Two-compartment neuronal spiking model expressing brain-state specific apical-amplification, -isolation and -drive regimes

There is mounting experimental evidence that brain-state specific neural mechanisms supported by connectomic architectures serve to combine past and contextual knowledge with current, incoming flow of evidence (e.g. from sensory systems). Such mechanisms are distributed across multiple spatial and temporal scales and require dedicated support at the levels of individual neurons and synapses. A prominent feature in the neocortex is the structure of large, deep pyramidal neurons which show a peculiar separation between an apical dendritic compartment and a basal dentritic/peri-somatic compartment, with distinctive patterns of incoming connections and brain-state specific activation mechanisms, namely apical-amplification, -isolation and -drive associated to the wakefulness, deeper NREM sleep stages and REM sleep. The cognitive roles of apical mechanisms have been demonstrated in behaving animals. In contrast, classical models of learning spiking networks are based on single compartment neurons that miss the description of mechanisms to combine apical and basal/somatic information. This work aims to provide the computational community with a two-compartment spiking neuron model which includes features that are essential for supporting brain-state specific learning and with a piece-wise linear transfer function (ThetaPlanes) at highest abstraction level to be used in large scale bio-inspired artificial intelligence systems. A machine learning algorithm, constrained by a set of fitness functions, selected the parameters defining neurons expressing the desired apical mechanisms.Comment: 19 pages, 38 figures, pape

EEG-based effective connectivity distinguishes between unresponsive states with and without report of conscious experience and correlates with brain complexity

Objective methods for distinguishing conscious from unconscious states in humans are of key importance for clinical evaluation of general anesthesia and patients with disorders or consciousness. Here, we test the generalizability of a DTF-based algorithm - a measure of effective connectivity - as an objective measure of conscious experience during anesthesia and correlate it with a well-tested index of consciousness: the Perturbational Complexity Index (PCI). We reanalyzed EEG data from an experimental study in which 18 healthy volunteers were randomly assigned to one of three types of general anesthesia: propofol, xenon, and ketamine. EEG was recorded before and during anesthesia, and DTF was calculated from every 1-second segment of the EEG data to quantify the effective connectivity between channel pairs. This was used to classify the state of each participant as either conscious or unconscious, and the classifications were compared with the participant’s delayed report of experience, and the PCI. The algorithm was more likely to classify participants as conscious in the awake state than during propofol and xenon anesthesia (p0.05). Furthermore, the DTF-based confidence of being classified as conscious was highly correlated with PCI (r2=0.48, p<0.05). These results provide further support for the notion that effective connectivity measured between EEG electrodes can be used to distinguish between conscious and unconscious states in humans

Synergy of Glutamatergic and Cholinergic Modulation Induces Plateau Potentials in Hippocampal OLM Interneurons

Oriens-lacunosum moleculare (OLM) cells are hippocampal inhibitory interneurons that are implicated in the regulation of information flow in the CA1 circuit, inhibiting cortical inputs to distal pyramidal cell dendrites, whilst disinhibiting CA3 inputs to pyramidal cells. OLM cells express metabotropic cholinergic (mAChR) and glutamatergic (mGluR) receptors, so modulation of these cells via these receptors may contribute to switching between functional modes of the hippocampus. Using a transgenic mouse line to identify OLM cells, we found that both mAChR and mGluR activation caused the cells to exhibit long-lasting depolarizing plateau potentials following evoked spike trains. Both mAChR- and mGluR-induced plateau potentials were eliminated by blocking transient receptor potential (TRP) channels, and were dependent on intracellular calcium concentration and calcium entry. Pharmacological tests indicated that Group I mGluRs are responsible for the glutamatergic induction of plateaus. There was also a pronounced synergy between the cholinergic and glutamatergic modulation, plateau potentials being generated by agonists applied together at concentrations too low to elicit any change when applied individually. This synergy could enable OLM cells to function as coincidence detectors of different neuromodulatory systems, leading to their enhanced and prolonged activation and a functional change in information flow within the hippocampus

Physiological roles of Kv2 channels in entorhinal cortex layer II stellate cells revealed by Guangxitoxin-1E

