State-Dependent Cortical Unit Activity Reflects Dynamic Brain State Transitions in Anesthesia

Distinct neural activities of the cortical layer 2/3 across isoflurane anesthesia: A large-scale simultaneous observation of neurons

Anesthesia inhibits neural activity in the brain, causing patients to lose consciousness and sensation during the surgery. Layers 2/3 of the cortex are important structures for the integration of information and consciousness, which are closely related to normal cognitive function. However, the dynamics of the large-scale population of neurons across multiple regions in layer 2/3 during anesthesia and recovery processes remains unclear. We conducted simultaneous observations and analysis of large-scale calcium signaling dynamics across multiple cortical regions within cortical layer 2/3 during isoflurane anesthesia and recovery in vivo by high-resolution wide-field microscopy. Under isoflurane-induced anesthesia, there is an overall decrease in neuronal activity across multiple regions in the cortical layer 2/3. Notably, some neurons display a paradoxical increase in activity during anesthesia. Additionally, the activity among multiple cortical regions under anesthesia was homogeneous. It is only during the recovery phase that variability emerges in the extent of increased neural activity across different cortical regions. Within the same duration of anesthesia, neural activity did not return to preanesthetic levels. To sum up, anesthesia as a dynamic alteration of brain functional networks, encompassing shifts in patterns of neural activity, homogeneousness among cortical neurons and regions, and changes in functional connectivity. Recovery from anesthesia does not entail a reversal of these effects within the same timeframe.

Microstimulation reveals anesthetic state-dependent effective connectivity of neurons in cerebral cortex

Complex neuronal interactions underlie cortical information processing that can be compromised in altered states of consciousness. Here intracortical microstimulation was applied to investigate the state-dependent effective connectivity of neurons in rat visual cortex in vivo. Extracellular activity was recorded at 32 sites in layers 5/6 while stimulating with charge-balanced discrete pulses at each electrode in random order. The same stimulation pattern was applied at three levels of anesthesia with desflurane and in wakefulness. Spikes were sorted and classified by their waveform features as putative excitatory and inhibitory neurons. Microstimulation caused early (<10ms) increase followed by prolonged (11-100ms) decrease in spiking of all neurons throughout the electrode array. The early response of excitatory but not inhibitory neurons decayed rapidly with distance from the stimulation site over 1mm. Effective connectivity of neurons with significant stimulus response was dense in wakefulness and sparse under anesthesia. Network motifs were identified in graphs of effective connectivity constructed from monosynaptic cross-correlograms. The number of motifs, especially those of higher order, increased rapidly as the anesthesia was withdrawn indicating a substantial increase in network connectivity as the animals woke up. The results illuminate the impact of anesthesia on functional integrity of local circuits affecting the state of consciousness.

Monitoring and evaluation of anesthesia depth status data based on neuroscience

Monitoring and analysis of anesthesia depth status data refers to evaluating the anesthesia depth status of patients during the surgical process by monitoring their physiological index data, and conducting analysis and judgment. The depth of anesthesia is crucial for the safety and success of the surgical process. By monitoring the state of anesthesia depth, abnormal conditions of patients can be detected in a timely manner and corresponding measures can be taken to prevent accidents from occurring. Traditional anesthesia monitoring methods currently include computer tomography, electrocardiogram, respiratory monitoring, etc. In this regard, traditional physiological indicator monitoring methods have certain limitations and cannot directly reflect the patient's neural activity status. The monitoring and analysis methods based on neuroscience can obtain more information from the level of brain neural activity.

PURPOSE

In this article, the monitoring and analysis of anesthesia depth status data would be studied through neuroscience.

METHODS

Through a controlled experiment, the monitoring accuracy of traditional anesthesia status monitoring algorithm and neuroscience-based anesthesia status monitoring algorithm was studied, and the information entropy and oxygen saturation of electroencephalogram signals in patients with different anesthesia depth were explored.

