Frontiers in Systems Neuroscience

Derived from previous observations on equal and cross-frequency coupling, we evaluated the proposal that equal and cross-frequency phase synchronization may characterize the integration-segregation perspective of cerebral sensory-motor processing. Using brain recordings obtained in normal conditions and in conditions of diminished sensory input (eyes closed wakefulness, sleep and coma, when there is presumably less functional segregation of sensory-motor processing in neural networks), we assessed potential differences in partitioning of the synchrony state space linked to cross-frequency synchronization. More partitions were found in conditions of decreased sensory input. In addition, there was a less complex synchrony state space in cross-frequency as compared with equal-frequency coupling, in terms of fewer connectivity configurations. These results support the idea that equal-frequency coupling favours integration from multiple brain regions occurring in a complex synchrony state space rich in possible connectivity configurations, whereas cross-frequency coupling contributes to segregation, or localized sensory-motor transformations taking place in specific brain areas. This evidence may contribute to new considerations about the much-discussed role of multi-frequency relations in neuronal activity, and how the structural and functional modular organization of the nervous system is able to generate the coordinated activity needed for conscious and appropriate cognitive behaviors in complex environments.

Nitrergic neurons (NN) are inhibitory neurons capable of releasing nitric oxide (NO) that are labeled with NADPHd histochemistry, allowing the study of their distribution and morphology. The rat primary somatosensory (S1) and motor (M1) cortices are a favorable model to investigate the morphology of the NN population. The distribution of the type I NN of the forepaw representation in the primary somatosensory (S1) and motor (M1) cortices of the rat in different laminar compartments and the morphological parameters related to the cell body and dendritic arborization were measured and compared. We found that the neuronal density in the S1 (130 NN/mm3) was higher than in the M1 (119 NN/mm3). Most NN neurons are multipolar (S1 with 58%; M1 with 69%) and a minority are horizontal (S1 with 6%; M1 with 12%). NN found in the S1 had a higher verticality index than those of the M1, and no statistical differences was found for the others morphological parameters. We also demonstrated statistical differences for most of the morphological parameters of the NN between different cortical compartments of the S1 and M1. Our results indicate that the NN of the forepaw in the S1 and M1 correspond to a single neuronal population whose functionality is independent of the different types of sensory and motor processing. However, the morphological differences found between cortical compartments of S1 and M1, as well as the higher density of NN found in the S1 indicate that the release of NO varies along and between the areas. In memoriam of Joao Guedes da FrancaThis paper was done under the supervision of Professor Joao Guedes da Franca and his contribution to this paper was fundamental. He was a great young scientist who left us too soon. Joao Franca made important contributions to the anatomy of the cerebral cortex in several species. His great scientific expertise and rigorous application of anatomical and electrophysiological techniques will be always remembered.

Cross-frequency coupling (CFC) has been proposed as a fundamental mechanism mediating communication between neuronal assemblies through rhythmic interactions across multiple frequency bands, including delta, theta, alpha, beta, and gamma oscillations. Recent findings suggest that slow harmonics in the delta and theta ranges within the brainstem underlie cardiorespiratory rhythms through phase-phase CFC (Kawai, 2023). In contrast, higher-frequency gamma oscillations (>30 Hz) convey information-rich signals via phase-amplitude CFC mechanisms. To date, triple CFC modes have not been characterized in any brain region. Notably, simultaneous delta-theta-gamma coupling--encompassing both phase-phase and phase-amplitude interactions--appears to operate cooperatively, suggesting functional integration through emergent synchrony within the brainstem. Multiple recordings from the nucleus tractus solitarius (NTS) demonstrate that the power and coherence of these synchronized oscillations exhibit distinct spatiotemporal patterns along the dorsoventral axis, reflecting differentiation among large-scale efferent systems and cytoarchitectural domains (Kawai, 2018a; Negishi and Kawai, 2011). Robust gamma activity, phase-coupled with delta and theta oscillations generated by resilient harmonic oscillators within the NTS and the broader brainstem network, may constitute a cooperative mechanism for large-scale homeostatic regulation. The dynamic balance of signal power between slow (delta/theta) and fast (gamma) components could nonlinearly modulate oscillator network dynamics and widespread projection systems throughout the brain. Such integrative neural dynamics likely support adaptive, whole-body responses to fluctuations in the interoceptive environment.