The medial entorhinal cortex (mEC) is strongly involved in spatial navigation, memory, dementia and epilepsy. Although potassium channels shape neuronal activity, their roles in mEC are largely unknown. We used the new Kv2 blocker Guangxitoxin-1E (GTx; 10–100 nm) in rat brain slices to investigate Kv2 channel functions in mEC layer II stellate cells (SCs). These neurons project to the hippocampus and are considered to be grid cells representing space. Voltage clamp recordings from SCs nucleated patches showed that GTx inhibited a delayed rectifier K+ current activating beyond –30 mV but not transient A-type current. In current clamp, GTx (i) had almost no effect on the first action potential but markedly slowed repolarization of late spikes during repetitive firing; (ii) enhanced the after-depolarization (ADP); (iii) reduced fast and medium after-hyperpolarizations (AHPs); (iv) strongly enhanced burst firing and increased excitability at moderate spike rates but reduced spiking at high rates; and (v) reduced spike clustering and rebound potentials. The changes in bursting and excitability were related to the altered ADPs and AHPs. Kv2 channels strongly shape the activity of mEC SCs by affecting spike repolarization, after-potentials, excitability and spike patterns. GTx is a useful tool and may serve to further clarify Kv2 channel functions in neurons. We conclude that Kv2 channels in mEC SCs are important determinants of intrinsic properties that allow these neurons to produce spatial representation. The results of the present study may also be important for the accurate modelling of grid cells. This is the peer reviewed version of the article which has been published in final form at https://doi.org/10.1113/JP273024. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving

Apical drive - a cellular mechanism of dreaming?

Dreams are internally generated experiences that occur independently of current sensory input. Here we argue, based on cortical anatomy and function, that dream experiences are tightly related to the workings of a specific part of cortical pyramidal neurons, the apical integration zone (AIZ). The AIZ receives and processes contextual information from diverse sources and could constitute a major switch point for transitioning from externally to internally generated experiences such as dreams. We propose that during dreams the output of certain pyramidal neurons is mainly driven by input into the AIZ. We call this mode of functioning “apical drive”. Our hypothesis is based on the evidence that the cholinergic and adrenergic arousal systems, which show different dynamics between waking, slow wave sleep, and rapid eye movement sleep, have specific effects on the AIZ. We suggest that apical drive may also contribute to waking experiences, such as mental imagery. Future studies, investigating the different modes of apical function and their regulation during sleep and wakefulness are likely to be richly rewarded

Validation of a new approach for distinguishing anesthetized from awake state in patients using directed transfer function applied to raw EEG

Abstract We test whether a measure based on the directed transfer function (DTF) calculated from short segments of electroencephalography (EEG) time-series can be used to monitor the state of the patients also during sevoflurane anesthesia as it can for patients undergoing propofol anesthesia. We collected and analyzed 25-channel EEG from 7 patients (3 females, ages 41–56 years) undergoing surgical anesthesia with sevoflurane, and quantified the sensor space directed connectivity for every 1-s epoch using DTF. The resulting connectivity parameters were compared to corresponding parameters from our previous study (n = 8, patients anesthetized with propofol and remifentanil, but otherwise using a similar protocol). Statistical comparisons between and within studies were done using permutation statistics, a data driven algorithm based on the DTF-parameters was employed to classify the epochs as coming from awake or anesthetized state. According to results of the permutation tests, DTF-parameter topographies were significantly different between the awake and anesthesia state at the group level. However, the topographies were not significantly different when comparing results computed from sevoflurane and propofol data, neither in the awake nor in anesthetized state. Optimizing the algorithm for simultaneously having high sensitivity and specificity in classification yielded an accuracy of 95.1% (SE = 0.96%), with sensitivity of 98.4% (SE = 0.80%) and specificity of 94.8% (SE = 0.10%). These findings indicate that the DTF changes in a similar manner when humans undergo general anesthesia caused by two distinct anesthetic agents with different molecular mechanisms of action

Capacity for consciousness under ketamine anaesthesia is selectively associated with activity in posteromedial cortex in rats