RESULTS

The experiment proved that the average monitoring accuracy of the traditional anesthesia state monitoring algorithm in patients' blood drug concentration and oxygen saturation reached 95.55 and 95.00%, respectively. In contrast, the anesthesia state monitoring algorithm based on neuroscience performs better, with the average monitoring accuracy of drug concentration and oxygen saturation reaching 98.00 and 97.09%, respectively. This experimental result fully proved that the monitoring performance of anesthesia state monitoring algorithms based on neuroscience is better.

CONCLUSION

The experiment proved the powerful monitoring ability of the anesthesia state monitoring algorithm based on neuroscience used in this article, and explained the changing trend of brain nerve signals and oxygen saturation of patients with different anesthesia depth states, which provided a new research method for the monitoring and analysis technology of anesthesia depth state data.

Spontaneous and Visual Stimulation Evoked Firing Sequences Are Distinct Under Desflurane Anesthesia

Recurring spike sequences are thought to underlie cortical computations and may be essential for information processing in the conscious state. How anesthesia at graded levels may influence spontaneous and stimulus-related spike sequences in visual cortex has not been fully elucidated. We recorded extracellular single-unit activity in the rat primary visual cortex in vivo during wakefulness and three levels of anesthesia produced by desflurane. The latencies of spike sequences within 0-200 ms from the onset of spontaneous UP states and visual flash-evoked responses were compared. During wakefulness, spike latency patterns linked to the local field potential theta cycle were similar to stimulus-evoked patterns. Under desflurane anesthesia, spontaneous UP state sequences differed from flash-evoked sequences due to the recruitment of low-firing excitatory neurons to the UP state. Flash-evoked spike sequences showed higher reliability and longer latency when stimuli were applied during DOWN states compared to UP states. At deeper levels, desflurane altered both UP state and flash-evoked spike sequences by selectively suppressing inhibitory neuron firing. The results reveal desflurane-induced complex changes in cortical firing sequences that may influence visual information processing.

Arousal system stimulation and anesthetic state alter visuoparietal connectivity

Cortical information processing is under the precise control of the ascending arousal system (AAS). Anesthesia suppresses cortical arousal that can be mitigated by exogenous stimulation of the AAS. The question remains to what extent cortical information processing is regained by AAS stimulation. We investigate the effect of electrical stimulation of the nucleus Pontis Oralis (PnO), a distinct source of ascending AAS projections, on cortical functional connectivity (FC) and information storage at mild, moderate, and deep anesthesia. Local field potentials (LFPs) recorded previously in the secondary visual cortex (V2) and the adjacent parietal association cortex (PtA) in chronically instrumented unrestrained rats. We hypothesized that PnO stimulation would induce electrocortical arousal accompanied by enhanced FC and active information storage (AIS) implying improved information processing. In fact, stimulation reduced FC in slow oscillations (0.3-2.5 Hz) at low anesthetic level and increased FC at high anesthetic level. These effects were augmented following stimulation suggesting stimulus-induced plasticity. The observed opposite stimulation-anesthetic impact was less clear in the γ-band activity (30-70 Hz). In addition, FC in slow oscillations was more sensitive to stimulation and anesthetic level than FC in γ-band activity which exhibited a rather constant spatial FC structure that was symmetric between specific, topographically related sites in V2 and PtA. Invariant networks were defined as a set of strongly connected electrode channels, which were invariant to experimental conditions. In invariant networks, stimulation decreased AIS and increasing anesthetic level increased AIS. Conversely, in non-invariant (complement) networks, stimulation did not affect AIS at low anesthetic level but increased it at high anesthetic level. The results suggest that arousal stimulation alters cortical FC and information storage as a function of anesthetic level with a prolonged effect beyond the duration of stimulation. The findings help better understand how the arousal system may influence information processing in cortical networks at different levels of anesthesia.