The state of neural oscillation is important for various brain functions. In the basolateral nucleus of amygdala (BA), the oscillation frequency is accelerated in retrieval of conditioned fear memory. The amygdala receives sensory inputs from associated cortex and thalamus. Therefore, we tried to apply the bimodal sensory stimulation at slow frequency (5 Hz, functional frequency in behavioral context) for the entrainment of the BA oscillation. Young adult rats (P24-30) were stimulated by LED illuminator and acoustic speaker at 1 or 5 Hz for 1 hour. Immediately after the stimulus was finished, BA slices were prepared and whole-cell recording was applied to projection neuron. The slow (0.5-2 Hz) rhythmic IPSCs obtained from the pyramidal neuron was accelerated at [~]4 Hz by synchronous opto-acoustic stimulation at 5 Hz. However, the frequency of the neuron at the later recording did not change in the same slice, suggesting that this induced entrainment is transient and reversible phenomenon. As a result, the power distribution was shifted from 0.1-2 to 2-6 Hz by synchronous bimodal 5 Hz stimulation. The regularity of the interval between IPSCs, quantified by rhythm index and the concentration of power around peak frequency in the power spectrum, was not changed by rhythmic sensory stimulation. These results suggest that synchronous bimodal sensory stimuli control the neuronal oscillation frequency by applying with rhythmicity.

Temperature is one of the least studied biophysical characteristics of the brain, although both the rate of biochemical reactions and the electrical activity of nervous tissue directly depend on it. The purpose of this study was to analyze the relationship between brain and body temperatures in anesthetized animals. Simultaneous measurement of brain and body temperature (rectally) was carried out at ambient temperature controlled with a thermal mat. The temperature of the deep layers of the somatosensory cortex was measured by ultralocal thermometry using a diamond thermometer. Under anesthesia, the body and brain temperature dropped to 27 C (4 degrees above ambient temperature). When the thermal mat was turned on, the brain and body began to heat up synchronously. The brain initially lagged behind, but when the critical temperature was reached, it began to release heat in quantities exceeding the influx from the blood, reaching physiological values of 37C. A reverse experiment with decreasing the temperature of the thermal mat showed a similar picture: a synchronous start of the decrease, but with reverse dynamics. Thus, we can distinguish two phases of the brains reaction to external heating: passive - when neuronal activity is decreased, and active - after internal regulatory mechanisms are triggered, which, in its turn, slows down the temperature drop. In general, the data obtained in the present work indicate that the temperature of neural tissue is not linearly related to body temperature.

NADPH diaphorase (N-d) is used to a histochemical identification of subgroup of neuronal cells. Beside regular intracellular N-d positivity, membrane-related positivity revealed as a specialized staining pattern in the pigeon brain stem. In the investigation of the nervous system of homing pigeons (Columba livia) with N-d staining, we found a specialized structure, which temporally was termed as N-d tubular glomerular body/structure or as T-J body related to the last name of authors. This N-d positive specialization constituted by tubular components bilaterally located in the medial to the lemniscus spinalis in the medulla oblongata. The tubular components were moderate staining. T-J body was a longitudinal oriented structure of 2400 m with N-d staining. N-d positive tubular components were twisted and intermingled together. Beside the young adult pigeons, T-J body s were also consistently detected in the aged pigeons. Membrane-related staining were also detected in the other rostral nuclei in the brain stem. With discussion and review of related scientific literatures, T-J body was considered as a new anatomical structure or a new feature of the existent nucleus. In summary, beside N-d intracellular distribution, there were other three N-d membrane-related localizations: mini-aggregation, patch-aggregation, and arrangement along tubular unit.

