Biology subjects

Rubido, N.

Publications and source records attributed to Rubido, N..

8 recordsLinked to original sources

bioRxiv2023

Dorsal and median raphe neuronal firing dynamics characterized by non-linear metrics

The dorsal (DRN) and median (MRN) raphe are the main serotonergic nuclei, being implicated in sleep and mood regulation. The DRN is mainly serotonergic, where neurons have regular spiking activity, slow firing rate (FR), and long action potential duration (APD). The MRN is divided in a median serotonergic region and a paramedian region, containing principally GABAergic neurons, resulting in more diverse neurochemical and electrophysiological features. In the present study, we aimed to enrich the characterization of the raphe nuclei neurons by using non-linear metrics. This was done by analyzing the neuronal basal firing profile in both nuclei of urethane-anesthetized rats using Ordinal Patterns (OP) Entropy, Bins Entropy, and Permutation Lempel-Ziv Complexity (PLZC). In a first step, we found that typical linear metrics - such as FR, coefficient of variation (CV), and APD - fail to distinguish between MRN and DRN neurons, while OP entropy is significantly different between these nuclei. We also found that the FR has a strong linear relationship with CV, Bins Entropy, and PLZC. Similarly, CV has a strong correlation with FR and Bins Entropy, whereas PLZC shows a strong linear fit with Bins Entropy. However, OP Entropy has either a weak or no linear relationship with the rest of the metrics tested, suggesting that OP Entropy is a good metric to differentiate neuronal firing profiles. In a second step, we studied how these metrics are affected by the oscillatory properties of the firing patterns. We found that all metrics are sensitive to rhythmicity - with the exception of OP Entropy. Again, this highlights OP Entropy as a powerful and useful quantity for the characterization of neuronal discharge patterns.

neuroscience↗

bioRxiv2021

Low Frequency Oscillations drive EEG's complexity changes during wakefulness and sleep

Recently, the sleep-wake states have been analysed using novel complexity measures, complementing the classical analysis of EEGs by frequency bands. This new approach consistently shows a decrease in EEGs complexity during slow-wave sleep, yet it is unclear how cortical oscillations shape these complexity variations. In this work, we analyse how the frequency content of brain signals affects the complexity estimates in freely moving rats. We find that the low-frequency spectrum - including the Delta, Theta, and Sigma frequency bands - drives the complexity changes during the sleep-wake states. This happens because low-frequency oscillations emerge from neuronal population patterns, as we show by recovering the complexity variations during the sleep-wake cycle from micro, meso, and macroscopic recordings. Moreover, we find that the lower frequencies reveal synchronisation patterns across the neocortex, such as a sensory-motor decoupling that happens during REM sleep. Overall, our works shows that EEGs low frequencies are critical in shaping the sleep-wake states complexity across cortical scales.

neuroscience↗

bioRxiv2021

OFF-periods reduce the complexity of neocortical activity during sleep

Complexity of electroencephalographic signals decreases during slow-wave sleep (SWS), however, the neural mechanism for this decrease remains elusive. Here, we show that this complexity reduction is caused by synchronous neuronal OFF-periods. We analyse in-vivo recordings from neocortical neuronal populations, finding that OFF-periods in SWS trap cortical dynamics, making the population activity more recurrent, deterministic, and less chaotic than during REM sleep or Wakefulness. Importantly, when we exclude OFF-periods, SWS becomes indistinguishable from Wakefulness or REM sleep. In fact, we show that spiking activity for all states has a universal scaling compatible with critical phenomena. We complement these results by a critical branching model that replicates our experimental findings, where we show that forcing OFF-periods to a percentage of neurons suffices to generate a decrease in complexity that replicates SWS.

neuroscience↗

bioRxiv2020

Gamma band alterations and REM-like traits underpin the acute effect of the atypical psychedelic ibogaine

Ibogaine is a psychedelic alkaloid that has attracted scientific interest because of its important antiaddictive properties evidenced in observational studies in humans, and in models for substance-use-disorders in rodents. Its subjective effect has been described as intense vivid dream-like experiences occurring while awake; hence, ibogaine is often referred to as an oneirogenic psychedelic. While this unique dream-like profile has been hypothesized to aid the antiaddictive effects in the past, the electrophysiological signatures of the ibogaine psychedelic state remain unknown. In our previous work, we showed in rats that ibogaine administration promotes a waking state with abnormal motor behavior, accompanied by a decrease in NREM and REM sleep. Here, we performed an in-depth analysis of the intracranial electroencephalogram during "ibogaine wakefulness". Ibogaine induced gamma oscillations with larger power than control levels but less coherent and less complex; i.e., this state shows clear REM sleep traits within the gamma frequency band. Thus, our results provide novel biological evidence for the association between the psychedelic state and REM sleep, and an empirical basis for the oneirogenic conjecture of ibogaine.