Weakly Correlated Local Cortical State Switches under Anesthesia Lead to Strongly Correlated Global States

During recovery from anesthesia, brain activity switches abruptly between a small set of discrete states. Surprisingly, this switching also occurs under constant doses of anesthesia, even in the absence of stimuli. These metastable states and the transitions between them are thought to form a "scaffold" that ultimately guides the brain back to wakefulness. The processes that constrain cortical activity patterns to these states and govern how states are coordinated between different cortical regions are unknown. If state transitions were driven by subcortical modulation, different cortical sites should exhibit near-synchronous state transitions. Conversely, spatiotemporal heterogeneity would suggest that state transitions are coordinated through corticocortical interactions. To differentiate between these hypotheses, we quantified synchrony of brain states in male rats exposed to a fixed isoflurane concentration. States were defined from spectra of local field potentials recorded across layers of visual and motor cortices. A transition synchrony measure shows that most state transitions are highly localized. Furthermore, while most pairs of cortical sites exhibit statistically significant coupling of both states and state transition times, coupling strength is typically weak. States and state transitions in the thalamic input layer (L4) are particularly decoupled from those in supragranular and infragranular layers. This suggests that state transitions are not imposed on the cortex by broadly projecting modulatory systems. Although each pairwise interaction is typically weak, we show that the multitude of such weak interactions is sufficient to confine global activity to a small number of discrete states.SIGNIFICANCE STATEMENT The brain consistently recovers to wakefulness after anesthesia, but this process is poorly understood. Previous work revealed that, during recovery from anesthesia, corticothalamic activity falls into one of several discrete patterns. The neuronal mechanisms constraining the cortex to just a few discrete states remain unknown. Global states could be coordinated by fluctuations in subcortical nuclei that project broadly to the cortex. Alternatively, these states may emerge from interactions within the cortex itself. Here, we provide evidence for the latter possibility by demonstrating that most pairs of cortical sites exhibit weak coupling. We thereby lay groundwork for future investigations of the specific cellular and network mechanisms of corticocortical activity state coupling.

Theoretical foundations of studying criticality in the brain

Criticality is hypothesized as a physical mechanism underlying efficient transitions between cortical states and remarkable information-processing capacities in the brain. While considerable evidence generally supports this hypothesis, nonnegligible controversies persist regarding the ubiquity of criticality in neural dynamics and its role in information processing. Validity issues frequently arise during identifying potential brain criticality from empirical data. Moreover, the functional benefits implied by brain criticality are frequently misconceived or unduly generalized. These problems stem from the nontriviality and immaturity of the physical theories that analytically derive brain criticality and the statistic techniques that estimate brain criticality from empirical data. To help solve these problems, we present a systematic review and reformulate the foundations of studying brain criticality, that is, ordinary criticality (OC), quasi-criticality (qC), self-organized criticality (SOC), and self-organized quasi-criticality (SOqC), using the terminology of neuroscience. We offer accessible explanations of the physical theories and statistical techniques of brain criticality, providing step-by-step derivations to characterize neural dynamics as a physical system with avalanches. We summarize error-prone details and existing limitations in brain criticality analysis and suggest possible solutions. Moreover, we present a forward-looking perspective on how optimizing the foundations of studying brain criticality can deepen our understanding of various neuroscience questions.

General anesthesia globally synchronizes activity selectively in layer 5 cortical pyramidal neurons

General anesthetics induce loss of consciousness, a global change in behavior. However, a corresponding global change in activity in the context of defined cortical cell types has not been identified. Here, we show that spontaneous activity of mouse layer 5 pyramidal neurons, but of no other cortical cell type, becomes consistently synchronized in vivo by different general anesthetics. This heightened neuronal synchrony is aperiodic, present across large distances, and absent in cortical neurons presynaptic to layer 5 pyramidal neurons. During the transition to and from anesthesia, changes in synchrony in layer 5 coincide with the loss and recovery of consciousness. Activity within both apical and basal dendrites is synchronous, but only basal dendrites’ activity is temporally locked to somatic activity. Given that layer 5 is a major cortical output, our results suggest that brain-wide synchrony in layer 5 pyramidal neurons may contribute to the loss of consciousness during general anesthesia.