The cerebral cortical changes associated with propofol-induced unconsciousness remain unknown. While the anesthetic agent affects the entire cerebral cortices, there might be spatiotemporal differences in cortical changes. In particular, we hypothesized that there might be spatiotemporal differences in cortical changes with propofol-anesthesia. To address this hypothesis, we investigated power spectrum changes in electrocorticography (ECoG) signals obtained during the induction phase from awake state to unconsciousness. We found that, 1) the power increased in the range of frequencies < 46 Hz (delta to low gamma), and decreased in the range (62-150) Hz (high gamma), in global channels during the induction phase. 2) The power in the frontoparietal network (FPN), specifically the superior parietal lobule and prefrontal cortex, started to change early, but took a long time to completely change. However, the power in the default mode network (DMN) started to change late, but took a short time to completely change. 3) The power change ({Delta}Power) in the DMN was more conspicuous than that of the dorsal attention network (DAN) in high gamma frequency. Considering that the FPN is involved in communication with the external world and that DMN is involved in communication with self, loss of consciousness induced by general anesthesia results from first, disrupted communication between self and external world, and is then followed by disrupted communication within self, with decreased activity of the FPN, and later, attenuated activity of the DMN. Significance StatementWe investigated the spatiotemporal changes of power spectrum in human electrocorticography (ECoG) during the induction phase from awake state to unconsciousness. We found that from delta to low gamma frequency, the power increased, while in high gamma frequency, the power decreased over all channels. The power in the frontoparietal network (FPN) preferentially changed, then the power in the DMN changed later. The power in DMN decreased more than those in other RSNs in high gamma frequency. Loss of consciousness induced by general anesthesia results from first, disrupted communication between self and external world, followed by disrupted communication within self, with decreased activity of the FPN, and later, attenuated activity of the DMN.

Neural activity in the olfactory bulb is reflected in local field potentials (LFPs). Functionally, LFPs in the olfactory bulb are categorized into different frequency bands: 1-4 Hz, 6-12 Hz, 25-50 Hz, and 65-130 Hz, which respectively correspond to respiration, sniffing, slow gamma, and fast gamma oscillations. While gamma oscillations in the olfactory bulb are modulated by respiration and sniffing, it remains unknown how and whether the modulation of LFP oscillations is affected by the time of day. To address this question, we recorded LFPs in the olfactory bulb, hippocampus, and neocortex of unrestrained mice for up to 3 d. For each recording site, we calculated the correlation coefficients of normalized LFP powers between pairs of frequency bands in the three regions during the dark and light periods. We then compared these correlations with those generated by surrogate data to investigate whether the correlation was statistically significant. We found that the correlation between sniffing and slow gamma oscillations was higher in the dark period than in the light period. Our finding has the potential to shed light on the coding scheme of olfactory information that is dependent on the light/dark cycle.

Neuron activity in the sensory cortices mainly depends on feedforward thalamic inputs. High-frequency activity of a thalamic input can be temporally integrated by a neuron in the sensory cortex and is likely to induce larger depolarization. However, feedforward inhibition (FFI) and depression of excitatory synaptic transmission in thalamocortical pathways attenuate depolarization induced by the latter part of high-frequency spiking activity and the temporal summation may not be effective. The spiking activity of a thalamic neuron in a specific temporal pattern may circumvent FFI and depression of excitatory synapses. The present study determined the relationship between the temporal pattern of spiking activity of a single thalamic neuron and the degree of cortical activation as well as that between the firing rate of spiking activity of a single thalamic neuron and the degree of cortical activation. Spiking activity of a thalamic neuron was recorded extracellularly from the lateral geniculate nucleus (LGN) in male Long-Evans rats. Degree of cortical activation was assessed by simultaneous recording of local field potential (LFP) from the visual cortex. A specific temporal pattern appearing in three consecutive spikes of an LGN neuron induced larger cortical LFP modulation than high-frequency spiking activity during a short period. These findings indicate that spiking activity of thalamic inputs is integrated by a synaptic mechanism sensitive to an input temporal pattern. Significance StatementSensory cortical activity depends on thalamic inputs. Despite the importance of thalamocortical transmission, how spiking activity of thalamic inputs is integrated by cortical neurons remains unclear. Feedforward inhibition and synaptic depression of excitatory transmission may not allow simple temporal summation of membrane potential induced by consecutive spiking activity of a thalamic neuron. A specific temporal pattern appearing in three consecutive spikes of a thalamic neuron induced larger cortical local field potential modulation than high-frequency spiking activity during a short period. The findings indicate the importance of the temporal pattern of spiking activity of a single thalamic neuron on cortical activation.