neuroscience↗

bioRxiv2020

Communication through coherence by means of cross-frequency coupling

The theory of communication through coherence (CTC) posits the synchronization of brain oscillations as a key mechanism for information sharing and perceptual binding. In a parallel literature, hippocampal theta activity (4 - 10 Hz) has been shown to modulate the appearance of neocortical fast gamma oscillations (100 - 150 Hz), a phenomenon known as cross-frequency coupling (CFC). Even though CFC has also been previously associated with information routing, it remains to be determined whether it directly relates to CTC. In particular, for the theta-fast gamma example at hand, a critical question is to know if the phase of the theta cycle influences gamma synchronization across the neocortex. To answer this question, we designed a new screening method for detecting the modulation of the cross-regional high-frequency synchronization by the phase of slower oscillations. Upon applying the method, we found that the long-distance synchronization of neocortical fast gamma during REM sleep depends on the instantaneous phase of the theta rhythm. These results show that CFC is likely to aid long-range information transfer by facilitating the cross-regional synchronization of faster rhythms, thus consistent with classical CTC views.

neuroscience↗

bioRxiv2020

Electrocortical temporal complexity during wakefulness and sleep: an updated account

The states of sleep and wakefulness are critical physiological processes associated with different brain patterns of activity. The intracranial electroencephalogram allows us to measure these changes, thus, it is a critical tool for its study. Recently, we showed that the electrocortical temporal complexity decreased from wakefulness to sleep. Nevertheless, the origin of this complex activity remains a controversial topic due to the existence of possible artifacts contaminating the brain signals. In this work, we showed that complexity decreases during sleep, independently of the electrode configuration employed. This fact strongly suggests that the basis for the behavioral-state differences in complexity does not have an extracranial origin; i.e., generated from the brain.

neuroscience↗

bioRxiv2019

Decreased electrocortical temporal complexity distinguishes sleep from wakefulness

In most mammals, the sleep-wake cycle is constituted by three behavioral states: wakefulness (W), non-NREM (NREM) sleep, and REM sleep. These states are associated with drastic changes in cognitive capacities, mostly determined by the function of the thalamo-cortical system. The intra-cranial electroencephalogram or electocorticogram (ECoG), is an important tool for measuring the changes in the thalamo-cortical activity during W and sleep. In the present study we analyzed broad-band ECoG recordings of the rat by means of a time-series complexity measure that is easy to implement and robust to noise: the Permutation Entropy (PeEn). We found that PeEn is maximal during W and decreases during sleep. These results bring to light the different thalamo-cortical dynamics emerging during sleep-wake states, which are associated with the well-known spectral changes that occur when passing from W to sleep. Moreover, the PeEn analysis allows to determine behavioral states independently of the electrodes cortical location, which points to an underlying global pattern in the signal that differs among the cycle states that is missed by classical methods. Consequently, our data suggest that PeEn analysis of a single EEG channel could allow for cheap, easy, and efficient sleep monitoring.

neuroscience↗

bioRxiv2018

Nasal respiration entrains neocortical long-range gamma coherence during wakefulness

Recent studies have shown that slow cortical potentials in archi-, paleo- and neocortex, can phase-lock with nasal respiration. In some of these areas, gamma activity ({gamma}: 30-100 Hz) is also coupled to the animals respiration. It has been hypothesized that this interaction plays a role in coordinating distributed neural activity. In a similar way, inter-cortical interactions at {gamma} frequency has been also associated as a binding mechanism by which the brain generates temporary opportunities necessary for implementing cognitive functions. The aim of the present study is to explore if nasal respiration entrains inter-cortical interactions at {gamma} frequency.\n\nSix adult cats chronically prepared for electrographic recordings were employed in this study. Our results show that slow cortical respiratory potentials are present in several areas of the neocortex and olfactory bulb during wakefulness. Also, we found cross-frequency coupling between the respiratory phase and the amplitude of {gamma} activity in all recorded areas. These oscillatory entrainments are independent of muscular activity, because are maintained during cataplexy induced by carbachol microinjection into the nucleus pontis oralis. Importantly, we observed that respiratory phase modulates the inter-cortical gamma coherence between neocortical pairs of electrodes during wakefulness. However, during NREM and REM sleep, breathing was unable to entrain the oscillatory activity, neither in the olfactory bulb nor in the neocortex. These results suggest a single unified phenomenon involving cross frequency coupling and long-range {gamma} coherence across the neocortex. This fact could be related to a temporal binding process necessary for cognitive functions during wakefulness.

neuroscience↗