It remains unclear how specific cortical regions contribute to the brain’s overall capacity for consciousness. Clarifying this could help distinguish between theories of consciousness. Here, we investigate the association between markers of regionally specific (de)activation and the brain’s overall capacity for consciousness. We recorded electroencephalographic responses to cortical electrical stimulation in six rats and computed Perturbational Complexity Index state-transition (PCIST), which has been extensively validated as an index of the capacity for consciousness in humans. We also estimated the balance between activation and inhibition of specific cortical areas with the ratio between high and low frequency power from spontaneous electroencephalographic activity at each electrode. We repeated these measurements during wakefulness, and during two levels of ketamine anaesthesia: with the minimal dose needed to induce behavioural unresponsiveness and twice this dose. We found that PCIST was only slightly reduced from wakefulness to light ketamine anaesthesia, but dropped significantly with deeper anaesthesia. The high-dose effect was selectively associated with reduced high frequency/low frequency ratio in the posteromedial cortex, which strongly correlated with PCIST. Conversely, behavioural unresponsiveness induced by light ketamine anaesthesia was associated with similar spectral changes in frontal, but not posterior cortical regions. Thus, activity in the posteromedial cortex correlates with the capacity for consciousness, as assessed by PCIST, during different depths of ketamine anaesthesia, in rats, independently of behaviour. These results are discussed in relation to different theories of consciousness

General Anesthesia Disrupts Complex Cortical Dynamics in Response to Intracranial Electrical Stimulation in Rats

The capacity of human brain to sustain complex cortical dynamics appears to be strongly associated with conscious experience and consistently drops when consciousness fades. For example, several recent studies in humans found a remarkable reduction of the spatiotemporal complexity of cortical responses to local stimulation during dreamless sleep, general anesthesia, and coma. However, this perturbational complexity has never been directly estimated in non-human animals in vivo previously, and the mechanisms that prevent neocortical neurons to engage in complex interactions are still unclear. Here, we quantify the complexity of electroencephalographic (EEG) responses to intracranial electrical stimulation in rats, comparing wakefulness to propofol, sevoflurane, and ketamine anesthesia. The evoked activity changed from highly complex in wakefulness to far simpler with propofol and sevoflurane. The reduced complexity was associated with a suppression of high frequencies that preceded a reduced phase-locking, and disruption of functional connectivity and pattern diversity. We then showed how these parameters dissociate with ketamine and depend on intensity and site of stimulation. Our results support the idea that brief periods of activity-dependent neuronal silence can interrupt complex interactions in neocortical circuits, and open the way for further mechanistic investigations of the neuronal basis for consciousness and loss of consciousness across species

Distinguishing Anesthetized from Awake State in Patients: A New Approach Using One Second Segments of Raw EEG

Objective: The objective of this study was to test whether properties of 1-s segments of spontaneous scalp EEG activity can be used to automatically distinguish the awake state from the anesthetized state in patients undergoing general propofol anesthesia. Methods: Twenty five channel EEG was recorded from 10 patients undergoing general intravenous propofol anesthesia with remifentanil during anterior cervical discectomy and fusion. From this, we extracted properties of the EEG by applying the Directed Transfer Function (DTF) directly to every 1-s segment of the raw EEG signal. The extracted properties were used to develop a data-driven classification algorithm to categorize patients as “anesthetized” or “awake” for every 1-s segment of raw EEG. Results: The properties of the EEG signal were significantly different in the awake and anesthetized states for at least 8 of the 25 channels (p < 0.05, Bonferroni corrected Wilcoxon rank-sum tests). Using these differences, our algorithms achieved classification accuracies of 95.9%. Conclusion: Properties of the DTF calculated from 1-s segments of raw EEG can be used to reliably classify whether the patients undergoing general anesthesia with propofol and remifentanil were awake or anesthetized. Significance: This method may be useful for developing automatic real-time monitors of anesthesia

Behavioral effects of sub-anesthetic ketamine in a go/no-go task

Background and aims While psychedelic agents are known to have powerful, but largely unexplained, effects on contents of consciousness, there is an increasing interest in the potential clinical usefulness of such drugs for therapy, and legalization is discussed in some countries. Thus, it is relevant to study the effects of psychedelic compounds not only on experience, but also on behavioral performance. Methods Seven healthy participants performed a motor response inhibition task before, during, and after sub-anesthetic doses of intravenously administered ketamine. The infusion rate was individually adjusted to produce noticeable subjective psychedelic effects. Results We observed no statistically significant impact of sub-anesthetic ketamine on reaction times, omission errors, or post error slowing, relative to the preceding drug-free condition. However, we did observe significant correlations between performance impairment and self-reported, subjective altered states of consciousness, specifically experience of “anxiety” and “complex imagery.” Conclusions Considering the limited number of participants and large variation in strength of self-reported experiences, further studies with wider ranges of ketamine doses and behavioral tasks are needed to determine the presence and strength of potential behavioral effects