Accumulating evidence suggest that general anesthetics with diverse chemical structure reduce cerebral metabolism with consequent reduction of intracellular adenosine triphosphate (ATP) levels. How cerebral hypometabolism is associated with the typical electroencephalographic (EEG) changes under general anesthesia remains largely unknown.. We hypothesized that the deficit in ATP production would reduce high-frequency activity, increase low-frequency activity, and cause burst suppression, which are common dose-dependent anesthetic effects on the EEG. To test the hypothesis, we developed a novel neural network model consisting of leaky integrate-and-fire neurons with additional dependency on ATP dynamics. The effect of varying rate of ATP production on neuronal and population activity patterns was simulated under various excitatory/inhibitory balance conditions. A decrease of ATP production suppressed neuronal spiking and enhanced synchronization of neurons over a range of excitatory/inhibitory synaptic strength ratios. As anticipated, the initially asynchronous fast activity was replaced by globally desynchronized slow oscillation and, on further decrease of ATP production, changed into burst suppression with enhanced global synchronization. This study substantiates a novel biophysical mechanism for anesthetic-induced EEG changes through a relationship between energy production and synchronization of neural network.

We are not individuals, we are much better described as ecosystems due to trillions of bacteria and other microorganisms that inhabit us. We now know that gut microbiota can greatly influence many physiological parameters that in turn may impact several cognitive functions, such as learning, memory, and decision making processes. This mutualistic symbiotic relation known as the gut-brain axis is also constrained by external factors such as dietary habits such as animal protein and lipids intake. Using a novel combination of Machine Learning and Network Theory techniques, we provide evidence from an indigenous population in Guerrero Mexico, that both brain and gut-microbiota connectivity, evaluated by Minimum Spanning Tree as the critical backbone of information flow, diminish under either low protein or lipids intake. We discuss then how this loss of connectivity may translate into a reduction of the individuals capacity to cope with perturbations as loss of connectivity may be linked with losses in antifragility.

Human brain experiences vibration of certain frequency during various physical activities such as vehicle transportation and machine operation or accidents, which may cause traumatic brain injury or other brain diseases. However, little is known about what happened to brain after vibration stimuli. Here, with a custom-built electromagnetic actuator, vibration was induced in the brain while cerebral blood flow (CBF) and brain stiffness were measured at 20, 30, 40 Hz for 52 healthy volunteers. With increasing frequency, multiple regions of the brain showed increasingly reduced CBF, while the size of such regions also expanded. The vibration-induced CBF reduction regions largely fell inside the brains default mode network (DMN), with about 58 or 46 % overlap at 30 or 40 Hz, respectively. By establishing a biomechanical co-variance network based on tissue stiffness, analysis of small-world properties and modularity showed an increased disruption of the network with increased frequency. These findings demonstrate frequency-dependent features of vibration modulation to brain. Furthermore, the overlap between CBF reduction regions and DMN, and the vibration-induced decrease of biomechanical network connections suggest a interweaved relationship between blood flow, tissue stiffness, and cognitive functions. These may provide critical insights into the mechanical stimulus to brain and vibration-induced brain pathologies.

Neuronal dynamics such as brain criticality have recently been attributed to optimal information processing. Brain criticality attempts to elucidate the collective dynamics of a large number of neurons. It posits that the brain operates near critical to the critical point, although the field is rife with controversies and contrasting evidence. Similar computational capacities are observed during sharp wave ripples in the hippocampus prompting the need to correlate their dynamics. In the current study, the measures of avalanche criticality including neuronal avalanches, branching process, crackling noise relation, and deviation from criticality coefficient and Hurst exponents for long-range temporal correlations in rodent hippocampus during sharp wave ripples are reported. The evidence for mixed subcritical to critical dynamics in the hippocampus and minimal difference between ripple and no ripple times across measured metrics was found. The evidence demonstrates heterogeneity in signatures of criticality among animals and brain areas, indicating the presence of broad-range neuronal dynamics.

