) waves, here we investigated how single abnormalities in voltage- or transmitter-gated channels in the neocortex or thalamus lead to SWDs. ResultsWe found that a selective increase in the tonic {gamma}-aminobutyric acid type A receptor (GABA-A) inhibition of first order thalamocortical (TC) neurons or a selective decrease in cortical phasic GABA-A inhibition are sufficient to generate [~]4 Hz SWDs (as in humans) that invariably start in neocortical territories. Decreasing the leak conductance of higher order TC neurons leads to [~]7 Hz SWDs (as in rodent models) while maintaining sleep spindles at 7-14 Hz. ConclusionBy challenging key features of current mechanistic views, this simulated ictal corticothalamic activity provides novel understanding of ASs and makes key testable predictions.

neuroscience↗

bioRxiv2022

Novel method for reliably measuring spontaneous postsynaptic potentials/currents in whole-cell patch clamp recordings in the central nervous system

Measurements of miniature postsynaptic currents (mPSCs) or potentials (mPSPs) in the soma of neurons of the central nervous system (CNS) provide a way of quantifying the synaptic function at the network level and, therefore, are routine in the neurophysiology literature. These miniature responses (or minis) are thought to be elicited by the spontaneous release of a single neurotransmitter vesicle, also called quantum. As such their measurement at the soma can potentially offer a technically straightforward way of estimating quantal sizes of central synapses. However, popular methods for detecting minis in whole-cell recordings fall short of being able to reliably distinguish them from background physiological noise. This issue has received very limited attention in the literature and its scope as well as the relative performance of existing algorithms have not been quantified. As a result, solutions for reliably measuring the quantal size in somatic recordings also do not exist. As the first step in proposing and testing a potential solution, we developed and described a novel mPSP/mPSC detection algorithm as part of our quantal analysis software called minis. We tested its performance in detecting real and simulated minis in whole-cell recordings from pyramidal neurons in rat neocortical slices and compared it to two of the most-used mini detection algorithms. This benchmarking revealed superior detection by our algorithm. The release version of the algorithm also offers great flexibility via graphical and programming interfaces.

neuroscience↗

bioRxiv2021

Stretching and squeezing of neuronal log firing rate distribution by psychedelic and intrinsic brain state transitions

How psychedelic drugs change the activity of cortical neuronal populations and whether such changes are specific to transition into the psychedelic brain state or shared with other brain state transitions is not well understood. Here, we used Neuropixels probes to record from large populations of neurons in prefrontal cortex of mice given the psychedelic drug TCB-2. Drug ingestion significantly stretched the distribution of log firing rates of the population of recorded neurons. This phenomenon was previously observed across transitions between sleep and wakefulness, which suggested that stretching of the log-rate distribution can be triggered by different kinds of brain state transitions and prompted us to examine it in more detail. We found that modulation of the width of the log-rate distribution of a neuronal population occurred in multiple areas of the cortex and in the hippocampus even in awake drug-free mice, driven by intrinsic fluctuations in their arousal level. Arousal, however, did not explain the stretching of the log-rate distribution by TCB-2. In both psychedelic and naturally occurring brain state transitions, the stretching or squeezing of the log-rate distribution of an entire neuronal population reflected concomitant changes in two subpopulations, with one subpopulation undergoing a downregulation and often also stretching of its neurons log-rate distribution, while the other subpopulation undergoes upregulation and often also a squeeze of its log-rate distribution. In both subpopulations, the stretching and squeezing were a signature of a greater relative impact of the brain state transition on the rates of the slow-firing neurons. These findings reveal a generic pattern of reorganisation of neuronal firing rates by different kinds of brain state transitions.

neuroscience↗

bioRxiv2018

Distinct structure of cortical population activity on fast and infraslow timescales

Cortical activity is organised across multiple spatial and temporal scales. Most research on the dynamics of neuronal spiking is concerned with timescales of 1 ms - 1 s, and little is known about spiking dynamics on timescales of tens of seconds and minutes. Here, we used frequency domain analyses to study the structure of individual neurons spiking activity and its coupling to local population rate and to arousal level across frequencies ranging from 0.01 to 100 Hz. In mouse medial prefrontal cortex (mPFC), the spiking dynamics of individual neurons could be quantitatively captured by a combination of interspike interval and firing rate power spectrum distributions. The relative strength of coherence with local population often differed across timescales: a neuron strongly coupled to population rate on fast timescales could be weakly coupled on slow timescales, and vice versa. On slow but not fast timescales, a substantial proportion of neurons showed firing anti-correlated with the population. Infraslow firing rate changes were largely determined by arousal rather than by local factors, which could explain the timescale dependence of population coupling strength of individual neurons. These observations demonstrate how individual neurons simultaneously partake in fast local dynamics, and slow brain-wide dynamics, extending our understanding of infraslow cortical activity beyond the mesoscale resolution of fMRI studies.

neuroscience↗