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Activity of layer 5 PNs synchronizes globally in different anesthetics

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Other mouse cortical cell types show no consistent increase in synchrony

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Changes in layer 5 synchrony coincide with the loss and recovery of consciousness

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Basal, but not apical, layer 5 dendrites are in synchrony with somas

Consciousness is supported by near-critical slow cortical electrodynamics

Mounting evidence suggests that during conscious states, the electrodynamics of the cortex are poised near a critical point or phase transition and that this near-critical behavior supports the vast flow of information through cortical networks during conscious states. Here, we empirically identify a mathematically specific critical point near which waking cortical oscillatory dynamics operate, which is known as the edge-of-chaos critical point, or the boundary between stability and chaos. We do so by applying the recently developed modified 0-1 chaos test to electrocorticography (ECoG) and magnetoencephalography (MEG) recordings from the cortices of humans and macaques across normal waking, generalized seizure, anesthesia, and psychedelic states. Our evidence suggests that cortical information processing is disrupted during unconscious states because of a transition of low-frequency cortical electric oscillations away from this critical point; conversely, we show that psychedelics may increase the information richness of cortical activity by tuning low-frequency cortical oscillations closer to this critical point. Finally, we analyze clinical electroencephalography (EEG) recordings from patients with disorders of consciousness (DOC) and show that assessing the proximity of slow cortical oscillatory electrodynamics to the edge-of-chaos critical point may be useful as an index of consciousness in the clinical setting.

Network Model With Reduced Metabolic Rate Predicts Spatial Synchrony of Neuronal Activity

In a cerebral hypometabolic state, cortical neurons exhibit slow synchronous oscillatory activity with sparse firing. How such a synchronization spatially organizes as the cerebral metabolic rate decreases have not been systemically investigated. We developed a network model of leaky integrate-and-fire neurons with an additional dependency on ATP dynamics. Neurons were scattered in a 2D space, and their population activity patterns at varying ATP levels were simulated. The model predicted a decrease in firing activity as the ATP production rate was lowered. Under hypometabolic conditions, an oscillatory firing pattern, that is, an ON-OFF cycle arose through a failure of sustainable firing due to reduced excitatory positive feedback and rebound firing after the slow recovery of ATP concentration. The firing rate oscillation of distant neurons developed at first asynchronously that changed into burst suppression and global synchronization as ATP production further decreased. These changes resembled the experimental data obtained from anesthetized rats, as an example of a metabolically suppressed brain. Together, this study substantiates a novel biophysical mechanism of neuronal network synchronization under limited energy supply conditions.

State-Dependent Synchrony and Functional Connectivity in the Primary and Secondary Whisker Somatosensory Cortices

Synchronized activity plays an important role in sensory coding and memory and is a hallmark of functional network connectivity. However, the effect of sensory activation on synchronization and cortical functional connectivity is largely unknown. In this study, we investigated the effect of whisker activation on synchronization and functional connectivity of the primary (wS1) and secondary (wS2) whisker somatosensory cortices at the single-cell level. The results showed that during the spontaneous pre-stimulus state, neurons tended to be functionally connected with nearby neurons which shared similar tuning characteristics. Whisker activation using either ramp-and-hold stimulation or artificial whisking against sandpaper has significantly reduced the average overall pairwise synchronization and functional connectivity within the wS1 barrel and wS2 cortices. Whisker stimulation disconnected approximately a third of neuronal pairs that were functionally connected during the unstimulated state. Nearby neurons with congruent tuning properties were more likely to remain functionally connected during whisker activation. The findings of this study indicated that cortical somatosensory networks are organized in non-random small world networks composed of neurons sharing relatively similar tuning properties. Sensory whisker activation intensifies these properties and further subdivides the cortical network into smaller more functionally uniform subnetworks, which possibly serve to increase the computational capacity of the network.