BackgroundUP-DOWN state is considering as a dominant electrographic pattern during immobility and slow wave sleep. This study is focused on the analysis of spatial distribution and neuronal correlates of the DOWN state in rats MethodsLocal field potentials and multiunit discharges were recorded bilaterally in the prefrontal cortex (PFC) and hippocampus of non-anesthetized, tethered rats (Sprague Dawley, males, weight 350-400g) with 256 channel, 4 shank silicon probes. We have focused our study on the analysis of the positive wave of slow oscillations (SOs), which is considered as the DOWN (silent) state of the UP-DOWN state in the anterior cingulate (AC), prelimbic (PL) areas of PFC and hippocampus during immobility. ResultsOur experiments showed that SOs occurred intermittently with a mean interval 1.4{+/-}0.8 ({+/-}SD) seconds. The SOs began with the DOWN state, and they were generated locally within AC or PL areas, or simultaneously in AC, PL and hippocampus bilaterally (generalized SOs). The DOWN state of local SOs in the AC was associated with a decreased rate of multiunit discharges. Similar waves in the PL area were associated with increased multiunit discharges. We observed high speed propagation of generalized SOs that occurred with 3-6ms delay within left and right PFC and less than 10ms delay between the PFC and CA1 area of hippocampus. All generalized SOs were associated with decreased multiunit discharges. ConclusionOur data support the hypothesis that neocortical networks are sufficient to generate focal SOs but the participation of external input is needed for occurrence of generalized SOs.

As social beings, humans make decisions partly based on social interaction. Observing the behavior of others can lead to learning from and about them, potentially increasing trust and prompting trust-based behavioral changes. Observation-based decision making involves different neural structures. The orbitofrontal cortex (OFC) and lateral prefrontal cortex (LPFC) are known as neural structures mainly involved in processing emotional and cognitive decision values, respectively, while the anterior cingulate cortex (ACC) plays a pivotal role as a social hub, integrating the afferent expectancy signals from OFC and LPFC. This paper presents a neurocomputational model of the interplay between observational learning and trust, as well as their role in individual decision-making. Our model elucidates and predicts the emotional and rational behavioral changes of an individual influenced by observing the action-outcome association of an alleged expert. We have modeled the neurodynamics of three cortical structures (OFC, LPFC, and ACC) and their interactions, where the neural oscillatory properties, modeled with Dynamic Bayesian Probability, represent the observers attitude towards the expert and the decision options. As an example of an everyday behavioral situation related to climate change, we use the choice of transportation between home and work. The EEG-like simulation outputs from our model represent the presumed brain activity of an individual making such a choice, assuming the decision-maker is exposed to social information.

The brains of black 6 mice (Mus musculus) and Sebas short-tailed bats (Carollia perspicillata) weigh roughly the same and share mammalian neocortical laminar architecture. Bats have highly developed sonar calls and social communication and are an excellent neuroethological animal model for auditory research. Mice are olfactory and somatosensory specialists, used frequently in auditory neuroscience for their advantage of standardization and wide genetic toolkit. This study presents an analytical approach to overcome the challenge of inter-species comparison with existing data. In both data sets, we recorded with linear multichannel electrodes down the depth of the primary auditory cortex (A1) while presenting repetitive stimuli trains at ~5 and ~40 Hz to awake bats and mice. We found that while there are similarities between cortical response profiles in both, there was a better signal to noise ratio in bats under these conditions, which allowed for a clearer following response to stimuli trains. Model fit analysis supported this, illustrating that bats had stronger response amplitude suppression to consecutive stimuli. Additionally, continuous wavelet transform revealed that bats had significantly stronger power and phase coherence during stimulus response and mice had stronger power in the background. Better signal to noise ratio and lower intertrial phase variability in bats could represent specialization for faster and more accurate temporal processing at lower metabolic costs. Our findings demonstrate a potentially different general auditory processing principle; investigating such differences may increase our understanding of how the ecological need of a species shapes the development and function of its nervous system.

The lateral prefrontal cortex has been classically defined as an associative region involved in the so-called executive functions, such as guiding behavior based on abstract rules and mnemonic information. However, most neurophysiological studies on monkeys did not address the issue of whether distinct anatomical sectors of lateral prefrontal cortex play different functional roles. The main aim of this work is to study functional properties of neurons recorded from a large part of ventrolateral prefrontal cortex (VLPF) of two monkeys performing passive visual tasks and a visuo-motor task, and to map them on the anatomical areas defined on the basis of our recent parcellations. Our results show that distinct VLPF areas differently contribute to visual processing and action organization along the caudo-rostral axis. In particular, the processing of visual stimuli, independent of whether passively presented or exploited for guiding behavior, primarily involves posterior VLPF areas (especially caudal area 12r), while the elaboration of visual and contextual information for action organization mainly involves intermediate VLPF areas (especially middle 46v). In this latter sector, visual stimuli/instructions appear to be encoded in a pragmatic format, that is in terms of the associated behavioral outcome. Finally, more anterior areas are characterized by a low responsiveness to the employed tasks. Altogether, our findings indicate that posterior VLPF areas represent the first processing stage of visual input, intermediate areas primarily contribute to the selection and planning of contextually appropriate behaviors, while rostral areas could be involved in more complex abstract processes.

In complex natural environments, sensory systems are constantly exposed to a large stream of inputs. Novel or rare stimuli, which are often associated with behaviorally important events, are typically processed differently than the steady sensory background, which has less relevance. Neural signatures of such differential processing, commonly referred to as novelty detection, have been identified on the level of EEG recordings as mismatch negativity and the level of single neurons as stimulus-specific adaptation. Here, we propose a multi-scale recurrent network with synaptic depression to explain how novelty detection can arise in the whisker-related part of the somatosensory thalamocortical loop. The architecture and dynamics of the model presume that neurons in cortical layer 6 adapt, via synaptic depression, specifically to a frequently presented stimulus, resulting in reduced population activity in the corresponding cortical column when compared with the population activity evoked by a rare stimulus. This difference in population activity is then projected from the cortex to the thalamus and amplified through the interaction between neurons of the primary and reticular nuclei of the thalamus, resulting in spindle-like, rhythmic oscillations. These differentially activated thalamic oscillations are forwarded to cortical layer 4 as a late secondary response that is specific to rare stimuli that violate a particular stimulus pattern. Model results show a strong analogy between this late single neuron activity and EEG-based mismatch negativity in terms of their common sensitivity to presentation context and timescales of response latency, as observed experimentally. Our results indicate that adaptation in L6 can establish the thalamocortical dynamics that produce signatures of SSA and MMN and suggest a mechanistic model of novelty detection that could generalize to other sensory modalities. Author summaryCortical sensory neurons have been shown to be capable of novelty detection, that is they respond more vigorously when a novel, unexpected stimulus is presented, and less so when the stimulus is part of a predictable sequence. However, the neural mechanism underlying this capability is not yet fully understood. Here, we developed a thalamocortical network model that accounts for novelty detection and reproduces physiologically observed neural response patterns in the somatosensory cortex. Specifically, our results demonstrate that the novelty signal arises from the complex recurrent interplay between thalamic neurons and cortical neurons in layers 4 and 6. This work therefore provides a concrete mechanism that can serve as a starting point for further investigating the neural circuit mechanisms underlying novelty detection.

Key operations in modeling visual processing in living systems are those that process a pattern as a holistic object, for example, in pattern recognition to ensure invariance to translation and rotation. In this article, we describe a neural module we synthesized for moving a pattern along a cortical layer without losing its shape. The module has the form of a three-layer neural network with two types of inhibitory neurons, one of which is a universal "prohibition" logic element. Modeling showed that such operations can be implemented using the proposed neural module by additionally synchronizing its operation using endogenous pacemakers with a gamma rhythm frequency. The mechanism of such synchronization is similar to the clock sweep mechanism in electronics. We believe we have clearly demonstrated the possible role of gamma-based brain activity as a mechanism for synchronizing computations in living neural networks for the first time. This opens up new possibilities for constructing neuromorphic architectures for real-time visual recognition.

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.