Paradoxical anesthesia: Sleep-like EEG during anesthesia induced by mesopontine microinjection of GABAergic agents

General anesthetic agents are thought to induce loss-of-consciousness (LOC) and enable pain-free surgery by acting on the endogenous brain circuitry responsible for sleep-wake cycling. In clinical use, the entire CNS is exposed to anesthetic molecules with LOC and amnesia usually attributed to synaptic suppression in the cerebral cortex and immobility and analgesia to agent action in the spinal cord and brainstem. This model of patch-wise suppression has been challenged, however, by the observation that all functional components of anesthesia can be induced by focal delivery of minute quantities of GABAergic agonists to the brainstem mesopontine tegmental anesthesia area (MPTA). We compared spectral features of the cortical electroencephalogram (EEG) in rats during systemic anesthesia and anesthesia induced by MPTA microinjection. Systemic administration of (GABAergic) pentobarbital yielded the sustained, δ-band dominant EEG signature familiar in clinical anesthesia. In contrast, anesthesia induced by MPTA microinjection (pentobarbital or muscimol) featured epochs of δ-band EEG alternating with the wake-like EEG, the pattern typical of natural non-rapid-eye-movement (NREM) and REM sleep. The rats were not sleeping, however, as they remained immobile, atonic and unresponsive to noxious pinch. Recalling the paradoxical wake-like quality the EEG during REM sleep, we refer to this state as "paradoxical anesthesia". GABAergic anesthetics appear to co-opt both cortical and spinal components of the sleep network via dedicated axonal pathways driven by MPTA neurons. Direct drug exposure of cortical and spinal neurons is not necessary, and is probably responsible for off-target side-effects of systemic administration including monotonous δ-band EEG, hypothermia and respiratory depression. SIGNIFICANCE STATEMENT: The concept that GABAergic general anesthetic agents induce loss-of-consciousness by substituting for an endogenous neurotransmitter, thereby co-opting neural circuitry responsible for sleep-wake transitions, has gained considerable traction. However, the electroencephalographic (EEG) signatures of sleep and anesthesia differ fundamentally. We show that when the anesthetic state is generated by focal delivery of GABAergics into the mesopontine tegmental anesthesia area (MPTA) the resulting EEG repeatedly transitions between delta-wave-dominant and wake-like patterns much as in REM-NREM sleep. This suggests that systemic (clinical) anesthetic delivery, which indiscriminately floods the entire cerebrum with powerful inhibitory agents, obscures the sleep-like EEG signature associated with the less adulterated form of anesthesia obtained when the drugs are applied selectively to loci where the effective neurotransmitter substitution actually occurs.

Differential Effect of Anesthesia on Visual Cortex Neurons with Diverse Population Coupling

Cortical neurons display diverse firing patterns and synchronization properties. How anesthesia alters the firing response of different neuron groups relevant for sensory information processing is unclear. Here we investigated the graded effect of anesthesia on spontaneous and visual flash-induced spike activity of different neuron groups classified based on their spike waveform, firing rate, and population coupling (the extent neurons conform to population spikes). Single-unit activity was measured from multichannel extracellular recordings in deep layers of primary visual cortex of freely moving rats in wakefulness and at three concentrations of desflurane. Anesthesia generally decreased firing rate and increased population coupling and burstiness of neurons. Population coupling and firing rate became more correlated and the pairwise correlation between neurons became more predictable by their population coupling in anesthesia. During wakefulness, visual stimulation increased firing rate; this effect was the largest and the most prolonged in neurons that exhibited high population coupling and high firing rate. During anesthesia, the early increase in firing rate (20-150 ms post-stimulus) of these neurons was suppressed, their spike timing was delayed and split into two peaks. The late response (200-400 ms post-stimulus) of all neurons was also suppressed. We conclude that anesthesia alters the visual response of primarily high-firing highly coupled neurons, which may interfere with visual sensory processing. The increased association of population coupling and firing rate during anesthesia suggests a decrease in sensory information content.